IntroductionThere is a high prevalence of hypertensive crisis with myocardial injury, as evidenced by elevation in cardiac troponin levels. The risk factors predisposing patients to developing a myocardial injury, detectable troponin, and increase in serial troponin in this population are not known.Methodsth revision, Clinical Modification (ICD-10-CM) codes between 2016-2018 (n=467). Logistic regression was used to determine the important predictors of myocardial injury evidenced by troponin elevation >99th percentile of upper reference level (URL), detectable troponin (> 0.015 ng/ml), and increase in serial troponin levels.A retrospective study was designed to include all patients, presenting to the emergency room, diagnosed with hypertensive crisis, using International Classification of Diseases, 10Resultsth percentile of the initial troponin level among all patients was 0.433 ng/ml. A total of 15% had a myocardial injury, and the significant risk factors associated with it were body mass index (BMI) < 30 kg/m2 , congestive heart failure  and prior use of aspirin . About 35% had detectable troponin, and BMI < 30 kg/m2 , CHF , elevated creatinine  and age <61 years  were associated with it. The factors associated with an increase in serial troponin were BMI < 30 Kg/m2 , CHF , coronary artery disease  and non-Caucasian race .The 99Conclusionth percentile URL, and the majority of these patients have minimal changes in serial troponin. Low BMI was associated with higher initial and serial troponin levels, and this obesity paradox was stronger among females and older patients.About one-third of patients with the hypertensive crisis have detectable troponin. Still, among these, less than half have troponin levels >99 About one to two percent of patients with hypertension will develop hypertensive crisis in their lifetime . It occuth percentile of the upper reference level (URL), there is myocardial injury [th percentile cut-offs for each troponin assay to diagnose myocardial injury [For the accurate and timely diagnosis of myocardial injury, cardiac troponins (troponin) are the guideline-recommended biomarker. When there is an elevation of troponin of > 99l injury , 9. If sl injury . In morel injury , 12. Howl injury , 14. Thel injury -19. th percentile levels for patients admitted with hypertensive crisis, among all patients and different phenotypes, as well as identify the important risk factors associated with troponin levels among these patients. We were particularly interested in the association of troponin levels and body mass index (BMI), as this has never been explored among patients with hypertensive crisis, and because of the known “obesity paradox”. Despite the high prevalence of hypertensive crisis and possible adverse cardiovascular outcomes among those with elevated troponin, the risk factors associated with myocardial injury, detectable troponin and changes in serial troponin levels are largely not known , 20. TheMethodsth revision, Clinical Modification (ICD-10-CM) codes were used for the identification of the qualifying diagnoses. The cohort included all patients ≥ 18 years old with the diagnosis of hypertensive urgency, hypertensive emergency or unspecified hypertensive crisis, by utilizing the following primary diagnostic codes: I16.0, I16.1, and I16.9, respectively. Patients with missing laboratory values (n=43) or those diagnosed with the acute coronary syndrome (n=6) were excluded. A retrospective cohort study was designed based on emergency room visits at Cabell Huntington Hospital / Marshall University Medical Center. Data from the electronic medical record (EMR) was extracted for the time period from October 2016 to October 2018. International Classification of Diseases, 10Variables of InterestCovariates included baseline demographics: age, gender, race, BMI and smoking status; also comorbidities commonly associated with heart disease were included such as diabetes, hyperlipidemia, cerebrovascular accident, CAD, heart failure, chronic kidney disease (CKD), cerebrovascular accident (CVA) and peripheral vascular disease (PVD). ICD-10-CM codes were used to identify these comorbidities. Other selected variables were: initial creatinine levels, an average of first three systolic and diastolic blood pressures (SBP and DBP), as well as prior outpatient medications including calcium channel blockers, beta-blockers, diuretics, aspirin, angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB) and statins. Cardiac troponin assayth percentile of URL is ≥ 0.045 ng/ml [The troponin assay used during the study period was Siemens Dimension Vista® System ; limit of detection of 0.015 ng/ml, coefficient of variation (CV) 10% is 0.04 ng/ml and the 9945 ng/ml .Outcomesth percentile was identified for the whole cohort and by age, gender, BMI, CKD, and race. The primary outcome was myocardial injury  initial detectable troponin; 3) change in serial troponin. Those covariates significantly associated with the outcome in bivariate analyses (with p<0.10) were used to build a full adjusted model. Odds ratio (OR) were calculated with a 95% confidence interval (CI), comparing the significant risk factors associated with the outcome, using binary logistic regression analysis. We also tested for interactions between our main effect variable (BMI) and the subgroups  using models adjusted for variables similar to those included in the model. A two-sided p-value of ≤0.05 was considered significant for main effects and for interactions.The data are presented as proportions, means (± standard deviation), and in case of non-normal distribution as median with inter-quartile range (IQR). Comparisons were made using the t-test for normally distributed continuous variables, Mann-Whitney U-test for non-normally distributed continuous variables, Fisher exact test for categorical variables with any field including less than six patients, and chi-square test for the other categorical variables. The Kolmogorov-Smirnov test was used to test for normality. We tested the associations between all covariates and the three outcomes with troponin levels 1) initial >992 was calculated to assess the performance of the model. Because sensitive cardiac troponins had a non-normal distribution, natural log transformation was performed on values in ng/ml to avoid negative values. Data were analyzed using Statistical Package for Social Sciences (SPSS) software .To test for best fitting model between troponin levels and BMI, scatter plots and curve estimation analyses  were performed. Quadratic and cubic curves were not included, because scatter plots and the Loess curve did not reveal such an association and were clinically not expected. Rth, 95th, and 99th percentiles were 0.071 ng/ml, 0.137 ng/ml and 0.433 ng/ml respectively  to generate 99th percentile; however, the 90th and 95th percentiles were higher in African Americans than among Caucasians. A total of 467 patients presenting to the emergency department (ED) with a hypertensive emergency, hypertensive urgency or unspecified hypertensive crisis were included in the study. The median initial troponin value of all patients was ≤ 0.015 ng/ml , while the 90th percentile)Myocardial injury 2, age ≤ 61 years, elevated creatinine, and prior diagnosis of heart failure. Non-Caucasians and prior use of beta-blocker showed a non-significant trend towards detectable troponin  patients were found to have detectable troponin  . In obese patients n=229, 49%), the 959%, the 9Serial troponin levels2, non-Caucasians, prior diagnosis of heart failure, and prior CAD were significantly associated with an increase in troponin levels from baseline. Prior use of beta-blocker showed a non-significant trend towards change in troponin   had a positive change in serial troponin levels compared to their initial troponin Table . Patientth percentile) was stronger in older age group  and females . There was no effect modification by the subgroups between the association of BMI and detectable troponin and positive serial troponin levels . We identified the significant risk factors that predict myocardial injury, detectable troponin, and increase in serial troponin levels among hypertensive crisis patients. There are several major findings and important clinical implications of the study. This is the first study to establish 99th percentile of URL and the 99th percentile of troponin for all patients was 0.433 ng/ml . However, only < 1% had a relative change in serial troponin levels of greater than 20%, suggesting the majority of hypertensive crisis patients will be categorized as chronic myocardial injury. This provides evidence that serial troponin levels can potentially, more reliably, differentiate hypertensive crisis from ACS patients, rather than one-time troponin level. The second major finding is that patients with lower BMI, prior CHF and prior use of aspirin were the only factors significantly associated with myocardial injury. Interestingly, we also found the negative association between BMI and the myocardial injury was significantly stronger among female and older patient groups. Third, low BMI and prior diagnoses of CHF were the only variables consistently associated with all outcomes . First, in our cohort, 15% had troponin >99Other minor findings are 1) there was no association with presenting blood pressure  and troponin levels among all patients and in subgroups (data not shown); 2) elevated creatinine contributes to troponin being detectable but not with myocardial injury; 3) younger compared to older age group patients had higher association with detectable troponin , and overall troponin levels had a significant negative linear relationship with age; 4) no significant difference between troponin levels and gender after adjusting to significant covariates; 5) non-Caucasians were more likely to have detectable troponin and increase in serial troponin, but not myocardial injury.Body Mass Indexth percentile of the troponin level for patients with obesity was significantly lower than non-obese patients. Patients with BMI < 30 kg/m2 were significantly associated with higher odds of myocardial injury, detectable troponin, and an increase in serial troponin levels. After adjusting for significant covariates, there was a negative linear and inverse relationship between BMI and troponin level. Although it is well known that obesity is an independent risk factor for developing heart disease, there are several large databases that have demonstrated that obese patients have a better short and long term prognosis compared to normal/low weight, among those with CAD and heart failure patients; commonly referred to as the “obesity paradox” [In our study, the 99paradox” -28. We fparadox” . HoweverOther clinical variables and implicationsth percentile was lower among patients <61 years, lower creatinine and CKD, after adjusting for significant covariates, patients <61 years and elevated creatinine were independently associated with detectable troponin, but not with myocardial injury and serial troponin levels. There was a strong significant negative linear relationship between initial troponin and age and creatinine. This is in contrast to previous studies that have suggested a higher URL for older patients group. The mechanism for the negative relationship between troponin and age among these patients is not known. A possible explanation could be that secondary hypertension is more common among the younger patient group, and manifest different phenotype, etiology, and mechanisms of troponin leak compared to older counterparts. Another possible explanation for such a finding could be that younger patients tend to be less compliant with their medications leading to more extreme elevations in blood pressure and thus causing more myocardial injury. There is also less awareness, treatment, and control of hypertension in younger adults, and this adverse outcome is possibly reflected by higher troponin levels among our study patients.Even though the 99In our study, apart from BMI, those patients with a prior diagnosis of CHF, was the only other covariate, that had significantly higher odds of having a myocardial injury, a detectable troponin, and serial troponin levels. This is consistent with prior studies showing that most patients with stable chronic heart failure have detectable troponin, even when the heart failure is chronic and the patient is euvolemic. Patients with prior CAD had significantly higher odds of having detectable troponin levels and a non-significant trend towards myocardial injury, as they are more likely to have a myocardial injury because of increased myocardial oxygen demand and limited supply . LimitationsOur study was single-center, retrospective and our data set was limited to the use of ICD-10-CM data (from October 2015). Based on our data, we cannot investigate the different causes of troponin elevation. We could not identify other acute conditions , that are known to cause troponin elevation and may coexist at the time of admission. Despite this is the first study, we were limited by sample size. There are several other clinical tools  and methods of obesity measurement  which were unavailable and could potentially better explain troponin levels and warrants further research. About one-third of patients with the hypertensive crisis have detectable troponin. Still, among these patients, less than half have troponin levels consistent with myocardial injury, and the majority of these patients have minimal changes in serial troponin. Low BMI, prior CHF, and use of aspirin are independently associated with myocardial injury among these patients. Low BMI is significantly associated with higher initial and serial troponins. The significant negative association between BMI and the myocardial injury was stronger among female and older patient groups. These observations enhance our knowledge of pathophysiology, risk factors, and the clinical importance associated with baseline and serial troponin levels among hypertensive crisis patients.


