Although great progress has been made in the prevention and treatment of AIDS, there are still a considerable number of new infections annually, especially in adolescents. With the advance of technology, game-based education has gradually become an important tool for changing healthy behaviors among youth.A protocol for conducting a randomized controlled trial to evaluate the “AIDS Fighter · Health Defense”, a game-based AIDS education project aimed at improving the ability of adolescents to prevent AIDS. During the four-week intervention, participants will receive: 1) A virus combat game; 2) Goal setting to eliminate HIV; 3) Questions to be answered to be resurrected in the game; 4) Points ranking; 5) Recognition and Rewards. The primary outcomes include changes in participants’ knowledge, stigma attitude, and risk behaviors attitude related to AIDS after four weeks of intervention. The secondary outcomes are the participants’ AIDS-related risk behaviors three and six months after the intervention.AIDS Fighter· Health Defense may be an innovative approach to help adolescents improve AIDS prevention capabilities, fill the gap in game-based AIDS prevention education in China, and gain experience of AIDS management.ChiCTR2000040195. Registered 25 November 2020.Chinese Clinical Trial Registry:  Acquired Immunodeficiency Syndrome (AIDS) is a global disease that seriously threatens human health . By the Developing countries, represented by China, have problems in AIDS prevention education, such as outdated education model, poor effect of education, and uneven distribution of educational resources , 6. TherBelow we describe the protocol of our randomized controlled trial to evaluate a game-based intervention to improve adolescents’ AIDS prevention ability in China. The intervention, called AIDS Fighter · Health Defense, is a 4-week game experience, and includes components designed to increase AIDS-related knowledge, improve AIDS prevention motivation, and strengthen AIDS prevention behaviors among adolescents. This study is guided by the Information-Motivation-Behavioral Skills Model (IMB Skills Model), which believes that the prevention of AIDS requires comprehensive intervention from three aspects: AIDS-related information, motivation, and behavior skills . In the There is no statistical difference between AIDS Fighter · Health Defense intervention group 1 and AIDS Fighter · Health Defense intervention group 2 in AIDS-related knowledge, stigma attitude, risk behaviors attitude and the incidence of risk behavior;Compared with adolescents in the control groups, those in the AIDS Fighter · Health Defense intervention groups will have More AIDS-related knowledge, less AIDS-related stigma and fewer AIDS-related risk behaviors.Comparison between control group 1 and control group 2, group 1 will show better effects in improving AIDS-related knowledge, attitude and behaviors.Study participants will be recruited from adolescent volunteers and allocated to one of the four randomized groups after completing a baseline survey Fig.  (AIDS FiThis study is aimed at improving the AIDS prevention capabilities of adolescent students. The inclusion criteria are: 1) Students aged 15–24 years; 2) Participants have clear consciousness, no mental disorders, and able to read and express themselves; 3) Participants were informed about the study and voluntarily participated in the study (< 16 years old requires the consent of the guardian). Those who are diagnosed as HIV positive will be excluded from the study.Goal setting has been identified as an effective behavior change procedure . The stoSeven levels were contained in the game: immune system, blood system, skin and mucous membrane system, nervous system, respiratory system, digestive system, urogenital system. There will be corresponding animation prompts for the success or failure of the game. If they fail, it will prompt them that HIV has invaded the human body, and display pictures of symptoms corresponding to the level of content as a warning education. The game interface is shown in Fig. Participants will have a chance to answer questions if they failed during the battle. If they answer correctly, they will be resurrected and continue to fight, otherwise, the game will fail. Questions include knowledge of AIDS prevention, antiretroviral treatment, pre-exposure and prophylaxis.The “knowledge corner” contains a variety of AIDS knowledge, as AIDS prevention, diagnosis, antiretroviral treatment, pre-exposure prophylaxis, etc. What is taught in the form of texts, pictures and videos. Players can earn points by reading articles or watching videos, and the points are included in the rankings; Moreover, players can leave a message in the “Consultation” column, or conduct online consultation by identifying the QR code of the Internet hospital.Points could be earned by logging in to the game, breaking through levels, reading articles or watching videos, etc. The point for logging in is 1, once a day. Points for breaking through levels is 5 for the first level, 10 for the second level, 15 for the third level, and so on, and may only be accumulated once a day. Two points can be awarded for reading an article or watching a video for more than 30 s. One point could be earned each time if they pick up a condom or antiviral medicine during the game, and the points can be accumulated. The points and rankings of themselves and their friends in the game can be viewed.Educational resources can be edited and upload to the “knowledge corner” through the management system, and the system can realize the following data collection functions:1) Player’s basic personal information; 2) Player’s points and rankings; 3) Player’s message and consultation information; 4) Player’s answers to questions; 5) When did the player log in to the game and how long has it been used; and 6) What did the players learn in the “knowledge corner”.Participants will receive the educational game “AIDS Fighter · Health Defense” and will be required to play the game and learn AIDS education essays or videos in the “knowledge corner” at least 5 days a week and 20 min a day. A data management system will be used to monitor the time participants played in the game, and whether they have learned the content in the “knowledge corner”. After four weeks of intervention, the effect of the intervention will be evaluated by using the same questionnaire as applied in the baseline survey.Participants will be informed that they will be recognized and rewarded after completing daily game tasks and completing four-week follow-up assessments according to the points ranking. The top 20% will receive a “Gold Award” and 50 RMB in cash, the middle 30% will receive a “Silver award” and 50 RMB in cash, and the lowest 50% will receive a “Bronze award” and 20 RMB in cash.Participants will receive “AIDS Fighter · Health Defense”, without limitation in time to play the game or learn the content of the “knowledge corner”, and there are no incentives as recognition or rewards. Participants play this game according to their preference. Four weeks later, the same questionnaires will be used to measure the effect of their use of the game.Participants will receive classroom teaching once a week for 100 min each time. The total time is the same as the time required by the AIDS Fighter · Health Defense intervention group 1. A regular teacher will conduct AIDS prevention classroom education on a fixed day each week and the content of the lecture is consistent with the knowledge in the game.Participants will be added to the QQ chat group , and the same educational resources as the “knowledge corner” in AIDS Fighter · Health Defense will be uploaded to the QQ group. Participants will then be reminded to learn the knowledge by themselves daily. But there are no gamification elements, such as barriers, points ranking, answering questions, rewards, etc.Participants will be recruited through online recruitment and on-site recruitment. The sufficient statistical power to detect changes in AIDS knowledge, attitude and behaviors after the intervention are