Trypanosoma cruzi and is thus an important public health problem. Parasite persistence during chronic infection drives pathologic changes in the heart, including myocardial inflammation and progressive fibrosis, that contribute to clinical disease. Clinical manifestations of CCC span a range of symptoms, including cardiac arrhythmias, thromboembolic disease, dilated cardiomyopathy, and heart failure. This study aimed to investigate the role of signal transducer and activator of transcription-3 (STAT3) in cardiac pathology in a mouse model of CCC. STAT3 is a known cellular mediator of collagen deposition and fibrosis. Mice were infected with T. cruzi and then treated daily from 70 to 91 days post infection (DPI) with TTI-101, a small molecule inhibitor of STAT3; benznidazole; a combination of benznidazole and TTI-101; or vehicle alone. Cardiac function was evaluated at the beginning and end of treatment by echocardiography. By the end of treatment, STAT3 inhibition with TTI-101 eliminated cardiac fibrosis and fibrosis biomarkers but increased cardiac inflammation; serum levels of interleukin-6 (IL-6), and IFN−γ; cardiac gene expression of STAT1 and nuclear factor-κB (NF-κB); and upregulation of IL-6 and Type I and Type II IFN responses. Concurrently, decreased heart function was measured by echocardiography and myocardial strain. These results indicate that STAT3 plays a critical role in the cardiac inflammatory–fibrotic axis during CCC.Chronic Chagasic cardiomyopathy (CCC) is a severe clinical manifestation that develops in 30%–40% of individuals chronically infected with the protozoal parasite  Trypanosoma cruzi and currently affects an estimated 6–7 million people predominantly in Central and South AmericaChagas disease is caused by infection with the parasite The earliest cardiac histopathology findings in fatal cases of CCC were characterized by the persistence of parasites in the heart combined with diffuse fibrosis and inflammation in the myocardium . FurtherT. cruzi induces a pro-inflammatory response in which inflammatory cells infiltrate the myocardium, contributing to cardiac dysfunction  domain resulting in its phosphorylation  has been implicated as a key promoter of fibrosis development in animal models of fibrotic diseases . STAT3 arylation  at tyrosrylation . STAT3 hrylation  resultinrylation . Inhibitrylation . Importarylation . T. cruzhe heart . TogetheBased on the findings summarized above, we hypothesize that STAT3 contributes to the chronic low-grade inflammation and progression of fibrosis seen in CCC and that use of TTI-101 may reduce cardiac fibrosis and/or inflammation in a mouse model of CCC. We have previously reported on our BALB/c mouse model of CCC that replicates the persistent inflammation and progressive fibrosis characteristic of human disease . The stuT. cruzi H1 strain trypomastigotes, a DTU I strain originally isolated from a human patient with chronic cardiomyopathy in Mexico, were isolated from the blood of infected BALB/c mice [blood form trypomastigotes (bt)] at peak parasitemia [24–32 days post infection (DPI)] (n (DPI)] . Blood fT. cruzi bt suspended in 0.1 ml sterile saline (n = 80) or sterile saline alone (n = 20) as previously described , purchased from Taconic Biosciences, NY, USA, were injected intraperitoneally with 500 escribed . Mice weescribed .T. cruzi nuclear DNA . Data were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) , and parasite equivalents were calculated from a standard curve of known parasite contents . Total DNA was isolated from blood and heart tissue using a DNEasy 96 blood and tissue kit according to the manufacturer’s guidelines . Parasitemia and cardiac parasite burden were assessed by quantitative real-time PCR as previously described . Brieflycontents .in vitro experiments, a stock of TTI-101 was prepared in dimethyl sulfoxide (DMSO), which was added to cell culture media to achieve a final concentration of 20 µM. For in vivo experiments, TTI-101 was dissolved in DMSO to achieve a concentration of 25 mg/ml and administered once daily to mice from 70 to 91 DPI by intraperitoneal injection of 0.05 ml for a dose of 1.25 mg/mouse or 62.5 mg/kg body weight.TTI-101, formerly known as C-188-9, a proven inhibitor of STAT3 phosphorylation , was acqT. cruzi H1  was resuspended in 5% DMSO–95% HPMC  to a final concentration of 10 mg/ml. Mice were treated with 100 mg/kg benznidazole by oral gavage once daily from 70 to 91 DPI. This treatment scheme was previously shown to reduce cardiac parasite burdens to nearly undetectable levels in BALB/c mice acutely infected with cruzi H1 .T. cruzi infection. Cardiac fibroblast cells were grown for 24 h before infection to allow acclimation to culture conditions. All experimental groups were treated with a media change at this time, with the infected groups treated with three blood form T. cruzi Tc1 H1 trypomastigotes per cell, and the naive controls were treated with media alone. Cell lysate samples were collected at the following time points: 12, 24, 48, and 72 h. Protein in the lysate was quantified using a Pierce™ BCA Protein Assay Kit according to the manufacturer’s instructions , and all samples were diluted to 1 µg/µl. Protein isolated from lysate and cardiac tissue from mouse experiments (100 µg/well) was tested for concentrations of pY-STAT3 using ELISA . Samples were treated with RIPA Lysis and Extraction Buffer  for acquisition of lysate, according to manufacturer’s instructions. To test the effect of TTI-101 treatment on the levels of pY-STAT3 in cardiac fibroblasts, this experiment was repeated with TTI-101 treatment. Immediately after infection, the cell cultures were then treated with 50 µg/ml TTI-101, dissolved in DMSO, or DMSO alone. TTI-101 treatment was replenished at the same concentration with media changes every 24 h. Cell lysate samples were collected as previously, and lysates were tested for concentrations of pY-STAT3 using ELISA following the manufacturer’s instructions. Two technical and biological replicates were measured for each factor analyzed.Cell cultures were treated with the compound after growth with and without The infection and treatment timeline is illustrated in At 70 and 91 DPI, echocardiography was performed on anesthetized mice as described . BrieflyThe images were analyzed with Fujifilm Visualsonics VevoLab, Inc., Ontario, Canada echocardiogram analysis software. The left ventricle dimensions were obtained from the M-mode images to determine ejection fraction, stroke volume, and cardiac output. Each measurement represents the mean of 15 cardiac cycles of identical projection, transducer position, and angle of frozen images. Cardiac output values were normalized according to animal weight. The short-axis and long-axis left ventricle B-mode images were analyzed using the VevoStrain Fujifilm Visualsonics, Inc. Ontario, Canada software, with each measurement representing three cardiac cycles per position. The short-axis images were used to obtain circumferential strain. The long-axis images were used to obtain longitudinal strain.via opening of the thoracic cavity. The heart was collected by excision and divided in half with sterile instruments. Then, one half was immediately fixed in 10% formalin solution and the other flash-frozen for later processing. The samples were dehydrated, embedded in paraffin, sectioned to 5 mm, fixed, and stained with hematoxylin–eosin (H&E) and Masson’s trichrome.At 91 DPI, all mice were anesthetized to a surgical plane of anesthesia with an intraperitoneal injection of ketamine (100 mg/kg) and xylazine (10 mg/kg), then euthanized Imaging of the stained sections was performed on three representative images of the left ventricle in distinct regions that did not overlap. The imaging was performed with an Amscope United Scope LLC, CA, USA ME580 brightfield microscope equipped with LMPLAN40-065 ×40 objective using an 18-megapixel camera at fixed upper and lower light levels. ImageJ software was used to quantify the total area of the images that represented inflammatory infiltrate (H&E) or collagen (Masson’s trichrome). Two sequential sections of the left ventricle were imaged, with three representative images obtained from distinct non-overlapping portions of myocardium in each section, representing approximately 5% of the area per section. Briefly, for total fibrosis, numerical values of the total myocardium and the Masson’s trichrome-stained collagen area were obtained by adding the values of each area obtained with photography of ×40 microscopic fields in a section; the fraction of total area of collagen deposition per area of the entire section analyzed was calculated for each animal. Total heart area was quantified as the total area of the myocardium that appeared in each image, with white background subtracted from the total area. This same protocol was performed for quantification of area of inflammation using H&E staining.For immunohistochemistry (IHC) staining, mouse hearts were fixed in formalin, embedded in paraffin, and sectioned, as above. Heart sections were incubated with rabbit anti-CD4 monoclonal IgG  or mouse anti-CD8 monoclonal IgG  antibody followed by incubation with horseradish peroxidase (HRP)-conjugated secondary antibody. Brown color was carried out by incubation with the chromogen 3,3-diaminobenzidine (DAB), and nuclei were counterstained with hematoxylin.Frozen cardiac tissues were processed using Qiagen RNeasy kit to isolate and purify mRNA according to the manufacturer’s instructions. The mRNA was quantified and converted to cDNA using Qiagen RT2 First Strand kit. The cDNA was quantified with Nanodrop, and 20 μg was used in the Qiagen RT2 Profiler PCR Array Mouse Fibrosis kit with SYBR Green Rox Mastermix or NF-κB (Mm00476361_m1) and STAT1 (Mm00439518_m1) primers  with TaqMan™ Gene Expression Master Mix. Quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) was carried out on an Applied Biosystems Viia 7 Real-Time PCR system. The relative quantitation of the genes was performed according to the ΔCt method using GAPDH as the internal control gene for individual primers and the housekeeping genes included in the mouse fibrosis array.To analyze the circulating levels of fibrosis biomarkers, inflammatory cytokines, and cardiac injury biomarkers, serum was collected from mice at 91 DPI. Blood was collected after transection of the descending aorta and caudal vena cava following euthanasia, and serum was collected from the blood. Concentrations of fibrosis biomarkers TGF-β and PDGF-D were measured using sandwich enzyme-linked immunosorbent assay (ELISA) kits according to the manufacturer’s instructions . Concentrations of inflammatory cytokines IL-6 and IFN-γ were measured using ELISA kits according to the manufacturer’s instructions . Protein extracted from cardiac tissue was analyzed for IL-6 