Most of us have heard of hibernation—the period where bears go dormant to escape harsh winter conditions. But, did you know that some frogs also undergo a form of hibernation? It is known as aestivation, and it is a period of dormancy associated with dry, summer conditions. Scientists think that aestivation evolved so animals could cope with challenges like limited food and water supplies. During aestivation, an animal dramatically decreases its metabolic rate for many months to conserve energy—this depression in metabolic rates may be the only way to stay alive.Cyclorana alboguttata) tend to hang out during aestivation. The team found the burrows to be quite hypoxic, meaning extremely low in oxygen. So, the team built a tunnel where oxygen concentration would be high at one end and low at the other end to determine where the frogs spent most of their time during dry, summer conditions. It turns out that the frogs preferred the low oxygen end of the tunnel. But, how were they able to stay in low oxygen conditions for so long? And, why did they choose low oxygen when high oxygen conditions were still available?Apparently, frogs can also reduce their metabolic rates for months on end, and Giulia Rossi and her team set out to determine how they do it. First, Rossi and her team examined the small holes in the wet, clay soil where green-striped burrowing frogs (To find out, Rossi and her team explored how low oxygen levels affect the frogs’ metabolism. They exposed the frogs to low oxygen or normal oxygen conditions for 7 weeks as the frogs entered aestivation. While we know from decades of research that most hibernating and aestivating animals lower their metabolic rate to conserve energy, we do not necessarily know how fast they do it. The team found that the frogs exposed to low oxygen conditions were able to lower their metabolic rate much more rapidly than the frogs maintained under normal oxygen conditions. Moreover, once frogs were aestivating, those that had been exposed to low oxygen had lowered their metabolism by nearly 30% more than the frogs that had been maintained under normal oxygen conditions. So, frogs actually choose microhabitats with low oxygen levels, like those small cavities in the soil, to help them slow down their metabolic rate faster and by more. Consequently, this allows these frogs to also slow down how fast their bodies are using stored resources and ultimately gives them better odds of surviving.Usually, we think animals try to avoid hypoxic conditions. Yet, this study suggests that hypoxia-seeking behaviours are important for frogs during dormancy and that the actual microhabitats are important too. So, whether an organism hibernates or aestivates, it seems that being able to select microhabitats that are appropriate for dormancy may represent an adaptation key to the survival of species across the globe. These findings also suggest that some of these microhabitats, like a muddy burrow for example, which may seem unimportant to us humans, can actually represent the difference between life and death for some organisms. Indeed, these critical microhabitats may be of a higher priority for conservation than we may have previously understood. As global climate change, and particularly global warming persists, these periods of dormancy and associated habitats may become more and more important for the survival of an array of animals and their ecosystems.It turns out that frogs are like sleeping beauty, but in small holes without oxygen…Section Editor: Jodie L. Rummerewalsh.sci@gmail.comIllustration by Erin Walsh; Email:


Persistent inflammation, immunosuppression and catabolism syndrome (PIICS) often occur after critical care. Disseminated intravascular coagulation (DIC) is expected to be associated independently with PIICS development. We retrospectively analyzed 5397 patients admitted to the Hitachi General Hospital emergency and critical care center during four years. We classified PIICS as C-reactive protein > 3.0 mg/dL or albumin < 3.0 g/dL or lymphocyte count < 800/μL on day 14. Prolonged hospital stay (>14 days) without PIICS and early recovery  were assigned as non-PIICS. Early death (death within 14 days) was identified. We analyzed the association between the International Society on Thrombosis and Haemostasis overt DIC and PIICS outcomes. Results revealed 488 PIICS, 416 early death and 4493 non-PIICS cases. Analyses showed DIC as associated significantly with mortality, the Barthel index at discharge and PIICS development. Multivariate regression analysis and a generalized structural equation model identified DIC on admission as an independent risk factor for PIICS in surviving patients. Persistent inflammation, immunosuppression and catabolism syndrome (PIICS) is prolonged inflammation associated with immunodeficiency and catabolism, often affecting patients after critical care ,2. Inter3, weight loss of > 10% or body mass index < 18 during hospitalization, Creatinine height index < 80%, albumin < 3.0 gm/dL, pre-albumin < 10 mg/dL and retinol binding protein < 10 μg/dL1 . Coagulation analyses of patients’ plasma were performed on admission with opt-out patient agreements.For the classification of PIICS, we first extracted “early death” patients, who died within 14 days and “early recovery” patients, who were discharged alive within 14 days. The other population included patients for whom the hospital stay was >14 days.Subsequently, PIICS patients were identified as CRP > 3.0 mg/dL or albumin < 3.0 g/dL or lymphocyte counts of <800/μL on day 14. CRP, albumin, and lymphocyte counts were extracted with the nearest measurements to day 14 within days 11–17. When the patients had no value for each factor, it was applied as negative in an or-conditional expression. “PIICS” was inferred if one or more of three components were matched. Patients were classified as “prolonged hospital stay without PIICS” if all three components were negative.Finally, early recovery and prolonged hospital stay without PIICS were categorized as “non-PIICS”.As patient characteristics, the following were extracted and evaluated: age, sex, DIC, sequential organ failure assessment SOFA score and the acute physiology and chronic health evaluation (APACHE II) score on admission. Coagulation abnormalities were scored using ISTH overt DIC criteria and the Japanese diagnostic criteria of acute phase DIC (JAAM-DIC)  10]. In. In10]. t-test or one-way analysis of variance when the null hypothesis is not rejected by the Shapiro–Wilk test. Continuous variables are expressed as the median (interquartile range) and are compared using Mann–Whitney U testing or Kruskal–Wallis tests when the null hypothesis is rejected by the Shapiro–Wilk test. Tukey–Kramer or Steel–Dwass tests were applied to examine differences of pairs in the multigroup. For categorical variables, the proportions of patients in the respective categories were calculated. Then the groups were compared using chi-squared tests or Bonferroni tests of multigroups. Nominal logistic regression analysis was applied to elucidate PIICS-in-PIICS and non-PIICS patients, excluding early death. Univariate logistic regression analysis was conducted first in each factor. Then, multivariate logistic regression analysis was performed with the factors. To check multicollinearity between independent variables, the variance inflation factor was calculated before performing multivariate logistic regression. Multicollinearity was regarded as present when the variance inflation factor was greater than 10.Continuous variables are expressed as the mean ± standard deviation and are compared using Student’s To elucidate the relative, complex association between factors and PIICS, we used a generalized structural equation model (GSEM) ,12. The p was less than 0.05 were inferred as significantly different *.GSEM analysis was done with R (R 3.6.1). The other statistical analyses were conducted using JMPpro14 . Results for which The study outline for patient extraction flow is depicted in Data of 5397 patients admitted to the ICU/emergency ward were analyzed. Of these patients, 416 patients died within 14 days (early death); 4248 patients were discharged alive (early recovery). Of the remaining 733 patients, for whom the hospital stay was > 14 days, 488 PIICS were identified as CRP > 3.0 mg/dL or albumin < 3.0 g/dL or lymphocyte counts < 800/μL on day 14; the other 245 patients were assigned as having Prolonged hospital stay without PIICS.CRP; C-reactive protein, PIICS; persistent inflammation, immunosuppression and catabolism syndrome.p < 0.0001, respectively). Patients with sepsis were more numerous in the ISTH overt DIC group (p < 0.0001). Initial CRP and albumin on admission were worse in patients with DIC than in non-DIC patients (p < 0.0001). p < 0.0001). The length of hospital stay was longer in the ISTH overt DIC group; the Barthel index at discharge  was also significantly lower in the ISTH overt DIC group . Moreover, for ISTH overt DIC vs. non-ISTH overt DIC, median CRP on day 14 was higher ; mean albumin on day 14 was lower . In particular, PIICS and early death outcomes were remarkably greater in the ISTH overt DIC group; early recovery occurred more often in the non-ISTH overt DIC group (p < 0.0001).Then, correlation between laboratory findings related to coagulopathy and PIICS outcomes were analyzed . SignifiTo investigate baseline risk factors for PIICS, we applied univariate and multivariate regression analysis for PIICS for patients in whom early death was excluded . Univarip < 0.001 and 0.09, p < 0.001, respectively). However, other factors, perhaps via overall severity, have the most significant effect on PIICS development .Regarding the GSEM, our model shows good fit to explain the association of interest: goodness-of-fit, 0.98; adjusted goodness-of-fit, 0.92; root mean square error of approximation index, 0.08 (95% CI 0.07–0.08); standardized root mean residual, 0.045. The association and corresponding standardized coefficients are shown in p < 0.05. Dotted lines represent lack of significant relation.A generalized structural equation model is described for the complex association