Studies investigating the association between single-nucleotide polymorphisms (SNPs) of the methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) and cancer risk report conflicting results. To derive a more precise estimation of the relationship between MTHFD1 polymorphisms and cancer risk, the present meta-analysis was carried out.A comprehensive search was conducted to determine all the eligible studies about MTHFD1 polymorphisms and cancer risk. Combined odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the strength of the association between the MTHFD1 polymorphisms and cancer risk. We investigated by meta-analysis the effects of 2 polymorphisms in MTHFD1: G1958A  and G401A . The overall results indicated no major influence of these 2 polymorphisms on cancer risk. For G1958A, a decreased cancer risk was found in acute lymphoblastic leukemia (ALL)/Asians  and other cancers . For G401A, the data showed that MTHFD1 G401A polymorphism was associated with a decreased colon cancer risk under dominant model .The results suggest that MTHFD1 G1958A polymorphism might be associated with a decreased risk of ALL and other cancers. Meanwhile, the MTHFD1 G401A might play a protective role in the development of colon cancer. Large-scale and well-designed case-control studies are necessary to validate the risk identified in the present meta-analysis. Cancer remains a major public health problem in the world. The complex etiology of this disease is not yet fully elucidated. Identifying risk factors for cancer is critically important to develop potential interventions and to expand our understanding of the biology of this disease. Cancer is a disease resulting from complex interactions between environmental and genetic factors Folate is a water-soluble B vitamin involved in one-carbon metabolism that plays an essential role in the synthesis, repair, and methylation of DNA MTHFD1 is the NADP-dependent tri-functional enzyme acting as 5,10-methylenetetrahydrofolate dehydrogenase; 5,10-methenyltetrahydrofolate cyclohydrolase; and 10-formylotetrahydrofolate synthetase A variety of molecular epidemiological studies have focused on the associations between MTHFD1 polymorphisms and cancer susceptibility. These studies have shown that the MTHFD1 polymorphisms occur in different types of cancer, but the results are inconclusive, partially because of the possible small effect of the polymorphism on cancer risk and the relatively small sample size in each of published studies. To solve the problem of inadequate statistical power and controversial results, it is necessary to carry out a systematic review and meta-analysis including subgroup analysis from all eligible studies to assess the association of the MTHFD1 polymorphisms with cancer risk.We searched for articles using the terms “methylenetetrahydrofolate dehydrogenase 1” or “MTHFD1”, “polymorphism” or “variation”, and “cancer” or “carcinoma” or “neoplasm” or “malignance” in PubMed, Cochrane Library and Embase electronic databases, and all eligible studies were published up to February 20, 2013. We evaluated all the retrieved publications to retain the most eligible studies. Authors were contacted directly regarding crucial data not reported in original articles. Of the studies with the same or overlapping data by the same investigators, we selected the most recent ones with the most subjects. We evaluated all associated publications to retrieve the most eligible literatures. The reference lists of reviews and retrieved articles were hand searched at the same time. We did not include abstracts or unpublished reports. When overlapping data of the same patient population were included in more than one publication, only the most recent or complete study was used in this meta-analysis.The following inclusion criteria were used to select literatures for the meta-analysis: (1) information on the evaluating of MTHFD1 polymorphisms and cancer susceptibility; (2) only the case-control studies were considered; (3) controls were without cancer; and (4) sufficient genotype data were presented to calculate the odds ratio (OR) with 95% confidence interval (CI). In addition, the following exclusion criteria were also used: (1) repeated or overlapping studies; (2) no usable data reported; (3) animal studies; (4) control population including malignant tumor patients; and (5) the study only involved a case population.Two investigators reviewed and extracted information from all eligible publications independently, according to the inclusion and exclusion criteria listed above. An agreement was reached by discussion between the two reviewers whenever there was a conflict. The following data were extracted: the first author’s last name, year of publication, ethnicity of the subjects, cancer type, and genotype distribution in cancer cases and controls. Different descents were categorized as Asian and Caucasian. If the ethnicity was not reported, we considered the ethnicity of the source population of the country where the study was performed. For case-control studies, data were extracted separately for each group whenever possible.http://ihg.gsf.de/cgi-bin/hw/hwa1.pl).All statistical tests performed in this study were two-tailed and p values less than 0.05 were considered significant, unless otherwise stated. Statistical analyses were performed with Review Manage, version 5.0 and Stata 10.0. We assessed the departure from the Hardy-Weinberg equilibrium (HWE) for the control group in each study using an online HWE calculator , recessive (AA vs GA+GG), dominant (AA+AG vs GG), and allelic (A vs G) models. For G401A polymorphism, we evaluated the same effects. The significance of the pooled OR was determined by the Z-test and P<0.05 was considered statistically significant. Subgroup analysis was performed using stratification by cancer type and ethnicity, respectively.If a cancer type contained less than two independent individual studies, it was categorized into the “other cancers” group. Testing for heterogeneity among studies was performed by Q-test. A P≥0.10 for the Q-test indicated a lack of heterogeneity among the studies. Either a random-effects model or fixed-effects model was used to calculate pooled effect estimates in the presence or absence of heterogeneity The process of selection of studies for inclusion in the meta-analysis is summarized in The main results of the meta-analysis of the association between MTHFD1 polymorphisms and cancer risk are shown in 17 independent studies with a total of 12348 cases and 44132 controls were included in the meta-analysis for G1958A polymorphism. The Q-test of heterogeneity was not significant and we conducted analyses using fixed effect models in both overall and subgroup analyses. In overall population analyses, we did not find any associations between G1958A polymorphism and cancer susceptibility in any genetic model. In subgroup analysis by cancer type, no significant association with cancer risk was demonstrated in overall population with head and neck cancer , colorectal cancer, and prostate cancer. We can find that the population of subgroup of ALL is all Asians. For acute lymphoblastic leukemia, significantly decreased risk was observed in dominant model , and allelic model . With respect to other cancers, the results indicated that G1958A was significantly associated with a decreased other cancers risk under recessive model . G1958A polymorphism was significantly associated with decreased acute lymphoblastic leukemia risk under dominant model , and allelic contrast  in Asians.There are 20 studies (8446 cases and 14020 controls) analyzing the relation between G401A polymorphism and the risk of cancer. In overall population, the Q test of heterogeneity was not significant and we conducted analyses using fixed effect models except in dominant model and allelic model. After subgroup analyses by cancer type, significant heterogeneity was effectively removed in colon cancer. We did not detect the association between G401A polymorphism and cancer risk in overall analysis. In subgroup analyses stratified by cancer type, the data suggested that G401A was associated with a decreased colon cancer risk under dominant model .In order to compare the difference and evaluate the sensitivity of the meta-analyses, we conducted sensitivity analysis to evaluate the stability of the meta-analysis. A single study involved in the meta-analysis was deleted each time the analysis was performed to reflect the influence of the individual data set on the pooled ORs. The corresponding pooled ORs were not materially altered (data not shown). Hence, results of the sensitivity analysis suggest that the data in this meta-analysis are relatively stable and credible.Publication bias was assessed by visual inspection of funnel plots in which the standard error of the log (OR) of each study was plotted against its log (OR). An asymmetric plot suggests a possible publication bias. Funnel plot asymmetry was assessed by the method of Egger’s linear regression test, a linear regression approach for measuring funnel plot asymmetry on the natural logarithm scale of the OR. As a result, publication bias was identified in certain comparisons (G1958A: AA+AG vs GG). The detailed data were shown in SNP is the most common form of human genetic variation, and may contribute to individual’s susceptibility to cancer. However, the underlying molecular mechanism is unknown. Genetic polymorphisms in the folate pathway have been investigated in a wide variety of diseases, such as neural tube defects The results indicate that MTHFD1 G1958A and G401A are not risk factors for developing cancer in the overall study populations. The potential explanation is that the effect of a single polymorphism might have a limited impact on cancer susceptibility. This is in accordance with the hypothesis that cancer is a multifactorial disease that results from complex interactions between environmental and genetic factors. Nevertheless, considering that these 2 polymorphisms may play different roles in different cancer susceptibility among different ethnic subgroups and the frequencies of these 2 polymorphisms polymorphism might be different among different ethnic groups, we further conducted subgroup analysis by ethnicity and cancer type in current meta-analysis.In this meta-analysis, when stratifying by ethnicity we found that