with ELISA kit as well. Protein in the sample was quantified using a Pierce™ BCA Protein Assay Kit according to the manufacturer’s instructions , and all samples were diluted to 1 µg/µl for analysis of 100 µg/well. After completing kit instructions, all plates were analyzed with a Bioteck colorimetric plate reader for appropriate absorbance wavelength per assay instructions (450 nm). All absorbance values were normalized to blank wells and compared to standard curve for calculation of concentrations. Two technical replicates were measured for each factor analyzed.post-hoc test. When comparing two treatment groups to each other, a Student’s t-test was used. Analyses were performed using GraphPad Prism, Inc., CA, USA software, version 3.0. p ≤ 0.05 was considered statistically significant.All results are shown as mean ± standard deviation of two independent animal experiments, with two technical replicates. One representative experiment is expressed. Data were found to be normally distributed with the Shapiro–Wilk normality test. Two-way ANOVA and multiple-comparisons test were used when comparing multiple treatment groups to the naive control or untreated (infected) control. These tests were followed by Tukey’s honestly significant difference T. cruzi-infected cardiac  expression, thereby reducing host inflammatory responses  and the Pathology and Histology Core at Baylor College of Medicine with funding from the NIH (P30 CA125123). TTI-101 was provided by Tvardi Therapeutics, Inc. DT is the inventor of several patents concerning TTI-101 that are owned by Baylor College of Medicine and licensed to Tvardi Therapeutics, Inc.; DT has ownership of this company’s stock.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Similar to the general population, the prevalence of central obesity is increasing among HIV-infected persons. There are little data on the burden of abdominal obesity using the waist-to-hip ratio measurement in HIV-infected patients in resource-limited settings, including Ethiopia. Therefore, this study aimed to assess the prevalence and associated factors of central obesity among HIV patients taking ART in an armed force comprehensive and specialized hospital, Addis Ababa, Ethiopia.  A cross-sectional study was conducted from March to April 2018. A systematic sampling method was used to select 353 study participants. Pretested World Health Organization stepwise questionnaire, document review, and anthropometric and biochemical measurements were used to collect data on different variables under the study. The collected data were entered into EpiData version 3 and analyzed by SPSS version 21. An adjusted odds ratio with 95% CI was considered to declare a statistically significant association. 3 , among respondents taking AZT + 3TC + EFV-based ART regimen , ABC + 3TC + ATV/r-based regimen , increased BMI , and abnormal blood pressure .  The prevalence of central obesity in this study was 71.7% (95% CI: 67%–76.4%). Besides, the odds of central obesity were associated with being female , among merchants , CD4 count <200 cells/mm It is possible to conclude that central obesity is a huge public health problem among the HIV-infected population in the study area. Being female, increased BMI, low CD4 count, AZT + 3TC + EFV, ABC + 3TC + ATV/r-based regimen, and abnormal blood pressure were associated with central obesity. Therefore, adequate attention must be paid to primary and secondary control of these factors to reduce the prevalence of abdominal obesity among HIV-infected patients. Effective viral suppression through the prolonged use of antiretroviral treatment (ART) has dramatically improved prognosis and survival evidenced by declining the toll of AIDS-related deaths . In EthiPeople living with treated HIV infection today enjoy greater life expectancy and thus are more exposed to the obesogenic environment and accumulate age-related cardiometabolic risk factors , 3. HIV-Studies showed that obesity affects 2 in 5 HIV-infected women and 1 in 5 HIV-infected men compared with men and women in the general population, respectively . HIV-infDifferent factors were implicated for central obesity such as female gender , advanceCentral obesity has been shown to correlate strongly with metabolic syndrome, hyperuricemia, and the progression of coronary calcium scores, which is a marker of cardiovascular disease (CVD) –18. AlsoCurrently, WHR is not so often used for evaluating central adiposity in the general population, and in its place waist circumference is the most widespread anthropometric measurement used. Besides, minimal agreement with BMI in identifying HIV/AIDS patients with increased cardiometabolic risk was reported . Hence, Even though numerous studies have been conducted on central obesity concerning HIV infection and ART in developed countries, there are few data on the burden of abdominal obesity using WHR in HIV-infected patients in resource-limited settings, including Ethiopia in general, and no study was done in the study area in particular. Therefore, this study aimed to assess the prevalence and associated factors of central obesity among HIV-infected patients taking ART in an armed force comprehensive and specialized hospital, Addis Ababa, Ethiopia, for the first time.A cross-sectional study was conducted from March to April 2018 at an armed force comprehensive and specialized hospital, Addis Ababa, which is the capital city of Ethiopia, the seat of the African Union, and economic commission for Africa. The hospital has been delivering health services to the defense forces including civilians in the Ministry of Defense. The hospital launched a free ART program at the end of 2003. The total number of subjects ever enrolled for HIV care before the study period was 4,329 . From the total numbers of adult subjects ever enrolled for HIV care, 2,263 adults were currently on ART in the hospital; from this, 1750 subjects were followed up during the study period.Individuals living with HIV/AIDS, aged ≥18 years, who had been receiving ART for at least 6 months or more and was able to communicate and provide informed consent were included in the study. Pregnant women and individuals who had a physical deformity of the waist and hip were excluded from the study.The sample size was calculated by using a single population proportion formula by taking a 50% proportion of central obesity among HIV patients on ART, since there was no study conducted in Ethiopia using WHR, 95% CI, and 5% margin of error, and the minimum final sample size becomes 384. The systematic sampling method was employed to select the study participants every 5th interval after preparing a sampling frame based on patient order when coming to the hospital for follow-up.We used the European cutoff point to interpret the waist-to-hip circumference ratio measurement for sub-Saharan African people according to International Diabetes Federation (IDF) recommendations; central obesity was defined as waist-to-hip ratio (WHR) ≥0.94 cm for men and ≥0.80 cm for women , 23.Data were collected using a structured questionnaire adapted from the WHO stepwise approach to chronic disease risk factor surveillance . The queWeight, height, waist circumference, and hip circumference were measured using calibrated equipment. Weight was measured using the SECA 704 medical weighing scale. Body mass index was calculated by dividing a person's weight in kilograms by the square of their height in meters. Waist circumference was measured at the horizontal plane which corresponds to the midpoint between the anterior superior iliac spine and the lower costal margin at the midclavicular line. Also, hip circumference measurement was done for participants by using a SECA 200 cm measuring tape. To improve the reliability of measurement for all anthropometric measurements, two readings were taken and the average of the two readings was recorded as the final measurement of the respondent.Blood pressure (BP) was measured using a standard adult arm cuff of mercury type sphygmomanometer after 5 min rest in the clinic by the nurses working in the ART clinic. To improve the reliability of measurement, three readings were taken with 5 min intervals and the average of the three readings was recorded as the final BP of the patient. But if the difference between the two readings was greater than 5 mmHg, a third measurement was taken and recorded as the final BP of the patient.Fasting blood was collected and analyzed by qualified laboratory technologists for biochemical measurements. The study subjects were requested to return to the clinics to provide fasting blood samples (4 ml) for blood glucose, lipid profile , and current CD4 count measurements the next day in case if they had eaten and the test was done in next morning. All measurements were analyzed in the Cobas Mira Plus spectrophotometer (Roche Diagnostics) equipped with calibration filters and DIASYS serum control.The questionnaire was first written in English and then translated into Amharic and back to English by linguistic experts, and it was tested before use. A research team of nine individuals  collected data on sociodemographic characteristics and performed clinical, behavioral, anthropometric, blood pressure, and biochemical measurements. A supervisory team  including the principal investigator was in place during the data collection. Both the interviewers and supervisors were trained for two days on the objective of the study, methods on how to collect data and interviewing approach, anthropometric measurement, biochemical measurement, and blood pressure measurement.The proper functioning of instruments, laboratory reagents, and technical performance was checked by using quality control samples (serum pool). Standard operating procedures (SOPs) were followed starting from sample collection up to result reporting. All laboratory procedures were handled by laboratory technologists. Before data analysis, cleaning was done.p value of less than 0.25 were selected for multivariable binary logistic regression analysis. Multivariable binary logistic regression models were used to isolate independent predictors of central obesity. A two-sided p value <0.05 along with an adjusted odds ratio (AOR) of 95% confidence interval was considered to declare statistically significant associations. The fitness of the model was checked using the Hosmer–Lemeshow test and the model was fitted having a p value of 0.57.The data were collected, cleaned, and checked for completeness and consistency manually. They were coded and entered into EpiData version 3.1. Then they were exported to SPSS (version 21.0) for further cleaning and statistical analysis. Descriptive statistics such as frequency, percentage, mean, and standard deviation were used to describe characteristics of the study population. Bivariate analysis was done using binary logistic regression, a variable of interest, and all covariate variables which had an association with the outcome variables at a Ethical clearance was obtained from the Institutional Review Board of the Institute of Health, Jimma University, and then permission was obtained from the armed force comprehensive and specialized hospital review board and ART clinic head. Written informed consent was secured from each study subject after the benefit, risk, and danger of participation were explained. Confidentiality was assured and maintained. A thumbprint or signature was used on the consent form. If the participants were diagnosed with lipid abnormality, fasting glucose impairment, and increased blood pressure, he/she was linked to the hospital for chronic care proper treatment, and follow-up of this disease as well coincides with HIV/ART disease. Every laboratory investigation was done according to the requirement of the patient. Health education on risk factors, consequences, and complications were provided to all of the participants after the compilation of data collection.A total of 353 respondents were included and analyzed in this study, yielding a response rate of 97%. 