between factors and PIICS. Inflammation and coagulopathy on the first day were found to be important factors for PIICS development. However, another factor, perhaps via overall severity, was found to have the greatest effect on PIICS development. Solid lines represent a significant relation with PIICS; persistent inflammation, immunosuppression and catabolism syndrome.This study found DIC to be associated not only with early death, but also with PIICS development in surviving patients. Furthermore, DIC affects the hospital stay and ADL at discharge. Age, male, sepsis, albumin, lymphocyte count, Hb, creatinine, HbA1c and ISTH overt DIC on admission were identified as risk factors that were independent of disease severity for PIICS in surviving patients.This report is the first of a study clarifying correlation between coagulopathy and PIICS based on large clinical data. Our results suggest that patients with DIC who are able to survive would die more frequently and that they would develop PIICS with greater likelihood. It has already been reported that DIC affected mortality and hospital stay length, possibly because of crosstalk with inflammation and consequent organ dysfunction ,17. AntiCoagulopathy is regarded as playing an important role in PIICS. Although the activation of coagulation is protective to counteract pathogens through fibrin deposition , excessiIn our generalized structural equation model, initial nutrition status, inflammation and coagulopathy affected PIICS development. It was reasonable because PIICS was fundamentally the inflammation and catabolism syndrome. These factors were mutually correlated through crosstalk between inflammation and coagulopathy. They were also affected strongly by the overall disease severity and infection condition. Sepsis has been reported as one of the strongest PIICS development conditions ,2. FurthNevertheless, the strongest factor exacerbating PIICS development was neither comorbidity nor sepsis, but disease severity. The APACHE II score was the strongest independent risk factor from initial CRP and albumin: it was sufficient to affect PIICS criteria. Coagulopathy is another aspect of severity. It is interesting that the greater severity engenders more PIICS, independent of the background and initial laboratory findings.This study included some limitations. First, this study was conducted as a single-center retrospective study. Regional and hospital characteristics may influence study results. Actually, many elderly patients in Japan are admitted to emergency and critical care centers. These study patients therefore included many elderly people. Second, this study included all patients who were admitted to our emergency and critical care center. Among them were patients with various diseases such as sepsis and post-surgery complications. To elucidate a disease-specific PIICS relation, the same analyses should be conducted with disease-limited patients in future studies. Third, some unmeasured or unknown confounding factors are expected to affect the multiple regression analysis. Actually, PIICS development cannot be explained solely by initial conditions and laboratory findings. Similarly, GSEM may have other confounding factors. Fourth, treatments after admission were not considered for this study. They may include some anti-coagulant therapy for DIC. Fourth, the CRP transition of this study includes a population for which treatment failure, including inadequate source control or other disease or infection, occurred during the clinical course. Therefore, PIICS and CCI are compound conditions including these treatment failures and second hits. Finally, CRP, albumin and lymphocyte counts on day 14 were allowed within days 11–17, which included deficits. Laboratory data should be collected accordingly on day 14 without deficits for future prospective studies.Results indicate DIC as an independent risk factor not only for mortality, but also for PIICS development in surviving patients.


Rhytidiadelphus squarrosus moss for the rapid and efficient removal of Co2+ ions and thioflavin T (TT). The biocomposite was extensively characterized using Fourier transformed infrared (FTIR), XRD, SEM, and EDX techniques. The magnetic biocomposite showed very good adsorption properties toward Co2+ ions and TT e.g., rapid kinetics, high adsorption capacity (218 μmol g−1 for Co and 483 μmol g−1 for TT), fast magnetic separation, and good reusability in four successive adsorption–desorption cycles. Besides the electrostatic attraction between the oxygen functional moieties of the biomass surface and both Co2+ and TT ions, synergistic interaction with the –FeOH groups of iron oxides also participates in adsorption. The obtained results indicate that the magnetically responsive biocomposite can be a suitable, easily separable, and recyclable biosorbent for water purification.Microwave synthesized iron oxide nanoparticles and microparticles were used to prepare a magnetically responsive biosorbent from  Considerable efforts are currently being made to eliminate contaminants that have caused growing concern from the large volume of industrial effluents and wastewaters . Among a3O4 functionalized activated carbon, confirming the role of Fe3O4 nanoparticles in the removal of dyes. Specifically, magnetic modification may decrease the BET surface due to the formation of iron (hydro) oxides on sorbent surface, and some pollutants can be adsorbed more efficiently on the surfaces of these precipitated (hydro)oxides  is a Freundlich constant referring to the adsorption capacity, and 1/n is a dimensionless unit representing surface heterogeneity.2+ and TT using magnetically responsive biomass as the adsorbent. The higher coefficients of determination (R2) of the Langmuir model for both Co (0.980) and TT (0.961) removal suggested that the adsorption behavior could be attributed to the monolayer chemical adsorption mechanisms [b, the magnetic biosorbent exhibited considerably higher affinity for TT (0.0072 L μmol−1) compared to Co2+ ions (0.0025 L μmol−1). The maximum adsorption capacity maxQ at 22 °C was 483 µmol g−1 for TT and 218 µmol g−1 for Co2+ ions, respectively. It should be highlighted that the maxQ value of the magnetic biosorbent for Co2+ ions is slightly higher than that of the native biomass counterpart, and for TT, it is significantly higher  on the biosorbent surface. The pHpzc of the magnetically responsive biosorbent determined by the pH drift method was 5.4. 2+ ions by the magnetic biosorbent. As was reported in our previous work [2+ adsorption by native R. squarrosus biomass. The adsorption capacity gradually increased from 3.6 to 134.8 µmol g−1 with the pH increasing from 2.0 to 6.0. The negligible uptake of Co ions observed at pH 2.0 could be closely related to the protonation of the oxygen-containing functional moieties  of the biosorbent surface, resulting in a competition (or ion exchange) between cobalt ions and the H+ or H3O+ ions in solution and electrostatic repulsion between the positively charged biomass surface and Co2+ ions. As the pH increased, the competition between Co2+ and H+ for functional moieties reduced significantly. Considering the pHpzc value, the biosorbent surface was negatively charged at >pH 5.4, and the electrostatic attraction between O-containing functional moieties and Co2+ ions became stronger, resulting in higher adsorption capacity  cation within pH ranging from 2.0 to 8.0 3−) are present at a solution pH > 8.0, and Co precipitation begins at pH > 8.0. We suppose that the notably higher removal capacity (172.3 µmol g−1) at the initial pH of 8.0 was related also to the formation of Co(OH)2 precipitates directly on biosorbent surfaces.The speciation of cobalt calculated using the MINEQL+ program indicated that Co particularly occurs as a Co0 to 8.0 . Other cmaxQ values of native and magnetically modified biomass for Co + for the H+ cations of surface ionogenic –FeOH groups. However, due to the complexity of the biomaterials, the above-mentioned mechanisms are acting simultaneously, to varying degrees, depending on the biosorbent surface ionization and the solution chemistry [Based on the comparison of s for Co , we assuosorbent . It is eand FeO− . With thsorption ,25. Motlsorption  revealedhemistry .pzc, the equilibrium solution pH decreased  as efficient desorbents and then used in four successive adsorption–desorption cycles. The appropriate handling of exhausted biosorbents is a limiting process influencing the economical efficiency and sustainability of biosorption technology. However, biosorbent reusability could effectively reduce the cost of industrial application and minimize the total amount of waste generation after the adsorption process . Conside−1 after the third cycle and to 179.6 µmol g−1 after the fourth cycle, indicating a high adsorption ability and a good reusability of the magnetic biosorbent for TT removal. In contrast, the adsorption capacity of Co2+ on the biosorbent significantly dropped from 134.2 to 86.8 µmol g−1 after the first adsorption–desorption cycle. After the next three cycles, only a slight decrease to 73.4 µmol g−1 was observed. The markedly higher decrease in the adsorption capacity of Co2+ ions on the biosorbent during the adsorption–desorption cycles as compared to TT confirmed the different adsorption behavior. In addition, four adsorption–desorption cycles practically did not affect the magnetic separation of biosorbent (3COOH), which is in agreement with the study of Wang et al. [The cyclic experiments  revealedosorbent , confirmg et al. . Moreoveg et al. , the phyR. squarrosus was successfully prepared using microwave synthesized nanoparticles and microparticles of iron oxides for the efficient removal of Co2+ and TT from aqueous solutions. The biocomposite displays improved biosorption performance compared with their non-magnetic biomass counterpart. Obtained experimental data of both Co2+ and TT biosorption were well fitted with the pseudo-n-order kinetic model and Langmuir isotherm with a maximal adsorption capacity of 218 μmol g−1 for Co and 483 μmol g−1 for TT. Based on the EDX elemental mapping, besides the oxygen-containing functional groups of biomass biopolymers, synergistic interaction with the –FeOH groups of iron oxides also participates in Co2+ and TT adsorption. The cyclic experiments showed that the adsorption capacity of biocomposite kept 75% for TT and 55% for Co2+ after the fourth cycle, indicating a high adsorption ability and a good reusability of the magnetic biosorbent especially for TT removal. Considering the obtained results, the prepared magnetic biosorbent is superior to other adsorbents in terms of its simple preparation, efficient separation, reusable properties, and high stability, making it suitable for both dye and metal adsorption from contaminated effluents and wastewater streams.A magnetically responsive biocomposite from


