Further, the proposed UV spectroscopic techniques were validated as per International Council for Harmonization guidelines. The methods showed good sensitivity, accuracy, and precision. Anticipated procedures were effectively utilized for the concurrent quantification of REM and MET in laboratory prepared mixtures and tablets. The high percent recovery with low standard deviation found for both analytes by all three methods confirms the accuracy and precision of the procedures. Finally, the greenness of the proposed spectroscopic methods, evaluated by semi-quantitative and quantitative methods, showed the eco-friendly nature of the methods. Furthermore, the proposed approaches were simple, accurate, sensitive, economic, and environmentally friendly and hence can be utilized for regular quality control of REM and MET formulation. The recent trend in green analytical chemistry is the development of green analytical methods using environmentally friendly solvents. Therefore, three ecofriendly manipulated UV spectroscopic techniques have been validated for the concurrent quantification of newly approved remogliflozin etabonate (REM) and metformin HCl (MET) tablets using water as a solvent. The first method was established using first derivative absorption spectroscopic method by determining the peak amplitude at 233.0 nm for REM and 252.2 nm for MET, a zero crossing of one the component. The second and third methods were based on the peak amplitude difference and first-order derivative absorption of the ratio spectra developed by the manipulation of scanned UV spectra. REM and MET showed good linearity in the series of 1–20 µg ml Common endocrinological diseases, like Diabetes Mellitus Type 2 (DMT2), are already enormous and growing at alarming percentile throughout the world. As estimated, the number of diabetic patients will increase to more than 500 million by the year 2030 and to more than 700 million by 2045 ,2. NumerOnly two analytical methods ,18 are dUV-spectroscopic methods are simple, rapid, and economical analytical methods for quality control of pharmaceutical preparations used regularly. However, direct UV spectroscopic methods suffer from multicomponent formulations effects and formulation additives effects ,37. FurtReference standards of REM (purity 99.2%) and MET (purity 98.96%) were purchased from Bioteck India Limited, Hyderabad, India. Ethanol used for the preparation of standard solution was analytical grade and has been procured from Sigma Aldrich, St. Louis, MO, USA. Ultra-pure water used during the experiments was arranged in the laboratory with Milli Q (Millipore USA) water purification system. REM (100 mg) and MET (500 mg/1000 mg) tablets were not available in the resident market; hence, tablets were prepared by mixing the required quantity of REM, MET, mannitol, talc, magnesium stearate, microcrystalline cellulose, colloidal silicon dioxide, and polyvinyl pyrrolidone. Shimadzu UV Spectrophotometer (UV-1700)  attached to the computer was utilized for recording the UV spectra. Quartz cuvettes with path length 1 cm were used for recording the spectra for both blank and sample. Instrument scanning speed was adjusted to medium speed with a slit width of 2 nm. UV-probe version 2.0 software  provided with the Shimadzu UV Spectrophotometer was used for the processing of the recorded spectra. Manipulation of UV spectra displayed noise; hence, to generate the smooth spectra, 4 nm has been used as a smoothing wavelength. Graduated long neck flasks used for preparing the stock solutions, working standard and formulation solutions were calibrated before use.Primary standard solutions were prepared by transferring pure drug REM (50 mg) in 50 mL ethanol, because REM was slightly soluble in water, whereas MET (50 mg) was dissolved in 50 mL ultrapure water as metformin HCl is highly water-soluble. Further, working calibration solutions were organized from the primary standards with ultrapure water by maintaining the equivalent amount of ethanol (200 µL) in all flasks. The blank solution consists of the same amount of ethanol (200 µL) as in the standard solutions and ultrapure water. REM and MET tablets were unavailable in the resident market; hence, simulated tablets consisting of 100 mg REM along with 500 mg/1000 mg MET were prepared in the laboratory. Accurately weighed REM (200 mg) was mixed with MET (1000 mg) and MET (2000 mg) separately along with known amount of excipients like mannitol, talc, magnesium stearate, microcrystalline cellulose, colloidal silicon dioxide, and polyvinyl pyrrolidone. All ingredients were thoroughly mixed and the sufficient amount of mixture equivalent to 100 mg REM and 500 mg MET/1000 mg MET was conveyed to a 50 mL graduated flask consisting of 25 mL of ethanol separately. After sonication of flasks for 5 min, the mixture was transferred into other graduated flasks using Whatman filter paper. The filter paper was rinsed with ethanol, and lastly, the volume was attuned to 50 mL by adding ethanol. Further, sufficient amount of water has been added to the aliquot of the above solutions to get the quantity of analytes in the linearity range. The laboratory prepared solutions of diverse portions of REM and MET were organized by transferring the required quantity of REM and MET primary solutions into 10 mL volumetric flasks. −1 for REM  and 2.5 to 35 µg mL−1 for MET . UV absorption of solutions was recorded between wavelength 200 nm to 300 nm against a blank solution. Then the first–order derivative spectra were generated from the stored spectra through 4 nm as ∆λ along with an amplifying feature of 10. The peak amplitude of REM spectra at a wavelength of 233.0 nm and zero crossings for MET and peak amplitude of MET at a wavelength of 252.2 nm and zero crossings for REM were measured. Then the regression equations and correlation coefficients were computed from the linearity curves generated by drawing the graphs using these amplitudes against respective concentrations of REM and MET separately. Calibration curves were constructed separately by transferring an adequate volume of stock solution of REM and MET to 10 mL graduated flasks. The final concentration of solutions for calibration curve were 1 to 20 µg ml−1 and 10 µg mL−1 solutions respectively. UV absorptions of both solutions were measured between 200 nm and 300 nm and the spectra were saved in the computer. Furthermore, required amount of REM and MET stock solution were transferred into same 10 mL graduated long neck flasks to obtain 1 to 20 µg mL−1 of REM and 2.5 to 35 µg mL−1 MET. Then the UV absorption of the solutions was measured in the wavelength 200 to 300 nm, and the spectra were stored. For quantification of REM, ratio spectra were generated by divining the above mixture spectra by spectrum of MET (10 µg mL−1), which were smoothened with 4 nm and stored. The peak amplitude at 248.6 nm was subtracted from the peak amplitude at 277.8 nm of the ratio spectrum. Then the regression equations and correlation coefficients were computed from the linearity curves generated by drawing graphs using amplitude difference value and the corresponding amount of REM. Correspondingly, the ratio spectra of MET were generated by dividing the spectra of analyte mixtures with a spectrum of REM 20 µg mL−1. Further, the variance among the two peak amplitudes of the smoothened ratio spectra was computed at 242.4 and 221.2 nm, and linearity curves were built against the respective concentration of MET. The appropriate volumes of REM and MET stock solutions were added into a 10 mL graduated flask separately to prepare 20 µg mLAbove recorded ratio spectra for REM were changed to first-order derivative spectra via 4 nm as ∆λ and peak amplitude was recorded at 288.4 nm. The regression equations and correlation coefficients were computed from the linearity curve raised by outlining a graph between peak amplitude and the corresponding concentration of REM. Similarly, ratio spectra of MET were changed to a first-order derivative ratio spectra by employing 4 nm as ∆λ. The spectrum height was recorded at 251.7 nm form the different concentrations spectra and plotted against the respective concentration of MET to generate the calibration curve. −1 and 4:20 µg mL−1 correspondingly. Similarly, sample solutions were prepared using the formulation solutions prepared by REM 100 mg and MET 1000 mg to get the finishing amount of 2:20 µg mL−1 and 3:30 µg mL−1 of REM and MET, respectively. Similarly, laboratory mixed solutions were arranged by my transferring necessary volume of REM and MET stock solutions to get different ratios of both the analytes. Absorption of these solutions was measured in the UV wavelength 200 to 300 nm, and spectra were deposited in the workstation. For the first derivative absorption method above, recorded spectra were changed to first-order spectra using 4 nm as ∆λ. Peak amplitudes were noted at 233.0 nm for REM and 252.2 nm for MET. For the ratio derivative absorption method, the spectra were divided separately by MET (10 µg mL−1) and by REM (20 µg mL−1) spectra to get respective ratio derivative spectra. For REM, the peak amplitude difference between 277.8 and 248.6 nm was recorded form REM ratio spectra; similarly, for MET, the peak amplitude of ratio derivative spectra of MET at 242.4 and 221.2 nm was recorded. Further, for the first derivative ratio spectra, the above-computed ratio spectra were changed into first-order derivative ratio spectra through 4 nm as ∆λ. Then, the spectrum amplitude was recorded at 288.4 nm for REM and at 251.7 nm for MET. Finally, the amount of analytes was computed from the respective regression equations. A sufficient amount of sample solutions were transferred from the formulation solutions prepared using REM 100 mg and MET 500 mg into 10 mL graduated flasks to get the quantity of analytes as in the formulation ratio 2:10 µg mLmax 232.9 nm, and it is completely overlapped with the UV absorption of REM,  and MET (2.5 to 35 µg mL−1) were scanned and converted to first derivative spectra, and peak amplitudes were measured at wavelength −232.9 nm and −252.2 nm for REM and MET respectively  of two components (REM and MET) is expressed as a sum of the product of the molar extinction coefficient and concentration. Given by the Beer’s law (Equation (1))R and ЄM are molar extinction coefficient of REM (R) and MET (M), respectively, at one particular wavelength, whereas CR and CM are the concentration of REM and MET, respectively. For quantification of one of the components from the mixture, absorption of only one component needs to be determined by canceling the absorption of another component, which can be carried out by dividing the absorption equation of combination by absorption equation of one of the analytes at a concentration M˚(AM˚ = ЄMCM˚); the simplified Equation is (2)The ratio spectroscopic method was based on dividing the mixture spectrum by one of the analyte spectra to obtain the ratio spectrum, which is free from the interference from the divisor analyte and excipients. Further, use of optimized spectrum as divisor reduces the noise and experimental errors. Another advantage of ratio spectra method over the zero crossing derivative method is that measurements were made in correspondence to the peaks; hence, the measurements are more accurate, sensitive, and specific. One of the disadvantages of zero crossing method is that a small drift at the zero crossing points will not coincide with the working wavelengths, making the measurements less accurate and precise. Hence, the ratio spectroscopic methods  were devM/CM˚ is constant (K), the above equation can be simplified to Equation (3)A is ARM/AM˚ absorbance of ratio spectrum of a mixture to one of the components at some concentration (M˚), SR is the AR/AM˚ absorbance spectrum of one constituent REM to another constituent MET.The CR1 and S R2 were absorption values of spectra at wavelengths λ1 and λ2.From the above equation, K could be excluded by computing the absorbance variance (∆S) at two separate wavelength points (λ1 and λ2) of spectra, conferring to the below equationIt is clear from the Equation (4) that, component M is excluded completely; hence, the absorbance calculated between peak amplitudes at two different points represents only one component R. The concentration of compound R in the mixture can be determined by creating the linearity curve by plotting the graph between peak amplitude differences of ratio spectra with the corresponding concentration of component R. Similar procedure can be adapted to determine another component M from the mixture. −1), and the peak heights difference were determined from the ratio spectra (M/CM˚), which could be omitted by deducting the peak amplitude at 248.6 nm from 277.8 nm. The ratio spectra generated from mixture spectra and pure standard REM spectra showed the same amplitude difference, indicating REM could be estimated even in mixture with MET. Similarly, MET has been quantified by generating the ratio spectra by dividing the mixture spectra by REM spectra (20 µg mL−1). The two wavelengths selected were peak 247.4 nm and trough 221.2 nm; the peak amplitude difference between these two points is correlated to the amount of MET , present in the Equation (2), could be removed by transferring the ratio spectrum into first-order derivative spectrum. Derivative spectrum gives a number of positives (maximum) and negatives (minimum) spectra points; the amplitude of maximum or minimum is proportional to one of the components, eliminating the effect of another analyte as well as that of formulation excipients. Furthermore, the major advantage of ratio derivative spectroscopic method is measurements can be made at any of the maximum or minimum peaks, no need for working only at zero crossing points as in the zero-crossing derivative spectroscopic methods. The derivatization of ratio spectra gives high amplitude values when compared to derivatization of normal spectra. Further, this is a substitute to the aforementioned first derivative spectroscopic and ratio absorbance difference method for quantification of REM in presence of MET and Vice versa.The impact of constant  and 2.5 to 35 µg mL−1 of MET  were analyzed in triplicate. All experiments were conducted as per the optimized condition, and the regression parameters were tabulated :−1 of REM and 4, 14, 24, and 32 µg mL−1 of MET were prepared and analyzed in triplicate. For intra-day, solutions were analyzed in one day, and for inter-day, similar solutions were evaluated for three consecutive days  were analyzed using two concentrations in each ratio. Further, percent recoveries were calculated by standard addition method at three different concentrations by adding 50%, 100%, and 150% to earlier evaluated tablet solution comprising of 2 µg mL1 of MET . The ass1 of MET  of the fThree different greenness evaluation techniques were used to estimate the ecofriendly nature of the UV spectroscopic methods developed in this study. First method is semi qualitative method developed by Raynie et al. . EthanolAccording to the analytical eco-scale method  penalty Plotka-Wasylka introduced the combination of qualitative and quantitative greenness calculation method known as green analytical procedure index (GAPI) . GAPI coThree simple, accurate, UV spectroscopic methods were established for concurrent quantification of REM and MET without the use of any complicated mathematical processing. Derivative and ratio derivative methods have many advantages over liquid chromatographic methods in terms of speed, economy, and specificity. Furthermore, the developed methods utilized water as a major solvent, making them economical and ecofriendly, which was confirmed by three greenness evaluation methods of analytical procedure. The applicability of the current methods could be assessed by analyzing both analytes in laboratory prepared solutions in different ratios and in tablets with excellent accuracy and precision. Hence, these methods could be utilized for regular quality-control study of REM and MET formulations in pharmaceutical industries and clinical laboratories.


Quantification of antibiotic utilization is an essential component of antibiotic stewardship programs. In this multicentric study, we used different metrics to evaluate inpatient antibiotic use in children. The study objectives were to describe point prevalence of antibiotic use by indication and patient characteristics, to evaluate DOTs, LOTs and PDDs, and to compare PDDs to DDDs, which assume average maintenance dose per day in adults. All children hospitalized on the days of the study were included. Trained personnel collected demographic and clinical data from patients’ clinical records. We recorded information about antibiotics administered on the date of data collection, and in the previous 30 days of hospitalization. Of 810 patients, 380  received one or more antibiotics; prevalence of use was 27.0% for prophylaxis (219/810), and 20.7% (168/810) for treatment. Overall, 587 drugs were issued to the 380 patients receiving antibiotics (1.5 antibiotic per patient). When considering treatments, DOT and LOT per 100 patient-days were 30.5 and 19.1, respectively, resulting in a DOT/LOT ratio of 1.6. PDDs increased with age and approached DDDs only in children aged ≥ 10 years; the ratio between PDDs estimated in children aged ≥ 10 years and in 0–11 month-old infants ranged from 2 for sulfamethoxazole and trimethoprim, to 25 for meropenem. Our results confirm that DOT, LOT and PDD are better alternatives to DDD in children. Children represent an excellent population for the selection of resistant bacterial pathogens after recent antimicrobial use4. Therefore, the investigation of antibiotic consumption in the pediatric population is crucial, especially in the hospital setting where the risk of the emergence and transmission of bacterial resistance is dramatically increased3.Improving the use of antibiotics is an important patient safety and public health issue, as well as a global priority7. Quantification of antibiotic utilization is an integral part of ASPs. Hospital antibiotic consumption is commonly measured by calculating the daily defined doses (DDDs), as defined by the World Health Organization Collaborating Center for Drug Statistics Methodology, divided by a denominator indicating clinical activity (e.g. DDDs per 100 patient-days)9. DDD is calculated as the assumed average maintenance dose per day for a drug used for its main indication in adults. Even if DDDs allow the comparison of drug use between different settings and between different drugs, they do not reflect the dosage actually used for individual patients or specific patient populations10, and their use is not recommended in children11. To overcome these issues, in-hospital antibiotic use in children is frequently estimated by conducting point-prevalence surveys (PPS). Although the PPS design has been extensively used to evaluate antibiotic use, it cannot capture treatment duration. Other antibiotic consumption indicators are days of therapy (DOTs), length of therapy (LOTs) and prescribed daily doses (PDDs). DOTs are computed summing up the duration (in days) of each antibacterial drug received for treatments. LOTs are the number of days that a patient receives an antibacterial drug irrespective of the number of different drugs. DOTs and LOTs give an accurate estimation of polydrug therapy and duration of therapy, respectively; since they do not consider whether a nonstandard dose was given12, they could be considered as accurate metrics of drug use for children. The PDD provides the average daily amount of a drug that is actually prescribed13. In this multicentric study, we adopted different metrics to evaluate inpatient antibiotic use in hospitalized children. The study objectives were to describe point prevalence of antibiotic use by indication and patient characteristics, to