considered in sample size calculation, and131 participants are need in each group to maintain 80% statistical power. Assuming the attrition rate is 10%, the sample size of each group is determined to be 145, and the total sample size is 580.The study site is Luzhou City, Sichuan Province, China. Participants will be recruited from secondary school, high school, college and university. When they agree to participate in the research and complete the follow-up measurement and informed consent form will need to be signed for confirmation. After completing the research, each participant will receive a reward of 30 RMB in cash.Opaque envelopes will be prepared for randomization. In 580 envelopes, each will contain a note with the words “ AIDS Fighter · Health Defense Intervention Group 1” or “ AIDS Fighter · Health Defense Intervention Group 2” or “Control Group 1” or “Control Group 2” (145 envelopes per group). Participants will be randomized to select an envelope, then assigned to the corresponding group according to the information on the envelope. The data analysts are blinded to the allocation.The primary outcomes are AIDS-related knowledge, AIDS-related stigma attitude and AIDS-related behaviors attitude before and four weeks after the intervention. AIDS-related knowledge will be assessed through a self-made questionnaire with a total of 45 items, one point for a correct answer. The higher the score, means the more knowledge participants have learned. AIDS-related behaviors attitude will be assessed through a questionnaire with eight items, with one point for a correct answer. The higher the score, means the lower the risk of AIDS-related behaviors among participants. Five experts were invited to verify the content validity of these questionnaires, the item-level CVI (I-CVI) and the scale-level CVI (S-CVI) are both 1. 00. AIDS-related stigma attitude will be assessed through the Chinese version of Zelaya’s HIV/AIDS Stigma Scale, which was compiled by Zelaya , with 24Secondary outcomes are the AIDS-related behaviors followed up for three and six months after the intervention. Participants will receive cash rewards after completing the evaluation. AIDS-related behaviors will be assessed through the Questionnaire on the Health of Young Students that was issued by the Chinese Center for Disease Control and Prevention, which has 33 items and is the official questionnaire for the investigation of AIDS-related behaviors among adolescents in China. The fewer AIDS-related risk behaviors, the more the participants have gained AIDS prevention capabilities.www.wjx.cn, Ranxing information technology co., Ltd., Changsha, China). The database system automatically saves the data and ensures the safety, integrity and consistency of the data. The web server is hosted in Alibaba Cloud  and is protected by a corporate firewall, while a daily backup mechanism can ensure data security. Data has multi-level permission settings and password protection to ensure data security. In statistical analysis, general statistical analysis will be carried out by using standard statistical software and professional statistical software.All data will be directly recorded in the online database  will be used to find out whether there have differences between the AIDS Fighter · Health Defense intervention groups and the control groups in AIDS-related knowledge scores and attitude scores after the intervention of four weeks. Repeated Measures ANOVA will be used to see whether there have differences on the incidence of AIDS-related behaviors followed up for three and six months after the intervention in four arms. Intention-to-treat analysis will be used to account for the influence of attrition. The difference was statistically significant when This study has been approved by the Ethics Committee of Clinical Trials, Affiliated Hospital of Southwest Medical University, with the approved number: KY2020001. Participants who sign up will be screened, for those who meet the inclusion criteria, we will issue informed consent to them, and inform them in detail of the study purpose and process, number of participants, study duration, potential risks and benefits, random allocation, and data confidentiality.In developed countries, the focus of AIDS prevention education is on the sexual behavior of high-risk groups, but the focus of AIDS education in our study is on the AIDS-related knowledge of adolescents. The awareness rate of AIDS knowledge among the public in developed countries might be higher than China, and existing studies are mainly aimed at high-risk groups, such as men who have sex with men and adolescents who have sex without condoms , 19. ButAdolescents are in the sexually active period are a high-risk group of HIV infection , the awaTo meet the need of AIDS education of adolescents, the educational game “AIDS Fighter · Health Defense” was developed. As mentioned above, AIDS Fighter · Health Defense is a theory-based AIDS education game that can provide knowledge and skills to adolescents to prevent AIDS. Whether adolescents are interested in AIDS Fighter · Health Defense and insist on using it is the key to this study. If the game does not appeal to adolescents, it will not be popularized among them, nor have educational significance. To promote the use of this game by adolescents, the game is designed to be highly interactive and interesting, including gamification elements as levels, points, answering questions, rankings, and rewards. In the levels of the game, seven different organs and systems of the human body are simulated, it can vividly show the way HIV invades the human body and its performance if infected with HIV. This can not only improve the fun of the game, but also popularize the process of HIV invading the human body, which may increase users’ willingness to play the game and prevent AIDS.Four arms were designed in our research, including two intervention arms and two control arms. Participants in the two intervention groups will receive AIDS Fighter · Health Defense, one of which will strictly control the time spent in the game and provides incentives to increase motivation to use the game; Another group will receive AIDS Fighter · Health Defense, but without time limitation or incentives; One of the two control groups is classroom teaching and the other is autonomous learning. By comparing the intervention groups with the control groups, it can be found whether AIDS Fighter · Health Defense is better than classroom teaching and autonomous learning in improving participants’ AIDS prevention ability; By comparing the two intervention groups, we can figure out whether AIDS Fighter · Health Defense is attractive, whether players will voluntarily use the game to improve AIDS prevention capabilities. This will determine whether the game can be promoted on a large scale. By comparing the two control groups, we can understand the difference between classroom learning and autonomous learning in improving AIDS prevention capabilities. Such a design could see the differences in the effects of game-based intervention, classroom teaching, and independent learning in AIDS education. And provide evidence for choosing different AIDS education methods.We hope that the game-based interventions can be widely used in AIDS education in China and other countries. However, some countries are exam-oriented in evaluating the effect of education and there may be some resistance to the promotion and application of the game; parents may worry that their children will be addicted to the game and affect their academic performance , 27. To “AIDS Fighter · Health Defense” could be suitable for the public, high-risk groups of AIDS, and HIV-infected people. It could be an auxiliary educational tool for AIDS prevention for the public and high-risk groups, and for HIV-infected people to maintain long-term ART adherence and keep virus suppression. We believe that with the development of this study, we can provide an AIDS education method for China and other countries to improve the ability to prevent AIDS of public and the quality of life of HIV infected.