Multiple sclerosis (MS) is an immune-mediated disease that predominantly impacts the central nervous system (CNS). Animal models have been used to elucidate the underpinnings of MS pathology. One of the most well-studied models of MS is experimental autoimmune encephalomyelitis (EAE). This model was utilized to demonstrate that the cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) plays a critical and non-redundant role in mediating EAE pathology, making it an ideal therapeutic target. In this review, we will first explore the role that GM-CSF plays in maintaining homeostasis. This is important to consider, because any therapeutics that target GM-CSF could potentially alter these regulatory processes. We will then focus on current findings related to the function of GM-CSF signaling in EAE pathology, including the cell types that produce and respond to GM-CSF and the role of GM-CSF in both acute and chronic EAE. We will then assess the role of GM-CSF in alternative models of MS and comment on how this informs the understanding of GM-CSF signaling in the various aspects of MS immunopathology. Finally, we will examine what is currently known about GM-CSF signaling in MS, and how this has promoted clinical trials that directly target GM-CSF. Multiple sclerosis (MS) is a chronic immune-mediated disease that impacts approximately 2.3 million people world-wide . MS is cAnimal model systems of MS have provided insight into the immunopathology of MS. Studies in these models have directly and indirectly contributed to the development of disease-modifying agents that are utilized in the clinic . The mosCSF2 is encoded by 2.5kb mRNA that consists of four exons on the chromosome region 5q31 [GM-CSF is a 114 amino acid polypeptide that is secreted as a monomeric 23kDA glycosylated small glycoprotein protein, though the molecular weight can vary depending on the extent of glycosylation . Human Cion 5q31 ,13. Muriion 5q31 . The GM-ion 5q31 . Activation 5q31 ,17. Whenion 5q31 ,17. The ion 5q31 . GM-CSF ion 5q31 . GM-CSF ion 5q31 . GM-CSF ion 5q31 . The uprion 5q31 . Additioion 5q31 . Given t−/−Csf) reveal that GM-CSF is required for the development of functional alveolar macrophages through the regulation of the transcription factor PU.1 [GM-CSF is a pleiotropic cytokine that is known to be a major mediator in inflammation; however, GM-CSF also functions in maintaining homeostasis. In the lungs, GM-CSF is abundantly produced by epithelial cells. Murine studies utilizing GM-CSF-deficient mice . ntestine ,26,27. Intestine . This isntestine . Since G(35–55)), myelin basic protein (MBP), or proteolipid protein (PLP) are emulsified in complete Freund’s adjuvant (CFA) and subcutaneously injected into naïve recipient mice [(35–55) in CFA in mice on a C57BL/6J background, the mice develop a monophasic and chronic disease pattern that is characterized by white matter demyelination and peripheral CD4+ T cell and myeloid cell infiltration [(139–151). Active EAE induction in the SJL/J mice results in a relapsing–remitting disease course which is characterized by peripheral immune cell infiltration, inflammation, and demyelination (relapses), followed by the resolution of inflammation but the progression of white matter damage and axonal damage with no overt clinical symptoms (remission) [4 subunit of α4β1 integrin on the surface of lymphocytes, which prevents binding to the vascular cell adhesion molecule 1 (VCAM-1). This prevents T cells from migrating into the CNS parenchyma [Experimental autoimmune encephalomyelitis (EAE) is the most well-studied model of multiple sclerosis. This model was established in 1933 by Rivers and colleagues in an attempt to address human encephalitis resulting from rabbit spinal cord contamination in the human rabies vaccine . Since ient mice . The res–55), mye–55), myeltration . In addimission) . This momission) . The othmission) ,37,38. Tration [1–151. Actration [1–151. Actmission) . Natalizrenchyma ,42. Cons(35–55) and the clinical presentation in this particular stain of mice was a relapsing–remitting biphasic phenotype. The study found that, although functionally normal in terms of hematopoiesis, these mice are resistant to the EAE, which was demonstrated by the lack of immune cell infiltration into the CNS in addition to the absence of clinical symptoms, suggesting that GM-CSF is important for the development of demyelinating lesions and the migration and/or expansion of immune cells within the CNS [The first study to assess the role of GM-CSF in EAE pathology was conducted by McQualter and colleagues in 2001. Their goal was to determine whether GM-CSF played a critical and non-redundant role in promoting EAE pathology, which was based on previous findings suggesting that that concentration of GM-CSF was increased in the cerebral spinal fluid of patients with MS compared to healthy controls . To this the CNS . These fIfng−/−Il17a−/− mice was sufficient to induce EAE; however, −/−Csf2 mice, which lack GM-CSF, do no develop EAE, suggesting that other inflammatory mediators are not sufficient to induce pathology [GM cells. These cells have minimal expression of the master gene regulators of Th1 and Th17 cells, T-bet and RORγt. Microarray analysis revealed that the ThGM cells co-express GM-CSF and IL-3, which is not the case in either Th1 or Th17 cells. Additionally, when the three Th subtypes were adoptively transferred into -/-Rag2 mice, the ThGM cells caused more severe EAE compared to EAE induced by the transfer of Th1 or Th17 cells [GM are a distinct subset of pathogenic Th cells. To this end, they generated a fate-map and reporter of GM-CSF expression mouse stain, whereby they were able to identify a subset of Th cells that required IL-23R and IL-1R signaling but not IL-6R signaling, to promote pathogenesis [GM cells are, in fact, a distinct subset of Th cells during EAE. These cells may serve as novel therapeutic targets. A list of cell types that produce GM-CSF during EAE is summarized in In 2007, a study published by Ponomarev and colleagues identified the cellular source of GM-CSF during EAE as T cells and not CNS-resident microglia or other infiltrated peripheral immune cells . This stathology . A studyathology . Additioathology ,51,52. Tathology . A recenathology . Further17 cells . A recenogenesis . Furtherogenesis . Interesogenesis . When CCogenesis . Consequogenesis . It is ehi Ly6Chi egress from the bone marrow, across the blood–brain barrier, and into the CNS parenchyma, where these cells will upregulate the expression of proinflammatory cytokines [Csf2r on various immune cells, including CD103+ conventional dendritic cells, CNS-resident microglia, and neutrophils, does not alter the progression of EAE [Csf2r is deleted on CCR2+Ly6C+ monocytes, the mice are resistant to EAE and have a similar phenotype to the complete −/−Csf2  mice, suggesting that this particular subset of monocytes responds to GM-CSF and is critical in mediating EAE pathology [Once CD4+ T cells were found to be the major cellular source of GM-CSF during EAE, there was a need to understand which immune cell types were responding to the high level of GM-CSF that was being produced by these cells. One of the first studies to address this question suggested that myeloid cells are a major component of the inflammatory infiltrate, and these cells must migrate into the CNS prior to EAE relapses . Using Gytokines . Additioytokines ,71,72. Tn of EAE . Howeverathology . It is tathology ,73. In fathology . There iathology ,65.Csf2r is conditionally deleted in CD103+ dendritic cells, severe EAE could still be observed in these mice, suggesting that Csf2r expression on the CD103+ dendric cells is not exclusively required for EAE initiation and/or progression [In addition to monocytes, there are other cell-types that can respond to GM-CSF during EAE. The accumulation of CD103+ dendric cells in the lymph nodes is dependent on the presence of GM-CSF . The CD1gression . Neutropgression . Studiesgression . Furthergression . Therefogression ,68. Howegression . In a regression . They fogression . It is eThe role of GM-CSF in less commonly used models of MS has not been well elucidated. One model that may depend on GM-CSF signaling is the Theiler’s murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD) . Theiler−/−Csf2 mice, and the number of pathogenic CD4+ T cells in the lymph nodes was significantly decreased, suggesting that the accumulation of CD4+ T cells in the lymph nodes is dependent on GM-CSF [−/−Csf2 mice, the onset of clinical EAE symptoms was unaltered; however, perturbing GM-CSF signaling did alter the immune cell profile in the CNS, thereby decreasing disease severity and preventing the progression to chronic disability [Studies from animal models have convincingly demonstrated that GM-CSF plays a critical role in promoting EAE pathology. However, recent studies have brought the importance of this cytokine in the onset of disease into question. The first study performed by Pierson and Goverman sought to determine the role of GM-CSF in EAE that is induced in C3HeB/FeJ mice, which develop an inflammatory disease in both the brain and spinal cord . This mon GM-CSF . Howevern GM-CSF . Additiosability . This stAnimal models of MS have allowed us to gain significant insight into the role of GM-CSF in promoting this immune-mediated disease. Despite the breakthroughs in our understanding of this cytokines