the association between MTHFD1 G1958A polymorphism a decreased risk of cancer was significant only in Asians, not in the Caucasian population. Although the reasons for this difference remain controversial, there are several studies showing that it depends on a combination of differences in polymorphism distributions with nongenetic factors. Therefore, the difference of this polymorphism of MTHFD1 in Caucasians and Asians may result from interactions with environmental and social factors. On the other hand, the sample size and numbers of studies in Asian group were not adequate to evaluate the association. Other factors such as selection bias and different matching criteria may also play a role. In addition, considering the multistage character of cancer, genetic factors may play a role at specific stages only, which may vary between populations. Therefore, larger-scale studies and combined analysis are warranted to further confirm the effect of ethnic difference in this polymorphism on cancer risks. For G1958A, in the stratified analysis by cancer type, our results demonstrated that no significant associations were found in any genetic model among studies of colorectal cancer, head and neck cancer, and prostate cancer. For acute lymphoblastic leukemia, significantly decreased risk was observed in dominant model, and allelic model. With respect to other cancers, the results indicated that MTHFD1 G1958A was significantly associated with a decreased other cancers risk under recessive model. For G401A, MTHFD1 G401A polymorphism was associated with a decreased colon cancer risk under dominant model. One factor that would contribute to the discrepancy among different studies is that these 2 polymorphisms might play a different role in different cancer sites. However, even at the same cancer site, considering the possible small effect size of these 2 polymorphisms to cancer risk and the relatively small sample size in some studies, the discrepancy will become apparent since some of these studies may be underpowered to detect a small but real association. For acute lymphoblastic leukemia, there were only two studies included in the analysis with limited sample sizes, therefore, the results should be interpreted with caution. Considering the limited studies and population numbers of “other cancers” included in the meta-analysis, this may increase the risk of false negative findings. It is well recognized that there is individual susceptibility to the same kind of cancer even with the same environmental exposure. Host factors, including polymorphisms of genes involved in carcinogenesis, may have accounted for this difference. The discrepancy may have resulted from a differential effect of selection criteria in different cancers, which was dictated by the sample size in our meta-analysis, as well as the weight of each study. Other factors such as matched criteria may also have conferred an effect. The above differences may contribute to the inconsistent results. Therefore, it is very important to determine the unified selection criteria and to choose larger sample population studies.Heterogeneity is a potential problem that might affect the interpretation of the results. Additionally, heterogeneity may influence the results of meta-analyses. For G401A, evident heterogeneity between studies was observed in overall comparisons and also in certain subgroup analyses. In overall analysis, significant between-study heterogeneity existed in allelic model comparison and dominant model comparison. After subgroup analyses by cancer type, the heterogeneity was removed in colon cancer. However, significant heterogeneity existed in allelic and dominant models when stratified according to cancer type. There are some factors that could have contributed toward the heterogeneity. First, the reason might be that different genetic backgrounds and the environment existed among different individuals. Second, one possibility involves differences in the matching status. However, we cannot confirm this possibility because no detailed information was provided. Third, we attempted to determine if the heterogeneity might also be explained by other variables such as smoking status, drinking status, and environmental factors included in the different studies, but are unable to provide a reliable answer to this question because we did not have access to individual level data for these variables.Some limitations of this meta-analysis should be acknowledged. Firstly, only studies published were included in this meta-analysis, and nonsignificant or negative findings may be unpublished Our meta-analysis suggests that the MTHFD1 G1958A polymorphism might be associated with a decreased a decreased risk of ALL and other cancers. Meanwhile, the MTHFD1 G401A might play a protective role in the development of colon cancer. More well-designed epidemiological studies on specific ethnicity and cancer types, which were not well covered by existing studies, will be necessary to validate the findings identified in the current meta-analysis. Moreover, further evaluating the effect of gene–gene and gene–environment interactions on the MTHFD1 polymorphisms and cancer risk are necessary.Figure S1The flow diagram for the review process and outcomes of inclusion and exclusion.(DOC)Click here for additional data file.Table S1Main characteristics of studies included in this meta-analysis.(DOC)Click here for additional data file.


Cellular chaperones and folding enzymes play central roles in the formation of positive-strand and negative-strand RNA virus infection. This article examines the key cellular chaperones and discusses evidence that these factors are diverted from their cellular functions to play alternative roles in virus infection. For most chaperones discussed, their primary role in the cell is to ensure protein quality control. They are system components that drive substrate protein folding, complex assembly or disaggregation. Their activities often depend upon co-chaperones and ATP hydrolysis. During plant virus infection, Hsp70 and Hsp90 proteins play central roles in the formation of membrane-bound replication complexes for certain members of the tombusvirus, tobamovirus, potyvirus, dianthovirus, potexvirus, and carmovirus genus. There are several co-chaperones, including Yjd1, RME-8, and Hsp40 that associate with the bromovirus replication complex, pomovirus TGB2, and tospovirus Nsm movement proteins. There are also examples of plant viruses that rely on chaperone systems in the endoplasmic reticulum (ER) to support cell-to-cell movement. TMV relies on calreticulin to promote virus intercellular transport. Calreticulin also resides in the plasmodesmata and plays a role in calcium sequestration as well as glycoprotein folding. The pomovirus TGB2 interacts with RME-8 in the endosome. The potexvirus TGB3 protein stimulates expression of ER resident chaperones via the bZIP60 transcription factor. Up-regulating factors involved in protein folding may be essential to handling the load of viral proteins translated along the ER. In addition, TGB3 stimulates SKP1 which is a co-factor in proteasomal degradation of cellular proteins. Such chaperones and co-factors are potential targets for antiviral defense. Positive-strand RNA viruses are among the largest group of viruses infecting plants worldwide and contribute to some of the most critical issues in agriculture. Two types of cellular alterations that are essential for (+) strand RNA virus replication and cell-to-cell movement include: (1) discrete and well characterized changes in the endomembrane architecture, and (2) the recruitment of host factors into viral protein containing complexes. With regard to changes in membrane architecture, viruses typically create membrane bound environments, called virus factories, to protect replication and assembly complexes from cellular defenses. At the electron microscopic level viroplasms are large virus factories that are amorphous structures containing virion particles, viral RNAs, and non-structural proteins, but typically exclude organelles. The term viroplasm was first used to describe such perinuclear virus factories produced by large DNA viruses and some (+) strand RNA viruses such as poxvirus and poliovirus. Recent research indicates that many plant infecting (+) strand RNA create microenvironments that are sometimes referred to as miniorganelles and these can range in size from vesicles or invaginations along organelle membranes to slightly larger virus factories. Typically these various membrane bound virus factories are induced by non-structural viral proteins and serve to concentrate replication proteins, viral genomes, and host proteins needed for efficient virus replication. Such extensive rearrangement of host membrane compartments are a hallmark of (+) strand RNA virus infection and the specific structures produces by various virus species have been reviewed in prior publications and will not be explored in depth here .The second cellular alteration mentioned above is the recruitment of host proteins, including cellular chaperones, to membrane bound sites required for virus replication and cell-to-cell movement. Among these are the heat shock protein (Hsp) 40, 70, 90, and 100 families of protein chaperones which are highly conserved across eukaryotes and are vital factors in the quality control of cellular proteins and protein complexes contributing to a wide range of cellular processes . ChaperoThis review discusses the various contributions of cellular chaperones and folding enzymes, including a variety of Hsp, to the formation of viral multi-protein complexes. This article contrasts the cellular functions of such proteins to provide the reader with adequate information to consider whether cellular chaperones are acting within their normal context to enable viral protein folding, trafficking, and functioning, or whether they are diverted from their normal activities to provide novel contributions to virus infection. Understanding the various contributions of protein chaperones to cellular and viral activities could enable researchers to determine when and where such factors could be targeted by antiviral compounds to suppress disease. Given the rapid evolution of plant viral genomes and the slow evolution of Hsp proteins, it is reasonable to consider that therapeutic interventions