Wet–dry cycles were performed to accelerate the corrosion of embedded rebars in reinforced concrete, following which the potential and impedance corresponding to the cycles were measured. For the reinforced concrete containing only NaCl, the passive film of the embedded rebar surfaces deteriorated after two weeks of accelerated corrosion, and its polarization resistance decreased. When 0.6 M LiNO2 per NaCl was added, the reinforced concrete deteriorated at the same rate as the normal embedded rebars, and the polarization resistance was higher than the initial values. When 1.2 M LiNO2 per NaCl was added, the passive film of the embedded rebars remained intact even after 10 weeks of accelerated corrosion, protecting the rebars from deterioration.In this study, the effect of NaCl and LiNO The use of reinforced concrete with embedded rebars has been increasing with the rapid advancement of the industry. Corrosion of rebars embedded in reinforced concrete is one of the major factors that affects the durability of concrete structures. In addition, despite the layering of concrete, the rebars embedded within concrete corrode, thereby making it easy for chloride ions to penetrate ,2.2 destabilizes the passive films around the embedded rebars, leading to the corrosion of the rebars from the electrochemical potential [Embedded rebars are protected from corrosion by stable passive films formed in the strong alkaline pH > 12.5) environment of concrete ,4. Howev environmotential ,8,9,10.The volume of the rebars increases as corrosion propagates and accelerates due to the corrosion products, resulting in concrete cracks. Extensive literature on the corrosion of embedded rebars and its measurements are available ,12. ExamTo establish fundamental research data, the electrochemical corrosion behavior of embedded rebars in concrete and the effects of chloride ions and corrosion inhibitors are analyzed using electrochemical techniques. Furthermore, to reduce the time required for corrosion of the rebars, a corrosion acceleration method was implemented. Corrosion acceleration was applied to the reinforced concrete specimen, and the characteristic changes in the open circuit potential (OCP) and impedance of the rebar embedded in the concrete, according to the corrosion acceleration time, were observed ,19. s), and polarization resistance (Rp) in the embedded rebars of the reinforced concrete were observed over several cycles of accelerated corrosion. The effects of chloride ions and the corrosion inhibitor content on the corrosion behavior of the embedded rebars were subsequently compared and analyzed. The results were used to evaluate the anticorrosive performance of the inhibitor and suggest the appropriate amount of inhibitor used.The changes in the impedance, solution resistance  was used in this study. Type 1 ordinary Portland cement (OPC), compliant with the ASTM C 150 standard , with a 2  was used as the corrosion inhibitor [Domestically sourced crushed stones were used as coarse aggregates, and domestically sourced washed sand was used as the fine aggregate. Polycarbonate admixtures were obtained from S.P . Moreover, NaCl  was used as the source of the chloride ions and LiNOnhibitor ,22.KS D 3504 D13 rebars  were used for reinforcing concrete , and wer3 chloride ions (C12). Additionally, 0 M LiNO2, 0.6 M LiNO2 (C12N6), and 1.2 M LiNO2 (C12N12) were added to the concrete samples containing chloride ions. 2 added.To analyze the effect of the polycarbonate additives on the corrosion behavior of the embedded rebars in concrete, four mixtures of varying concentrations were produced; details of the same are provided in To measure the corrosion behavior of the rebars embedded in concrete and evaluate the corrosion area, a reinforced concrete specimen was prepared. The reinforced concrete specimens were prepared by fixing a ϕ13 mm rebar (SD-400 deformed) at the center of a Ø100 × 200 mm cylindrical mold and then pouring the concrete into the mold. After cleaning the rebar surface by grit blasting, an epoxy coating was applied to the surface to observe the penetrating effect of the NaCl from the concrete immersed in the NaCl solution; only a length of 100 mm at the center of the concrete specimen was exposed. As one of the test methods to accelerate corrosion of the reinforced bars, the wetting-drying process was used. Wet–dry cycles accelerate corrosion due to the presence of excess water, and high temperature and humidity, thereby facilitating the diffusion of oxygen. However, as the water content increases, the diffusion of oxygen decreases; accordingly, the temperature and humidity are lowered so as to encourage diffusion and promote further corrosion. This approach was applied in the cycles performed herein to accelerate corrosion of the embedded rebars in concrete ,25. FiguA temperature and humidity chamber was used to maintain a constant wet period  for three days and a constant dry period  for four days; hence, each wet–dry cycle was 1-week-long . At the According to the electrochemical theory, a simple electrochemical electrode system can be described by an equivalent circuit ,15,16,17s denotes the solution resistance, Cdl is the capacitance of an electrical double layer, and Rp is the polarization resistance by the charge transfer reaction. Here, Rs corresponds to the impedance at the highest frequency and Rs + Rp corresponds to the impedance at the lowest frequency. For the rebar-embedded concrete, the Rp of the rebar accounts for contributions from the resistance of the film Rf and the charge transfer resistance Rct [p. In EIS, it can be assumed that the value of the Bode plot at 100 kHz is equal to Rs and that at 0.1 Hz is equal to Rs + Rp. Therefore, Rp can be calculated.Rance Rct ,15,16,17EIS was performed to measure the impedance of the reinforced concrete after each wet–dry cycle ,28,29,30−1 Hz−105 Hz was applied using a potentiostat. The data were subsequently analyzed using Nova software .For EIS, the electrode was allowed to stabilize to an open circuit immersed in a 3.5 wt% NaCl solution for 24 h. An AC voltage in the range of 10Metals used in rebars have a unique equilibrium electrode potential. This value is negatively related to the RE and represents the likelihood of the metal to ionize. This phenomenon is known to reflect its degree of corrosion ,33. TablAccordingly, the equilibrium electrode potential of the rebar in the concrete was measured to quantify the degree of corrosion of the rebar. The OCP of the rebar as a function of the accelerated corrosion time is shown in 2, which acts to retard the degradation of the stable passive film that forms around the embedded rebar owing to the strong alkaline nature of the concrete mixture [For the normal concrete, the OCP did not change significantly as compared to the other samples and remained stable between −0.25 and −0.15 V until the end of 10 weeks of accelerated corrosion, whereby it decreased to −0.315 V. For the C12N6 concrete, the OCP decreased with time from −0.1 to −0.284 V, at a rate much lower than that in the case of the concrete containing only chloride ions. This can be attributed to LiNO mixture ,35,36. F mixture .3 chloride ions and 1.2 M LiNO2, the OCP remained stable between −0.05 and −0.15 V. The OCP after 10 weeks of cycles was measured to be −0.142 V, corresponding to less than 10% corrosion as per ASTM C 876, implying that no significant corrosion had taken place. This is because the use of an LiNO2 concentration equal to or higher than 1.2 M inhibits the degradation of the passive film surrounding the embedded rebar.For the C12N12 concrete with 1.2 kg/mThe Bode modulus plot shows the impedance Z as a function of the applied frequency. The plots can be categorized by the impedance at a high frequency and the impedance at a low frequency. At a high frequency, the impedance can be used to determine the electrolyte resistance based on the electrode reaction time, and at a low frequency, the polarization resistance of the rebars due to the diffusion and movement of the substances can be identified ,28,29.The Bode modulus plots of all test specimens at the selected accelerated corrosion cycles are shown in p can be calculated for the embedded rebars. The calculated Rp values are shown in As the curves in each Bode modulus plot change according to the accelerated corrosion cycle, the polarization resistance Rp of the embedded rebars increased until the second week of the accelerated corrosion cycles and decreased after the fourth week. This can be attributed to the degradation of the passive films of all embedded rebars as they enter the initial stages of corrosion. For the normal, C12, and C12N6 concrete specimens, the Rp of the embedded rebar in the C12N12 concrete continued to increase until the fourth week of the accelerated corrosion cycles and decreased after the sixth week. Hence, the addition of 1.2 M LiNO2 per added chloride ion enables better protection of the passive film on the embedded rebars as compared to the concrete without chloride ions. Further, 1.2 M LiNO2, or more, must be added to the concrete with 1.2 kg/m3 chloride ions to retain the protection capability of LiNO2.Notably, the R2, although a concentration