estimate DOTs, LOTs and PDDs as additional metrics to quantify antibiotic use, and to compare PDDs to DDDs by antibiotic and age group.A growing body of evidence demonstrates that hospital based antibiotic stewardship programs (ASPs) can both optimize the treatment of infections and reduce adverse events associated with antibiotic useIn our study, we included 810 children. Patients were mostly males , aged ≥  10 years years  and with a length of hospital stay ≤ 7 days   received one or more antibiotics. The proportion of patients receiving antibiotics significantly varied by hospital, age, sex, comorbidities and surgical procedures. In particular, the prevalence of use was significantly higher in patients aged ≥ 2 years compared to those in the first year of life, in males with respect to females, in patients without comorbidities compared to those who had at least one chronic disease, and in patients who underwent at least one surgical procedure . Children receiving antibiotics for surgical or medical prophylaxis accounted for 14.3% (116/810) and 12.7% (103/810) of the hospitalized patients, respectively. Surgical prophylaxis lasted more than 24 h in 76.7% of the patients (89/116). Patients treated for CAIs were 13.2% (107/810) of children, followed by patients treated for HAIs .Overall, 587 drugs were issued to the 380 patients receiving antibiotics (1.5 antibiotic per patient), mainly administered intravenously . Prescriptions for treatments were 42.8% (251/587); of those, the majority of antibiotics was administered for CAIs , and the remaining for HAIs . Overall, microbiological cultures were performed before starting the antibiotic therapy in 54.5% of the treatments (137/251). In 23.1% of the prescriptions (58/251), the results of the antibiogram were available and the antibiotic therapy could be considered as targeted, whereas 68.1% (171/251) of the treatments were empirical. The main infection sites were respiratory tract infections (both low tract and pneumonia), bloodstream infections, and urinary tract infections, which were reported as the reason for therapy in respectively 29.9%, 23.5% and 2.4% of the antibiotic treatments for infections.The top three antibiotic classes were combinations of penicillins including β-lactamase inhibitors , third-generation cephalosporins  and aminoglycosides  of first-generation cephalosporin prescriptions J01DB) were issued for surgical prophylaxis, followed by second-generation cephalosporins  and imidazole derivatives  , fluoroquinolones (J01MA) and combinations of penicillins including β-lactamase inhibitors (J01CR) were mainly prescribed for medical prophylaxis  , third generation cephalosporins  and combinations of penicillins including β-lactamase inhibitors  whereas HAIs were mainly reported for penicillins with extended spectrum , glycopeptides  and aminoglycosides .DOTs and LOTs were estimated considering 414 inpatient antibiotic treatments, over a total of 9458 inpatient days, retrospectively evaluated considering the 30 days prior to the collection of the point prevalence data on antibiotic use. Overall, we estimated 30.5 DOTs per 100 patient days and a 19.1 LOT per 100 patient days resulting in a DOT/LOT ratio of 1.6 Table . DOT andThe overall DOT/LOT ratio of 1.6 indicated that the combination antibacterial treatment was common Table .Table 14. We showed how hospital and patient characteristics, such as age and comorbidities, are related to the use of antibiotics, and other authors have shown that the prevalence of antibiotic use is higher in third-level hospitals where patients generally have more complex conditions15. As patient population characteristics are major determinants of antibiotic consumption, risk adjustment should be adopted to compare antibiotic consumption data among hospitals and over-time. In our results, previous surgery was significantly associated with antibiotic use and surgical prophylaxis was the most frequent indication. As previously documented16, we showed a suboptimal appropriateness of antibiotic surgical prophylaxis; in fact, there was still a proportion of patients treated with non-recommended broad-spectrum active substances, such as III-IV generation cephalosporins.Out of more than 800 children included in our study, 47% were treated with at least one antibiotic. This estimate is higher than reported in European hospitalized children, where the point prevalence of antibiotic use was 39.6%17. In our study, approximately 77% of the patients undergoing surgical prophylaxis received surgical prophylaxis for more than 24 h. This is in line with previous prevalence surveys, which estimated a proportion of children subject to prolonged surgical prophylaxis (> 1 day) fluctuating between 67 and 78% in Europe16. These data show that even in the most documented evidence-based area of practice, which recommends a surgical antimicrobial prophylaxis duration of less than 24 h, clinicians tend to overprescribe, and this is a global phenomenon not exclusively limited to Europe3. Combinations of sulfonamides and trimethoprim and combinations of penicillins including beta-lactamase inhibitors have been the most widely used active substances for medical prophylaxis, being widely used to prevent opportunistic infections in neutropenic patients18. Medical prophylaxis, as well as infection treatments, include a wide range of diseases and it is therefore difficult to identify unambiguous recommendations in patients with very different clinical conditions.Another worrying aspect is the duration of surgical prophylaxis; in fact, although a prolonged exposure does not reduce the risk of surgical site infections, it represents a relevant ecological risk19. We collected DOT, LOT and PDDs as more specific antibiotic indicators for infection treatments with respect to DDDs, which are not recommended for children because doses used are typically much smaller than in adult populations, so this measure underestimates patient exposure to drugs11. DOT and LOT have been used to monitor antibiotic use and to assess the impact of antibiotic stewardship programs on improving appropriateness of prescriptions in children13. We showed that calculation of DOT and LOT by retrospectively reviewing medical records was feasible.Although point prevalence surveys are useful to assess the pattern of in-hospital antibiotic prescriptions, antibiotic use should be preferably expressed with multiple metrics20. Intensive care units were the setting with the highest antibiotic use, with LOT and DOT rates per 100 days of 28.5 and 47.2, respectively. Moreover, a DOT/LOT ratio of 1.6 confirms the frequent resort to multi-therapies found in the prevalence survey where an equal average number of active substances per patient was detected.DOT/100 patient days was comparable with antibiotic prescriptions for infections in a secondary pediatric hospital in the Netherlands, where the average DOT/100 in neonatal and pediatric wards was between 23 and 453, our study showed that PDD increased with age and approached to DDD only in children aged ≥ 10 years. Although there was no difference between DDDs and PDDs of antibiotic drugs belonging to the class of aminoglycosides and cephalosporins in this age group, a difference was observed for other antibiotic drugs. PDDs lower than DDDs could be explained considering that children’s weight is lower than the standard weight used to compute DDDs, otherwise PDDs higher than DDDs could be reconducted to the patients’ clinical conditions to be treated. It could be the case of meropenem that is frequently used to treat serious healthcare associated bloodstream infections requiring more aggressive dosages.Both LOTs and DOTs included the underlying assumption that antibiotic dosing was appropriate. PDDs represented the real prescribed doses of drugs in children. As reported also in a previous study21.This multicentre study was conducted in four stand-alone tertiary care children’s hospitals located in Regions in the North, Centre, and South of Italy. Trained investigators collected data regarding antibiotic prescriptions from clinical records minimising the effect of information bias on our study results. Additionally, in contrast to studies that are based on information collected directly from patients medical clinical records, we had no need to restrict the sample size. The study limitations are inherent to the epidemiological methods of our cross-sectional survey, where the main purpose was to describe prescribing patterns in hospitals. The overall rate provided is the average. We did not control for patient case mix, disease incidence, prevalence of different types of infections, variations in resistance levels, institutional factors, all of which can influence antibiotic use patternsIn conclusion, our results confirm that DOT, LOT and PDD are better alternatives to DDD in children. The availability of electronic clinical records can greatly enhance data accessibility to calculate DOT, LOT and PDD data and use those data within antibiotic stewardship programs, as alternative to DDDs in pediatric population.This study was conducted between November and December 2016 and involved four tertiary care children’s hospitals in Italy: Ospedale Infantile Regina Margherita , Ospedale dei Bambini di Brescia , Bambino Gesù Children’s Hospital  and Ospedale Pediatrico Giovanni XXIII . These tertiary care children’s hospitals have a total number of beds ranging from a minimum of 157 to a maximum of 607, with an annual number of inpatients ranging from 5700 to 27,000. Pediatric surgeries and pediatric intensive care units are present in all the participating centres; Onco-Haematological Units and Neonatal Intensive Care Units are present in three centres.14, drug brand name, route of administration, dosage, number of doses per day, and indication for antibiotic administration, defined as community-acquired infections (CAIs), hospital-acquired infections (HAIs), medical