in murine models, the role of GM-CSF in MS is still not completely elucidated. It has been known for some time that the concentration of GM-CSF is significantly increased in the cerebral spinal fluid (CSF) of patients with active MS compared to healthy controls . SimilarSimilar to EAE, monocytes appear to be the major cell types that respond to GM-CSF in MS . GM-CSF There are numerous clinical trials that are attempting to target GM-CSF or the GM-CSF receptor for the treatment of autoimmune diseases . One bioGM cells, the role of GM-CSF signaling in lesion-associated microglia and astrocytes, and the functional importance of GM-CSF-producing B cells in patients with MS. Despite these shortcomings in the literature, GM-CSF appears to be a promising therapeutic target for treating MS progression. Evidence from the literature also strongly alludes to the notion that a combined therapy approach that includes inhibiting the biological function of GM-CSF will likely be the most efficacious approach to treat MS.Murine models of MS have allowed us to gain insight into the important role that GM-CSF plays in mediating neuroinflammation. These models have proven to be a useful tool for studying immune cell infiltration and the resulting inflammatory milieu, given that many of the major underpinnings of EAE pathology have been validated in patients with MS. These models have established that CD4+ T cells are the major cellular source of GM-CSF during EAE, and the monocytes are the major cell type that responds to that GM-CSF. These monocytes can then infiltrate into the CNS and promote inflammation, demyelination, and axonal loss. These cells and their downstream mediators are ideal targets for MS therapies. However, there is still much to be learned about the role of GM-CSF in mediating EAE pathology. Additional studies need to access the importance of Th


Corynebacterium striatum is part of the human flora, it has recently drawn attention both for its multidrug resistance and its role as an invasive infection/outbreak agent. This cross-sectional study aimed to determine the antimicrobial resistance and clonal relationships among C. striatum strains. In total, 81 C. striatum strains were identified using Phoenix-100TM . The antimicrobial resistance of the strains was determined using the Kirby–Bauer disk diffusion method. Clonal relatedness among the strains was performed via arbitrarily primed polymerase chain reaction (AP-PCR). All 81 C. striatum strains were resistant to penicillin, cefotaxime, ciprofloxacin, and tetracycline, but susceptible to vancomycin and linezolid. The resistance rates to gentamicin, erythromycin, and clindamycin were 34.6%, 79%, and 87.7% respectively. AP-PCR results showed no predominant clone among the C. striatum strains. Corynebacterium striatum is reportedly the cause of an increasing number of invasive infections/outbreaks. Moreover, treatment options are limited. The study showed that vancomycin, linezolid, and gentamicin can be selected for the empirical treatment of C. striatum infections. Although no single-clone outbreak was observed in our hospital, small clonal circulations were observed within some units, indicating cross-contamination. Therefore, a comprehensive infection control program is warranted in future.Although  Corynebacterium species (spp) are aerobic, non-spore-forming, club-shaped Gram-positive rods. They are ubiquitous in the environment (soil and water) and some species are commensal of normal human skin and mucous membranes. To date, over 100 species have been identified, and 54 of them are associated with human infections , eosin methylene blue (EMB) agar (BD), and chocolate agar (BD). For blood culture, 8–10 mL of each patient’s blood was inoculated into BD BACTEC Plus vials and incubated in the Bactec FX 40  automated blood culture system for seven days. Samples with positive signals were inoculated on 5% sheep blood Columbia agar, EMB agar, and chocolate agar plates. After an incubation period of 24–48 h, 35°C in 5% CO2 atmosphere conditions. The inhibition zone diameters formed around the antibiotic discs were measured and interpreted using the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines [Corynebacterium spp. in the EUCAST guidelines, the EUCAST interpretive criteria for Streptococcus pneumoniae was used. Accordingly, C. striatum strains showing an inhibition zone diameter of ≥22 mm were considered sensitive and <19 mm were considered resistant. Similarly, the zone diameter breakpoint recommended by EUCAST for Viridans streptococci was used for cefotaxime. As such, C. striatum strains showing an inhibition zone diameter of ≥23 mm were considered susceptible and <23 mm were considered resistant. Streptococcus pneumoniae ATCC 49619 was used for quality control [The antibiotic susceptibility of the strains was determined using the Kirby–Bauer disk diffusion method. The bacterial suspension adjusted 0.5 Mc Farland turbidity was inoculated by sterile cotton swap to the surface of Mueller–Hinton fastidious agar  plate containing 5% defibrinated horse blood and 20 mg/L β-NAD. Nine antibiotic discs were used: Penicillin (1 unit), ciprofloxacin (5 µg), gentamicin (10 µg), vancomycin (5 µg), linezolid (10 µg), erythromycin (15 µg), clindamycin (2 µg), cefotaxime (5 µg), and tetracycline (30 µg). Antibiotic discs were provided by BBL  and MAST . The antibiotic discs were placed on the MH-F agar plates within 15 min of inoculation on the plates. The plates were incubated for 16–24 h at 35 °C in 5% COidelines . However control . The antC. striatum strains was determined using the arbitrarily primed polymerase chain reaction (AP-PCR) method. AP-PCR was carried out at the Inonu University Molecular Microbiology Laboratory as described previously [C. striatum strains were inoculated on 5% sheep blood agar. After 24–48 h of incubation, pure bacterial cultures were obtained. Genomic DNA was isolated using the QIAsymphony total nucleic acid isolation kit. M13 primers (5′-GAGGGTGGCGGTTCT-3′) were used for amplification under the following conditions: Initial denaturation for 5 min at 94 °C, followed by 40 cycles consisting of denaturation at 94 °C for 60 s, annealing at 40 °C for 60 s, and extension at 72 °C for 2 min. The amplification products were separated by electrophoresis in a 1.5% agarose gel with ethidium bromide for 1.5 h at 100 V, and the band profiles were visualized using the Gel Logic 2200 imaging system  under ultraviolet light. The band profiles were analyzed using the Gel Compar version 6.6 software program . The Dice Similarity Coefficient (DSC) was used in similarity calculations for band analysis, whereas the Unweighted Pairwise Grouping Mathematical Averaging (UPGMA) method was used for clustering analysis. The strains were identified as different genotypes if the DSC was <95% and as the same genotype if it was ≥95%. A dendrogram was created using the UPGMA clustering algorithm.The clonal relationship among eviously . The sto(P) value of ≤0.05 was considered statistically significant in the 95% confidence interval.The data were analyzed using the Minitab 17  statistical software program. Descriptive statistics were expressed as number (n), percentage (%), and mean and standard deviation. The Kolmogorov–Smirnov test was performed to determine whether the variables were normally distributed. For the comparison of continuous variables, two-sample t-test was used. The Pearson’s Chi-squared test or Fisher’s Exact test was used for comparison of categorical variables if applicable. A probability This study was reviewed and approved by the Noninterventional Clinical Research Ethics Board of Karabuk University .C. striatum as an invasive infection/outbreak agent and the rising antibiotic resistance of strains. Although C. striatum is part of the normal human flora, it should not be overlooked when isolated from clinical specimens, as it may actually be a cause of infection. Therefore, the microbiologist and clinician should cooperate to reach a final decision. In the present study, C. striatum strains showed high-level resistance to most commonly used antibiotics. Therefore, based on our in-vitro antibiotic susceptibilities results, vancomycin, linezolid, and gentamicin can be selected for the empirical treatment of C. striatum infections. However, the antibiotic resistance profile of C. striatum should be monitored regularly, and empirical antibiotic treatment regimens should be revised. Although no single-clone C. striatum outbreak was detected in our hospital, polyclonal dissemination was detected and small clonal spreads were observed, indicating cross-contamination. Therefore, we should perform the effective infection control measures. In addition, compliance of HCWs to hand hygiene and cleaning of medical equipment and hospital surfaces with appropriate disinfectant should be monitored.This study highlighted the increasingly frequent occurrence of