higher than 1.2 M LiNO2 may be required for environments having high salinity in the air, such as coastal structures.The embedded rebar in the C12 concrete underwent the most rapid deterioration; the rebars embedded in the normal and C12N6 concrete were corrosion initiated at the ninth week of the accelerated corrosion cycle. However, the embedded rebar in the C12N12 concrete was observed to undergo no significant deterioration at the end of 10 weeks of cycles. The passive films were significantly stable with 0.6 M LiNO2.The polarization resistance of the normal, C12, and C12N06 concrete increased until the end of the second week of cycles and then decreased, while that of the C12N012 concrete increased until the end of the fourth week and then decreased. This is attributed to the presence of the corrosion inhibitor, LiNOp at the end of 10 weeks of cycles at 31.7 Ω cm3. The Rp values of the normal, C12N06, and C12N12 samples, in increasing order, were 57.6, 113.8, and 223.8 Ω cm3, respectively. With 1.2 kg/m3 NaCl and more than 0.6 M LiNO2 added to concrete, the reinforced concrete is expected to inhibit corrosion more than the normal concrete.C12 presented the lowest RThe performance of the corrosion inhibitor and the corrosion behavior of the embedded rebars in concrete were analyzed using wet–dry cycles and electrochemical techniques. In addition, it was confirmed that the corrosion of the rebar embedded in the concrete can be protected from the penetration of chloride ions using an appropriate inhibitor. Through electrochemistry and microanalysis of in/organic inhibitors, their mechanisms toward inhibiting corrosion may be considered in future research.In this study, the effects of adding chloride ions and corrosion inhibitors to concrete on the embedded rebars within concrete were analyzed and compared. To accelerate the corrosion of the embedded rebars, wet–dry cycles were performed, and the natural potential and impedance were measured at the end of each 1-week wet–dry cycle. The results are presented as follows:


The POSS incorporation led to a more hydrophobic and smoother surface for further perovskite deposition, resulting in the increase in the grain size of perovskite. An appropriate POSS passivation layer could effectively reduce the recombination of the electron and hole at grain boundaries and increase the short-circuit current from 18.0 to 20.5 mA·cm−2. Moreover, the open-circuit voltage of the cell could slightly increase over 1 V.Polyhedral oligomeric silsesquioxane (POSS), featuring a hollow-cage or semi-cage structure is a new type of organic–inorganic hybrid nanoparticles. POSS combines the advantages of inorganic components and organic components with a great potential for optoelectronic applications such as in emerging perovskite solar cells. When POSS is well dispersed in the polymer matrix, it can effectively improve the thermal, mechanical, magnetic, acoustic, and surface properties of the polymer. In this study, POSS was spin-coated as an ultra-thin passivation layer over the hole transporting layer of nickel-oxide (NO X, being in favor of hole transport and blocking electrons efficiently, is one of the most potential alternatives to PEDOT:PESS. Moreover, NiOX leads to the higher open-circuit voltage (VOC) of PSCs because its work function exhibits a good alignment with valence band of CH3NH3PbI3 (MAPbI3) [X and improve the crystal size of perovskite layer. Although they revealed enhanced efficiencies, few studies were reported about how to improve the NOX HTL for the fabrication of efficient PSCs. It remains a challenge to develop new passivation methods for the PSCs with NOX imported as HTL in their structure.In recent years, the perovskite solar cells (PSCs) have become considered among the most promising photovoltaic materials with rapidly increasing power conversion efficiency (PCE) from 3.8 to 25.5% in a very short period of time , owing t(MAPbI3) . To redu(MAPbI3) ,12,13. R(MAPbI3) , sodium (MAPbI3) , and pol(MAPbI3) , have be3 and be used as a hole blocking layer to balance the electron–hole injection of light-emitting devices [OC and PCE owing to the decrease in the charge trap density and trap-state energy level [X HTL in a PSC structure through its hydrophobic nature and ability of trap suppression. Here, the PSCs have been fabricated with the inverted structure of fluorine-doped tin oxide (FTO)/NOX/POSS/MAPbI3/PC61BM/Bathocuproine (BCP)/Ag structure. The effect of POSS content on photovoltaic properties has been analyzed using different microscopy and spectroscopy techniques. Enhanced surface hydrophobicity and flatness were induced by the POSS passivation to significantly increase the grain size of perovskite. For an optimized concentration of 0.01-mg·mL−1 POSS, the short circuit current (JSC) increased from 18.0 to 20.5 mA·cm−2, an increase of 13.9%. This enhancement was mainly due to the decrease in grain boundaries and the resistance of the charge recombination.Polyhedral oligomeric silsesquioxane (POSS) possesses a hybrid structure of inorganic siloxane cage associated with organic groups. Combining hybrid and hollow characteristics, POSS exhibits special mechanical, electrical and optical properties as important building blocks for biomedical and optoelectronic materials ,18. The  devices ,21. Liu gy level . The hydgy level . In this−1) were purchased from Ruilong optoelectronics, Taiwan. Nickel(II) initrate hexahydrate (99.9985%), ethylene diamine , and ethylene glycol monomethyl ether  were purchased from Alfa Aesar . Acryloisobutyl POSS was received from Hybrid Plastics Inc. . Methylammonium idodide (MAI), lead(II) iodide (PbI2), and bathocuproine  were purchased from Xi’an Polymer Light Technology . 6,6-Phenyl-C61-butyric acid methyl ester (PC61BM) were purchased from Solenne BV . Anisole was purchased from Acros Organics . Anhydrous solvents such as dimethyl sulfoxide (DMSO), dimethyl formamide (DMF), chlorobenzene (CB), and isopropanol (IPA) were purchased from Sigma Aldrich  and used without further purification.FTO-coated glass substrates  were masked by polyimide tape as T-shape pattern. Then, the unmasked portion of the FTO was etched with zinc powder/HCl solution (6 M) and then cleaned with a detergent to remove the surface residue and zinc powder, following ultrasonically with ethanol, isopropanol, and deionized water for 15 min, respectively. The fabrication process of PSCs was illustrated in X solution was spin-coated on the cleaned FTO glass substrates at 4000 rpm for 40 s and then heated at 100 °C for 10 min, followed by 300 °C for 1 h. 80 μL of POSS IPA solution in the concentration of 0, 0.005, 0.01, 0.015, and 0.05 mg·mL−1, was spin-coated on the as-prepared NiOX substrates at 6000 rpm for 20 s and then heated at 100 °C for 10 min, respectively. MAPbI3 was prepared by dissolving 0.2305-g MAI and 0.6684-g PbI2 in DMSO/DMF in the volumetric ratio of 1:4 and then stirring the solution for one day. Sixty microliters (60 μL) of the MAPbI3 solution was spin-coated on the POSS-passivated substrates at 4000 rpm for 25 s in a glove box. Nine seconds (9 s) after the start of the spinning, 500 μL of anisole was dropped upon the MAPbI3-coated substrates as an anti-solvent. The substrates were then heated at 100 °C for 12 min to complete the film formation. Ten microliters (10 μL) of PC61BM CB solution was spin-coated onto the perovskite layer at 3000 rpm for 20 s. Then, the samples were heated at 80 °C for 10 min. Eighty microliters (80 μL) of BCP IPA solution was spin-coated upon the PC61BM layer at 5000 rpm for 20 s. Finally, a silver layer with 100 nm thickness was formed on the surface of the devices through thermal deposition under a vacuum of 5 × 10−6 torr and a plating rate of 0.8–0.9 Å/s. The structure of the designed devices in this study is shown in The fluorine doped tin oxide (FTO) glass substrates  equipped with a source meter . Electrochemical impedance spectra (EIS) were measured over the frequency range of 50 mHz to 1 MHz with a potential perturbation of 10 mV using an electrochemical workstation . The incident photon-to-electron conversion efficiency (IPCE) spectra of cells were measured using an external quantum efficiency measurement system .The crystalline phase of the perovskite crystals was characterized through X-ray diffraction (XRD) using an X-ray diffractometer  and CuKα radiation (wavelength 0.15418 nm) with a fixed operating voltage of 30 kV and a fixed current of 15 mA. The morphology of the perovskite layers and devices were examined using a field-emission scanning electron microscope . The absorption and photoluminescence (PL) emission spectra of the perovskite crystals were determined using a UV–Vis spectrometer  and a fluorescence spectrometer , respectively. The contact angle of the POSS-passivated surface was determined using a contact angle analyzer . The photocurrent density–voltage (J–V) characteristics were measured under irradiation of 100 mW·cm3 perovskite structure, respectively [2 formed in the perovskite layer [3 crystal nor results in PbI2 separated out from MAPbI3 layer. In particular, the XRD peak related to plane (110) recorded for the sample POSS-0.01 shows the highest intensity compared to