172 (48.7%) respondents were female. The mean age of the participants was 44.6 ± 8.85 years. Regarding education, 205 (58.1%) respondents have attended primary/secondary education. Concerning occupation, 87 (24.6%) of them were employed. Looking upon marital status, 248 (70.3%) respondents were married .117 (33.1%) respondents were found to be at WHO clinical stage II at baseline. After ART initiation, 209 (59.2%) of them had >107 months of ART duration at the time of the survey. Moreover, 185 (52.4%) respondents were found in TDF + 3TC + EFV-based ART regimen. The proportions of the participants who smoked cigarettes, drank alcohol, and chewed khat were 13 (3.7%), 131 (37.1%), and 12 (3.4%), respectively. 288 (81.6%) respondents were depressed at the time of the survey .The mean levels of TC, LDL, and HDL were 1.99.3 (±46.3), 117.6 (±56.4), and 49.1 (±14.82) mg/dl, respectively. The mean baseline and current CD4 counts were 182.58 (±144.19) and 455.69 (±262.84), respectively. The mean recent viral load was 10895.9 ± 79634. Likewise, the mean of the FBS level of the study participants was 108.55 (±48.879) mg/dl. As well, the mean waist circumference and hip circumference of the participants were 88.8 (±9.97) and 94.68 (±9.28) cm respectively .The prevalence of central obesity in this study was 71.7% (95% CI: 67%–76.4%). 155 (43.9%) female respondents developed central obesity. Besides, 138 (39.1%) respondents who developed central obesity attended primary/secondary education. As well, 94 (26.6%) respondents who developed central obesity were found to be at WHO clinical stage II at baseline. Furthermore, 154 (43.6%) respondents who developed central obesity had >107 months of ART duration. 125 (35.4%) respondents who developed central obesity were found in TDF + 3TC + EFV-based ART regimen. Among the participants who developed central obesity, 92 (26.1%) consumed alcohol. 129 (36.5%) of the respondents had abnormal total cholesterol (TC), and 172 (48.7%) had abnormal low-density lipoprotein (LDL) .All the variables were entered into multivariate binary logistic regression analysis by the enter method of model selection. After adjusting for potential confounders by logistic regression, sex, occupational status, type of ART regimen, current CD4 counts, BMI, and abnormal blood pressure were associated with central obesity.In this study, the odds of central obesity were 85.6  times higher among females compared to males. Likewise, the odds of central obesity were 18.8  times higher among merchants compared to housewives.3 compared to respondents who had a CD4 count >500 cells/mm3.Moreover, the odds of central obesity were decreased by 97%  among participants who had a CD4 count <200 cells/mmLikewise, the odds of central obesity were 8.73  times higher among respondents taking AZT + 3TC + EFV compared to AZT + 3TC + NPV-based ART regimen. However, participants taking ABC + 3TC + ATV/r-based regimen were 82%  protective against central obesity compared to AZT + 3TC + NPV-based ART regimen.2, the odds of central obesity increased by 3.5 .As the BMI of the participants increased by 1 kg/mThe odds of central obesity were 2.53  times higher among participants who had abnormal blood pressure when compared to their counterparts . This finding is higher than those in studies conducted elsewhere, for instance, 4% in the United States , 12.6% iThe present study also revealed that sex, occupational status, type of ART regimen, current CD4 counts, BMI, and abnormal blood pressure were associated with central obesity.The odds of central obesity were higher among females compared to males. This finding is supported by studies conducted in Brazil , NigeriaBesides, women have substantially more total adipose tissue than men, and these whole‐body sex differences are complemented by major differences in tissue distribution .The odds of central obesity were higher among merchants than among housewives. This may be related to having a high-income result in sedentary life which was associated with central obesity .The study further showed that increased BMI results in increased odds of central obesity. This finding is evidenced by studies done in Malaysia . This co3 but not among patients with higher CD4 counts [In this study, a higher CD4 count increased the odds of central obesity. This finding is similar to those in other studies conducted elsewhere , 25. How4 counts . The resAbnormal blood pressure results in higher odds of central obesity. This finding is in line with studies done in Cameroon  and IndoFurthermore, the odds of central obesity were higher among respondents taking AZT + 3TC + EFV compared to AZT + 3TC + NPV-based ART regimen. . LikewisThe strength of the present study is that central obesity is assessed using WHR, which is useful in early detecting possible signs of excess fat deposition in those infected with HIV. Although findings in this study are useful for policy, there are some noteworthy limitations. For example, the data were collected in a cross-sectional study; therefore, our study may not assign causation.From the findings of the study, it is possible to conclude that central obesity is a huge public health problem among the HIV-infected population in the study area. Being female, increased BMI, low CD4 count, AZT + 3TC + EFV, ABC + 3TC + ATV/r-based regimen, and abnormal blood pressure were associated with central obesity. Therefore, adequate attention must be paid to primary and secondary control of these factors to reduce the prevalence of abdominal obesity among HIV-infected patients.


Sepsis is an inflammatory response caused by infection with pathogenic microorganisms. The body shock caused by it is called septic shock. In view of this, we aimed to identify potential diagnostic gene biomarkers of the disease.Firstly, mRNAs expression data sets of septic shock were retrieved and downloaded from the GEO (Gene Expression Omnibus) database for differential expression analysis. Functional enrichment analysis was then used to identify the biological function of DEmRNAs . Machine learning analysis was used to determine the diagnostic gene biomarkers for septic shock. Thirdly, RT-PCR  verification was performed. Lastly, GSE65682 data set was utilized to further perform diagnostic and prognostic analysis of identified superlative diagnostic gene biomarkers.A total of 843 DEmRNAs, including 458 up-regulated and 385 down-regulated DEmRNAs were obtained in septic shock. 15 superlative diagnostic gene biomarkers  for septic shock were identified by machine learning analysis. RF (random forests), SVM (support vector machine) and DT (decision tree) models were used to construct classification models. The accuracy of the DT, SVM and RF models were very high. Interestingly, the RF model had the highest accuracy. It is worth mentioning that ARHGEF18 and FCER1A were related to survival. CACNA2D3 and DUSP3 participated in MAPK signaling pathway to regulate septic shock.Identified diagnostic gene biomarkers may be helpful in the diagnosis and therapy of patients with septic shock.The online version contains supplementary material available at 10.1186/s12879-022-07056-4. Sepsis is an inflammatory response caused by infection with pathogenic microorganisms. The body shock caused by it is called septic shock. Sepsis is a reaction to systemic infections , 2. SeptMost of septic shock is caused by microbial infections  . In earlDiagnosis and prognostic detection of diseases at the molecular level are now the general trend of development, which is also widely used by researchers in sepsis , 15. MohGEO  Gene Ex. The oriIn this study, Limma and metaMA packages were executed for identification of the DEmRNAs. The inverse normal method was used in the metaMA software package to merge P values. The FDR  is the result obtained by repeating the test and correction of the original P value by the Benjamin and Hochberg methods , 25. Thehttps://david.ncifcrf.gov/) database was used for GO  and KEGG  functional enrichment analysis [To identify the function of identified genes, the DAVID , ‘e1071’ package in R (https://cran.r-project.org/web/packages/e1071/index.html) and ‘random forests’ packet (https://cran.r-project.org/web/packages/randomForest/) was used to establish the DT model, SVM model and RF model, respectively. Tenfold cross-validation was used to compare the average misjudgment rates of the three models. Tenfold cross-validation was used to avoid the overfitting effect [https://pypi.org/project/mltools/1.0.2/).Firstly, the R language in glmnet package was used to reduce data dimensions. The package not only has a large number of models, but also is much faster . Secondlg effect , 31. TheThe GSE95233 data set  was used for electronic expression verification. The GSE65682 data set  contains 28 days of survival information of patients. This data set was used to further analyze the diagnostic and survival ability of key diagnostic gene biomarkers.9/L or < 4.0 × 109/L, or more than 10% immature neutrophils; (5) patients with initial septic shock; (6) patients had cardiovascular organ dysfunction, acute respiratory distress syndrome, dysfunction of two or more other organs; (7) patients had complete clinical data, including gender, age, height, weight, etc. Patients with a history of cancer or other diseases, chemotherapy, radiotherapy, etc., and incomplete clinical data were excluded. The individuals in the normal control group were gender and age matched with the case group and had no disease before and within 2 weeks after sampling. Those individual who took glucocorticoids, had a history of febrile disease or any