Gestural communication is ubiquitous throughout the animal kingdom, occurring in species that range from humans to arthropods. Individuals produce gestural signals when their nervous system triggers the production of limb and body movement, which in turn functions to help mediate communication between or among individuals. Like many stereotyped motor patterns, the probability of a gestural display in a given social context can be modulated by sex steroid hormones. Here, we review how steroid hormones mediate the neural mechanisms that underly gestural communication in humans and nonhumans alike. This is a growing area of research, and thus we explore how sex steroids mediate brain areas involved in language production, social behavior, and motor performance. We also examine the way that sex steroids can regulate behavioral output by acting in the periphery via skeletal muscle. Altogether, we outline a new avenue of behavioral endocrinology research that aims to uncover the hormonal basis for one of the most common modes of communication among animals on Earth. Gesture plays a fundamental role in animal communication. As humans, we are intimately aware of this fact, given that individuals from all cultures across the globe use gesture to convey ideas, thoughts, and feelings to others . It is tIn this mini-review, we explore this topic from the point of view of the endocrine system, assessing how hormones modulate the integration of body movement into animal communication programs. We define gesture as the process by which an individual actively moves its face, limbs, and/or body in a coordinated manner  to help facilitate communication . This brWhy would hormones influence animal communication, and which hormones are most likely to do so? The answer to the first question centers around the major role of hormone action, which provides context-appropriate regulation of behavior , 10. In This brings us to sex steroids—namely, androgens, estrogens, and progestins. These hormones are principally produced by the gonads, and mediate sperm production in males and follicular development in females . At the Because gestural communication often facilitates reproduction, it stands to reason that sex steroids regulate its production in this context. But, how? We know surprisingly little about this topic . One facThe brain controls the production of gestural communication, determining not only when it is performed, but also how it is performed. Some of the most interesting work that explores this process is in humans using functional magnetic resonance imaging to determine brain regions associated with different forms of gestural communication. For example, studies in men and women investigating the neural basis of co-speech gestures—the hand movements we tend to make while we speak , 13—findEven less is understood about how sex steroids act on these areas to modulate co-speech gesture. The first hint that such effects may occur comes from work in humans and other nonhuman animals showing that many of the brain regions mentioned above either express steroid hormone receptors  or are connected to brain areas that have these receptors . The secSex steroids similarly impact motor centers in the brain, which are also involved in the production of co-speech gesture. Preliminary research, for example, suggests that cancer patients undergoing androgen deprivation therapy exhibit a marked decline in gray matter within the primary motor cortex . MoreoveAlthough this small body of research implies that sex steroids may exert some influence on the neural basis of co-speech gesture, we must recognize that exceptionally little is known about how these effects are borne out. The first step in addressing this gap is to generate a better understanding of how the brain controls co-speech gesture. This is admittedly a tall order, but ultimately a fascinating question given the degree to which such behavior in ingrained in our communication [even congenitally blind patients produce co-speech gesture ]. The neOne might expect that the study of gestural communication in nonhuman animals would quickly dry up. How many species communicate with gesture, and what role could hormones possible play in this process? The answer to the first part of the question is simple: Nearly all social species use gesture to signal to others, whether they are of the same or different species. Gestures vary tremendously among taxa, ranging from chest pounding to dancing behavior  30-36)..30-36). Our understanding of how sex steroids regulate gestural displays starts with classic studies that probe the mechanisms underlying postural and reflexive control necessary for copulation and courtship. One of the best examples comes from work on lordosis in rats. This is not a gesture per se; rather, it is a stereotyped mating posture that signifies sexual receptivity and thus mediates successful mating . NonetheIn males, the medial preoptic area (mPOA) is the principal node that mediates sexual behavior, as opposed to the VMH , 43. MorSerinus canaria) shows that a nucleus within the song control system—the robust nucleus of the arcopallium —directly innervates both the DM (part of the ICo) and RAm  , 5150, 5earlier) . IntegraBonasa umbellus) provides a potential link between these effects and gestural display. Males of this species perform a territorial and courtship display, in which they stand erect on a log in the forest and rapidly flap their wings up and down to generate a low-frequency drumming noise that booms through the forest  for motor skills involved in sexual display. The nuclei are typically viewed as respiratory premotor nuclei, but they are also involved in the execution of other tasks that require alteration of respiratory patterning such as vomiting and abdominal straining . This, ae forest . Histoloe forest ; thus, eManacus vitellinus), for example, express high levels of androgen receptor throughout much of the arcopallium. These tropical birds produce a courtship display in which they rapidly jump around the forest floor, snapping their wings together in mid-air to generate a loud, firecracker-like pop  shows that the motoneurons innervating the cloacal muscles contain high levels of estrogen receptor, which stands in contrast to the dearth of estrogen receptor in most other regions of the spinal cord’s ventral horns . From here, we can begin to assess how actions of estrogen, androgens, and progestins modulate these brain nuclei to influence gesture. Other intriguing questions will undoubtedly emerge from studies in this area, such as how central steroid action influences the development of gestural displays . Might sWe must also recognize that sex steroids act peripherally to influence gestural communication. This process can be conceptualized as steroidal modulation of substrates that respond to “instructions” sent from the brain about how to move the body in a specific manner. The idea makes more sense if we consider the nature of the gestures that many animals produce for communication, especially those that demand performance skills and abilities that would not normally be attributed to the species in question  . So how First, sex steroids might act directly on the musculoskeletal system to adjust how the striated muscle and its associated structures actuate movement. In particular, androgenic steroids, like testosterone, play a powerful role in the regulation of muscle, which expresses high levels of androgen receptor compared with many other tissues in the body , 78. AndLythrypnus dalli), males defend nest sites and court females by performing swim displays, in which they repeatedly extend and retract their pelvic and dorsal fins. The muscles that actuate these fin movements contain high levels of androgen receptor compared with other major muscles that power swimming  have evolved intricate waving displays with their hindlimbs to compliment acoustic communication in especially noisy environments, such as under a waterfall. Androgens help activate these displays likely by acting on the musculature that extends, rotates, and retracts the femur (Unfortunately, little work has been carried out to explore how peripheral steroid action influences central control of behavior. Recent work in frogs, however, suggests that it likely plays a role. Species like the Bornean rock frog (he femur . Becausehe femur , 107.Going forward, there are many gaps to fill with regard to our knowledge about sex steroids and their ability to act via the musculoskeletal system to modulate gestural displays. Hints from endocrinological research that estrogens and progestins modulate muscle performance should be examined in a behavioral context. Are the effects of these hormones on select muscles necessary to generate certain types of display movements? If so, why? How do these hormones change muscle physiology in a functionally meaningful manner? Equally important is a more thorough understanding of how sex steroid-mediated signaling from the muscle to the spinal cord regulates behavior. We have known about this phenomenon for decades, yet it has gained little steam in terms of informing our understanding of behavioral modulation. How might changes to spinal cord morphology induced by peripheral sex steroid action alter motor skills and/or muscle synergies that guide complex movements used to communicate?Anolis lizards, for example, species that exhibit greater rates of territorial push-up display express higher levels of androgen receptor in their forearm muscles (An emergent view from the research described above is that sex steroid systems act as channel through which gestural signals can evolve. Accordingly, selection for specific gestural patterns and routines may proceed through concurrent changes to the systems by which sex steroids regulate motor command . Support muscles . Push-up muscles , 111, in muscles . This laBuilding on this idea is work that explores how the androgen receptor itself might evolve. While steroid receptors are thought to be highly conserved, recent work shows that androgen receptor protein in birds does vary across taxa . In partIn sum, we briefly reviewed the literature that currently provides the basis of our understanding about the relationship between the endocrine system and gestural communication in vertebrates. Most of this work focuses on regulation through sex steroids, acting on pathways in the brain that mediate sexual reflexes and postures. Such research is just beginning to extrapolate these ideas to nonmodel systems, which have evolved highly complex gestural displays that incorporate dance, acrobatics, and other movements requiring a high degree of fine motor control. It appears that the key to understanding these processes lies in untangling the neural pathways that integrate facets of sociality with motor control systems. However, sex steroids also appear to act via the spinal cord and muscular system to prime the body thereby allowing it to appropriately respond to “instructions” from the brain. We end the review with a brief reflection on the evolution of these displays—namely, the idea that changes to the mechanisms underlying steroid action throughout the neuraxis can help precipitate adaptive modifications to gestural communication systems. Thus, sex steroid systems currently appear to be a primary conduit for the evolution of sexual movement programs.