targeting host components of the viral replication and transport machinery could offer a reliable approach to controlling disease.Figure 1A). Nucleotide exchange factors (NEFs) are another set of cellular partners which stimulate dissociation of ADP and this fosters client dissociation upon refolding . Hsp70 can also partner with Hsp90 or Hsp100 (or ClpB) family to solubilize and refold protein aggregates into the native state  which identify and recruit substrates to Hsp70 through direct interactions . Hsp70 plays a vital role in localizing the TBSV replicase to organellar membranes and in membrane insertion of the replication proteins in vitro and in Nicotiana benthamiana plants  and interact with the 2a protein  it is the p33 and p92 proteins. The p92 is produced by translational readthrough of the UAG stop codon at the end of the p33 domain. Both of the replicase proteins have membrane anchoring domains and assemble with viral RNA template along membrane sites . Yeast Ha plants . Two yeaa plants . The 1a a plants . The yea protein . Mutatiotivation . While YDrosophila. In yeast, FHV requires Ydj1p and Hsp70 chaperones for virus replication  increased FHV RNA3 accumulation  is primarily an insect infecting virus and is not defined as a plant virus, but is important to consider alongside TBSV and BMV because there are key similarities with regard to the viral replicases, and in laboratory experiments FHV replicates in plant cells as well as yeast and lication . Single mulation . The comlymerase . Thus, wFigures 4), although its role in these complexes is not yet described is such detail. Affinity purified Tomato virus mosaic virus  replicase identified Hsp70, eEF1A, TOM1, and TOM2A proteins associating with membrane bound complexes. TOM1 and TOM2A are integral membrane proteins normally associated with the vacuolar membrane but are highjacked by the ToMV replicase to the membrane site of virus replication (Arabidopsis Hsc70-3 and the poly(A) binding protein (PABP) in ER-derived vesicles  strand RNA viruses include the potyviruses, closteroviruses, and pomoviruses. There is also evidence that the Hsp70 machinery contributes to the intercellular transport of (-) strand RNA genome containing tospoviruses.Figure 2B) and its activities appear to be unlike the function of cellular Hsp70 that is depicted in Figure 1. Closteroviruses are filamentous viruses that have a long flexuous particles formed by the major capsid protein and a short tail formed by the minor capsid protein (CPm). For Citrus tristeza virus (CTV) and Beet yellows virus (BYV) Hsp70h combined with the viral encoded p61 protein enables the assembly of full-length virions by specifically enabling tail assembly by CPm  interactions and virion assembly there are two examples. The first example is the closterovirus movement protein (MP) which is itself an Hsp70 homolog (Hsp70h). The Hsp70h plays dual roles in virion assembly and intercellular movement . Given the multimeric nature of CPs it is possible that the Hsp70 machinery ensures proper protein folding and prevents CP aggregation . First is RME-8, another DNAJ-like chaperone, which interacts with the pomovirus TGB2 MP . RME-8 localizes to endocytic vesicles and interacts with cytosolic Hsp70 to control clathrin-dependent endocytosis . This factor belongs to a subclass of the DNAJ family that only contains the J-domain. Such factors contribute to protein translocation into the mammalian ER, plant peroxisomes, and microtubule formation. The particular role of the NtDnaJ_M541 protein is not known but researchers proposed that it either mediates Hsp70 dependent mechanism of virus movement or itself provides the motive force for ribonucleoprotein translocation to the plasmodesmata  protein functions . Hsp100 N. tabacum Hsp101 enhances translation of Ω-containing constructs in yeast. Genetic analysis of Hsp101 interactions with the TMV 5′ leader showed that it binds to a poly(CAA) sequence within Ω and aids the recruitment of eIF4F . Its clients are often properly folded or are in a near native state. Hsp90 proteins have three functional domains: nucleotide-binding domain (NBD) at the N-terminus, the middle domain (MD) which is involved in client and co-chaperone binding, and the dimerization domain (DD) at the C-terminus .Hsp90 is a highly conserved eukaryotic molecular chaperone. It contributes to the stabilization, or activation of proteins that are involved in signal transduction, protein trafficking, and immunity. Hsp90 typically forms a dimer and its associations with client proteins, as for Hsp70, are regulated by co-chaperones as well as ATP binding and hydrolysis . The Hsp90 machinery also associates with ubiquitin-dependent degradation processes that contribute to immune regulation  and Rar1 are essential to the function of many NLR proteins . NLR proteins are pathogen sensors which contribute to host immunity by activating disease defense responses (Hsp90 can lead to the loss of NLR-mediated defense responses in plants. Most NLR proteins exist in a cell in a near native state but upon recognition of a pathogen effector the NLR proteins are folded and may form dimer or multimeric complexes that are necessary for immune regulation. The Hsp90–SGT1–Rar1 machinery is needed for Rx- or N-mediated resistance to Potato virus X (PVX) or TMV  or TMV , RPM1 orsyringae , Mi-1 reematodes , Mla-resn barley  among otto Hsp90 . This moRar1 was shown in soybean and Arabidopsis to be essential for the induction of pathogenesis-related (PR) gene expression and contributes to PAMP-mediated immunity  infection in susceptible hosts . The N. benthamiana Hsp90 was reported by Figure 3; There are also reports showing Hsp90 plays a positive role in Bamboo mosaic virus , Red clover necrotic mosaic virus , and FHV infection and it appears to provide different partnerships with the various viral replicases  machinery which regulates the folding of newly synthesized proteins . Proper Figure 1). In this system ERdj3, which is a member of the Hsp40 family, first binds to the unfolded proteins and recruits BiP . Similar to CRT/CNX system, BiP undergoes cylces of binding and release from unfolded proteins. Co-chaperones include ERdj3 which is an Hsp40 and PDI. When proteins fail to mature properly, they are directly cleared from the ER and degraded by the ubiquitin-proteasome system.Both the CRT/CNX and BiP chaperone systems sequester malformed proteins in the ER for refolding. N-linked glycosylation occurs through the transfer of a triglucosylated, branched chore oligosaccharide to a nascent polypeptide. The core oligosaccharide is trimmed by ER resident glucosidases to the monoglucosylated form. CNX and CRT recognize N-linked glycans attached to proteins which function to ensure the glucose is removed from the glycan. Improperly trimmed glycans can go through a reiterative process of transfers between the glucosidases and CNX/CRT to ensure proper maturation prior to ER export. BiP resembles other Hsp70 proteins in that its interactions with cofactors and substrates are regulated by the ATPase cycle  that functions during N-mediated resistance . In the absence of ER stress, BiP binds to the ER luminal domain of IRE1. Upon stress, BiP moves away from IRE1 and binds to the unfolded protein. IRE1 possesses a cytosolic endoribonuclease domain which is activated by the uncoupling of BiP and IRE1 . This complex includes the co-chaperones SKP1 and Cullin. While TGBp3 is not known to induce Hrd1p/Der3p it has been shown to activate expression of SKP1 (Curiously there are other ubiquitin ligases that interact with the 26S proteinase, including SCF E3 ubiquitin ligase complex ( of SKP1 . Other p of SKP1 . Up-reguYdj1, JJJ, JJ2, and ZOU1 are Hsp40 homologs in yeast that act independently of Ssa1/2 to enable replication of either BMV or FHV (Ydj1 appears to be uncoupled from Hsp70 for BMV replication. However, we do not yet understand whether these Hsp70 and Hsp40 separately or in combination regulate the folding and assembly or membrane anchoring of the viral replicases. It worth speculating that Hsp chaperones aid in recruiting essential host factors such as the PABP, eEF1a, or eIF4a into the replication complex or to stabilize associations between viral proteins that comprise the replication complexes (Hsp70 and virus movement, there is evidence that Hsp70 overexpression enhances virus movement but mechanistically we know very little about its role in the plasmodesmata or interactions with viral MPs. It is intriguing that the closterovirus MP is an Hsp70 homolog which functions to stabilize the virion as well as direct plasmodesmata trafficking. Perhaps further studies with this protein will provide insight into the activities Hsp70 contributes to intercellular trafficking.This article provides examples where plant viruses subvert a few key cellular chaperones and cofactors from their normal cellular function into viral protein complexes and examples where certain chaperones are likely to function within their normal cellular context, and viral proteins are the recognized substrates. With regard to subversion of chaperones, the tombusvirus, tobamovirus, and potyviruses require Hsp70, while BaMV and dianthoviruses require Hsp90 to participate early in the formation of active membrane anchored replication complexes . It is pV or FHV . The comomplexes . They maomplexes . In summYdp1, CPIP, RME-8, and NtDNAJ_M541 are J-domain proteins that are subverted by the plant viruses. Except for Ydp1 which associates with the BMV replicase, most interact with structural or MPs. CPIP is described as a factor that down-regulates the potyvirus CP, RME-8 is involved in endocytic trafficking of the pomovirus TGB2 protein from the plasma membrane toward the cell interior, and the role of the NtDNAJ_M541 protein is not yet defined . These fFinally, the potexvirus TGB3 protein up-regulates the expression of ER resident chaperones via bZIP60 transcription factor indicates that the ERQC machinery plays a vital role in plant virus infection , 2012a. While the above discussion of Hsp40, Hsp70, and Hsp90 supports the hypothesis that the chaperone machinery is somewhat dismantled and reconfigured to support virus replication, the newer data concerning CPIP, RME-8, and NtDNAJ_M541, and the ERQC could be viewed as evidence that the chaperone machinery is diverted to recognizing alternative substrates while their cellular functions are unaltered. In other words, the endocytic machinery and ERQC machinery appears to remain intact but the virus piggybacks onto the machinery to achieve a successful infection. This is important to consider because it could represent a manner in which the virus can evade defense within the host and avoid recognition by the immune system. Alternatively, we know so little about how plant viruses interact with the endocytic machinery or ERQC machinery but we do know that both systems can achieve protein degradation. Endosomes containing viral components could fuse with the vacuole to degrade viral components and ERQC machinery to down-regulate infection by identifying viral proteins as foreign or aberrant products that need to be degraded through the proteasome. Thus, these machineries could be part of an immune response. We do know from animal virus research that RNA viruses have mechanisms to cleverly evade recognition by the host immune system and this can include interacting with the host autophagic machinery in a manner that promotes infection. Future research is likely to examine the exciting possibilities that the ERQC machinery or endocytic machinery are natural extensions of the antiviral defense machinery or essential pathway to achieving successful infection. Understanding their roles in infection could be quite valuable for designing strategies for controlling virus disease which target host machinery that is vital for infection.