chronic/acute disease that is slightly associated with inflammation within 2 weeks of sampling were excluded.The inclusion criteria for patients were diagnosed with septic shock. Detailed inclusion criteria for patients with septic shock were as follows: (1) the body temperature > 38 ℃ or < 36 ℃; (2) heart rate > 90 times per minute or greater than 2 standard deviations in the normal heart rate range of different ages; (3) respiratory rate > 20 times per minute or PaCO2  < 32 mmHg; (4) white blood cell count > 12.0 × 10−ΔΔCt method [According to the above criteria for septic shock, 16 blood samples from 8 patients and 8 normal controls were obtained for RT-PCR . Total RNA was extracted by using RNAliquid ultra-speed whole blood (liquid sample) kit . FastQuant cDNA synthesis kit  was used to synthesize the cDNA. RT-PCR was performed using SuperReal PreMix Plus (SYBR Green) SuperReal reagent . Each experiment was repeated three times. GAPDH  and ACTB (actin beta) were used as internal control for gene detection. The relative expression levels were calculated as fold-changes using the 2t method .This study was approved by the ethics committee the Second Affiliated Hospital of Shandong First Medical University (20200406).The GraphPad Prism was used to perform all statistical analyses. The significance cutoff of RT-PCR was P = 0.05 (Duncan’s multiple range test). One-way ANOVA  with orthogonal contrasts and mean comparison procedures were used to detect differences between cases and normal controls. Experiments were independently repeated at least 3 times.According to screening criteria of FDR < 0.01 and |Combined.ES|> 1.5, a total of 843 DEmRNAs were identified. Among which, 458 were up-regulated and 385 were down-regulated , all DEmRNAs were mainly involved in immune response, positive regulation of immune system process and leukocyte activation. In GO terms of CC (cell composition), all DEmRNAs were mainly involved in vesicle, cytoplasmic vesicle and nucleolus. In GO terms of MF (molecular function), all DEmRNAs were mainly involved in protein dimerization activity, cytokine binding and non-membrane spanning protein tyrosine kinase activity. The result is shown in Fig. After reducing data dimensions, a total of 28 DEmRNAs were retained Table A. AccordClassification models were constructed based on the screened 15 genes. The RF model had the highest accuracy. The accuracy, sensitivity, specificity and AUC of each model using the tenfold cross-validation process is listed in Table https://cran.r-project.org/web/packages/survival/index.html) was used to analyze the prognostic value of ARHGEF18 and FCER1A. The results showed that ARHGEF18 and FCER1A were significantly negatively correlated with survival  plays an important regulatory role in pancreatic cells . In patiMGST1 , an important redox and detoxification enzyme, play a crucial role in cell defense and hematopoiesis , 37. CLEKLRF1 (killer cell lectin like receptor F1) is an activating homodimeric C-type lectin-like receptor, which plays an important role in regulating the activity of natural killer cells and monocytes . RecentlThe protein encoded by ARHGEF18 (Rho/Rac guanine nucleotide exchange factor 18) plays an important role in activating eosinophils and other white blood cells . Sepsis The MAPK (mitogen-activated protein kinase) signaling pathway play a crucial part in the regulation of diseases, such as anti-inflammatory, analgesic, protective injury, etc. . MAPK coHowever, this study has certain limitations. Firstly, the sample size of the RT-PCR experiment is small, which may lead to a certain degree of error. More blood samples from septic shock patients are further needed to verify the expression of the identified mRNAs. Secondly, the molecular mechanism of DEmRNAs during septic shock has not been studied. More experiments are needed to further research the underlying mechanism of the disease.In this study, in order to identify potential diagnostic gene biomarkers of septic shock, machine learning method was performed, followed by prognostic analysis. 15 superlative diagnostic gene biomarkers  for septic shock were identified by machine learning analysis. It is worth mentioning that ARHGEF18 and FCER1A were related to survival. CACNA2D3 and DUSP3 participated in MAPK signaling pathway to regulate septic shock. Identified diagnostic gene biomarkers may be helpful in the diagnosis and therapy of patients with septic shock. This study can provide a basis for the research of septic shock.Additional file 1: Figure S1. Batch effect processing between different data sets.Additional file 2: Figure S2. Validation analysis in GSE95233 data set. A: Electronic expression validation of 15 diagnostic gene biomarkers in GSE95233 data set. **** represent P < 0.0001; B: ROC curve of DT classifier; C: ROC curve of RF classifier; D: ROC curve of SVM classifier. AUC: area under curve, ROC: receiver operating characteristic. Additional file 3: Table S1. All DEmRNAs.Additional file 4: Table S2. Calculation of Matthew’s Correlation Coefficient.


Entamoeba histolytica is a protozoan-pathogen-causing amoebic liver abscess (ALA). After amoeba establishment in the liver, it causes abundant infiltrate of neutrophils. Liver tissue damage by neutrophils results in part from anti-amoebic oxidative intermediates, including reactive oxygen species (ROS), reactive nitrogen species (RNS), and hypochlorous acid (HOCl), derived from the myeloperoxidase (MPO) enzyme. Ascorbic acid (ASC) is an antioxidant that acts as a scavenger for ROS and NOS-derived free radicals. No previous information regarding the effect of ASC concerning the participation of MPO in an experimental model of ALA in hamsters has been reported. Thus, the aim of the present work was to analyze the effect of ASC on acute ALA development and to measure the activity and gene expression of the MPO enzyme. Hamsters were treated with ASC (800 mg/kg) and then intrahepatically inoculated with E. histolytica trophozoites. Animals were sacrificed at 3, 6, and 12 h post-inoculation (p.i.), and liver samples were collected. The percentage of lesions, amoeba in situ count, MPO activity, and mpo gene expression were ascertained. Compared to ALA hamsters without ASC treatment as the control group (CT), the ALA group treated with ASC had a significant decrease in liver lesions  and viable amoeba count (12 h p.i.) and an increase in MPO activity (12 h p.i.) and mpo gene expression (6 h/12 h p.i.). These data suggest that ASC ameliorated liver damage caused by oxidizing products via modulation of mpo expression and activity. Entamoeba histolytica (E. histolytica). This species of amoeba can invade the intestine and then disseminate to target organs such as the liver and form amoebic liver abscesses (ALA)  . As docues (ALA) .The acute inflammatory response entails extensive leukocyte lysis causing, in part, liver parenchyma damage . Hepatic2O2) by superoxide dismutase enzyme (SOD). Ultimately, the H2O2 acts as a substrate for myeloperoxidase (MPO) to produce HClO  due to its antioxidant free radical scavenging activity and its presumably immunomodulatory protective role .Previous studies indicated that ASC might alleviate or prevent infections caused by bacteria, viruses, and parasites .Leishmania infantum (Tripanosoma cruzi (A protective effect of ASC against protozoan infections has been previously reported in mice infected with infantum  or Tripama cruzi . ProbablMesocricetus auratus), with 100 g body weight. The animals were handled in accordance with Mexican federal regulations for animal experimentation and care . The current protocol was developed based on the ARRIVE guidelines for reporting animal research and was approved by the Ethics in Research Committee of the Escuela Superior de Medicina, Instituto Politécnico Nacional (IPN). All hamsters used in this study were handled in accordance with the guidelines of the 2000 AVMA Panel of Euthanasia.This study was conducted in male golden hamsters  at 37°C, as previously described  . The organ was removed and weighed; then, the lesions were dissected, and their weight was quantified to obtain the percentage of damaged parenchyma. After this, fragments of lesions and healthy areas were fixed with 4% of paraformaldehyde for histological and immunochemistry analysis; additional liver samples were immediately frozen at −80°C in phosphate-buffered saline (PBS) pH 7.2 until use in MPO activity assays or in TRIzol  for real-time PCR (qRT-PCR) mpo expression assays. All procedures were conducted according to the methods previously described in detail . Animals received ASC (800 mg/kg of weight) by the orogastric route every 24 h for 3 days prior to amoeba inoculation. Hamsters were then inoculated by the intrahepatic route with 1 × 10n detail .Liver tissues fixed with 4% paraformaldehyde in PBS were dehydrated, embedded in paraffin, sliced into 7-μm sections, and stained with hematoxylin–eosin . Damaged2O2 in PBS for 30 min at room temperature (RT). Nonspecific reactions were blocked by treatment with 3% fetal bovine serum in PBS for 1 h at RT. The slides were incubated with D avidin solution , washed with PBS, and incubated with biotin solution for 15 min. Sections were incubated overnight at 4°C with 1 μg/ml rabbit polyclonal anti-MPO . The samples were then incubated with a biotin-goat anti-rabbit IgG H+L DS grade secondary antibody,  at 3 μg/ml for 1 h, followed by incubation with streptavidin–biotin peroxidase  at 2.5 μg/ml for 1 h. Diaminobenzidine  and H2O2 as substrate were added. The sections were counterstained with hematoxylin (1:9), dehydrated, and analyzed by microscopy   .g at 4°C for 15 min. The supernatant was removed and then stored at −80°C until use. Myeloperoxidase chlorination assays were performed following the manufacturer’s recommendations . The results were read with a 96-well fluorescence reader . Fluorescence was analyzed with an excitation wavelength of 480−495 nm and an emission wavelength of 515−525 nm to determine relative fluorescence units (RFUs). To obtain the MPO activity, the equation previously reported was applied . RNA quantification was carried out using a Nanodrop Lite . cDNA was synthesized according to previously reported methods . Expression of the mpo gene in hamsters (Gene iD: 101830171) was determined by utilizing a prediction of the mpo gene sequences found in the NCBI database. The sequence of the hamster gapdh, used as an internal control (Gene ID: 106022412), was taken from the same database. Specific oligonucleotide primers were generated using the aforementioned method, and the primer sequences employed for hamsters were mpoF 5′ GCTGTGCACT GAACACACCT3′ and mpoR 5′ TTTAGGAAGCTACGGGATGG′. The reaction mixture was used as previously described (gapdh (Expression of the  methods . Specifiescribed . qRT-PCRd (gapdh .t-test. If