other samples, indicating that 0.01-mg·mL−1 POSS incorporation leads to the best crystallinity. X/POSS/MAPbI3 samples with various POSS incorporation. All of curves display the same cut-off edge at 779 nm but different absorption intensity in the range of 400~530 nm. Introduction of POSS over the NOX layer improves the photo-absorption of MAPbI3 and the strongest absorption rate is related to sample POSS-0.01.The XRD patterns of the perovskite layers with various POSS contents have been measured under dark standard conditions at room temperature and presented in ectively . These Xectively ,26. No pte layer . This re3 layers deposited over POSS layers fabricated with various POSS contents. The images were recorded at two kinds of magnification. Some pinholes can be observed on the surface of the pristine perovskite layer. When the ultra-thin POSS passivation layer is introduced, the number of pinholes is reduced and reaches the minimum level at concentration of 0.01-mg·mL−1 POSS, which means that the coverage of the perovskite layer is more complete at this optimum POSS concentration. When the POSS concentration increases over 0.01 mg·mL−1, the number of voids increases again. In addition to the pinholes, the POSS concentration also influences the grain size of MAPbI3. When the concentration of POSS increased from 0 to 0.01 mg·mL−1, the crystal growth of MAPbI3 progressively accelerated and the grain size of perovskite enlarged from 162.3 to 226.9 nm. However, grain size decreased to 167.5 nm when the POSS concentration increased to 0.05 mg·mL−1  of the MAPbI3 grown over the substrate with various POSS amounts present a dominant peak around 753 nm under 500 nm excitation , the POSS-0.01 increases the PCEs and the photocurrent density from 13.3 to 15.6% and from 18.0 to 20.5 mA·cm−2, an increase of 17.3 and 13.9%, respectively. OC, JSC, fill factor (FF), and PCE) of the control cell and the champion cell POSS-0.01. The individual data, average value, and standard deviation are shown in the figures. The higher average PCE and Jsc were obtained for POSS passivated cells. However, the average FF is lower for the POSS passivated cell which is probably due to increased series resistance of the passivated cells. However, the VOC of the POSS-0.01 is slightly higher than that of the control cell, responding the fact that lowering the charge recombination rate would lead to increasing VOC [sing VOC ,29.OC under dark conditions  of the EIS of the PSCs with various POSS contents present two semicircles at the high and low frequency regions measured at V = Vnditions . We usednditions , the decgher JSC ,35. We ianalysis . The POSlar cell . POSS paX) and the perovskite layer (MAPbI3) of PSCs. POSS passivation can make the surface of the NiOX layer more hydrophobic and smoother surface, which leads to a significant increase in the MAPbI3 grain size and a slight increase in VOC. However, in addition to the increase in interface resistance, too much POSS makes the surface of NiOX become too hydrophobic to spread over the perovskite solution and thus results in pinholes and a small grain size. A 0.01-mg·mL−1 POSS passivation displays the best performance, which increases the JSC from 18.0 to 20.5 mA·cm−2 and an enhancement of 17.3% for PCE. The performance improvement arises mainly from the decrease in the rate of charge recombination.In summary, this is the first attempt to use POSS as a passivation layer between the hole transport layer (NiO


Efficient load transmission between concrete and steel reinforcement by bonding action is a key factor in the process of the design procedure of bar-reinforced concrete structures. To enhance the bond strength of steel/concrete composites, the impact of graphene nanoplatelets (GnP) on the bond stress and bond stress–slip response of deformed reinforcement bars, embedded in high-performance concrete (HPC), was investigated using bar pullout tests. In the current study, 36 samples were produced and examined. The main variables were the percentages of GnP, the steel reinforcement bar diameter, and embedded length. Bond behavior, failure mode, and bond stress-slip response were studied. Based on the experimental findings, the inclusion of GnP had a significant favorable influence on the bar-matrix interactions due to the bridging action of GnP as a nano reinforcement. For 0.02 wt.% of GnP, the bond strength was enhanced by more than 41.28% and 53.90% for steel bar diameters of 10 and 16 mm, respectively. The HPC-GnP mixture displayed a reduction in the initial slippage in comparison to the control sample. The test findings were compared to the prediction models created by other researchers and the ACI 408R-12 code. Concrete, the most widely used building material, has long been able to meet the growing needs of mankind. Concrete buildings have long been made up of many types of concrete, such as normal concrete, high-strength concrete (HSC), and high-performance concrete (HPC). For its improved mechanical characteristics and durability, HPC is increasingly used in high-rise buildings, bridges, and offshore constructions. High-strength concrete is described as concrete with a low water/binder ratio and an adapted aggregate-to-binder ratio to regulate its dimensional stability  and adequately water-cured (to control autogenous shrinkage) . The invFor optimal design in reinforced concrete structures, effective and dependable force transmission between reinforcement and concrete is essential ,3. BondePrevious studies have shown that bond strength is regulated by several parameters . For exa3 [2 [2 [On the contrary, current research efforts focus on finding new methods to improve concrete performance by nanoengineering the physicomechanical and chemical characteristics of cement, which is the major binding ingredient in the mix . Nanomat3 , nano-Si3 [2 , and nan3 [2 [2 , as rein3 [2 [2 ,20. Kons3 [2 [2  reportedA new possibility for nanosized cementitious additives has emerged with the recent discovery of graphene ,23, whicA handful of recent research showed that the inclusion of graphene nanoplatelets in cementitious composites exhibited excellent mechanical properties. The review study of Rehman et al.  demonstrIn accordance with the reported study by Konsta et al. , which rReviewing the studies on the impact of graphene nanoplatelets on HPC and bond strength, no appreciable investigation has been conducted. Therefore, in this study, experimental tests and mathematical verification according to the available models were performed. The parameters affecting the bond strength  were examined. In order to accomplish this goal, the HPC compressive strength was first obtained at a curing age of 28 days. Then, 36-cylinder samples were tested for bond-slipping behavior between HPC-GnP and rebar. Finally, the pullout test results were analyzed, and the reliability of available models was studied.In the current investigation, the experimental program was conducted to investigate the bond stress-slip behavior and pullout strength of reinforcement bars embedded in the HPC with GnP. The major variables of this study were: (i) different percentages of GnP by weight of cement , (ii) the steel reinforcement bar diameter  and conformed to the requirements of ASTM C150/C150M . Silica 2.The size of silica fume particles was determined using Field Emission Scanning Electron Microscopy (FESEM) as shown in Commercially available GnP was supplied by XG Sciences, Inc. . The ACI guidelines 211.1 revised by Aïtcin  were conTests were performed on a sample size of 36 to determine the bond stress of the HPC-GnP combination. The pullout test was performed using a Universal Testing Machine (UTM) with a capacity of 200 kN. The monotonic loading speed employed in this study was 0.367 kN/s. The loading and total displacement parameters were acquired using a built-in data logger within the UTM to maintain the load and displacement during the test. Total displacement for slippage and steel elongation were recorded. The braking force or the maximum load exerted to remove the steel rebar from the concrete was provided by the machine. The force was applied until the yielding of the steel bar or the bar slipped out from the specimen. The compressive strength of HPC samples with the mixtures listed in As seen in GnP was employed to enhance the mechanical properties and filling characteristics of HPC in the current investigation. The effect of modulating the characteristics of HPC with GnP on bar-to-concrete adhesion has not been investigated. The findings of the pullout test for HPC-GnP are described in this section. According to the results indicated in The bonding between the reinforcing bars and the concrete has been studied by several researchers. A selection of these models is described below. Using the following formula, Orangun et al.  proposedτu=τu= showed improved bond stress, which was near to the same enhancement of 0.02 wt.% of GnP.The use of GnP reinforced HPC can lead to a decrease in the length of anchoring required for deformed bars.Esfahani and Rangan’s prediction equation was able to nearly predict the bond stress of GnP-incorporated samples with a mean ratio of 0.99 and a standard deviation of 0.12.