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The current prognostic model to estimate the survival in hepatocellular carcinoma (HCC) patients treated with transarterial hepatic selective internal radiotherapy (SIRT) is not fully characterized. The aim of this study was to establish a new scoring model including assessment of both tumor responses and therapy-induced systemic changes in HCC patients to predict survival at an early time point post-SIRT.Between 2008 and 2012, 149 HCC patients treated with SIRT were included into this study. CT images and biomarkers in blood tested at one month post-SIRT were analyzed and correlated with clinical outcome. Tumor responses were assessed by RECIST 1.1, mRECIST, and Choi criteria. Kaplan-Meier methods were used to estimate survival curves. Cox regression was used in uni- and multivariable survival analyses and in the establishment of a prognostic model.A multivariate proportional hazards model was created based on the tumor response, the number of tumor nodules, the score of the model for end stage liver disease (MELD), and the serum C-reactive protein levels which were independent predictors of survival in HCC patients at one month post-SIRT. This prognostic model accurately differentiated the outcome of patients with different risk scores in this cohort (P<0.001). The model also had the ability to assign a predicted survival probability for individual patients.A new model to predict survival of HCC patients mainly based on tumor responses and therapy-induced systemic changes provides reliable prognosis and accurately discriminates the survival at an early time point after SIRT in these patients. Hepatocellular carcinoma (HCC) is the sixth most common malignancy worldwide with increasing incidence especially in the western world Staging systems are commonly used to classify malignant diseases. Staging of the underlying end-stage liver disease in HCC is usually performed using the Child-Pugh classification In this study, we have analyzed possible prognostic predictors including tumor responses, therapy-induced systemic changes in a cohort of HCC patients after SIRT. Our aim was to establish a scoring model which may provide reliable prognostic information about the clinical outcome of these patients at an early time point post-therapy.The records of consecutive patients who had received Yttrium-90 radioembolization therapy for HCC at the University Hospital of Essen, Germany, from June 2008 until December 2012 were reviewed. A total of 149 patients were identified and enrolled into this study. Baseline demographics and tumor characteristics are summarized in All data were analyzed retrospectively in an anonymous fashion according to the principles expressed in the Declaration of Helsinki which was approved by the Ethics Committee of the University Hospital of Essen. All patients gave their written consent that their information was stored in the hospital database and could be used for research.The microspheres used were glass-based  and are composed of 20–25 µm particles. Pretreatment mesenteric angiography and technetium-99 m macroaggregated albumin scans were performed to assess gastrointestinal flow and lung shunting One month after the intervention a physical examination, an abdominal CT scan and blood tests were performed. Thereafter, assessment was performed every 3 months. The endpoint of our study was December 31, 2012; the death of patient was confirmed by using the social security death index. Otherwise, patients were censored at the endpoint of our study. The CT attenuation (density) of each tumor was measured in Hounsfield units (HU) on the portal venous phase by drawing a region of interest around the margin of the entire tumor at baseline and 1-month after SIRT. The HU of all lesions were combined and a mean for each patient was calculated Survival time was calculated from the date of initial treatment to the date of death or loss to follow-up. The Kaplan–Meier analysis was applied to compare the survival distributions of different groups of patients. The MELD score was calculated using the equation: 9.57x ln [creatinine (mg/dl)] + 3.78 x ln [bilirubin (mg/dl)] + 11.2 x ln  + 6.43 The variables acquired at one month after the initial SIRT with a p value of <0.05 in the univariate analysis were selected to develop a multivariate Cox proportional hazards model with p value criteria for inclusion <0.1 . SPSS 18.0 software package was used for data analysis. The continuous variables from blood test were logarithmized and entered the survival analysis. A p value of <0.05 was considered statistically significant with a confidence interval of 95%.149 patients with HCC were treated with Yttrium-90 transarterial radioembolization. The most common adverse events were fatigue, nausea, vomiting, and abdominal pain. 106 (71%) patients died, 37 patients were alive, and 6 patients were lost to follow up at the endpoint of our study. As shown in Kaplan–Meier methods were used to calculate the median survival times and the survival probabilities for the “partial response (PR), stable disease (SD), and progression disease (PD)” according to RECIST 1.1, mRECIST, and Choi criteria. One month after SIRT therapy, the tumor responses for RECIST 1.1 and mRECIST were not associated with the survival in our setting . To calculate the probability of survival at t months of a given patient use the following equation: S(t) = S0(t)exp(score−2.6), as described previously When variables with univariate significance were introduced into in a multivariate model, the tumor response for Choi criteria, MELD score, the number of lesions, and serum CRP level were selected as independent prognostic predictors of survival . Based oThe c-statistics of the model for this cohort was 0.731 (95% [CI]  =  0.643–0.818). The c-statistics is defined as probability of concordance given comparability, and a c-statistics greater than 0.7 is generally considered a useful test This model showed that patients with lower scores consistently had a better long-term survival. When the prognosis of patients with risk score less than 2.1 were defined as “Good”, patients with scores higher than 3.1 were “Poor”, and other patients with score between 2.1 and 3.1 were classified as “Fair”. There were significant differences in the mean survival times  and the survival probabilities among patients with good, fair, and poor prognosis as analysed by the Kaplan–Meier method , resulting in at least 500,000 deaths per year accounts for 90% of all liver cancers It is well known that the determination of a prognosis is much more complex in HCC patients than in patients with other solid tumors due to the therapy-induced changes of liver function SIRT with 90-yttrium microspheres is an emerging tool for the treatment of primary and metastatic liver cancer that has shown promising efficiency. SIRT may lead to disease stabilization without actual shrinkage of tumor size, but showing decrease in hypervascularity and producing necrosis. The Choi criteria consider not only tumor size but also changes in tumor density on CT, resulting in a higher predictability of response In our study the underlying liver function as assessed by the MELD score, could also serve as an independent predictor of survival which was consistent with previous data We incorporated Choi criteria as a gauge of tumor response and MELD score as an indicator of liver disease severity. The multivariate analysis showed that the tumor response, the number of tumor nodules, MELD score and serum CRP levels independently determine the survival of these patients. A prognostic scoring model was established according to these variables. Being a continuous score, the new model could accurately differentiate the outcome of patients with different risk scores. High-risk patients who are expected to have a decreased survival probability can be thus identified at only one month after SIRT and could be subjected to intensify clinical monitoring or could be considered for early alternative therapeutic strategies. Specifically, the model has the ability to assign predicted survival probabilities. It is easy to calculate the risk score according to the model equation.Although the number of patients included in this study is limited, concerning the evaluation of prognosis after this locoregional therapy, the assessment of both tumor responses and therapy-induced changes of serum biomarkers which represent the systemic responses would be more relevant for HCC patients. In conclusion, this retrospective single-center study on a homogenous HCC cohort treated by SIRT is the first exploring approach to identify tumor responses and therapy-related changes of serum markers at one month after treatment for the early estimation of prognosis which is needed to be validated by further, larger prospective treatment studies.