or surgical prophylaxis. For antibiotics used for treating infections, collected information included also the site of infection and whether microbiological investigations were performed prior to starting antibiotic therapy. The protocol of this study was approved by the Ethical Committee of the Bambino Gesù Children’s Hospital (N° 1238_OPBG_2016) and all methods were performed following relevant guidelines and regulations. Since data were collected by reviewing medical charts and were analyzed anonymously, informed consent was not deemed necessary. The need for informed consent was waived by the Ethical Committee of the Bambino Gesù Children’s Hospital.The data collection was carried out during a calendar week and involved all children hospitalized on the study days. Data were collected by trained personnel from patients’ paper medical charts. Information collected for each patient included: age, sex, length of hospital stay, and ward type. To assess point prevalence, we collected information about antibiotics administered during the days of data collection. To estimate DOT and LOT, we retrospectively recorded information about antibiotics administered during hospitalization, up to 30 inpatient days prior to the week of data collection. Information on antibiotics included Anatomical Therapeutic Chemical Classification code, ATC J01)22. All the data were analyzed anonymously.All the collected data were uploaded on REDCap (Research Electronic Data Capture) database which is a secure web application for building and managing online surveys and databases, available at no charge to not-for-profit institutionsPatients were described according to demographic and clinical factors. Collected data were presented as count and proportions  or median and interquartile range . The wards where the patients were hospitalized were categorized as medical , surgical  and intensive care units (ICUs) .The metrics we calculated included point prevalence of antibiotic use, DOTs, LOTs and PDDs. The prevalence of antibiotic use was calculated as the ratio between the number of patients under treatment with at least one antibiotic on the survey day, and the total number of hospitalized patients. Prevalence of use was computed by age group , sex, hospital ward, lenght of hospital stay, comorbidities, surgical procedures during hospitalization, participating centre and indication. Comparisons among groups were conducted using the Chi-squared test.Antibiotic drugs were classified according to the Anatomical Therapeutic Chemical Classification code (ATC: J01); a percentage distribution of antibiotic drugs substances by indication of use was computed considering the antibiotic prescription administered on the survey date and those received in the previous 30 days.20, considering the 30-days study period. For each patient, DOTs were computed summing up the duration (in days) of each antibacterial drug received for treating infections. LOTs were the number of days that a patient received an antibacterial drug irrespective of the number of different drugs12. DOTs/100 patient days and LOTs/100 patient days were computed stratifying for sex, age classes, ward type, type of active substances and targeted versus empirical therapy; groups comparisons were performed using Student’s t-test and one way ANOVA test. PDDs were defined as the observed dose received by each patient in grams and was calculated for the most frequently used antibiotics. Due to the extremely large differences in dosing in pediatrics, ranging from pre-term neonates to teenagers, median PDDs, and the respective IQRs, were estimated and stratified into five age groups , as previously described3. All statistical analyses were conducted using STATA 13 .DOTs and LOTs were computed on treatments


In vivo and in vitro, Met exerted cardioprotection function of decreasing myocardial inflammation and apoptosis with a decrease in the level of autophagy. Moreover, Met significantly inhibited autophagosome formation and restore the impairment of autophagosome processing, which lead to cardioprotection effect of Met. Akt was up-regulated in Met-treated I/R hearts and miransertib, a pan-AKT inhibitor, was able to reverse the alleviating autophagy effect of Met. We demonstrate that Met protects cardiomyocytes from I/R-induced apoptosis and inflammation through down regulation of autophagy mediated by Akt signaling pathway.Metformin (Met) is a major widely used oral glucose lowering drug for the treatment of type 2 diabetes. It is reported that metformin could regulate autophagy in various diseases of cardiovascular system including in I/R injury, diabetic cardiomyopathy and heart failure. Autophagy plays a controversial role in ischemia/reperfusion (I/R) injury, and this research was performed to explore the cardioprotective effect of Met on I/R injury and discuss the underlying mechanism of autophagy in it.  Acute myocardial infarction (AMI) is one of the major diseases threatening human life in the world in vivo model of I/R and an in vitro model of H2O2-induced I/R injury. Our findings led to a new view that Met could compromise autophagy, thus dampen apoptosis, inflammation in non-diabetic myocardium and protected heart from I/R injury through activating Akt. This study provided us an insight into the mechanism of Met in protecting myocardial I/R injury under a new perspective.Therefore, the aim of this study was to investigate the role of autophagy in the protection of Met against non-diabetic myocardial I/R injury, using an All experiments performed on animals were approved by Animal Care and Use Committee of Wenzhou Medical University and were in accordance with the ARRIVE guidelines for reporting experiments involving animals. Specific pathogen free (SPF) male C57BL/6 mice (20-25g), 7-8 weeks old, were obtained from the SLAC Laboratory Animal Centre of Shanghai. In each cage, 3-4 mice could take food and water at will under a 12 h light-dark cycles with a constant room temperature (25±2 °C) for one week before the experiment. All efforts were made to minimize the suffering of the animals and the number of animals. The results were based on the rule of the replacement, refinement or reduction (the 3Rs). H9C2 cells was obtained from the American Type Culture Collection , were cultured in Dulbecco's Modified Eagle's Medium (DMEM) containing 4.5 g/L glucose, 10% fetal bovine serum (FBS), and 1% penicillin/streptomycin at 37°C in a humidified atmosphere. All of the above cells were passaged for less than 6 months from the day of recovery. Primary cultures of neonatal mouse cardiac myocytes were prepared as described previously Surgical ligation of the left coronary artery (LCA) was performed as described previously in vitro is 6.When cells reached 70-80% confluence, subsequent experiments were performed. Briefly, H9C2 cells were cultured with 250µM H2O2 in DMEM containing 2% FBS for 4 h to induce I/R procedure. To evaluate the protective effects of Met and the role of autophagy, cells were pretreated with Met (50 μM), CQ (10 μM) for 12h, rapamycin (100 nM) and 3-MA (10 mM) for 2h. The exact group size for each experimental group Akt knockout cultured primary cardiomyocytes were generated with CRISPR-Cas9 plasmid and crRNA (sequence: 5'-ACAGAGAAATTGTTCAGGGG-3') targeting host gene (Akt) expression vector. The CRISPR-Cas9 system was produced by Ribo-Bio . Experimental samples were obtained 72 h after transfection according to the directions of the manufacturer.2O2  were added to cardiomyocytes and incubated for 4 h to determine an appropriate condition of I/R procedure. On the other hand, Met, rapamycin, CQ and 3-MA were pretreated as described above. After treatment, the cells were washed with phosphate-buffered saline (PBS), and then cells were incubated in 10% CCK-8 solution (v/v) for an additional 2 h and cell viability was evaluated by CCK-8 assay. The amount of cell viability was normalized to the control group, which was considered as 100%.Cell viability was assayed with the CCK-8 according to the manufacturer's protocol. In brief, H9C2 cells were planted in 96-well plates (5000 cells/ well) and incubated in DMEM with 10% FBS at 37 °C until confluence reached 70-80%. At first, various doses of HFluorescent probe MDC is a marker for autophagolysosomes to evaluate autophagy Fluorescent dye Tetramethylrhodamine ethyl ester (TMRE) was used to measure mitochondrial membrane potential (MMP) according to the manufacturer's instructions. H9C2 cells were loaded with TMRE (20 nM) for 30 minutes at 37 °C in the dark. Cells were washed 3 times with PBS, and then fluorescence images were captured using fluorescent microscope (Olympus). In order to determine the relative level of TMRE, values of each sample were divided by the mean value of samples from the control group.The level of CK-MB was assayed in serum according to the manufacturer's instructions with a microplate reader .Evan blue and triphenyltetrazolium chloride (TTC) double staining were used to assess infarct size. At the end of reperfusion, LAD was ligated again and 0.3 ml 2% Evan blue was injected into the inferior vena cava of mice. After turned to blue, the heart was removed quickly. Then, rinsed with saline, the heart was embedded in OCT and frozen at -20 °C. Five 1mm thick slices were produced and were incubated in 1% TTC at 37 °C for 20 min. The area that turned red after dyeing was defined as area at risk (AAR). The non-ischemic area was deep blue. The area that turned pale was defined as Infarct area (INF). A percent of infarcted area over total area at risk was calculated by Image J software.The mouse heart was fixed at least 24 h in 4% formalin solution and embedded in paraffin. The sections (4 µm) were made and fixed on glass slides, then stained with hematoxylin-eosin (H&E). Light microscopy (Olympus) was used to observe the pathological structural changes of heart.in vivo PI labeling as described previously We examined the level of apoptosis