Immunoglobulin G4 (IgG4)-related diseases are characterized by abnormal IgG4 levels, swelling, and marked infiltration and fibrosis of the lymphocytes and IgG4-positive plasma cells, causing hypertrophic lesions or nodules. The cause is currently not well understood. IgG4-related diseases involving lesions limited to the pleura are extremely rare. Herein, we report an IgG4-related disease presenting with multiple pleural nodules confirmed by thoracoscopic surgical biopsy.18F)-fluorodeoxyglucose positron emission tomography imaging exhibited tracer accumulation in the nodules. A thoracoscopic surgical biopsy was performed. Histopathological examination revealed hyalinized fibrous tissue with a high degree of plasma cell-based inflammatory cell infiltration. Immunohistochemically, IgG4-positive cells were conspicuous, accounting for 70.5% of the plasma cells. The postoperative serum IgG4 concentration was 289 mg/dL. We diagnosed the patient with an IgG4-related disease with multiple pleural nodules. The postoperative course was good, and the patient is currently being followed up.A 74 year-old man was referred to our department for definitive diagnosis of multiple pleural nodules after 1 year of follow-up. Computed tomography of the chest revealed multiple pleural nodules, while 2-deoxy-2-( IgG4-related disease should be considered in cases presenting with multiple pleural nodules. Immunoglobulin G4-related disease (IgG4-RD) is attracting increasing attention as a relatively new disease originating in Japan , 2. In a18F)-fluorodeoxyglucose demonstrated maximum standardized uptake values of 4.93 and 3.18 in the lateral nodule and the nodule at the dorsal side of the descending aorta, respectively  of the chest (Fig. ely Fig. a–c. A stely Fig. d. The IgIgG4-RD is a newly recognized fibroinflammatory condition characterized by tumefactive lesions, a dense lymphoplasmacytic infiltrate rich in IgG4-positive plasma cells, storiform fibrosis, and elevated serum IgG4 concentrations . Based oThe case was diagnosed with IgG4-RD with multiple pleural nodules based on the histological features and the postoperative high serum IgG4 levels, according to the diagnostic criteria for IgG4-RRD. The patient had a career working as a welder in the iron works, with an unknown history of asbestos exposure. There are reports of pleuritis related to IgG4-RRD in asbestos-exposed individuals , and cliIn IgG4-RRD, the goal of the treatment is to maintain the lung function. Though there is no current consensus on the indication of treatment for IgG4-RRD, systemic corticosteroid therapy is recommended for patients with symptoms and with a high disease activity , 9. The The patient was diagnosed with IgG4-RD with multiple pleural nodules. He is being followed up closely following the biopsy, and a steroid treatment has been planned if the IgG4 levels rise or pleural effusion occurs.IgG4-RD should be considered in cases presenting with multiple pleural nodules.


Collateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the emergence of antimicrobial resistance. However, it remains unclear how to best design CS-based treatment schedules. To address this problem, we use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. We confirm that simultaneous and one-day cycling treatments could supress resistance in the presence of CS. We show that the efficacy of CS-based cycling therapies depends critically on the order of drug administration. Finally, we find that reciprocal CS is not essential to suppress resistance, a result that significantly broadens treatment options given the ubiquity of one-way CS in pathogens. Overall, our analyses identify key design principles of CS-based treatment strategies and provide guidance to develop treatment schedules to suppress resistance. Collateral sensitivity-based antibiotic treatments may have the potential to limit the emergence of antimicrobial resistance. Here, the authors use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. Innovative strategies to reduce the rate that AMR develops are thus critically needed. Treatment with antibiotics in individual patients represents one important situation where de novo AMR may emerge3. However, current clinical antibiotic-treatment strategies, i.e., which types of antibiotics are included as well as timing and dosage, typically do not explicitly consider within-host emergence of AMR. Instead, current strategies used in clinical practise are primarily based on exposure targets that are associated with sufficient bacterial kill in preclinical studies, or with clinical outcomes in patient studies4. Thus, there is a need for clinical dosing strategies specifically designed to suppress AMR emergence5.Antimicrobial resistance (AMR) is a worldwide health threat due to the reduction of clinically effective antibiotics. Current drug discovery pipelines of new-in-class antibiotic agents are insufficient to offset the emergence of new AMR6. In this context, collateral sensitivity (CS), where resistance to one antibiotic leads to increased sensitivity to a second antibiotic, has been proposed as a potential strategy to suppress AMR8. CS has been characterized in vitro, typically by evolving AMR strains and then quantifying correlated changes in the sensitivity to other antibiotics11. CS effects have been characterized for several clinically relevant pathogens, including Escherichia coli9, Pseudomonas aeruginosa12, Enterococcus faecalis13, Streptococcus pneumoniae14, and Staphylococcus aureus15. CS relationships between antibiotics can either be one-directional, where decreased sensitivity to one antibiotic show CS to a second antibiotic but not the reverse, or reciprocal, where decreased sensitivity to either of the antibiotics results in CS to the other. Reciprocal CS is often considered a prerequisite for effective CS-based treatments, but such relationships have been less frequently observed compared to one-directional CS15.Trade-offs associated with AMR are of increasing interest to design antibiotic dosing strategies that suppress the within-host emergence of AMR6, it remains unclear when CS-based dosing strategies are most likely to be beneficial, and how to design specific multi-drug antibiotic dosing schedules based on CS. Furthermore, it is unclear how pathogen-specific factors, such as CS effect magnitude and directionality, fitness costs of resistance, and mutation rates, as well as pharmacological factors related to pharmacokinetics and pharmacodynamics for different drug types, can affect optimal dosing schedules.CS-based treatment strategies can use different designs to combine antibiotics showing a CS relationship, including simultaneous, sequential, or cyclic  administration. For example, consider a cycling drug strategy using two antibiotics showing reciprocal CS Fig. . Initial15. However, to translate in vitro CS findings to in vivo or clinical treatment scenarios, consideration of pharmacodynamic (PD) and pharmacokinetic (PK) factors is essential, as these determine the differential impact of different antibiotics on the concentration-dependent effects of bacterial growth, inhibition and killing17. By affecting bacterial dynamics, antibiotic PK-PD can have a profound influence on resistance evolution, and are therefore key elements to design optimised CS-informed treatments. In addition, it is necessary to disentangle the respective impacts of these separate parameters. Doing so requires a highly controlled system, where each factor can be modified separately; this level of control cannot be established experimentally. To this end, a mathematical modelling approach can be highly valuable, as such models permit precise control of each factor. In addition, mathematical models are important tools to integrate multiple biological and pharmacological factors contributing to treatment outcomes, including different PK parameters of specific antibiotics in patients, antibiotic-specific PD parameters, and pathogen-specific characteristics such as strain fitness and the magnitude of CS effects. Thus, using a mathematical modelling approach allows us to address key questions relating to CS-based treatments that have yet to be fully answered.Experimental in vitro studies are essential to characterize the incidence, evolvability and magnitude of CS, all of which are important but isolated components that may contribute to the success of CS-based treatments18 and Markov19 models evaluating antibiotic cycling in vitro and in silico, which provide insight into the importance of the design of the cycling regimen. Furthermore, a stochastic evolution model has been developed