Early emerging characteristics of visual orienting have been associated with a wide range of typical and atypical developmental outcomes. In the current study, we examined the development of visual disengagement in infants at risk for autism.We measured the efficiency of disengaging from a central visual stimulus to orient to a peripheral one in a cohort of 104 infants with and without familial risk for autism by virtue of having an older sibling with autism.At 7 months of age, disengagement was not robustly associated with later diagnostic outcomes. However, by 14 months, longer latencies to disengage in the subset of the risk group later diagnosed with autism was observed relative to other infants at risk and the low-risk control group. Moreover, between 7 months and 14 months, infants who were later diagnosed with autism at 36 months showed no consistent increases in the speed and flexibility of visual orienting. However, the latter developmental effect also characterized those infants who exhibited some form of developmental concerns (but not meeting criteria for autism) at 36 months.Infants who develop autism or other developmental concerns show atypicality in the development of visual attention skills from the first year of life. Autism spectrum disorders (ASD) (henceforth autism) are primarily defined on the basis of social and communication impairment in childhood. Recent lessons from genetic studies have highlighted substantial overlap between autism and related conditions Central to the phenotype of autism are patterns of focal and narrowed attention focus A specific developmental account of the origins of the narrow processing style observed in autism relates to early emerging difficulties in visual attention Supporting evidence for the proposal that the development of visual attention plays a critical role in autism comes from studies using the gap-overlap task with children and adults. This task measures flexibility in attention switching in response to the presentation of a peripheral target in the presence or absence of a central fixation stimulus. A disengagement index is typically derived from this task measuring the cost of disengaging from a central stimulus to orient to a peripheral one. Thus, the gap task is also thought to reflect top-down control of attention Little is known about the early development of visual attention in autism because the condition is rarely diagnosed before 2 years of age. Converging lines of evidence indicate that general deficits, as well as specific precursors to some symptoms, are present early on in autism [reviewed in Recent studies focusing on infants at risk for autism by virtue of having an older diagnosed sibling have highlighted a range of atypical brain and behavioral functions not only in those infants who receive a diagnosis but also in the at-risk group as a whole Preliminary evidence from several longitudinal studies suggests that characteristics of visual attention are associated with autism symptoms emerging in toddlerhood. In one study, an increase, rather than the expected decrease, in latencies to disengage from a central fixation to a peripheral object between 6 and 12 months characterized those infants who went on to a provisional autism diagnosis at 2 years In the current study, we tested the hypothesis that atypical visual disengagement during infancy is associated with autism-related outcomes in a new cohort of infants at risk for autism due to having an older sibling with the disorder [different from the group reported in our previously published work One hundred four infants from the British Autism Study of Infant Siblings (www.basisnetwork.org) took part in the current study . Along with several other measures, the infants were seen for the visual attention task when they were 6 to 10 months and again when they were 12 to 15 months. Subsequently, 52 (from 54) of those at risk for autism were seen for assessment around their second birthday and 53 were seen around their third birthday by an independent team. During the 36-month visit, a battery of clinical research measures was administered including the Autism Diagnostic Observation Schedule and the Autism Diagnostic Interview. Consensus ICD-10 criteria were used to ascertain diagnosis in a subgroup of infants at risk using all available information from all visits by experienced researchers . et al.n = 53). While recurrence rates approaching 30% have been found in other moderate size samples It is worth noting that the recurrence rate reported in the current study (32.1%) is higher than that reported in the large consortium paper recently published by Ozonoff During their first and second visits, infants were administered a battery of tasks containing stimuli that varied across different tasks and with short breaks in between. The stimuli and procedure for the gap task were adapted from those reported in our previous study (16). Infants were presented with the stimuli on a 46-inch liquid crystal display monitor, while seated on their parent’s lap at 60 cm distance. Looking behavior was monitored and recorded through video from an adjacent room. All trials in this task began with a centrally presented animation. The animations, subtending around 13.8°×18°, expanded and contracted to attract the infant to the center before the onset of the trial. The peripheral target was presented randomly either to the right or the left of the central fixation stimulus at the eccentricity of 15°. Peripheral targets were always the same  subtending 6.3°×6.3°. The purpose of freezing the motion of the central stimulus during the overlap period was to better match the relative attractiveness of the two competing stimuli. Without this feature, the central and peripheral stimuli would have been unbalanced, leading to artificially lengthened disengagement values. The peripheral target remained displayed until the infant looked at it or until 2.5 seconds elapsed. Once the infant looked to the target or if the maximum duration was reached, an attractive animation of an animal with sound replaced the peripheral target and the next trial was presented. The rate of trial presentation was controlled by the experimenter.In the baseline condition, the central fixation stimulus was extinguished and the peripheral target appeared simultaneously; in the overlap condition, the animated peripheral target appeared while the central fixation stimulus remained displayed (but not animated) so that the two stimuli overlapped. More overlap trials were presented because these trials are less likely to yield valid reaction times , especially in atypical infants. The two conditions were presented pseudorandomly across two blocks that were identical except for the central fixation stimulus, to maintain the infant’s interest in the task. Trial presentation continued until the infant became fussy or until a maximum of 70 trials was reached. The session was repeated if infants were excessively fussy. Of the 104 infants, data from 4 (2 at-risk) were excluded at the 7-month visit and 6 (2 at-risk) at the 14-month visit due to loss to follow-up, technical problems, or excessive fussiness or fatigue. Video recordings of the infants’ looking behavior overlaid in real time with input from the stimulus screen were coded offline frame by frame by coders who established reliability of at least .9 (Cohen’s κ) for the validity of trials and correlation between saccadic reaction times was .87 on a training dataset. Coders were blind to outcome status of the infants but not to risk group membership. Trials were considered invalid if any of the following criteria were met: 1) the infant looked away from the screen at any point; 2) the infant did not look at the central stimulus immediately before the presentation of the peripheral stimulus; or 3) the infant blinked or looked away during the presentation of the peripheral stimulus. Saccadic reaction time data were analyzed for valid trials where the infant oriented toward the peripheral target after 100 to 1200 milliseconds of its appearance. If the infants did not look at the peripheral target within this period, reaction time was not analyzed and the trial was considered a failure to disengage (percentages for each group are presented in ps>.12) or in the percentage of trials where they failed to disengage . Reaction times for each group in each condition are reported in ps>.11). While our focus was to test longitudinal developmental change between 7 and 14 months, in view of the age variability within each visit, we explored correlations between chronological age and RT measures in the two conditions within each visit. Age distribution within each visit was unrelated to RT , consistent with previous studies supporting relatively stable reaction times across the ages studied Neither the risk groups  nor groups defined based on 36-month outcomes  differed in the total number of trials completed or in the number of valid trials , indicating that Infants who had overall slower RTs exhibited poorer NVT scores at 36 months. There was no main effect of outcome group , indicating that overall reaction times did not differ among the groups.To test our hypothesis, we used a generalized linear model (GLM) with the following repeated measures factors: condition , age , and outcome group ascertained at 36 months  as a between-subjects factor. To test the specificity of any observed effects to the diagnostic outcomes, we included 36-month nonverbal T-score (NVT) . Planned comparisons focused on two potential explanations of the observed three-way interaction. First, we examined whether cross-sectional performance at 7 months or 14 months was associated with diagnostic outcomes  but no main effect of outcome  or condition×outcome interaction . At 14 months and after controlling for NVT, there was a significant main effect of condition  and a significant condition×outcome interaction  but no main effect of outcome . Bonferroni corrected post hoc tests revealed that the groups did not differ from each other at 7 months in either condition. However, at 14 months, the at-risk-ASD group showed prolonged overlap RT relative to the control group (p = .001), the at-risk-typical group (p = .001), and the at-risk-other group (p = .04).A three-way interaction of condition×age×outcome was significant  and the at-risk-typical  groups but not in the at-risk-other  or at-risk-ASD  groups. Moreover, specific gains in the overlap versus baseline conditions were evident from a significant condition×age interaction in the control group  and the at-risk-typical  groups but not in the at-risk-other  or at-risk-ASD  groups. The developmental changes were most pronounced in the group later diagnosed with ASD where 40% of infants had longer disengagement latencies at 14 months relative to 7 months. The second planned comparison explored whether developmental changes between 7 months and 14 months within each group were associated with 36-month diagnostic outcomes, controlling for NVT. We ran separate GLM for each group with the repeated measures factors condition and age and NVT as a covariate. The main effect of age was significant in the control  and the British Autism Study of Infant Siblings (BASIS) funding consortium led by Autistica (www.basisnetwork.org) to MHJ. Further support for some of the authors is from Autism Speaks and European Cooperation in Science and Technology ( COST) action BM1004. The BASIS team in alphabetical order: Simon Baron-Cohen, Rachel Bedford, Patrick Bolton, Susie Chandler, Holly Garwood, Teodora Gliga, Kristelle Hudry, Greg Pasco, Andrew Pickles, Leslie Tucker, and Agnes Volein. We are very grateful for the enormous contributions BASIS families have made toward this study.The authors report no biomedical financial interests or potential conflicts of interest.