Mycobacterium tuberculosis, and examine three previously validated CSF immunological biomarkers – vascular endothelial growth factor, interferon-gamma and myeloperoxidase – in terms of the expected changes in normal brain metabolism. We then model the downstream metabolic effects expected, predicting pivotal altered metabolic pathways that would be reflected in the urinary profiles of TBM subjects. Our cascading metabolic model should be adjustable to account for other types of CNS bacterial infection(s) associated with chronic neuroinflammation, typically prevalent, and difficult to distinguish from TBM, in the resource-constrained settings of poor communities.A new paradigm in neuroscience has recently emerged – the brain–gut axis (BGA). The contemporary focus in this paradigm has been gut → brain (“bottom-up”), in which the gut-microbiome, and its perturbations, affects one’s psychological state-of-mind and behavior, and is pivotal in neurodegenerative disorders. The emerging brain → gut (“top-down”) concept, the subject of this review, proposes that dysfunctional brain health can alter the gut-microbiome. Feedback of this alternative bidirectional highway subsequently aggravates the neurological pathology. This paradigm shift, however, focuses upon non-communicable neurological diseases (progressive neuroinflammation). What of infectious diseases, in which pathogenic bacteria penetrate the blood–brain barrier and interact with the brain, and what is this effect on the BGA in bacterial infection(s) that cause chronic neuroinflammation? Persistent immune activity in the CNS due to chronic neuroinflammation can lead to irreversible neurodegeneration and neuronal death. The properties of cerebrospinal fluid (CSF), such as immunological markers, are used to diagnose brain disorders. But what of metabolic markers for such purposes? If a BGA exists, then chronic CNS bacterial infection(s) should theoretically be reflected in the urine. The premise here is that chronic CNS bacterial infection(s) will affect the gut-microbiome and that perturbed metabolism in both the CNS and gut will release metabolites into the blood that are filtered (kidneys) and excreted in the urine. Here we assess the literature on the effects of chronic neuroinflammatory diseases on the gut-microbiome caused by bacterial infection(s) of the CNS, in the context of information attained via metabolomics-based studies of urine. Furthermore, we take a severe chronic neuroinflammatory infectious disease – tuberculous meningitis (TBM), caused by  All disease starts in the gut.” The gut-microbiome is made up of innumerable microbes, which function in a mutualistic relationship with the human host (you are what you eat” and “gut feelings” (A new paradigm in neuroscience has emerged in recent years – the brain–gut axis (BGA) – involving bidirectional communication between the brain and gut. This implicates a variety of pathways, including the enteric nervous system (ENS), central nervous system (CNS), gastrointestinal tract (GIT), endocrine system/GI hormones, and immune response, all integrated to orchestrate the bidirectional feedback loop of the BGA. As averred by Hippocrates, the Greek physician acknowledged by many as the father of modern medicine, “man host . Currentman host . Stable man host . Over theelings” . Consideeelings” . PerturbThe focus of this review is on the brain–gut (“top-down”) direction of the BGA. In particular, perturbations of brain metabolism induced by invading bacteria and, as a consequence, gut dysbiosis. Within the contemporary paradigm of a perturbed BGA, most of the relevant research centers on non-communicable neurological diseases, synonymous with a slow, gradual progression of neuroinflammation. However, the link between the brain–gut concept and CNS bacterial infection(s) is less prevalent in the literature, and hence the focus of this review. The most recent and comprehensive review of the BGA was by As a proof of a novel concept for the BGA, we use three previously validated immunological CSF markers of tuberculous meningitis (TBM) – vascular endothelial growth factor (VEGF), interferon-gamma (IFN-γ), and myeloperoxidase (MPO) – to model/predict the metabolic changes, and are the basis for postulating a metabolic cascade, expected within the brain of a TBM patient. It is well known that important diagnostic and prognostic information related to alterations in metabolic cascades and disruption of homeostasis can be characterized through metabolite profiling of urine . Hence, According to the brain–gut (“top-down”) concept, the brain can alter the community structure and function of the gut-microbiome in a bidirectional interaction feedback loop, characterized by continuous communication between the CNS and the GIT . The GITThe CNS is well shielded by the BBB, the major site of blood–CNS exchange. The barrier comprises microvascular endothelial cells, astrocytes and pericytes, and is tasked with the regulated passage of molecules into and out of the brain . NeurotrStreptococcus agalactiae, Gram-negative bacilli including Escherichia coli, Klebsiella pneumoniae, Listeria monocytogenes, Neisseria meningitidis, and Streptococcus pneumoniae Within the cascade, the first step of bacterial invasion involves transitioning across the compromised BBB into the subarachnoid space. Pathogens can cause disruption of the BBB, which enables their passage into the brain. The various host defenses are usually inadequate to control the infection. Leukocytes traverse the BBB and patrol the brain parenchyma under normal conditions. During inflammation, as result of infection, the BBB junctions (adherens and tight) that regulate the flux of ions, polar molecules, and macromolecules from the systemic circulation can be compromised, thus traffic is greatly increased at these junctions. Bacteria may cross the BBB by transcellular penetration after bacterial adhesion to endothelial cells or via infected leukocytes. Pinocytosis, increased by leukocytes combating bacteria that might have invaded following disruption of tight junctions or via the “Trojan horse” mechanism – phagocytes infected with the pathogen transverse the BBB . Leukocy(2)Microglia cells, the primary immune effector cells in the brain, continuously survey the brain parenchyma and respond to very subtle alterations in their microenvironment and in the brain’s structural integrity . Microgl(3)Bacterial cell wall material, enzymes, and toxins cause direct injury to neurons and indirect damage by increasing vascular permeability that causes edema and further injury. Microglial cells respond to bacterial pathogens and neuronal injury by the production of reactive oxygen species (ROS), nitrous oxide, and peroxynitrite. Immune response also contribute to neurotoxicity via release of proteases and excitatory amino acids. Several signaling molecules, such as catecholamines, serotonin, dynorphin and cytokines, used by the host for neuronal and neuroendocrine signaling, are also likely to be secreted into the gut lumen .(4)2O2) are direct triggers of Streptococcus pneumoniae. H2O2 rapidly diffuses through eukaryotic cell membranes to damage intracellular targets thus increasing intracellular Ca2+, damaging mitochondria, and causing the release and translocation of mitochondrial apoptosis-inducing factor. Increased intracellular ROS and Ca2+ precedes morphologic changes that lead to brain cell apoptosis Pathogenic bacteria that causes meningitis exhibit antiphagocytic capsular polysaccharide ability which enables survival within the blood. Hence, changes in the gut involves hematogenous dissemination of bacteria, initiating meningitis via mucosal adhesion of the organism and subsequent systemic invasion . The int(6)Stratification of intestinal bacteria on the luminal side of the epithelial barrier also depend on secreted immunoglobulin A (IgA). IgA specific for intestinal bacteria is produced with the help of intestinal dendritic cells that sample the small numbers of bacteria penetrating the overlying epithelium. Some meningeal pathogens produce proteases that cleave to human immunoglobulin subclasses , allowing adherence of bacterial strains to mucosal surfaces and crossing the mucosal barrier . IgA1 prThe CNS can communicate with the gut via signaling molecules carried by the CSF and blood, which in turn may alter gut composition and physiology. Evidence for this communication between the gut and the brain includes the following: (1) it is well known that toxins or abnormal metabolites that enter the bloodstream are ultimately removed from the blood, in an attempt to maintain a state of cellular homeostasis, and excreted via the urine ; (2) bioTBM, a severe infectious disease caused by Mtb, is a chronic form of bacterial meningitis (BM), resulting in chronic neuroinflammation often associated with irreversible neurological damage/dysfunction. TBM develops in severity in progressive stages , and a uniform case definition  for diagnosis has been standardized . TBM is Mycobacterium tuberculosis (Mtb) – about which several studies have been conducted using urine for the detection of clinically relevant biomarkers  – a disease caused by omarkers . The detpatients ; a sensipatients ; and a spatients . Within patients , the dirpatients ; and a spatients . HoweverOf particular interest, as it pertains to our review, is that bacterial antigen-specific assays perform particularly poorly when used for diagnosing bacterial CNS infection from urine collected from patients, even in