to assess the robustness of collateral sensitivity20. None of these models, however,   characterise the bacterial dynamics underlying resistance evolution. In addition, these models do not include PK-PD relationships and lack consideration of clinical PK, which are key factors when translating the findings into clinical dosing strategies. Udekwu and Weiss developed a deterministic PK-PD model to study clinically relevant cycling schedules for CS-informed treatments and evaluated their ability to delay the emergence of antibiotic resistance21. This simulation study serves as an important step toward designing clinically effective CS-based treatments. However, to take further steps towards such treatments, there is a need for a more comprehensive evaluation of the impact of several pharmacological and pathogen-associated factors related to dosing schedule designs, as well as specifically evaluate the impact of CS effects on treatment outcomes in comparison to the situation without CS.A number of mathematical models have been developed to evaluate multi-drug therapies in relation to collateral effects, often using shifts in the minimum inhibitory concentration (MIC) or other summary metrics as endpoints. These models include deterministicIn the current study, we aim to build on previously established models in order to determine if and when CS-based dosing schedules lead to suppression of within-host emergence of antibiotic resistance. We utilise a mathematical modelling approach to comprehensively study the influence of key pathogen-specific factors and the contribution of PK and PD properties to identify key design principles to inform rational design of antibiotic multi-drug dosing schedules that suppress AMR.A) and drug B (DB) on bacterial population dynamics including four states, which include an antibiotic sensitive bacterial subpopulation (WT), one mutant subpopulation resistant to DA but sensitive to DB (RA), one mutant subpopulation sensitive to DA but resistant to DB (RB), and one double mutant subpopulation resistant to both DA and DB (RAB)  Fig . The fraWT). We show that the impact of reciprocal CS on resistance dynamics is dependent on the simulated drug type and dosing regimen  or reciprocal CS  is sufficient to fully suppress resistance development. This is illustrated for treatments using concentration-dependent bacteriostatic antibiotic in Fig. Any for bacteriostatic , we found resistance levels close to the scenario without any CS  for both of these treatments.We next sought to determine if reciprocity is a requirement for CS-based treatments to suppress de novo resistance. We find that bactericidal and bacteriostatic drugs showed the same overall behaviour for treatment outcomes when tested in relation to CS directionality . In con.5% Fig.  vs 12.4%.5% Fig. ). OveralA) for all non-simultaneous regimens  and the impact of CS on de novo resistance development would help identify in which clinical scenarios CS could be exploited to improve treatment. To this end, we simulated a set of dosing regimens (using same-type antibiotics) resulting in Css ranging between 0.5 and 4 × MICWT. These simulations revealed that CS has the greatest impact on RAny for Css close to the MICWT  on RAny for most treatment scenarios. However, when concentration-dependent bactericidal drugs were dosed simultaneously the presence of fitness costs slightly increased the PoR (maximum ΔPoR 10.2%). The presence of fitness cost increased the impact of CS on PoR the three-day cycling regimen using time-dependent antibiotics . This is illustrated with the one-day cycling treatments shown in Fig. B, but failed for all with pre-existing RA. For three-day cycling regimens and pre-existing resistance towards the first antibiotic, CS was shown to increase the PoR for RAB . We show that the impact of mutation rate on the PoR was dependent on the combination of treatment design and the antibiotic type used, especially in the presence of CS   Fig. , initialss) of 1.5 × MICWT (or 0.75 × MICWT for simultaneous dosing regimens), which led to complete killing of the sensitive population but did allow emergence of resistance to occur. This concentration can be considered to reflect a narrow-therapeutic window antibiotic, e.g., where the antibiotic concentration required for bacterial killing is closer to the MIC because of the occurrence of (severe) toxicities at higher concentrations. Indeed, for concentrations (much) higher than the MIC, or simultaneously administrating two drugs above the MIC, the benefit of CS rapidly disappears , one-day cycling regimens and simultaneous antibiotic treatments are most relevant to benefit from CS, whereas for high mutation rates , sequential and simultaneous antibiotic treatments are the most beneficial  and/or when the administered antibiotics induce mutagenesis , this should be considered in the design of dosing schedules. With respect to the competition between different bacterial subpopulations occurring in vivo, we included a bacterial carrying capacity which introduces clonal competition. During clonal competition, competition between subpopulations can lead to their suppression, e.g., high densities for one subpopulation can suppress the growth of a second subpopulation, even if the second population might be more fit. Treatments giving rise to clonal competition-based containment, where the selection pressure favours specific subpopulations which will in turn suppress others due to the capacity limitation of the system, have been suggested as a potential strategy to suppress AMR34. In our simulation, we observe a clear impact of clonal competition. When CS is present, single resistant subpopulations are unable to reach high enough levels to suppress the growth of the double resistant mutant, which allows the double mutant to take over, for some treatments. This supports the value of characterizing CS-based treatments beyond the quantified summary metric of collateral effect.To better characterize the population dynamics of pathogens in response to antibiotic treatment under the presence of CS, we studied the effect of fitness costs of antibiotic resistance and mutation rates leading to antibiotic resistance. We find that introducing fitness costs had a negligible effect on PoR for the majority of the simulated CS-based treatments, with the exception of the three-day cycling using time-dependent antibiotics Fig. J and N, otics 10− mut/bp/h21 by explicitly comparing treatment outcomes to a base scenario without CS to determine the specific contribution of CS effects, and by performing a more systematic analysis of key drug- and pathogen-specific factors that could influence optimal CS-based treatment scenarios. In addition, we incorporated mutations as random events to capture the stochastic nature of resistance evolution, which is overlooked when using purely deterministic models. Our mathematical model was designed to facilitate the identification of the primary factors driving the success or failure of antibiotic treatments in a general setting, and not for specific antibiotics and/or pathogens. We thereby did not consider factors that could further contribute to treatment outcomes for specific pathogens or antibiotics. We did not consider that more complex evolutionary mutational trajectories can occur with associated complex patterns of changes in antibiotic sensitivity and MIC35, which are not easily definable to apply to antibiotic treatment in general. Other factors not considered include local antibiotic tissue concentrations37, pharmacokinetic drug–drug interactions or the contribution of the immune system. We expect that such factors will not affect the specific subpopulations studied in different ways and therefore will not have a great impact on the general findings derived in this analysis.Our study advances the work by Udekwu and Weiss38. Combined drug effects can furthermore be modelled according to different null interaction assumption, including: (i) dependence of drug effects through a shared mechanism of action (Loewe additivity)39, (ii) independent drug effects with a shared maximum drug effect (Bliss independence)40, or (iii) fully independent additive drug effects38 as implemented in this paper. The choice of null interaction model, or the presence of drug interactions  may influence treatment outcomes in particular for simultaneous treatment schedules. Although an analysis of the effect of various possible drug interactions was beyond the scope of this analysis, we do expect this will be an important factor to consider when designing CS-based treatment for specific antibiotic