The aim of this study was to develop and validate a reliable clinical prediction rule that could be employed to identify patients at higher likelihood of mortality among those with hematological malignancies (HMs) and bacterial bloodstream infections (BBSIs).3) ; nosocomial infection ; age ≥65 years ; and Charlson Comorbidity Index ≥4 . The variables unable to be evaluated at that time  were not included in the final logistic model. The equal-weight risk score model, which assigned 1 point to each risk factor, yielded good-excellent discrimination in both cohorts, with areas under the receiver operating curve of 0.83 versus 0.93  and good calibration (Hosmer-Lemshow P = 0.16 versus 0.75).We conducted a retrospective cohort study in nine Italian hematological units. The derivation cohort consisted of adult patients with BBSI and HMs admitted to the Catholic University Hospital (Rome) between January 2002 and December 2008. Survivors and nonsurvivors were compared to identify predictors of 30-day mortality. The validation cohort consisted of patients hospitalized with BBSI and HMs who were admitted in 8 other Italian hematological units between January 2009 and December 2010. The inclusion and exclusion criteria were identical for both cohorts, with type and stage of HMs used as matching criteria. In the derivation set (247 episodes), the multivariate analysis yielded the following significant mortality-related risk factors acute renal failure ; severe neutropenia (absolute neutrophil count <100/mmThe risk index accurately identifies patients with HMs and BBSIs at high risk for mortality; a better initial predictive approach may yield better therapeutic decisions for these patients, with an eventual reduction in mortality. Intensified treatment protocols with chemotherapy and/or hematological stem cell transplantation (HSCT) result in greater chances of curing patients with hematological malignancies (HMs). However, these potentially life-saving treatments increase the risk of infectious complications. Bloodstream infections (BSIs) are among the most common and severe complications observed in patients with HMs, particularly if they are neutropenic, with a prevalence ranging from 11 to 38% Staphylococcus aureus, Enterobacteriaceae, and Pseudomonas aeruginosa have been reported, at different frequencies, as the most prevalent organisms causing BSI in patients with HMs Coagulase-negative staphylococci (CoNS), The crude mortality rates for patients with BSI vary from 12% to 42%, and attributable mortality rates as high up to 30% have been reported Several studies have evaluated the epidemiological and clinical characteristics of bacterial BSI (BBSIs) in patients with HMs The aim of the present study, conducted in 9 large Italian hospitals, was to develop and validate a reliable, easy-to-use, clinical prediction rule that could be employed to identify patients with higher likelihood of mortality among those with HMs and BBSI.The institutional review board  approved the study, and informed consent was waived because of the retrospecive observational nature of the study.To identify risk factors for mortality in patients aged ≥18 years with HMs and BBSI, we conducted a cohort study in nine Italian hematological units. The derivation cohort consisted of patients with BBSI and HMs admitted to the Catholic University Hospital, located in Rome, between January 2002 and December 2008. Recurrent episodes of BBSI for the same patient were excluded from the study. The primary outcome measured was all-cause mortality 30 days after BBSI onset. The survivor and nonsurvivor subgroups were compared to identify predictors of 30-day mortality.The validation cohort consisted of individuals hospitalized with BBSI and HMs who were admitted to 8 other Italian hematological units between January 2009 and December 2010. The inclusion and exclusion criteria were identical to those used for the derivation cohort, and patients included in the validation cohort were matched with those in the derivation set cohort according to type and stage of HMs.Data collected from hospital charts and the laboratory database included patient demographics, disease and disease stage at time of BBSI, type of HSCT , medical history, clinical/laboratory findings, treatment, and outcome of infection.The following terms were defined before the data analysis.Bacillus spp., Propionibacterium spp., CoNS, micrococci) or (II) the presence of any bacterial species in at least 2 consecutive blood cultures in a patient with a systemic inflammatory response syndrome A BBSI was defined as an infection manifested by (I) the presence in at least 1 blood culture of bacteria other than skin contaminants  was regarded as the date of BBSI onset.Infections were classified as polymicrobial if 2 or more different genera were recovered from specimens drawn during the first 48 h of infection, regardless of whether the isolates came from the same or different blood culture sets.The BBSI was classified as nosocomial if the index blood culture had been drawn more than 48 h after admission to our hospital 3. Neutropenia was considered prolonged if the duration was ≥10 days and severe if the ANC was <100 cells/mm3.Neutropenia was defined as an absolute neutrophil count (ANC) of <500 cells/mmAcute renal failure was defined as a serum creatinine value >2 mg/dL in patients with previous normal renal function or an increase of >50% of the baseline creatinine level in patients with preexisting renal dysfunction.The impact of comorbidities was determined by the Charlson Comorbidity Index t test for normally distributed variables and by the Mann-Whitney U test for non-normally distributed variables. Categorical variables were evaluated with the χ2 or two-tailed Fisher's exact test. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the strength of any association that emerged. Values are expressed as the means ± standard deviations (SD) (continuous variables) or as percentages of the group from which they were derived . Two-tailed tests were used to determine statistical significance; a P value of <0.05 was considered significant.Continuous variables were compared by Student’s P ≤0.10) were included in a logistic regression model, and a backward stepwise approach was used to identify independent predictors of mortality; in addition, to develop a scoring system that could be applicable at the onset of bacteremia, the variables unable to be evaluated at that time  were not included in the final logistic model. Variables were retained in the final model if the P value was ≤ 0.05. The final regression model was transformed into a point-based rule. An equal-weight risk score model, which assigned 1 point to each risk factor, was assessed; in addition, an unequal-weight risk score model, with weighted scores assigned to each variable obtained by dividing each regression coefficient by half of the smallest coefficient and rounding to the nearest integer, was also performed Variables associated with mortality in the univariate analysis (The discriminatory power of the prediction rule in the derivation group was expressed as the area under the receiver-operating characteristic curve (AUROC). An AUROC of 0.5 indicates no discriminative ability, and perfect discrimination  is reflected by an AUROC of 1. An AUROC exceeding 0.8 is usually indicative of good to excellent prediction; those in the 0.7–0.8 and 0.6–0.7 ranges reflect moderate and low predictive power, respectively. The sensitivity and specificity of the prediction rule - each with 95% CIs - were calculated at different cut-off values. Positive and negative predictive values  were obtained with standard methods.All statistical analyses were performed using the Intercooled Stata program, version 11, for Windows .Four hundred and ninety-four patients with HMs and BSI were included in the study. Two hundred and fifty-one patients with HMs and BBSI met the inclusion criteria for the derivation cohort. Four were excluded because of missing data; thus, a total of 247 cases were included in the analysis.E. coli (22.2%), P. aeruginosa (14.5%), and S. aureus (9.9%). The overall 30-day mortality rate was 21.1% (52/247) , (52/247) .P = 0.007) and had nosocomial bacteremia (P = 0.003), indwelling urinary catheter (P<0.001), chronic viral hepatitis (P = 0.03), neutropenia (P = 0.02), prolonged neutropenia (P<0.001), severe neutropenia (P<0.001), Charlson Comorbidity Index ≥4 (P<0.001), and a clinical presentation with acute renal failure (P<0.001). Nonsurvivors were also more frequently treated with corticosteroids (P<0.001); no significant differences between survivors and nonsurvivors were observed in terms of the type of etiological agents causing BBSI, although polymicrobial BBSI was more frequent in nonsurvivors (P = 0.02).The univariate analysis revealed significant differences between the survivor and nonsurvivor subgroups. A significantly higher percentage of the nonsurvivor group were ≥65 years of age ; severe neutropenia ; nosocomial infection ; age ≥65 years ; and Charlson Comorbidity Index ≥4  .Three hundred and forty-eight patients with HMs and BBSI were observed in the 8 hospitals involved in the validation study, and 247 were selected by matching criteria with patients from the derivation set; these were included in the validation cohort. Their baseline characteristics are summarized in A scoring system that could be used to predict mortality was developed based on the independent risk factors that were identified in the multivariate analysis. An equal-weight risk score model was assessed first, assigning 1 point to each risk factor. The distributions of scores according to outcome and of variables for different score points are reported in P = 0.17) were indicative of good calibration. The prediction rules derived using this scoring system are listed in P<0.001).The AUROC for these data was 0.83 , indicating that the model is an excellent predictor of mortality . The resThe unequal-weight model, which assigned a different weight to each risk factor based on the multivariable logistic regression coefficient, had the same AUROC values and similar calibration for both the cohorts; because the equal-weight risk score model was easier to apply than the unequal model, we chose to report on the first model only.P<0.001) for scores >3. As shown P = 0.75).The prediction rules derived from the scoring system in the validation set are listed in P<0.001). The 3 cut-off displayed a sensitivity, specificity, PPV, NPV, and an overall accuracy of 67%, 92%, 63%, 93%, and 88%, respectively. In the combined cohort, the prediction rule had