a significant (p<0.05) main effect or association was identified, the respective group means were compared using the Bonferroni test. All analyses were performed with the GraphPad Prism software version 6 .All experiments were performed at least three times independently. The results were expressed as means ± SD. The comparison between two groups was analyzed using Student’s unpaired two-tailed 1Ae, inserted box).Hematoxylin–eosin staining of ALA at 3, 6, and 12 h p.i. in hamsters treated or not treated with ASC showed inflammatory infiltrates constituted by polymorphonuclear leukocytes, mainly neutrophils (The percentage (%) of ALA at 3, 6, and 12 h was determined. ASC induced a significant decrease in the percentage of ALA lesions at 3, 6, and 12 h p.i. compared to the CT group , the inflammatory infiltrates showed cells with a positive staining for MPO . At 6 h p.i., no differences in MPO activity between the CT and ASC groups were observed. At 12 h p.i., the MPO activity increased significantly in ASC animals compared with the CT group (p<0.05) (MPO activity was determined in hamsters inoculated with mpo gene expression level was significantly increased at 6 (p<0.01) and 12 h p.i. (p<0.05) in the ASC-treated group relative to the CT group. At 3 h of ALA development, mpo gene expression was lower in the ASC group than in the CT group (p<0.01)  the hepatic parenchyma damage modification, (ii) the number of viable amoebae, (iii) the ALA resolution, and (iv) the MPO enzyme alteration. In this study, for the first time, it is reported that ASC induces histopathological changes in ALA evolution, as evidenced by the reduction in both hepatic parenchyma damage and the number of viable amoebae. As we hypothesized, the percentage of lesion of hamsters treated with ASC was smaller than CT hamsters; the viable amoebae percentage in ALA hamsters was lower (at 12 h p.i.) with ASC treatment. As we expected, the changes in the percentages of viable trophozoites are related to the kinetics of the expression and activity of MPO observed in the hamsters treated with ASC.E. histolytica and treated with ASC showed damaged trophozoites, as evidenced by lytic spaces, compared with the CT group; this finding showed that ASC changed the overall outcome of the early stages of ALA. In our study, the ASC diminished the ALA percentage, implying that ASC might have an effect on the resolution of ALA in the acute phase. No previous work on ALA and ASC has been reported; however, in other intracellular parasitosis, the effect of ASC has been evaluated. Plasmodium berghei and Plasmodium falciparum growth and that ASC absorption causes the accumulation of ROS in red-blood-infected cells, inducing the apoptosis of these parasites. In addition, T. cruzi, and in vivo, the parasites number in murine Chagas’s disease model was lower than that in the CT group.A pioneering work by E. histolytica and treated with ASC. The antioxidant effect of ASC may explain the reason why the number of viable amoebae present in inflammatory infiltrates was higher in the first hours after ALA establishment, since it has been reported that E. histolytica is susceptible to oxidizing agents , Escuela Superior de Medicina, Instituto Politécnico Nacional.ACB: performed experiments, data analysis, figure preparation and participated in writing and review of manuscript. RAJL: performed experiments, sampling, histopathology count, statistical analysis of histopathology data, and figure preparation. LMCJ: liver sampling processing for histopathology observation, myeloperoxidase labeling, figure preparation, and data analysis. MEDS: data analysis, figure editing, critical manuscript reading, manuscript formatting, and editing. JJSL: drafting preparation and critical reading. JPY: original conception, experimental design, manuscript drafting, reference curation, searching, retrieving, reading, sorting, and selection. All authors contributed to the article and approved the submitted version.This study was supported by Consejo Nacional de Ciencia y Técnología (Grant/Award Number: 181566) and Secretaria de Investigación y Posgrado, Instituto Politécnico Nacional (Grant/Award Number: 20190288).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


L3), Visceral Fat Area (VFAL3) and Subcutaneous Fat Area (SCFAL3). The second method was an software (Anthropometer3D), allowing an automatic multislice measurement of Lean Body Mass (LBMAnthro3D), Fat Body Mass (FBMAnthro3D), Muscle Body Mass (MBMAnthro3D), Visceral Fat Mass (VFMAnthro3D), and Sub-Cutaneous Fat Mass (SCFMAnthro3D) on the PET/CT. All anthropometrics parameters were normalised by the patient's height. The primary end point was overall survival time. Univariate and then stepwise multivariate cox analysis were performed for significant parameters. Finally, Spearman's correlation between MBAL3 and MBMAnthro3D was assessed. Forty-one (44%) patients had low skeletal muscle mass. The median overall survival was 18 months for low skeletal muscle mass patients versus 36 months for non-low skeletal muscle mass patients (p = 0.019). Low skeletal muscle mass , serums albumin level < 35 g/l (HR = 2.203 [1.19–4.09]), Buzby Index < 97.5 (HR = 2.31 [1.23–4.33]), WHO score = 0 (HR = 0.59 [0.31–0.86] and MBMAnthro3D < 8.56 kg/m2 (HR = 2.36 [1.41–3.90]) were the only significant features in univariates analysis. In the stepwise multivariate Cox analysis, only MBMAnthro3D < 8.56 kg/m2  and WHO score = 0  were significant. Finally, muscle quantified by MBAL3 and MBMAnthro3D were found to be highly correlated (Spearman = 0.9). Low skeletal muscle mass, assessed on the pre-treatment PET/CT is a powerful prognostic factor in patient treated by radiochemotherapy for a NSCLC. The automatic software Anthropometer3D can easily identify patients a risk that could benefit an adapted therapy.Low skeletal muscle mass is a well-known prognostic factor for patients treated for a non-small-cell lung cancer by surgery or chemotherapy. However, its impact in patients treated by exclusive radiochemotherapy has never been explored. Our study tries to evaluate the prognostic value of low skeletal muscle mass and other antropometric parameters on this population. Clinical, nutritional and anthropometric date were collected for 93 patients treated by radiochemotherapy for a NSCLC. Anthropometric parameters were measured on the PET/CT by two methods. The first method was a manual segmentation at level L3, used to define Muscle Body Area (MBA Despite progress in the care of this pathology, the prognostic remains poor with a 5-Years overall survival rate of 18.6%2.Lung cancer is one of the most common cancer in USA in 2018, and the deadliest cancer3 (CRT). This treatment can be given sequentially or concurrently, usually at a dose of 60–66 Gy in 30–33 fractions over 6–7 weeks. A radiotherapy boost is not recommended, a trial led to poorer survival4. Pretherapeutic evaluation includes cardiac, pulmonary function assessments and general status review. Nutritional status is a well-known prognostic factor in cancer, with an influence on toxicities, response to treatment, surgical complications and overall survival in several localisations6. The usual tools are Body Mass Index, weight history and albumin serum level. But in the last decades, there have been an increased interest for qualitative nutritional assessment, and particularly for skeletal muscle mass and sarcopenia.For patients with a disease who can benefit from the surgery because of a locally unresectable lesion or with a contraindication for surgery, the standard of care is radiotherapy, with or without platin-based chemotherapy12. Prado et al. showed that sarcopenia at baseline, defined by a quantitative approach, assessed by CT-scan of Skeletal Muscle Area (SMA) on the third lumbar vertebra, is a powerful prognostic factor for solid tumours of the respiratory and gastrointestinal tracts10. For lung cancer, prevalence of sarcopenia at diagnosis varies between 24 and 74%12. To our knowledge, the prognostic impact of sarcopenia  on overall survival in patient treated by exclusive radiochemotherapy, and more generally anthropometrical parameters evaluated by CT-scan10, has not yet been evaluated.Sarcopenia is a multifactorial metabolic syndrome characterized by a loss of skeletal muscle mass with or without loss of fat mass, associated with reduced physical function and poor tolerance to anticancer therapyThe primary objective was to evaluate the impact of low muscular mass (by Prado and Baumgartner) with two segmentation methods, in a population of patients treated by exclusive curative radio-chemotherapy for localised NSCLC.The second objectives were to evaluate the impact of clinical, nutritional and anthropometric parameters .18FDG-PET/CT with available images, and chemoradiotherapy for a curative aim treatment exclusively. Exclusion criteria included surgery, palliative treatment and presence of metastasis. Clinical, morphological, nutritional, and imaging parameters at baseline were collected.A single-center retrospective open study was performed in the Henri Becquerel Cancer Center, Rouen, France. A computerized review of patients treated for a NSCLC was undertaken. The population included all new patients referred to the radiotherapy department with a NSCLC between 2012 and 2015. The inclusion criteria were histologically confirmed NSCLC cancer, pre-therapeutic extension assessment by 13.As regarding baseline clinical data, age, sex, WHO performance status, histological subtypes, cancer location and TNM stage were collected. The baseline nutritional parameters were weight, weight loss history (over the last 6 months), size, body mass index (BMI), serum albumin levels, and Nutritional Risk Index3). Using Common Terminology Criteria for Adverse Events (CTCAE) V4.03, we collected grade ≥ 3 toxicities of the treatment for cardiac, gastric, pneumologic, biological and nephrologic events .We also collected treatment parameters: chemotherapy protocol, number of chemotherapy lines, type of treatment  radiotherapy dose (Gy), number of treatment days, volume treated at 60–66 Gy .With 18FDG-PET/CT), and overall survival.From our institution follow, we collected time to progression . Skeletal muscle was identified and quantified by use of Hounsfield Unit (HU) thresholds (− 29 to + 150)14. The L3 skeletal muscles were psoas, paraspinal muscles and abdominal wall muscles. We segmented the L3 skeletal muscle cross-sectional area on two adjacent cross-sectional images of the third lumbar vertebra, and the mean value for both images was defined as skeletal muscle lumbar 3 areas (cm2). This value was normalized for stature to estimate the Skeletal Muscle Index 14. Using the sex specific cut-offs defined by Prado et al., low skeletal muscle mass was defined as an SMI < 52.4cm2/m2 for men and < 38.5 cm2/m2 for women10. Using the same method, we measured Visceral Fat Mass (VFM) and Subcutaneous Fat Mass (SCFM).Skeletal muscle mass was assessed using the 18FDG-PET/CT. This software uses a multi-atlas segmentation method combined with an extrapolation of the body parts outside the field of acquisition. Lean Body Mass (LBM), Fat Body Mass (FBM), Muscle Body Mass (MBM), Visceral Fat Mass (VFM) and Subcutaneous Fat Mass (SCFM) can be measured automatically by this software. 