and necrosis in the myocardium by The mouse heart were harvested at 7 days after I/R injury and fixed at least 24h in 4% formalin solution and embedded in paraffin. The sections (4 µm) were made and fixed on glass slides. Collagen fibers were stained by Masson's trichrome kit according to the manufacturer protocol.The myocardium was fixed with 2.5% glutaraldehyde as well as stained in uranyl acetate and dehydrated in ethanol. Following this, they were embedded in epoxy resin and examined with a transmission electron microscope . Five fields were randomly selected from each sample and used to calculate the number of autophagosomes.Western blotting was carried out in previous studies Statistical analysis was performed by the SPSS software 21.0. Statistically significant differences were evaluated by Student t test (for two groups) and one-way ANOVA with Tukey's post hoc test or nonparametric Kruskal-Wallis test followed by the Bonferroni test (for multi-group). The data are expressed as mean±SD. P<0.05 was considered significant.Met, CQ, TTC, Evans Blue, dimethyl sulfoxide (DMSO), TMRE, MDC, PI, Hoechst was obtained from Sigma-Aldrich . Miransertib was purchased from Selleck Chemicals .DMEM and FBS were purchased from Gibco Laboratories .CCK-8 was purchased from Dojindo Laboratories .The commercial assay kits for the CK-MB were from Jiancheng Bioengineering . The primary antibodies used were anti-IL-1β, anti-glyceraldehyde-3-phosphate dehydrogenase (GAPDH) Bioworld , anti-IL-6 , anti-Bax, anti-phospho-Akt, anti-Akt, anti-phospho-mTOR and mTOR, anti-phospho-AMPK and AMPK, anti-Beclin-1, anti-P62, anti-Atg5 were purchased from Cell Signaling Technology . In addition, anti-LC3B from Sigma and anti-Bcl-2 from Absin were used. All the antibodies were from rabbits and dilutions of antibodies were 1:1000, except anti-GAPDH (1:5000).in vitro experiment. By detecting cell viability, we pretreated H9C2 cells with different concentrations of H2O2 for 4 hours, and finally decided to treat H9C2 cells with 250 µM H2O2 for 4 hours to mimic I / R injury in vivo  15 min before surgery, then the myocardial infarction size, serum CK-MB, myocardial apoptosis as well as myocardial pathological changes were detected. As shown in Figure in vivo results, the accumulation of autophagic vesicles detected by MDC showed that the number of autophagic vacuoles in Met treatment group was significantly less than that in I/R injury group  and apoptotic protein (Bax) increased, while anti-apoptotic protein (Bcl-2) decreased and MDC staining (cardiomyocytes). These findings suggested that Met-mediated autophagy depends on the activation of Akt signaling pathway.To detect whether metformin inhibits autophagy during I/R injury via Akt signaling pathway, we employed miransertib or Akt-KO (CRISPR/Cas9) to inhibit Akt, both in vivo and in vitro.Acute myocardial infarction (AMI) is one of the main causes of death threatening human life A growing number of studies have confirmed the activation of autophagy levels in many pathological states of the cardiovascular system, such as myocardial hypertrophy Myocardial ischemia and reperfusion can trigger necrosis and apoptosis, both of which can lead to the loss of myocardial cells and thus reduce cardiac function Both experimental and clinical studies confirm that Met holds the ability to protect the heart from impairment of hyperglycemia In the present study, we found that Met attenuated I/R injury, and phenotypically, Met attenuated cardiomyocyte apoptosis, inflammatory responses during myocardial I/R injury which were due to Met-mediated alleviation of autophagy. Meanwhile, these beneficial effects could be reversed by inhibition of autophagosome formation (with rapamycin) or autophagosome processing(with CQ), illustrating that the cardioprotection of Met was mediated by reducing autophagosome formation and restoring autophagosome processing. Previous study demonstrated that the accelerated death of cells occurred mainly in the reperfusion stage rather than in the ischemic stage However, some of our conclusions seemed to conflict with other studies. First, great deals of studies have verified that Met has a protective effect by activating autophagy via the AMPK pathway in various diseases The potential limitation of our study is that we only studied the protective effect of acute, low dose Met preconditioning on myocardial I/R injury. But in fact, whether Met injected during reperfusion has the same or other autophagy-related protective mechanisms also seems to be of great necessary. And studies had shown that chronic Met therapy was of cardioprotection In summary, our study confirms for the first time that pre-ischemic injection of an acute, single, low-dose Met attenuates myocardial autophagy, thereby inhibiting inflammation and apoptosis, and protects against myocardial I/R injury. This cardioprotective effect is related to activate Akt signaling pathway.Supplementary figures and tables.Click here for additional data file.


Thermotogales and Aquificales, while a 76 aa insert in SecA is specific for the order Thermales and Hydrogenibacillus schlegelii. Phylogenetic analyses on SecA sequences show that the shared presence of these CSIs in unrelated groups of thermophiles is not due to lateral gene transfers, but instead these large CSIs have likely originated independently in these lineages due to their advantageous function. Both of these CSIs are located in SecA protein in a surface exposed region within the ATPase domain. To gain insights into the functional significance of the 50 aa CSI in SecA, molecular dynamics (MD) simulations were performed at two different temperatures using ADP-bound SecA from Thermotoga maritima. These analyses have identified a conserved network of water molecules near the 50 aa insert in which the Glu185 residue from the CSI is found to play a key role towards stabilizing these interactions. The results provide evidence for the possible role of the 50 aa CSI in stabilizing the binding interaction of ADP/ATP, which is required for SecA function. Additionally, the surface-exposed CSIs in SecA, due to their potential to make novel protein-protein interactions, could also contribute to the thermostability of SecA from thermophilic bacteria.SecA is an evolutionarily conserved protein that plays an indispensable role in the secretion of proteins across the bacterial cell membrane. Comparative analyses of SecA homologs have identified two large conserved signature inserts (CSIs) that are unique characteristics of thermophilic bacteria. A 50 aa conserved insert in SecA is exclusively present in the SecA homologs from the orders  Thermotoga maritima, which can survive within a wide temperature range of 55–90 °C, has been an area of intense research interest [Thermus aquaticus (Taq) polymerase in the technique of polymerase chain reaction (PCR) [Thermophilic organisms (bacteria) are of great scientific interest due to their ability to grow at temperatures well above 60 °C ,2,3,4,5.interest . Thermosinterest . Specifion (PCR) . Severalon (PCR) ,11,12. Oon (PCR) . The incon (PCR) . Sequencon (PCR) ,15,16. Eon (PCR) ,17.Aquificae, Deinococcus–Thermus, and Thermotogae [Thermotoga maritima, Thermus aquaticus, and Aquifex aeolicus), are notable for their thermostable enzymes [Aquificae is primarily comprised of thermophilic–hyperthermophilic organisms [Thermotogales and Thermales) of these bacteria [Thermotogae, Aquificae, and Deinococcus–Thermus) of bacteria and their suborders [Within the domain Bacteria, hyperthermophilic organisms are mainly present in three bacterial phyla viz. rmotogae ,19,20,21 enzymes ,9,22. Horganisms ,20, in tbacteria ,24,25,26uborders ,28,29,30Thermotogales (phylum Thermotogae) and Aquificales (phylum Aquificiae), while another large 76 aa insert has uniquely shared characteristics of the SecA homologs from the order Thermales (phylum Deinococcus–Thermus) and in Hydrogenibacillus schlegelii, a thermophilic bacterium from the phylum Firmicutes. The shared presence of these large and unique sequence features in the SecA proteins from only the hyperthermophilic members of these phyla strongly suggests that the identified genetic/biochemical changes are related to the thermophilic characteristics of these organisms and they should be playing an important role in the thermostability of this protein.SecA is a conserved ATPase whose homologs are well-preserved among all bacteria ,32. It cThermotogales and Aquificales), we have performed molecular dynamics (MD) simulation at two different temperatures (303.15 K and 363.15 K) using the available SecA structure (TmSecA) from T. maritima, which contains this large CSI. The results from MD simulation studies identify a conserved network of water molecules whose interaction with the bound nucleotide in the SecA protein is mediated/stabilized by certain conserved residues from this CSI in TmSecA. The significance of these observations in the context of the specificity of the identified CSIs for thermophilic organisms are discussed.We report here the results of phylogenetic studies examining the evolution of these large CSIs in the thermophilic organisms, as well as the sequence compositions, structural features, and location of these CSIs in the SecA protein structure using the homology models and available structural information. Lastly, to gain some insights into the functional significance of the 50 aa CSI in SecA protein (which is uniquely found in members of the orders www.GLEANS.net). Unless otherwise indicated, all of the reported CSIs are specific for the group of interest, and similar CSIs were not observed in homologs from any other bacterial species within the top 500 BLASTp hits examined.The described CSIs in the SecA proteins were identified as described in earlier work ,38,39. IFor phylogenetic studies, protein sequences for SecA homologs for species from different groups of interest were obtained by means of BLASTp searches. A