an AUROC of 0.86  (When we combined the two cohorts (n = 494), the predictive effects of the model were similar to those observed in the derivation and validation sets. The ORs for mortality associated with a score of ≥3 was 24.18  .A score that can be used to predict the likelihood of mortality is useful in the evaluation of patients with severe infections because it offers criteria to use when choosing a clinical management strategy. In high-risk populations, such as those admitted to intensive care units (ICUs), several scores are already widely used to predict clinical outcomes To the best of our knowledge, there have been no publications to date reporting the analysis of mortality-based scores in adult non-ICU patients affected by HMs with concurrent BBSI. We have developed and validated an easy-to-use risk stratification tool that is based on five variables that were found to be independently associated with mortality in a population of 494 patients.Our study was conducted in nine hematological centers that regularly admit high numbers of patients with HMs. The possible confounding effects of different types of HMs and/or various stages of treatment were minimized by matching patients in the derivation and validation cohorts according to these parameters.3), nosocomial infection, age ≥65 years, and Charlson Comorbidity Index ≥4.The multivariate model identified five factors associated with a higher mortality for patients with BBSI and HMs. These include acute renal failure, severe neutropenia  in the validation cohort than in the derivation cohort (20.6%); this finding is important considering the better global performance of this score in the validation cohort. In addition, the prevalence of Gram-negative agents, which are usually associated with a worse outcome, is significantly higher in the validation cohort than in the derivation cohort; this result reinforces the predictive value of the score independent of the etiological agents responsible for the BBSI.When a threshold of ≥3 was used, the specificity of prediction was over 90% in the derivation set and 94% in the validation set. Although sensitivity was relatively low at 58% in the derivation set, it reaches 83% in the validation set, and the high specificity of the prediction could improve the targeting of patients with a higher mortality risk.Decisions related to the initiation of more intensive care treatments are challenging, especially when they concern patients with cancer. While the decision to admit patients with cancer to ICUs is difficult to make and should be based on the prognosis for each patient, the application of close patient monitoring and life-support measures should be implemented in all patients with BBSI and a high risk of mortality .3 following cytotoxic chemotherapy) and/or significant medical co-morbidities; the second classification risk proposed is the Multinational Association for Supportive Care in Cancer (MASCC) scoring system, with a cut-off ≤21 to identify high-risk patients In the updated clinical practice guideline for the use of antimicrobial therapy in neutropenic patients with cancer developed by the Infectious Diseases Society of America (IDSA), two different risk classifications have been proposed for identifying high-risk patients: the first is based on expert opinion and identifies high-risk patients as those with anticipated prolonged (≥7 days duration) and profound neutropenia  Our scoring system has been developed specifically for hospitalized patients with HMs and concurrent BBSI, and it can be applied soon after BBSI onset. For this reason, it could be used for risk assessment in the setting of patients with HMs and BBSI, as well as in association with the classifications proposed in the IDSA guidelines for the management of patients with febrile neutropenia and cancer.Finally, inappropriate antimicrobial therapy during the empirical phase of treatment has been well demonstrated as the main risk factor for mortality in non-hematological patients with BBSI It is important to note that the application of the scoring system in empirical treatment decision-making processes needs further validation to quantify its value as a risk assessment tool compared with the clinical judgment of hospitalists, which is likely to be variable from one setting to another.In conclusion, we stress that BBSI in patients with HMs is a frequently observed clinical condition that requires prompt recognition and treatment with adequate antibacterial therapy, with consideration of the increasing number of multi-drug resistant etiological agents. Our results have demonstrated that patients with BBSI at higher levels of mortality risk can be reliably identified by the application of a simple clinical prediction rule based on five easy-to-define variables that are readily available at the time of BBSI onset. This type of risk stratification could be an important strategy for improving clinical decision-making in high-risk patients, such as patients with HMs.


Dynamic multileaf collimator (DMLC) and static multileaf collimator (SMLC), along with three-dimensional treatment planning system (3-D TPS), open the possibility of tissue compensation. A method using electronic tissue compensator (ETC) has been implemented in Eclipse 3-D TPS  at our center. The ETC was tested for head and neck conformal radiotherapy planning. The purpose of this study was to verify the feasibility of DMLC and SMLC in head and neck field irradiation for delivering homogeneous dose in the midplane at a pre-defined depth. In addition, emphasis was given to the dosimetric aspects in commissioning ETC in Eclipse. A Head and Neck Phantom  was used for the dosimetric verification. Planning was carried out for both DMLC and SMLC ETC plans. The dose calculated at central axis by eclipse with DMLC and SMLC was noted. This was compared with the doses measured on machine with ion chamber and thermoluminescence dosimetry (TLD). The calculated isodose curves and profiles were compared with the measured ones. The dose profiles along the two major axes from Eclipse were also compared with the profiles obtained from Amorphous Silicon (AS500) Electronic portal imaging device (EPID) on Clinac 6 EX machine. In uniform dose regions, measured dose values agreed with the calculated doses within 3%. Agreement between calculated and measured isodoses in the dose gradient zone was within 3 mm. The isodose curves and the profiles were found to be in good agreement with the measured curves and profiles. The measured and the calculated dose profiles along the two major axes were flat for both DMLC and SMLC. The dosimetric verification of ETC for both the linacs demonstrated the feasibility and the accuracy of the ETC treatment modality for achieving uniform dose distributions. Therefore, ETC can be used as a tool in head and neck treatment planning optimization for improved dose uniformity. Missing tissue compensation is of great importance to achieve dose homogeneity in head and neck radiotherapy (RT). Different strategies of tissue compensation have been reported. The multThe purpose of this study was to verify the feasibility of DMLC and SMLC in head and neck field irradiation for delivering homogeneous dose in the midplane at a pre-defined depth. In addition, the emphasis was given to the dosimetric aspects in commissioning ETC in eclipse. Additionally, dosimetric verification and comparison of ETC in phantom on two Varian linear accelerators (Clinac 6 EX and 2100 CD) were performed, and the results are reported.A head and neck phantom  procured earlier at our center was further modified to accommodate various dosimetric detectors. A special insert for an ion chamber  was fabricated in the midline of phantom normal to the transverse plane, and the same was used for thermoluminescence dosimetry (TLD) measurements. In addition, a special holder was designed to place the extended dose range  films in sagittal and coronal planes. The phantom has also the provision to fill water to maintain homogeneous tissue equivalent medium for dosimetry. This phantom was then scanned at 0.2 cm interval in a Somatom CT-simulator . The scanned images were exported via DICOM to Eclipse.We have MLC provision on two linear accelerators. The Clinac 6 EX and 2100 CD linear accelerators have Millennium 120- leaves MLC and 52-leaves MLC respectively. The leaves of these single-focus MLCs have a rounded leaf end. The Millennium MLC includes 60 leaf pairs of which the central 40 leaf pairs cast a shadow of 0.5 cm width at isocenter, and the remaining leaves cast a 1 cm wide shadow. The Clinac 2100 CD has 26 leaf pairs, all projecting a shadow of 1 cm at the isocenter. The MLC transmission specified by the manufacturer was less than 4% for these MLCs. In our setup, the measured interleaf and intraleaf transmission was found to be within 2% and 1.5% respectively for both the linacs. The leaf-positioning accuracy for both the linacs was within 0.1 cm.2 were placed anterio-posterior (AP) and posterio-anterior (PA) in HN phantom as shown in Two isocentric, parallel-opposed coplanar 6 MV photon beams with a field size of 10 × 10 cmElectronic compensation is available for open coplanar photon fields. One cannot add an electronic compensator to an electron field, and electronic compensators cannot be used for arc fields or mixed field types (both isocentric and fixed SSD fields). Moreover, one field may not contain both a physical plane compensator and an electronic compensator.3 was used for dose calculation. Isodose distribution was computed using pixel-to-pixel modified Batho inhomogeneity corrections. Dose profiles along the two major axes for central axis were generated with DMLC. Similar procedure was followed to achieve uniform dose distribution in the midplane with SMLC. For SMLC, nine intensity levels were used. Altogether, a total of four plans (two each for Clinac 6 EX and 2100 CD) were generated. The doses calculated at the isocenter by Eclipse with DMLC and SMLC were noted. The calculated doses in the coronal plane of the phantom were then exported to OmniPro™ IMRT film dosimetry system  for comparison with the actual delivered fluence (measured).The computational grid size of 2.5 × 2.5 × 2 mmAbsolute central axis dose was measured at the isocenter at the depth of midplane with 0.13 cc thimble ionization chamber and NE electrometer  in both the linacs under same set-up as in eclipse. The absolute dosimetry with ion chambers was carried out using TRS-398 dosimetry protocol. VerificaThese measurements were repeated with TLD chips . The TLD chips were irradiated in the midplane of the