18FDG-PET/CT was acquired from the mid-thigh toward the base of the skull. Body parts below the ischia and above the eyes are estimated by using extrapolation factors for two tissues of interest (kmuscle for muscles and kfat for fat) calculated on the CT atlases as the mean ratio of whole-body voxels of fat (or muscle) divided by the numbers of voxels of fat (or muscle) between the ischia to the eyes. This segmentation generates three types of mask from ischia to eyes: the first for the body shape, the second for the abdominal cavity and the third for the muscles. From the three masks are extracted the fat voxels, the visceral fat voxels and the muscles voxels from ischia to eyes by using Hounsfield Unit (HU) thresholds of -190 to -30 for fat voxels and -29 to + 150 for muscle voxels. Then, MBM, FBM, LBM, VFM and SCFM are calculated as shown in Fig. We also measured anthropometric parameters with a second method, using Anthropometer3D software developed by our team, which allows a multi-slice measurement of several anthropometrics parameters on the CT of Characteristics of the sample were described using counts and percentages for qualitative variables, and median and extreme values for quantitative variables. Comparison of sample characteristics according to sarcopenia was established by a Chi-squared test (or Fisher's exact test) for qualitative variables, and a Student's (or nonparametric Wilcoxon Mann Whitney) test for quantitative variables. A risk alpha level of 5% was retained for each test.Overall and progression-free survival curves were estimated by the Kaplan–Meier method. The Log-rank test and a Cox model were used to compare overall and progression-free survival based on patients' skeletal muscle mass status, clinical, and nutritional characteristics.Prognostic values of anthropometric parameters on overall survival were established by Receiver Operating Characteristic (ROC). When Area Under the Curves (AUC) were significantly greater than 0.5, an optimal threshold was defined by simultaneously maximizing sensitivity and specificity. A survival analysis according to this factor, both as a continuous variable (Cox model) and as a binary variable dichotomized by the threshold (log-rank test) thus defined, was then carried out to confirm the prognostic value.Significant variables in univariate analysis (p < 0.05) were then included in a multivariate survival analysis model. Note that, to be restrictive in the variable selection due to small sample size, anthropometric parameters will be selected according to Cox model p-value < 0.05 by considering variable as continuous. Then, a model selection was carried out using a stepwise approach to successively include and remove parameters in order to obtain a unique model containing only the most relevant variables.The study protocol has been approved by the Centre Henri Becquerel Cancer scientific and ethic committee (IRB 2104B). The informed consent was lifted by the Centre Henri Becquerel Cancer scientific and ethic committee. All the date were anonymized. All methods were carried out in accordance with the relevant guidelines and regulations.All the authors give consent for publication.Between 2012 and 2015, 209 patients were addressed for radiotherapy of a lung cancer to the Centre Henri Becquerel. Flow-chart is shown in Fig. 15, only 4 (4.1%) patients had a BMI below standard for age, 13 (13.9%) using albumin serum levels (13.9%), and 28 (30.1%) using weigh loss histories. The majority of patients  was addressed for a stage III NSCLC treatment. Patients of stage I and II were addressed because of surgical contraindications and were treated with conventional radiotherapy, because pulmonary stereotactic radiotherapy was not available in our centre at the time of treatment. Adenocarcinoma was assessed in 50% of women and 37% of men.The general and nutritional characteristics of the sample are described in Table 2m2 for men and 38.4cm2/m2 for women), 41 patients (44.1%) had low skeletal muscle mass. General and nutritional parameters of low skeletal muscle mass and non-low skeletal muscle mass patients are described in Table Based on thresholds defined by Prado  patients were dead, whose 32 of the 41 low skeletal muscle mass patients (78%) and 30 of the non-low skeletal muscle mass patients (57%). The median overall survival was 26.2 months, 17.6 months for low skeletal muscle mass patients versus 36 months for non-low skeletal muscle mass patients  and Skeletal Muscular Index (cm2/m2) , an overall survival median time of 16.1 months was observed for the 37 patients below this threshold, and of 38.7 months for the others . With a threshold of 46.92 cm2/m2 for Skeletal Muscular Index , an overall survival median time of 17.1 months was observed for the 38 patients below this threshold, and of 35.7 months for the others . In univariate survival analysis, BMI < 21, albumin serum level < 35 g/l and NRI < 97.5 were associated with worse overall survival while WHO score = 0 was associated with a better overall survival. As concerning anthropometric parameters, SMI < 46.92 cm2/m2, low skeletal muscle mass (defined by Prado and Muscular < 8.56 kg/m2) were associated with a worse overall survival  Fig. a,b. With= 2.35 1.2–3.89, p= 2.35 1.2–3.89, pAt date of analysis, 70 patients had progressed or relapsed, whose 28 of the 41 low skeletal muscle mass patients (68%) and 42 of the non-low skeletal muscle mass patients (80.8%). The median progression free survival was 12.9 months, 13.3 months for low skeletal muscle mass patients and 11.2 months for non-low skeletal muscle mass patients  presented grade ≥ 3 toxicities. Thirty-eight patients (49%) needed a chemotherapy dose reduction and 43 (55%) needed chemotherapy report more than 15 days. Fifteen patients (16%) had an interruption of radiotherapy for more than 3 days, and 86 patients (92.4%) received the radiotherapy dose prescribed. There was only a significant difference according to low skeletal muscle mass for cardiac toxicities, with 12.9% of low skeletal muscle mass patients and 5.1% of non-low skeletal muscle mass patients (p = 0.02). The mainly observed toxicity was neutropenia, but rarely induced febrile neutropenia, precisely only 4 patients (12.5%), all were low skeletal muscle mass. Toxicities were not associated with anthropometric parameters measured by Anthropometer3D.The impact of low skeletal muscle mass has been increasingly studied over the last 10 years and many studies confirm its prognostic interest. However, data in patients treated with radiotherapy or radiochemotherapy remain limited.16. Il a study of stage I lung cancer treated by stereotactic radiotherapy, skeletal muscle mass had an impact on survival17.For NSCLC treated by RTCT, there is to our knowledge only one study, but which only included 41 patients, the lack of power of the study did not allow to highlight the prognostic character of low skeletal muscle mass (25 minus versus 53 months p = 0.13)18, show that low skeletal muscle mass (considered as a reflect of sarcopenia) is a more powerful prognostic factor than usual nutritional parameters like weight lost and serum albumin levels and confirm the importance to evaluate low skeletal muscle mass before starting treatments. The SMI was not predictive of overall survival in our study, but a muscular mass < 8.56 kg/m2 was. However, there was a strong correlation coefficient between these two measures. Decazes has shown that these measurements were correlated , calls for optimised management even if low skeletal muscle mass was not associated with increased toxicity. However, this may be secondary to the lack of power and the small number of patients who had to have their treatment interrupted. In our study, the CT slice comes from 18FDG-PET/CT examination, with acquisition parameters different from those used by Prado, like the slice thickness: we use a 2 mm slice thickness, while Martin used a 5 mm slice thickness and Prado didn’t described the acquisition parameters. Fuch and al showed that 5 mm slice thickness significantly increased muscle sectional area by 1.11% compared to 2 mm (p < 0.001)20. It could lead to a bad classification of patients by underestimate muscular area at L3 in our study. But we also showed that low skeletal muscle mass can be evaluated by automatic segmentation on every slice of the 18FDG-PET/CT examination and it should reduce the impact of slice thickness.A review confirms the interest of low skeletal muscle mass specifically in lung cancer but the included studies do not specifically study the stage III population treated with radiochemotherapy21, baseline systemic inflammation associated with a more frequent rate of metastasis and progression23, and an impact of low skeletal muscle mass on chemotherapy volume and distribution8. The absences of significant differences for progression free survival and toxicities in our study suggests that low skeletal muscle mass is probably more a powerful reflect of the patient’s general condition than the tumour aggressiveness.Mechanisms by which low skeletal muscle mass confers increased mortality have not been actually explained. Several theories can be suggested to explain the effect: an increase of susceptibility to nosocomial infectionSome limitations of our study should be noted, especially as concerning the sample size and few events observed. Indeed, at date of analysis, 62 patients were dead, whose 32 of the 41 patients with low skeletal muscle mass and 30 of the other patients. Moreover, as low skeletal muscle mass was observed in only 41 participants, yet the majority of analyses are based on this very small group, thus limiting interpretation of our results. Then, sarcopenia is defined by Prado et al. by using sex specific cut-offs. Due to the small number of women in our sample (n = 20), predictive performances of these female specific cut-offs need to be considered.18FDG-PET/CT at baseline is an independent and robust prognostic factor for overall survival in patients with NSCLC treated by exclusive radiochemotherapy. These easily gathered imaging features can identify an at-risk population who need a specific therapy. The use of Anthropometer3D can provide a current evaluation of skeletal muscle mass at practice.To conclude, low skeletal muscle mass assessed by CT sequence on Supplementary Information.