multiple sequence alignment of these protein sequences was constructed using ClustalX 2.1 . Poorly Thermotoga maritima and Thermus thermophilus SecA proteins lacking the 50 aa CSI were created using an in-house pipeline, “GlabModeller,” as described in earlier work [T. maritima (PDB ID: 4YS0) and T. thermophilus (PDB ID: 2IPC) were used as templates [The homology models of the ier work ,46,47,48emplates ,36. In bemplates . Selecteemplates , ERRAT [emplates , PROSA [emplates ,54, and emplates . These aT. maritima SecA (PDB ID: 4YS0) resolved at 1.85 Å were obtained from the protein data bank (PDB) and the homology model of TmSecA lacking CSI was utilized. The potential energy of the system was minimized using a 50,000-step steepest descendent method to relax the system and to avoid any steric clashes. Missing amino acid residues in the crystal structure of TmSecA were identified and fixed using the MODELLER implemented in the GlabModeller tool. After energy minimization, the system was equilibrated with isothermal–isochoric/NVT  ensemble and then 100 ns of MD simulation in the isothermal–isobaric/NPT  ensemble using the Nose–Hoover thermostat and Parrinello–Rahman barostat [T. maritima SecA with CSI and without CSI was carried out. The T. maritima SecA with ADP was simulated under two different reference temperatures of 303.15 K and 363.15 K. These large temperature gaps were selected to investigate the effect of temperature on the TmSecA dynamics during the simulation period. The root mean square deviation (RMSD) and hydrogen bond interaction calculations were carried out using the GROMACS utilities. All MD simulation runs were carried out using our local GROMACS certified graphical processing unit (GPU) accelerated high-performance computing system obtained from EXXACT Corporation [www.pymol.com).The all-atom molecular dynamics simulations were performed using  GROMACS 5.1.2 software ,57 with barostat ,60,61. Cporation . A totalporation , VMD [63Thermotogales and Aquificales. As seen from Thermotogae, this CSI is a shared characteristic of all members from the order Thermotogales, but it is not found in any of the species from the orders Peterotogales and Kosmotogales. It should be noted in this regard, that within the phylum Thermotogae, the order Thermotogales encompasses all of the thermophilic–hyperthermophilic organisms, whereas the other two orders lacking this CSI are comprised of mesophilic organisms [Thermotogae, this CSI is uniquely found in the organisms which are thermophilic–hyperthermophilic [Thermotogales, this large CSI is also commonly shared by different species belonging to the order Aquificales from the phylum Aquificae, which is also comprised exclusively of hyperthermophilic organisms. However, within this phylum members belonging to the order Desulfurobacteriales, which are strict anaerobes [Our comparative analysis of SecA protein sequences from different bacterial groups has identified several CSIs in SecA protein that are specific for particular groups/taxa of bacteria. However, the present study focuses on our identification of two large CSIs in the SecA protein, which are uniquely found in different homologs from the thermophilic–hyperthermophilic phyla of bacteria. The first of these CSIs shown in rganisms ,23,26,64mophilic ,28. Intenaerobes ,65, do nThermales belonging to the phylum Deinococcus–Thermus. The phylum Deinococcus–Thermus contains two extensively studied orders of extremophilic microorganisms i.e., Deinococcales and Thermales [Thermales is comprised exclusively of organisms that are thermophilic and hyperthermophilic [Deinococcales are known for their high degree of radiation resistance [Thermales but not in any of the homologs from Deinococcales. Further, in addition to the members from the order Thermales, this insert in SecA is also commonly shared by the species Hydrogenibacillus schlegelii, which is a thermophilic bacterium belonging to the phylum Firmicutes [The second large CSI in SecA protein that we have identified is a 76 aa insertion in a conserved region see , which ihermales ,30. Of tmophilic ,30, whersistance ,30,66. Irmicutes ,68,69. TThermotogae and Aquificae form distinct clades and the two orders of these bacteria viz. Thermotogales and Aquificales, which contained the 50 aa insert are separated from each other by other members of these phyla, which do not contain the 50 aa insert. Similarly, members of the order Thermales and the Firmicutes species H. schlegelli, both of which contained the 76 aa insert, also did not cluster together in the phylogenetic tree. Instead, members of the order Thermales branched with other members from the phylum Deinococcus–Thermus, whereas H. schlegelli branched within a cluster of other species from the phylum Firmicutes. If the shared presence of the 50 aa CSI and 76 aa CSI in the two indicated groups of organisms was due to horizontal gene transfers, then it was expected that the SecA genes from these CSI-containing organisms should have clustered together in the tree. However, as the observed branching pattern of the CSIs-containing organisms is contrary to this expectation, it strongly suggests that the shared presence of the large CSIs in either the order Thermotogales and Aquificales, or in Thermales and H. schlegelli, is not due to horizontal gene transfers. Instead the results obtained suggest that the genetic changes leading to these large inserts have occurred independently  in these lineages due to their presumed selective advantage.As both these large CSIs are present in only the thermophilic members from two different phyla of bacteria, it was of much interest to investigate how the shared presence of these genetic changes in two distinct groups/phyla of bacteria could be explained. Based on earlier work, horizontal gene transfers are indicated to occur frequently between members of the bacterial phyla that contain thermophilic–hyperthermophilic organisms ,26,28,70As the two large CSIs in the SecA proteins are found exclusively in the bacterial groups/orders that consist entirely of thermophilic and hyperthermophilic organisms, it strongly suggests that they play some role in the thermostability of the SecA protein. Hence, exploration of the functional characteristics of these CSI could provide some insights into the thermostability of the SecA protein. Based on earlier studies, thermostability of proteins is enhanced by an increase in the charged amino acids that facilitate increased ion-pair interactions and stabilize the protein in high entropy environment ,13. The Bacillus subtilis and Mycobacterium tuberculosis), and from thermophilic bacteria (Thermus thermophilus (PDB ID: 2IPC) and Thermotoga maritima (PDB ID: 4YS0)) [T. maritima SecA (TmSecA) [TmSecA protein lacking the 50 aa CSI, using the protocol described in the Methods section, for the comparative analyses of structural features and location of this conserved insert  (PDB: 2IPC) [TtSecA at the periphery of NBD2. However, unlike the 50 CSI in Thermotogales and Aquificales, this CSI is not in close proximity to the ADP–ATP binding site on the protein. However, due to its location, this CSI, through its role in enabling intramolecular ionic interactions, could be playing a role in stabilizing dimer formation at higher temperatures.The crystal structures of SecA are available from both mesophilic bacteria (: 4YS0)) ,71,72,73(TmSecA) . The difd insert B. As can protein ,74. The  protein . Althoug channel ,75. We hB: 2IPC) . As can Thermotogales and Aquificales in close proximity to the ADP–ATP binding site, we have carried out MD simulation studies to gain some insights into the function of this CSI. In this regard, we have initially investigated the dynamic of the 50 aa CSI’s flexibility from the trajectories obtained from the MD simulation studies on TmSecA structure with CSI (+CSI) and without CSI (−CSI) at two different temperature settings. The detailed protocol of the system setup for MD simulations is described in the Methods section. In total, four simulation runs were carried out using TmSecA (+CSI) and TmSecA (−CSI), each for 100 ns at two temperature settings of 303.15 K (30 °C) and 363.15 K (90 °C). A preliminary analysis was carried out to analyze the overall deviation of TmSecA (+CSI) and TmSecA (−CSI) relative to their native structures as a function of time using the trajectories along the 100 ns time scale at these temperatures. At 303.15 K, TmSecA (+CSI) appear relatively more stable with an average RMSD of <0.20 nm (<2.0 Å) (±0.04 nm) relative to 0.39 nm (3.9 Å) (±0.08 nm) for TmSecA (−CSI) (TmSecA (+CSI) relative to an average value of 0.36 nm (3.6 Å) (±0.6 nm) for its insertion truncated homolog TmSecA (−CSI) (TmSecA (−CSI) lacking the CSI showed a much higher degree of fluctuation, in comparison to the protein with the CSI, indicating that the TmSecA (+CSI) was more stable at the higher temperature over the simulation period.In view of the location of the 50 aa CSI in the SecA of A (−CSI) . SimilarA (−CSI) . AlthougTmSecA with ADP-bound contains a number of bound water molecules near the ADP-binding site [TmSecA which is located near the ADP-binding site. This observation is of much interest, as several earlier studies indicate that water molecules make significant contribution towards the binding affinity of the ligand or mediating protein-ligand complexes by forming bridges between the protein and the ligand [TmSecA might be interacting with the ADP molecule by forming intermediate interactions with water molecules.The crystal structure of ing site . Of these ligand ,78,79,80TmSecA (+CSI) after 50 ns of the simulation, and overall it contained more water molecules  when compared with TmSecA (−CSI) that contained an average total of 103 water molecules. However, at 363.15 K, the number of water molecules around the ADP-binding site for TmSecA (+CSI) decreased after 50 ns of simulation time to an average total of 103 water molecules, whereas