phantom at isocenter. The TLD measurements were performed on a commercial TLD-reader system  after 24 h after irradiation, and the average of the readings was estimated. For this, we assume our TLD as a benchmark with an estimated accuracy of ± 3%. TLD-100 (quantity 100) chips were annealed carefully at 400°C for an hour and subsequently cooled down to room temperature before using it for clinical purpose. These TLDs were irradiated after 24 h with Co-60 teletherapy machines with a known dose of 2 Gy at 5 cm depth in water-equivalent medium. These TLDs were read carefully using standard method mentioned above. Irrespective of the high variation in the sensitivity of an individual TLD in the entire group of 100, the segregated sensitivity variation in an individual TLD batch (approximately 20-30) was found to be ± 3%. Since the TLDs were read between 24 and 48 h post-irradiation, with proper handling no corrections were required and hence no corrections were applied. Measured doses with the ion chamber and TLD at central axis were then compared with calculated doses from eclipse TPS.Isodose distributions were also determined by EDR2 radiographic films. The film was kept inside the phantom in the midplane. The measured fluences in the form of isodose curves were then compared with the eclipse-calculated isodose curves. Similarly, the profiles measured on the EDR2 film were compared with those calculated by eclipse. Gamma analysis was performed with 3% and 3 mm as the pass criteria. The gamma histogram was generated and analyzed.Dose profiles along the two major axes passing through central axis were found to be flat across the treatment field for both DMLC and SMLC plans. These dose profiles were then compared with the profiles from Amorphous Silicon (AS500) electronic portal imaging device (EPID) on the Clinac 6 EX machine.The comparison of isodoses and the profiles shows that they are in good agreement and are thus clinically acceptable. Fgiures Usually fixed wedge filters are used for the lateral opposed fields in order to achieve a uniform dose, which could be improved with intensity-modulated fields, taking into account the missing tissue on the entire field area. Moreover, the ETC, compared to physical compensator, can speed up the treatment and also reduce skin dose, since it does not expose the patient to electron contamination. Electronic compensation does not require the high overhead in production that is present in mechanical compensators, and multi-beam treatments are much faster because there is no need to install a different physical compensator before execution of each treatment beam.For the DMLC-ETC plan, it was noticed that the monitor units (MU) were 1.15 times higher than those of SMLC-ETC plan. This in turn could increase the total treatment time and ultimately the integral dose for the DMLC-ETC plan. But this observation was true only up to the nine intensity levels for SMLC-ETC plan and not for levels higher than that. For more than nine intensity levels, a drastic increase (1.5 times) in MU was observed in SMLC-ETC plan compared to DMLC-ETC plan. However, this was not the scope of our study.The dosimetric verification of ETC for both the linacs demonstrated the feasibility and the accuracy of the ETC treatment modality for achieving uniform dose distributions. Flat profiles across the treatment field can be obtained. ETCs provided more flexibility in designing the profiles than the physical compensator method. Further advantages include finer intensity steps, more accurate dose distributions, adjustment during treatments and easy implementation. The use of ETC also eliminates the need for physical trays and mounting slots in the linac treatment head. The time required to design and fabricate the physical compensator can be saved. Therefore, ETC can be used as a tool in head and neck treatment planning optimization for improved dose uniformity. However, since the MLC dynamic mode is involved in the treatment, an extensive quality assurance should be carried out for individual plans.


Approximately 3% of employees are absent from work due to illness daily in Europe, while in some countries sickness absence exceeds 20 days per year. Based on a limited body of reliable studies, Greek employees in the private sector seem to be absent far less frequently (<5 days/year) compared to most of the industrialized world. The aim of this study was to estimate the levels of sickness absence in the private sector in Greece, using shipyard and national insurance data. Detailed data on absenteeism of employees in a large shipyard company during the period 1999–2006 were utilized. National data on compensated days due to sickness absence concerning all employees (around 2 million) insured by the Social Insurance Institute  were retrieved from the Institute’s annual statistical reports for the period 1987–2006. Sick-leave days per employee and sick-leave rate (%) were calculated, among other indicators. In the shipyard cohort, the employment time loss due to sick leave was 1%. The mean number of sick-leave days per employee in shipyards ranged between 4.6 and 8.7 and sick-leave rate (sickness absenteeism rate) varied among 2% and 3.7%. The corresponding indicators for IKA were estimated between 5 and 6.3 sick-leave days per insured employee (median 5.8), and 2.14–2.72% (median 2.49%), respectively. Short sick-leave spells (<4 days) may account at least for the 25% of the total number of sick-leave days, currently not recorded in national statistics. The level of sickness absence in the private sector in Greece was found to be higher than the suggested by previous reports and international comparative studies, but still remains one of the lowest in the industrialized world. In the 20-years national data, the results also showed a 7-year wave in sickness absence indexes (a decrease during the period 1991–1997 and an increase in 1998–2004) combined with a small yet significant decline as a general trend. These observations deserve detailed monitoring and could only partly be attributed to the compensation and unemployment rates in Greece so other possible reasons should be explored. Monitoring of sickness absences is an essential part of occupational health care. Even though sickness absence is not a simple function of ill health, and includes psychosocial factors and coping behaviors, it still remains a valuable tool to assess the impact of disease or other factors on a worker’s capacity and health status ,2. The rThe definition of absenteeism has been an issue of debate for several conferences of the International Labor Organization (ILO) , troubliSeveral indicators have been used to monitor absenteeism , like:  are fully compensated. In fact this lasts till the third day of a sick-leave spell, and afterwards the employee will be paid (50%) by the social insurance coverage scheme. Employees can get sickness benefits for up to one year and in some cases two years, before getting a disability pension, or even be fired if the employer or the insurance company argues that the employee is not willing to follow instructions to improve his health. In general an employee is entitled of sickness benefits for as many months as the years of employment completed. Sick leaves up to 2 days are commonly accepted by employee’s report of sickness (not exceeding 3–4 different spells per year). For sick-leave spells longer than 3 days a physician’s certificate is required and if the sick-leave spell is longer than 10 days it has to be validated by the insurance medical committee.In general, there are relatively few comparative studies on sickness absence, with several limitations  and it is considered that sickness absence has not been the subject of a systematic investigation in Greece so far . Based oDuring the 8-year study period the duration of sickness absence per employee ranged between 4.6 and 8.7 days/year, with an increasing tendency, while the mean duration of each sick-leave spell ranged between 5.9 and 8.6 days, demonstrating a declining trend. Around 1% of total employees were absent due to illness every day . FrequenShipyards data have shown that an average of 6.2 days lost per employee due to sick-leave compared to the estimated 5.9 days of IKA employees. Our data confirm that Greece has one of the lowest sickness absence rates in the European Union . HoweverSeveral reasons could explain the low sickness absence rate in Greece, as well as the diversity that exists across countries. Osterkamp and Röhn have reported several of these reasons in 2007; many applied in Greek case ,24. Couni.e., “presenteeism”) but the real effects of these parameters (unemployment or employment rate and retirement schemes) on sick leave duration are not well documented  = total number of sick-leave days/[total number of employees x number of working days (232)]The study population each year was calculated as the mean of the five corresponding values of the total number of employees, which it was updated every three months.–90%) of employees in the private sector, white and blue-collar workers [etc. . y = 1.33 in order to take into account the not recorded short spells (<4 days) extrapolating the relative data from the shipyard cohort . This approximation has also been suggested in the PhD thesis [Data regarding the total number of employees insured at IKA between 1987 and 2006, and compensated sick-leave days , were retrieved from the annual reports published online . InformaD thesis , but it Finally, we calculate sick leave rates by using as an annual mean the 232 days per employee. Statistical Package for Social Sciences (SPSS) program-version 17.0 was used for data entry and analysis. The low level of sickness absences in private sector in Greece was confirmed in our study, although it was found higher than the suggested in previous international studies. Sick leave rate was 2.5% and the total duration per employee was 5.8 days/year. Interestingly, short spells (<4 days) of sickness absences accounted at least for 25% of the total duration which currently is not recorded in national statistics. In the 20-years national data, results have shown a 7-year wave in sickness absence indexes (a decrease the period 1991–1997 and an increase in 1998–2004) combined with a small yet significant decline as a general trend. These observations deserve detailed attention and could only partly be attributed to the compensation and unemployment rates in Greece, while other factors should be explored in field studies whereas sick-leaves should always be monitored and evaluated as an assessment tool of the working environment.