Escherichia coli using five antibiotics, before measuring collateral effects on resistance to other paired antibiotics. During both isolation and phenotyping, we varied conditions in ways relevant in nature . This revealed that local abiotic conditions modified expression of resistance against both the antibiotic used during isolation and other antibiotics. Consequently, local conditions influenced collateral sensitivity in two ways: by favoring different sets of mutants  and by modifying expression of collateral effects for individual mutants. These results place collateral sensitivity in the context of environmental variation, with important implications for translation to real-world applications.Mutations conferring resistance to one antibiotic can increase (cross-resistance) or decrease  resistance to others. Antibiotic combinations displaying collateral sensitivity could be used in treatments that slow resistance evolution. However, lab-to-clinic translation requires understanding whether collateral effects are robust across different environmental conditions. Here, we isolated and characterized resistant mutants of IMPORTANCE When bacteria become resistant to an antibiotic, the genetic changes involved sometimes increase (cross-resistance) or decrease  their resistance to other antibiotics. Antibiotic combinations showing repeatable collateral sensitivity could be used in treatment to slow resistance evolution. However, collateral sensitivity interactions may depend on the local environmental conditions that bacteria experience, potentially reducing repeatability and clinical application. Here, we show that variation in local conditions  can influence collateral sensitivity in two ways: by favoring different sets of mutants during bacterial resistance evolution  and by modifying expression of collateral effects for individual mutants. This suggests that translation from the lab to the clinic of new approaches exploiting collateral sensitivity will be influenced by local abiotic conditions. As a result of antibiotic use, resistance is increasing in bacteria , necessi5–5–10–in vitro studies showed that different replicate populations exposed to the same antibiotic sometimes acquire collateral sensitivity to another antibiotic and sometimes do not  reduced pH (pH 6.5), as found in certain body compartments, including abscesses and parts of the gastrointestinal (GI) tract  between five pairs of antibiotics, each in four different experimental environments. Each antibiotic pair consisted of a selection antibiotic (which we used in mutant isolation) and a paired antibiotic . We chose pairs of antibiotics indicated by past work to at least sometimes display collateral sensitivity interactions , 6. The I) tract , 24; (iiI) tract ; and (ivI) tract .Escherichia coli K-12 MG1655 in the absence of antibiotics, before screening for antibiotic-resistant mutants, on agar with the selection antibiotic  for the relevant selection antibiotic and paired antibiotic, again across all four sets of abiotic conditions  was grown in liquid cultures (without antibiotics) overnight. (b) The cultures were transferred to agar with the same environmental conditions as during overnight growth  and the selection antibiotic at selection concentration. If there was growth after 48 h (resistant mutants), single colonies were picked and subjected to whole-genome sequencing (c). (d) For each mutant, dose response curves were measured against the selection antibiotic and a paired antibiotic in all four abiotic environments . From these curves we could calculate the antibiotic-free growth, the IC90 of the selection antibiotic, the IC90 of the paired antibiotic, and the growth at selection concentration (selection antibiotic only) for each mutant in each assay environment. (e) The same workflow was used for the other four antibiotic pairs, but using the selection and paired antibiotics given in the table. Although we show only single replicates here, we grew and selected 92 independent populations for each environment-antibiotic combination . We randomly chose up to 6 mutants to sequence and phenotype for each combination  The ancestral strain . Similarly, mutants selected in the same selection environment tended to have mutations affecting the same genes more often than mutants selected in different selection environments . Looking at each selection antibiotic separately, there was an effect of selection environment for cefuroxime  and streptomycin  but not trimethoprim and gentamicin (corrected P > 0.05). For streptomycin, the major differences were between the mutations selected in the low-pH environment and those in other selection environments. For cefuroxime, we found mutations in the penicillin-binding protein gene ftsI, but only in the presence of bile . Mutated genes influenced IC90 of chloramphenicol , GASC , and antibiotic-free growth . Mutated genes interacted with environment to influence IC90 of chloramphenicol , GASC , and antibiotic-free growth . Download FIG S2, TIF file, 0.3 MB.Phenotypes for chloramphenicol selected strains. (a) Nitrofurantoin resistance; (b) chloramphenicol resistance; (c) GASC of chloramphenicol; (d) antibiotic-free growth for the isolates resistant to chloramphenicol, where we have genotyping information. Thick lines show the mean phenotypic value for the 4 strains with mutations in Copyright © 2021 Allen et al.2021Allen et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mSystems.01055-21.8TABLE S1E. coli K-12 MG1655 reference) or the start position for multi-base-pair mutations. “Gene” is the gene(s) that was mutated; where there are two genes separated by a slash, the mutation occurred between them. The number in brackets represents either the nucleotide position from the start of the gene for mutations in coding regions or the distances to the neighboring genes in the case of intergenic mutations (minus and plus signs indicate upstream and downstream). “Gene mutated” is the gene influenced by the mutation, either because the mutation occurred in that gene or because the mutation affects the promoter region of that gene (as determined by breseq). Genes with a superscript 1 were intergenic mutations where breseq did not assign a gene, but we manually identified which promoter was influenced based on promoter information (https://ecocyc.org/). Genes with a superscript 2 are synonymous mutations; these are listed here and in hemB was mutated in other isolates, so we assigned this large deletion as affecting hemB. In some isolates, we could not identify any mutations, so no mutations information is given, but coverage is still reported. We were able to identify mutations in 84 of the strains. Download Table S1, DOCX file, 0.1 MB.Mutations identified in the 110 strains genotyped. Mutations were identified by breseq, run in consensus mode, using the genotype of the ancestral strain as a reference. All mutations detected by breseq are shown. “Sample Code” is shorthand for each mutant . Antibiotic abbreviations: CFR, cefuroxime; CHL, chloramphenicol; GEN, gentamicin; STR, streptomycin; TRM, trimethoprim. “Position” is the position in the genome that was mutated  , mutants selected against streptomycin and tested against tetracycline , and mutants selected against trimethoprim and tested against nitrofurantoin  but not for mutants selected against cefuroxime and tested against gentamicin . We found several genes that were consistently associated with collateral sensitivity to paired antibiotics , such as ubi mutants, which were on average collaterally sensitive to cefuroxime   , which in turn leads to a reduced membrane potential and hence reduced influx of aminoglycosides   compared ± 0.71) . For ind< 0.001) , and atp < 0.01) . Mutatio10.1128/mSystems.01055-21.3FIG S390 of antibiotics compared across directly and indirectly selected mutants and ancestral strain. Panels show resistance (IC90) to (a) cefuroxime, (b) gentamicin, (c) streptomycin, (d) trimethoprim, (e) tetracycline, (f) nitrofurantoin, (g) chloramphenicol, and (h) polymyxin B in the 4 different abiotic environments for all relevant strains. Strains shown are mutants directly selected with the same antibiotic (red box plots), mutants selected with another antibiotic , and the ancestral strain (yellow lines). See keys in individual panels for the specific drugs used for selection of mutants. Box plots show medians and interquartile ranges across all individual mutants measured under the relevant conditions (where the score for each mutant is first averaged across replicate assays). Data for the ancestral strain are the means of all independent estimates of IC90 under the relevant conditions (mean n = 4.8); error bars show standard errors of the means. y axes are log transformed and vary between panels. For the ancestral strain, assay environment had the strongest effects on resistance to gentamicin , streptomycin , and polymyxin , although only for gentamicin was this effect significant after accounting for multiple testing. All IC90 comparisons reported in the text are relative to the ancestral IC90 in the same abiotic environment. This could in theory influence the main effect of assay environment on collateral effects, as reported in the text (seen for the selection-paired drug combinations cefuroxime-gentamicin and trimethoprim-nitrofurantoin). However, we see the same main effect of assay environment in these two combinations when we use absolute IC90 of the paired drug for resistant mutants instead of IC90 relative to the ancestor . We also see a significant effect for streptomycin-selected mutants , which was not significant using IC90 relative to the ancestor (see the text). Download FIG S3, TIF file, 0.5 MB.ICCopyright © 2021 Allen et al.2021Allen et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 90 to nitrofurantoin: χ23 = 20.6; corrected P < 0.01). Mutants selected at high temperature  had significant collateral sensitivity. Mutations in phoPQ, which were associated with relatively high sensitivity to nitrofurantoin  (90 (not relative to the ancestor).Expression of average collateral effects to paired antibiotics also varied depending on the abiotic conditions during exposure to these antibiotics. For mutants selected against cefuroxime and trimethoprim, there was a significant effect of assay environment on average resistance to the paired antibiotics, relative to the ancestor under the same conditions  . Note th< 0.001) . Qualita< 0.001)  if we us29 = 38.3; corrected P < 0.001). For some mutants, this variation led to a switch between cross-resistance and collateral sensitivity, such as cpxA mutants  and pH  environments but were susceptible to cefuroxime at high temperature . cpxA is part of a two-component regulator which responds to misfolded proteins in the periplasm, activating the Cpx response, which has been shown to confer resistance to aminoglycosides (cpxA (as in our mutants) have the Cpx pathway locked into an activated state  of each mutant to its corresponding selection antibiotic in all four abiotic conditions: assay environment did not significantly alter the observed variation of IC90 among genotypes . Furthermore, we found no evidence that average IC90 was higher for mutants tested in sympatric environments (selection environment = assay environment) than in allopatric environments (selection environment ≠ assay environment), as would be the case if the mutations we detected conferred bigger increases in resistance in the abiotic conditions they were selected in . Thus, variation across assay environments of the relative changes in resistance (measured as IC90) conferred by different resistance mutations did not explain why we isolated different mutants in different conditions  may depend on local abiotic conditions . We founected in , 34 , measured in four sets of abiotic conditions (assay environment). Each panel shows mutants selected for resistance to the drug indicated for the panel, with the resistance to this selection drug as ICironment . MutantsCopyright © 2021 Allen et al.2021Allen et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 90. Therefore, GASC potentially provides additional