their numbers in TmSecA (−CSI) slightly increases to an average total number of 112 water molecules.Initially, we analyzed the hydration of the ADP-binding site by calculating the presence of a number of water molecules within the 9 Å from ADP during the entire simulation of 100 ns at 303.15 K and 363.15 K . At 303.TmSecA [TmSecA (+CSI) at 303.15 K , and adenine group of ADP or residues from the insert are shown as yellow dash lines. As can be seen, at both temperatures a network involving two to three water molecules are maintained throughout the simulation period. Although most of the water molecules are highly mobile, spending only a fraction of time in that position, interestingly the other water molecules that displace them occupy the same position and forms a network of water-mediated interactions that are highly similar to those observed in the crystal structure of TmSecA protein [Further analyses of the MD trajectories identifies a network of water molecules that shows a high degree of conservancy and stable occupancy near the loop residues (amino acid range 183 to 188) from the 50 aa CSI and these water molecules formed interactions with the adenine group of ADP similar to that observed in the crystal structure of TmSecA . In a se303.15 K A and 363303.15 K B, we sho protein .Thermotogales and Aquificales. As can be seen in The time evolution of the hydrogen bond interactions calculated between Glu185 and water molecules that are within the 4 Å of Glu185 over the course of 100 ns MD trajectory at 303.15 K and 363.15 K is shown in Thermophilic bacteria often exhibit many evolutionary adaptations that aids to retain the function of their proteins at very high temperatures ,11. ThesThermotogae, Aquificae and Deinococcus–Thermus), which harbor most such organisms [In the current work, we describe the identification of two large and unique molecular sequence features in the form of CSIs that are uniquely present in the SecA homologs from different thermophilic and hyperthermophilic members from all three main phyla of bacteria  lengths and exhibit a high degree of conservation in their amino acid sequences. As horizontal gene transfers among thermophilic organisms are indicated to occur frequently [Results presented here show that the two large CSIs in SecA protein are commonly shared by members from two different groups/phyla of organisms. While the 50 aa CSI in SecA is a uniquely shared characteristic of the members of the order equently ,26,28,70Aquificales but not by species from the order Desulfurobacteriales, which are also thermophilic. However, an important difference between members of the orders Aquificales and Desulfurobacteriales is that while the former order is comprised of species that are aerobic or microaerophilic and obtain energy from hydrogen or reduced sulfur compounds through molecular oxygen, the members of the latter order are strict anaerobes and they obtain energy by reduction of sulfate, nitrate, elemental sulfur, or other compounds by molecular hydrogen [It is of interest that within the phylum Aquificae, the 50 aa CSI is only shared by members of the order hydrogen ,29,87,88hydrogen ,65. ThesThermotogales and Aquificales, is located in a surface-exposed loop that lies in close proximity to the ADP/ATP-binding site in the protein. Our comparison of the crystal structure of T. maritima SecA containing the 50 aa CSI with its homology model lacking the 50 aa CSI has revealed that a number of water molecules form an intermediate interaction between the residues from this CSI and ADP molecule. Although the roles of conserved water molecules in mediating protein-ligand interactions have been increasingly recognized in recent years [TmSecA at two different temperatures . The results from MD studies identify a network of highly stable water molecules that form an intermediate interaction between the residues such as Glu185 from the 50 aa CSI and adenine group of ADP at both temperatures. Earlier studies have indicated that the hydrogen bonding capability of water molecules with charged amino acids contributes towards the stability of hydrogen bonds formed between coenzymes/cofactors like ADP/ATP and proteins [However, irrespective of the evolutionary mechanisms that underlie the shared presence of these CSIs, based on the specific presence of these large CSIs in SecA homologs from only the thermophilic-hyperthermophilic organisms, it is strongly anticipated that these CSIs should play an important role in the thermostability of this protein at high temperature. Results from our structural analyses show that both these CSIs are located on the surface-exposed loops in a functionally important domain (NBD1) of the SecA protein. Of the two CSIs in SecA, the 50 aa CSI, which is specific for the order nt years ,90,91,92proteins ,95,96,97Thermales and H. schlegelli, are present as surface-exposed loops in the structure of SecA protein. Based on earlier work, the surface loops in proteins are often involved in mediating novel protein-protein or protein-ligand interactions or in maintaining/stabilizing a specific oligomeric state of the proteins [However, the suggested role of the 50 aa CSI in stabilizing the binding of ADP/ATP to the protein at high temperature could be only one of the several factors by which this large CSI might be contributing towards the thermostability of the organisms for which they are specific. As noted earlier, these large CSI as well as the 76 aa CSI, specific to the member of the order proteins ,100,101.proteins ,104,105 proteins ,107,108.


Concrete cracking caused by corrosion of reinforcement could significantly shorten the durability of reinforced concrete structure. It remains critical to investigate the process and mechanism of the corrosion occurring to concrete reinforcement and establish the theoretical prediction model of concrete expansion force for the whole process of corrosion cracking of reinforcement. Under the premise of uniform corrosion of reinforcing steel bars, the elastic mechanics analysis method is adopted to analyze the entire process starting from the corrosion of steel bars to the cracking of concrete due to corrosion. A relationship model between the expansion force of corrosion of steel bars and the surface strain of concrete is established. On the cuboid reinforced concrete specimens with square cross-sections, accelerated corrosion tests are carried out to calibrate and verify the established model. The model can be able to estimate the real-time expansion force of reinforced concrete at any time of the whole process from the initiation of steel corrosion to the end of concrete cracking by measuring the surface strain of concrete. It could be useful for quantitative real-time monitoring of steel corrosion in concrete structures. Rust expansion force causes concrete cover to crack along reinforcement bars, which renders the reinforcement bars directly exposed to external environments, and dramatically reduces the protective capability of concrete to the reinforcing bars. Subsequently, it could further aggravate the corrosion process of steel bars, and induce the peeling of protective concrete layer, and eventually lead to the structural failure of corresponding systems. From this perspective, it is vital to investigate the corrosion and rust expansion process of concrete reinforcement to establish theoretical models for characterizing its underlying mechanism and inherent relationships.In marine and coastal regions, the existence of chloride ions in humid environments causes the steel bars buried in concrete to be gradually blunt and turning rusty, imposing serious impacts on reinforced concrete structures. Over the past decade, a significant number of reinforced concrete structures failed within their expected service-life ranges due to this so-called corrosion phenomenon. During these corrosion processes, the volumes of the rusted products turn larger than those of the original corresponding reinforcement bars leading to expansion forces to the surrounding. This kind of forces occurring at the interfaces between reinforcement bars and concrete elements due to expansion is termed as steel rust expansion force3 using three diverse approaches including theoretical analysis, experimental investigation and numerical simulation. Several theoretical models and functions were introduced to the understanding of the rust expansion cracking process and the relevant mechanisms in reinforced concrete structures. Based on the elasticity theory, Lu et al.4 put forward the calculation formula of rust expansion force right before and exactly at the instant moments of the expansion of surrounding concrete covers, assuming uniform corrosion of reinforcement. They discussed several influencing factors related to the expansion force of steel rust. Šavija et al.5 used a two-dimensional lattice model to understand the cracking mechanisms resulting from the process of reinforcement corrosion. The heterogeneous properties of concrete were considered for their mechanical investigation and analysis. Zhao et al.6 applied Gaussian function to the investigation of non-uniform corrosion process and proposed a multi-point corrosion model. They found that the location of the greatest corrosion is dependent on the pathway how the corrosives reach to the reinforcements and the concrete crack occurs near the point with the greatest corrosion degree. Supplementary to the theoretical analysis approach, multiple laboratory tests were carried out based on acoustic emission and optical measurement techniques. Zaki et al.7 adopted acoustic emission technology to understand the corrosion of steel bars. Their experiments showed that the acoustic emission technology can effectively monitor the preliminary process of corrosion associated with the reinforced concrete structure at an initial phase. Kashani et al.8 took advantage of a three-dimensional optical measurement technology to characterize the