documented septicemia cases . Barnes For this reason, we believe that the detection of the catabolic components (metabolites) of complex signaling pathways is a better option for the accurate and sensitive differential diagnosis of bacterial CNS infection(s), using urine collected from patients. First, Mtb-induced changes to tryptophan metabolism was evident, due to the presence of elevated urinary concentrations of indole-3-acetic acid, 5-hydroxyindole acetic acid, tryptophan, kynurenic acid and quinolinic acid, accompanied by significantly elevated levels of N-acetylanthranilic acid , support the findings of Bacteriological confirmation of TBM from CSF is not always possible, especially in children, so that diagnosis is mostly based on a combination of clinical findings, CSF analysis and radiological results . Since vA preliminary 3-marker CSF biosignature, comprising VEGF, IL-13 and cathelicidin LL-37 , correctly diagnosed childhood TBM with a sensitivity and specificity of 52 and 95%, respectively . The samin vitro ischemia  to be 6.2 [0.6–42], which indicates that CSF VEGF is a result of intrathecal production. This increase in CSF VEGF could be associated with: (1) a change in mental status, (2) seizures, (3) an elevated CSF WBC count (with neutrophils being the main source of VEGF), (4) elevated CSF protein and higher CSF:serum albumin ratios (marker of BBB breakdown), (5) severe BBB disruption, and, eventually, (6) death.In 2001, Van der Flier et al. showed no detectable CSF VEGF concentrations in patients with viral meningitis (VM), whereas 30% (11/37) of those patients with bacterial meningitis (BM) displayed detectably elevated concentrations of CSF VEGF (ranging from <25 to 633 pg/mL). Furthermore, elevated VEGF has been associated with an upregulation of MMP-9  – see BoMMPs are a large family of zinc-dependent proteolytic enzymes. Their main function involves remodeling of the connective tissues by degrading extracellular matrix molecules and are regulated by tissue inhibitors of metalloproteinases. These many compounds are subdivided according to their main substrates:•Gelatinases: MMP-2, MMP-9.•Collagenases: MMP-1, MMP-8, MMP-13.•Stromelysins: MMP-3, MMP-10, MMP-11.MMP-2 and MMP-9 digest type IV collagen and are subsequently implicated in the breakdown of the BBB via dissolution of the basement membrane underlying the endothelial cells. MMP-2 and MMP-9 production is strongly correlated with the development of neurological sequelae and induced by pro-inflammatory cytokines (IFN-γ) and other mediators (such as MPO). The amount of MMP present in CSF varies, depending on the severity of inflammation. MMP-2 and MMP-9 are detected in elevated amounts in the CSF of meningitis cases , with MMP- 9 correlating strongly with the number of neutrophils in VM.Within TBM, VEGF is localized in the microvessels and perivascular cells . Tumor nMyeloperoxidase (MPO), a heme enzyme (EC 1.11.1.7) and pro-inflammatory mediator present in the primary granules of polymorphonuclear leukocytes (PMNs), participates in oxygen-dependent microbiocidal activity of PMNs and triggers oxidative stress during acute and chronic inflammatory processes, resulting in the production of ROS. MPO can be measured in CSF as an index of inflammation  and leuk2O2 levels in CSF were associated with elevated BBB permeability, CSF albumin concentrations, and serum H2O2 concentrations. Lastly, it is important to note that MPO reacts with cell matrix metalloproteinases  via activated leukocytes (2–) formed by stimulated PMNs, forms 3-chlorotyrosine (3Cl-Tyr), and to a lesser degree, 3-nitrotyrosine (3NO2-Tyr) and N-chlorotaurine (2-Tyr can be used as a biomarker for peroxynitrite formation and is associated with an unfavorable outcome of BM. In a study of 59 children with confirmed BM (n = 23), increasing even further by day 5 of treatment. It was concluded that MPO may be involved in the oxidative stress associated with BM, as well as potentially contributing to BBB disruption. ukocytes , which iukocytes , with thotaurine . The 3Clotaurine , with GCotaurine . Other birmed BM , CSF MPO+ T cells and functions by activating microglia, thereby stimulating lymphocyte Th1 differentiation  and culture filtrate protein 10 (CFP-10); they are influenced by (1) the antigenic load, (2) host responsiveness to antigens, and (3) host–pathogen interactions (Interferon-γ (IFN-γ) is predominantly produced by CD4ntiation  and antintiation , after intiation ; (2) latntiation ; (3) latntiation ; (4) actntiation ; (5) actntiation ; (6) actntiation , immunodntiation ; (7) actntiation ; and (8)ntiation . Similarntiation  using IGractions .Consolidating from the literature, the CSF studies on IGRAs as a diagnostic tool for TBM , a weighn = 12) and probable (n = 8) TBM patients to be 28.7 ± 8.2 and 10.6 ± 2.8 UI/L, respectively. However, The use of IGRAs for the differential diagnosis of meningitis has, however, yielded a practical outcome. 2O2–Cl2 system yields similar oxidative markers in both TBM and BM.In summary, the overall trend across all CSF VEGF studies is a significantly higher concentration of VEGF in TBM patients than in other cases of meningitis. Of further note, The addition of VEGF and MPO with IFN-γ, as part of a 3-marker immunological biosignature of TBM in CSF , has yieGiven the background of IFN-γ, MPO, and VEGF described above, and the associated metabolic pathways of these signaling compounds, we propose a predictive metabolic model for TBM in the brain based upon previously published biochemistry fundamentals. This model, illustrated in Our predictive metabolic model shows how increased levels of VEGF result in a persistent metabolic burst caused by the induction of angiogenesis , whereby6, as a cofactor. Deficiency of P-5-P diverts tryptophan metabolism from production of NAD to the excessive formation of xanthurenic acid  and tryptophan catabolism  of the brain, using TBM as an example. We posit that if the BGA exists then chronic neuroinflammation within the brain caused by pathogenic bacteria (Mtb) will influence the gut microbiota, and the ideal biofluid to analyze this, reflecting the associated systemic changes, is urine. We support our postulate with data from published studies on urinary metabolomics, as follows.First, the strength of untargeted urinary metabolomics is clearly demonstrated in the literature. A previous untargeted urinary metabolomics study conducted on TBM cases, by Second, we take an independent, and initially unrelated, study that closely examined the immunological profile of TBM, in which three specific immunological markers in the CSF associated with neuroinflammation – VEGF, IFN-y, and MPO – were validated as diagnostic markers of TBM. We explored the background behind this 3-marker CSF immunological signature of TBM, in the context of its influence on the gut-microbiome and the subsequently altered urinary metabolome, using previously discovered urinary metabolites in TBM patients as proof  . By exteThird, we combined the sciences of immunology and metabolomics to create a novel integrated predictive metabolic model of TBM in the brain. By integrating relevant information from systems biology, our predictive cascading metabolic model should be adjustable to account for other types of bacterial infection(s) of the CNS that cause chronic neuroinflammation, such as neurosyphilis, bacterial brain abscesses and Lyme disease, as well as chronic non-bacterial CNS infections that are common in resource-constrained settings of poor communities, and sometimes difficult to distinguish from TBM, such as cerebral malaria and cryptococcal meningitis. Being so identified, based upon the literature, patients with VM and TBM exhibit a similar increase in CSF IFN-γ levels, both far greater than in patients with BM. Hence, a predictive metabolic model of cerebral malaria and cryptococcal meningitis would likely exclude CSF-based IFN-y and its subsequent downstream cascading metabolic influence – that is, no downstream tryptophan metabolic catabolites. What remains to be done is to identify the unique immunological markers associated with these other bacterial infection(s) of the CNS and predict and confirm their associated downstream metabolic markers that should be reflected in urine, which could be used diagnostically or to characterize these diseases better.In short, analysis of urinary metabolic profiles offers a wealth of metabolic information that can be traced back to an altered gut-microbiome, and to an inherently changed BGA, induced by chronic neuroinflammation from bacterial infection(s) of the CNS. This metabolic information from urine holds within it the potential to contribute to improved and early differential diagnosis of bacterial infection(s) in the CNS – a quicker and less invasive method of diagnosis than currently available. The review presented here provides support that, by taking existing validated immunological markers of infectious diseases in conjunction with metabolomics data and biochemistry fundamentals, it is possible to predict downstream metabolic products, most likely detectable via urinary metabolic profiling methods.SM conceptualized the manuscript. SI, SM, and DL planned the outline of the manuscript. SI wrote the manuscript. SM and DL supervised SI in the writing of the manuscript by providing critical feedback. RS provided clinical input and critically read the manuscript. All co-authors read and approved the final draft for submission.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.