information about why some types of mutants were associated with particular selection environments. GASC was calculated from the same dose-response curves as the IC90 and was positively correlated with IC90 across all mutants   . For cefuroxime-resistant mutants, GASC varied significantly among sets of mutants selected under different abiotic conditions, with bile-selected mutants performing best  (ftsI mutants) . Note that ftsI mutants also had relatively high IC90 on average . Our rationale here was that the mutations most beneficial during our screen (and most likely to result in formation of viable colonies) are not necessarily the mutations that confer the largest increases in IC 0.0001) . For tri< 0.001) , and the< 0.001)  varied a < 0.05) . Thus, amutants) . Consistmutants) . Despite average , althougfor GASC . In summ10.1128/mSystems.01055-21.5FIG S590 for 48 mutants, each measured against the relevant selection drug in each of the four assay environments. Each point is from an independent dose-response assay, with IC90 and GASC calculated from the same data. The different measures are transformed according to the way that the variables are input into the relevant models. These measures are highly correlated . Download FIG S5, TIF file, 0.1 MB.Correlation between GASC and ICCopyright © 2021 Allen et al.2021Allen et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mSystems.01055-21.6FIG S6E. coli with different drugs in different environments. The number of populations in which resistance was seen (one or more resistant colonies) varied with the combination of antibiotic and selection environment . The dashed line shows the maximum number of independent mutants . Download FIG S6, TIF file, 0.1 MB.Number of independent wells (of 92) which had resistant colonies after plating Copyright © 2021 Allen et al.2021Allen et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 90s . Relative to the ancestral strain in the absence of antibiotics , most types of resistant mutants showed evidence of growth costs, with 29 of the 57 mutants showing at least a 20% reduction in mean growth relative to the ancestor in one or more environment. However, this varied depending on the selection antibiotic   .F4,16 = 107, corrected P < 0.001; gentamicin, F5,12 = 23.0, corrected P < 0.001; streptomycin, F6,10 = 15.5, corrected P < 0.001; trimethoprim, F3,18 = 358, P < 0.001). For example, streptomycin-resistant mutants with mutations in atpG grew relatively poorly , as did trimethoprim-resistant mutants with phoPQ mutations . For all selection antibiotics, variation of antibiotic-free growth among different genotypes depended on the local abiotic conditions . Despite this, we did not find any evidence of matching between mutants and their selection environments in terms of antibiotic-free growth . In summary, local abiotic conditions modified the costs of resistance for our genotypes in the absence of antibiotics, but this did not explain the distribution of genotypes across selection environments in our mutant screen.For all selection antibiotics, mean antibiotic-free growth varied depending on which gene was mutated (y poorly  (differeutations  (differeacr) (marR and phoPQ) (ftsI and rpsL)  , global d phoPQ) , 40 and nd rpsL) –43, suggd rpsL) –, 45, whid rpsL) –, 47. In –E. coli .cpxA mutants only in a single environment at 37°C, we would have observed only that they mediate cross-resistance between gentamicin and cefuroxime  that have been found in previous studies  with additions to create variations in environmental conditions for basal, pH, and bile media. Basal medium (the base condition) is LB buffered at pH 7.0 with 0.1 M sodium hydrogen phosphate (Na2HPO4 and NaH2PO4). pH medium (acidic pH) is LB buffered at pH 6.5 with 0.1 M sodium hydrogen phosphate. Bile medium is LB with the addition of 0.5 g/liter of bile salts and buffered at pH 7.0 with 0.1 M sodium hydrogen phosphate. The temperature treatment uses the basal medium but is incubated at 42°C. When these conditions were on solid media , we instead used LB agar (Sigma-Aldrich), but other temperature and medium additions were the same. For overnight culture prior to assay, we incubated at 37°C in diluted LB .We used E. coli strain for each of the 4 selection environments , incubated for 20 h in the absence of antibiotics. Each entire culture was then transferred to a well of a 24-well plate containing 1 ml of agar corresponding to the same selection environment as the prior liquid culture plus one of five antibiotics at selection concentration . These selection concentrations were approximately equal to MICs for the ancestor. This meant the ancestral strain was effectively inhibited, but mutants with even moderately increased resistance could grow. A higher selection concentration was used for the aminoglycosides  in the pH medium because of the reduced efficacy against the ancestral strain in this environment (E. coli populations (each plated from a separate overnight culture grown in the absence of antibiotics) for each combination of 4 selection environments and 5 selection antibiotics. After incubation, each agar well was checked for the appearance of resistant colonies  according to the manufacturer’s instructions. Libraries were produced using the Illumina Nextera XT kit. Sequencing was performed on the Illumina HiSeq 4000 platform with 150-bp paired-end reads at the Functional Genomic Center, Zürich, Switzerland . Reads wftsI (phoQP) or having very closely related functions . In one mutant, we found a large deletion affecting multiple genes, including hemB, which was also altered in some other mutants; this mutation was designated as affecting hemB. This list of genes and gene sets was used in PERMANOVA (see “Statistics”). Sixteen mutants had multiple mutations affecting multiple genes ; in the other such cases, we categorized each mutant according to mutated genes known to be involved in resistance to the selection antibiotic . The ch600) using a spectrophotometer . Due to the time taken to read 64 plates, incubation and plate reading was staggered and the order was randomized. Some mutants failed to regrow during overnight incubation, resulting in some assay wells not being inoculated. To filter out these false negatives, we excluded OD600 scores from assay plates that were <0.03, but only if the OD600 in the overnight well (prior to inoculation of the assay well) was also <0.03 (both after subtracting blanks).We selected 75 strains with genotypic information to phenotype (and the ancestor), excluding mutants where very similar genotypes were already represented. Resistance of all mutants and the ancestral strain was quantified using broth dilution. For each antibiotic, we assayed each combination of strain, assay environment, and antibiotic concentration in four biological replicates, each in a separate temporal block. In each block of assays, we used a frozen master plate containing all strains organized in one of three randomized layouts  to inoculate a single preculture plate . We then incubated the preculture plate for 3 h before using it to inoculate all the overnight plates . Overnight cultures were then used to inoculate the assay plates using a pin replicator. Each mutant was tested against the relevant selection and paired antibiotics, and the ancestor was tested against all antibiotics, each at 8 concentrations (including zero) in each assay environment. After culturing assay plates for 20 h, we agitated the plates to resuspend bacteria and then measured the biomass of bacteria by optical density at 600 nm (OD90) of the selection antibiotic, (ii) growth at selection concentration (GASC) for the selection antibiotic, (iii) IC90 of the paired antibiotic, and (iv) growth in the absence of antibiotics. These phenotypes were calculated from the dose-response relationship data for the selection and paired antibiotics (for each replicate separately). We fitted a Hill function using nonlinear least-squares analysis in R (A × nk)/(nk + nC), where OD is the measured optical density and C is the antibiotic concentration. A is then the asymptote, k is the inflection point of the curve, and n is the Hill parameter controlling curve steepness. Thus, growth in the absence of antibiotics is equal to A, so for each combination of mutant and assay environment, antibiotic-free growth is the mean of the A parameters across all dose-response curves for this strain and environment. The IC90 for the selection and paired antibiotics can be calculated using the following formula, taking the parameters from the relevant fitted curve.For each mutant strain, we calculated four phenotypes: (i) 90% inhibitory concentration . In all cases, there was a strong correlation between the fit-dependent and fit-independent measures . We estmeasures .10.1128/mSystems.01055-21.7FIG S7P < 0.001). The red lines indicate exact identity. Download FIG S7, TIF file, 0.2 MB.Correlation between the 4 phenotypes measured when calculated using a method that requires a fitted Hill function (fit dependent) and a method that does not require a fitted Hill function (fit independent). Points represent values calculated from individual replicate dose-response measurements. Only points where both fit-dependent and fit-independent methods were calculated are plotted. The correlation measured by Pearson’s correlation coefficient is given at the bottom right of each panel; in all cases, this was significant  relative to the mean of the ancestral strain (log2 transformed) measured in the same environment. This controlled for any effects of assay environment on antibiotic inhibition of the ancestral strain .We treated the mutants selected for resistance against different antibiotics as independent data sets, due to the difficulty in comparing resistance across multiple antibiotics. This meant that we had only 5 independent mutants for chloramphenicol, which limited our ability to draw conclusions about this antibiotic. Therefore, we do not discuss the chloramphenicol-resistant mutants in the text, but they are included in the supplemental information for completeness . In eachl strain  and normFor each of the 4 phenotypes across the 4 antibiotic data sets, we fitted two mixed effects models . The fix10.1128/mSystems.01055-21.10TABLE S3Table S3, DOCX file, 0.03 MB.Significance of terms from phenotypic models reported in the text. Models A and B were separately fitted to the different phenotypes. The models were independently simplified to the minimal models by dropping nonsignificant (α = 0.05) terms (not included in higher-order interactions), as described in more detail in Materials and Methods. Grey cells are significant at an α value of 0.05 and are thus kept in minimal models. For the fixed-effect terms, cells are black if terms were still considered significant after multiple-testing correction ; this was tested only for fixed effects. Download Copyright © 2021 Allen et al.2021Allen et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the In both models, we included a nested random effect of strain  on intercept [+(1|Strain) in the lmer function] to account for variation between strains . We alsoF test for fixed-effects models and a likelihood ratio test (χ2 statistic) for mixed models. When the main effect of genotype is involved in a significant higher-order interaction (genotype: assay_environment) the main effect cannot be dropped, so significance is instead reported with an F test (on a type III ANOVA), regardless of whether the model contains random effects. For mixed models, the approximate degrees of freedom are calculated using lmerTest . These are reported in the text as corrected P values, and values below 0.05 are considered significant.For both the genotype and phenotype models, we tested 4 data sets (from four antibiotic combinations) for similar effects in parallel, therefore, when reporting the results of these tests, we give https://doi.org/10.5061/dryad.6m905qg16). Genomic data are relative to the reference genome of Escherichia coli K-12 MG1655 and have been uploaded as SNP tables relative to this reference in the Dryad data file.All raw data are available on Dryad (