three-dimensional corrosion morphology and patterns of reinforcing elements under accelerated corrosion situations. They constructed a list of probability distribution models for characterizing the geometric features of the corroded reinforcement components. Alhozaimy et al.9 implemented a series of laboratory tests to explore the mechanism related to the high corrosion phenomenon occurring at bar intersections. During the study, the related parameters, including half-cell potential, corrosion current, concrete resistivity, were derived from laboratory measurements. Torres-Acosta10 conducted experiments to find the critical level of bar corrosion for cracking concrete covers. The level was empirically projected by accounting specimen dimensions. Progresses and magnitudes of stresses due to corrosion were measured and quantitatively determined based on specimen sizes and material properties. With advances in computer technology, finite element analysis has been increasingly adopted for the numerical simulation of reinforcement corrosion process. Based on regular finite-element analysis technique, Molina et al.11 proposed a numerical method to simulate the cracking process in concrete subject to corrosion of reinforcement. These colleagues applied the so-called smeared-crack approach for investigating finite elements’ behavior, and integrated initial strains and property change to model the corrosion. Fernandez et al.12 combined three-dimensional finite element analysis and three-dimensional optical measurement technique to explore the mechanical impacts of corrosion surface pits on steel bars. Three-dimensional optical measurements were utilized for the acquisition of the related geometry information. Finite element analysis model was established for the understanding of failure course and the measuring of local impacts on the pertinent pits. The local influences of pits on corrosion mechanical properties with single and cyclic loading scenarios were examined. Redaeli et al.13 took the finite element analysis technique to characterize the chloride induced corrosion of reinforcing bars in concrete structure members. Ožbolt et al.14 proposed a 3D chemo-hygro-thermo-mechanical model to characterize the interaction among the non-mechanical factors and the mechanical features related to concrete. Two numerical examples were presented to illustrate the usage of the model.Many scholars studied the physical phenomena of rust expansion cracking in concrete structures and attempted to quantify the rust expansion force of steel barsThe existing theoretical models of expansion force of reinforcement bars generally lack a comparison with experimental data or a result verification process due to the difficulty in obtaining the experimental data on the expansion force of reinforcement bars. By combining theoretical analysis and experimental verification, this paper intends to analyze the whole rusting process of reinforcement bars under the condition of uniform corrosion. The accelerated corrosion test results are compared and cross-validated with those received from the analysis with the theory of elasticity. A relationship model between the rust expansion force of reinforcement and the surface strain of concrete is built, calibrated, and verified.Taking an squared cross section of the reinforced concrete which has a side length of 2a as the research object, it assumes that there is a reinforcement bar with the radius of R pointing to the center of the cross section and the uniform rust expansion force produced by the steel bar to be q. In order to combine the theory of complete contact of elasticity and Lame's solution, it firstly finds the largest inscribed circle for the square section of the specimen, and then locates the largest inscribed square S of the obtained circle. As in Fig. y, σy deviates from 0. Therefore, assuming σy = f1(y)g1(x)q, the stress function and stress components are obtained as Formula y=0 = 0, (τxy)y=0 = 0, (τxy)x=0 = 0. The stress and strain of the S-plane in Fig. In Fig. 15, the relationship model between concrete surface strain and steel rust expansion force can be obtained as Formula ,,7), q stC30 composite Portland cement and the clean river sand with particle sizes ranging between 5–10 mm are used for the test. Concrete proportioning is shown in Table 4 s, cracks appear at the contacting interface of the concrete and the steel tube. After that moment, the bounding force of concrete on the steel tube decreases and the tensile strains at the three measuring points grow at lower rates and gradually turn into declining mode, but these points are still in tension state. Until t = 2.2 × 104 s, the concrete piece cracks completely, and its surface transits from being tensile to be compressive. Measurement point 2 lies at the middle of the concrete surface and its measured strain is larger than those collected at the same time from points 1 and 3. Measurement points 1 and 3 are symmetric, and their strains are roughly equal in terms of magnitude.The variation patterns of strain versus time corresponding to the 1–3 measuring points on the concrete surface are shown in Fig. 4 s. After cracking, the confinements from concrete on steel tube decreases, and the compressive strain of the steel tube declines rapidly. Declining rate is significantly higher than that of rising during the early stage of testing.The dynamic strain patterns at six measuring points a–f on the inner wall face of the hollow steel tube are shown in Fig. 19. Figure The used strain gauge system can only measure the strains of a limited number of points on the concrete surface. To perform the full field analysis of the concrete surface strain, during the test, Basler CCD camera is used to collect the real-time strain information on concrete surface. The obtained figure series are then analyzed by the digital image correlation (DIC) method4 s, tensile strains appear at three points A,B,C, and keep rising. When t = 2.2 × 104 s in Fig. 4 s.It can be seen that, at the beginning of the test Fig. a,b, the n is the amount of bar corrosion (in mol); M is the molar mass of iron (55.8 g/mol); Q is the quantity of electricity passing by anode (in C); I(t) is the external current intensity (in A) at time t (in s); F is Faraday constant ; z is the absolute valency of ion and the value for iron is 2.Theoretically, through Faraday's Law, the corrosion amounts of rebars can be described based on the magnitude of passing current. The mass of substance that experiences chemical changes on anode rebars is proportional to the amount of electricity passing through the electrode. The corrosion mass ∆m can be calculated as:ρ is:The bar corrosion rate By the above equation, the real-time bar corrosion rate can be obtained. As in Fig. R = 8 mm, r1 = 5 mm, ES = 2.1 × 105 MPa, μ = 0.3. The change pattern of rust expansion force versus time is shown in Fig. Strains on the inner wall of the steel pipe vary at different points, and so do the rust expansion forces associated with the outer wall. Therefore, the strain at measuring point C of the inner wall of the steel pipe in Fig. C = 3 × 104 MPa, k = 0.6, μ = 0.3, a = 500 mm, the obtained results are plotted in Fig. Putting concrete surface strain data into Formula  for calcFrom the accelerated corrosion test, it can be found that the tensile strain on the concrete surface and the compressive strain on the inner wall of the reinforcement continue to increase prior to the appearance of cracks on the concrete surface. After the concrete cracks appear, the tensile strain of the concrete surface keeps decreasing. The concrete surface remains tensile until the concrete cracks completely. After complete cracking, the surface strain of concrete and the pressure strain of the inner wall of the reinforcement drop sharply, and the concrete surface changes from being tensile to be compressive.A relationship model between the steel rust expansion force and the concrete surface strain is established based on the theory of elasticity. It is calibrated and verified by the physical experiment data. The model is found to be sufficiently valid for concrete before the cracks appear, but cannot be used to deduce the rust expansion force of reinforced concrete structure after the cracks appear.In this paper, the prediction model for the rust expansion of the cuboid reinforced concrete specimen with square cross sections is established, and the accelerated corrosion test is carried out to study the relationship between the rust expansion force of reinforcement and the surface strain of concrete. Conclusions are as follows:20. The concise model proposed in this study can contribute to the quick prediction of the real-time rust expansion force in concrete structures to satisfy the above needs. In future, the research will be expanded to consider the non-uniform corrosion situation. Non-contact optical measurement methods will be introduced for calibrating theoretical models. Cohesive models and plastic models21 will also be considered for the rust expansion force prediction by comparing the advantages and disadvantages of different types of theoretical models.The real-time prediction of the rust expansion force of reinforcement before concrete cracks remains important to the durability design of concrete structures. It can also provide critical information to forecast structure deterioration and estimate remaining service life for various life cycle engineering purposesIt plans to study how the bar arrangements can affect the crack patterns, how the humidity can affect the cracking phenomenon, and how the cracks progress as time goes. Heating is simultaneously used to the current in this study. To use a compensation specimen which intends to eliminate the expansion effects due to heating is planned for conducting another series of experiments for comparison with our current study. The use of electrochemical techniques to measure corrosion will be considered.