combinations, where specific pharmacodynamic drug interactions can be explicitly incorporated.In this analysis we assumed independent additive drug effects, thus excluding the possibility of pharmacodynamic drug–drug interactions between antibiotics, e.g., synergy or antagonism41, derived from separate experimental studies. In addition,  published clinical population PK models for specific antibiotics43 can be incorporated, which include inter-individual variability or target site concentrations at the site of infection. This would allow development of tailored CS-based dosing regimens for specific antibiotics and pathogens. We did not evaluate how the presence of collateral resistance (CR) could impact treatment efficacy. Although such scenarios are beyond the scope of the current study, the flexibility of our developed framework allows for the incorporation of CR, and could thus serve as a tool to investigate how CR impacts treatment efficacy. Furthermore, cellular hysteresis, where non-genetic CS-like responses have been observed, may be another direction for which our modelling framework could be extended29.The developed modelling framework is applicable for the design of clinical treatment strategies for specific antibiotic agents and pathogens, where the model can be further expanded with additional pathogen-, drug-, and patient-specific characteristicsIn this study, we demonstrate how a mathematical modelling can address questions that are difficult to answer using an experimental approach. We conclude that CS-based treatments are likely to be able to contribute in the suppression of resistance. However, the success of such treatment strategies will be dependent on careful design of a dosing schedule, and requires explicit consideration of pathogen- and drug-specific characteristics. Our developed modelling framework delineates key factors for the overall design of effective CS-informed treatments and can be used to facilitating and help the design of treatments tailored to specific pathogens and antibiotic combinations. Although well-conserved CS effects remain a key requirement, we found that reciprocal CS may not be a requirement to design such dosing schedules, expanding the applicability of CS-based treatments. Such CS-based treatments appear to be most relevant for antibiotics with a narrow-therapeutic window, which are also the antibiotics where within-host emergence of resistance is most likely to occur.A) and drug B (DB). As a foundation for our model development, we used a deterministic PK-PD model developed by Udekwu and Weiss21, which explores the impact of different multi-drug treatments on time to resistance development in the presence of CS. We advanced the model by incorporating mutations as random events to capture the stochasticity of resistance evolution. We integrated the different model components into a framework that allowed us to simulate antibiotic multi-drug treatments while altering drug- and pathogen-specific factors as a strategy to disentangle their impacts on resistance development.A differential-equation based model, consisting of components accounting for antibiotic PK and PD, and associated bacterial population dynamics, was developed to study the impact of differences in pathogen- and drug-specific characteristics for different treatment strategies using two antibiotics, hereafter referred to as drug A  model, where each state represents a bacterial subpopulation with different antibiotic susceptibility towards DA but sensitive to DB (RA) (Eq. (A but resistant to DB (RB) (Eq. (A and DB (RAB)  (Eq. ), one muRA) (Eq. ), one muRB) (Eq. ), and onAB) (Eq. ). The inz, the subpopulation-specific net growth , the drug effect , and mutation transition(s) , if present.The above equations (Eqs. –7)) des) des7)) B with a mutation probability equal to the mutation rate (μ). The number of bacteria mutated per time step T , i.e., the bacterial subpopulation density of subpopulation z multiplied by the infection volume V, at time T . Doublez  was implemented as follows ) wer) wer7)) ows (Eq. ):9\docum16, where the effect of the ith antibiotic on bacterial subpopulation z  and resistant as 10 mg/L (MICR). Because the antibiotic concentrations are expressed as folds times MICWT, the absolute value of MICWT is arbitrary. However, the ratio between MICWT and MICR is of relevance. A tenfold increase was chosen to represent a significant increase for a biologically plausible scenario. Resistance-related CS effects were included on the two single resistant mutants (RA and RB), and were implemented as a proportional reduction (CSA and CSB) of the MIC of the sensitive wild-type bacteria (MICWT). The double resistant mutant (RAB) was fully resistant (MIC = MICR) to both antibiotic A and B, and did not have any collateral effects. The subpopulation- and antibiotic-specific MICs are stated below:Sensitive bacteria were defined as having a MIC of 1 mg/L (MICkGmax) represents the maximal net growth of the wild-type bacteria in the exponential growth phase. We considered resistance-associated fitness costs for the different mutant subpopulations. The fitness cost was incorporated using the factor Ffit, which introduced a fractional reduction of kGmax for each resistance mutation. Thus, each subpopulation is associated with a specific maximal net growth rate , determined by the subpopulation-specific fitness, and was implemented according to Eq. .The maximal net growth rate  was implemented according to Eq.  of the hypothetical pathogen was 0.7 h−1, thus representing a doubling time of 1 h. The infection-specific parameters were chosen to represent a human bacteraemia, thus a typical human blood volume of 5 L was used as the infection site volume44. An initial bacterial density of 104 colony forming units (CFU)/mL was used to represent an early stage of an established infection45. A system carrying capacity limitation (Bmax) of 108 CFU/mL45 was implemented according to Eq.  have identical one-compartmental PK with distribution volumes of one litre, 5-h half-lives, and no protein binding. Their half-lives were selected to represent antibiotics with clinically relevant short half-lives, thereby rapidly reaching steady-state concentrations with minimal accumulation. The drugs were administrated as intravenous bolus doses twice daily over a treatment duration of two weeks. Several different dosing regimens were simulated including monotherapy, sequential non-repetitive dosing, one- and three-days repeated cycling regimens, and simultaneous dosing. Here, sequential non-repetitive dosing represents a multi-drug treatment using DA for the first seven days and then switching to DB for the remaining seven days of the treatment. The repeated cycling regimens represent multi-drug treatments starting with DA for the duration of the cycling interval , then switching to DB for the same duration, and then back to DA, continuing the repeated cycling until the end of treatment. For sequential and repeated cycling treatments DA was always used as the starting drug. The doses used were obtained by calculating the required dose to achieve appropriate average steady-state concentration (Css) relative to the MICWT. The lowest dose (using 0.5 × MIC increments) that gave kill or stasis of the WT bacteria within the 24 h of treatment, but allowed for resistance development during monotherapy, was selected for all dosing regimens except for the simultaneous dosing, for which the dose for the individual antibiotics was reduced by half in order to allow for resistance development. Four different PD types were included using different combinations of representative parameter values of Hill (driver of antibiotic effect) and Gmin (type of antibiotic effect). The driver of the antibiotic effect, which is reflected by the steepness of the concentration-effect relationship (Hill), where shallow relationships are associated with time-over-MIC-dependency (Hill = 0.5) and steep relationship with concentration-dependency (Hill = 3). The type of antibiotic effects are commonly divided into bacteriostatic (Gmin = −1) or bactericidal (Gmin = −3). The corresponding PK-PD relationships of the four different antibiotic types are shown in Fig. The two hypothetical antibiotics used for the simulations  to achieve killing of the WT while allowing for emergence of resistance in the absence of CS, regardless of the drug type used  was used in order to keep the total dose constant, and to allow for resistance emergence in the absence of CS and comparable to non-simultaneous dosing regimens.An initial set of dose-finding simulations revealed that monotherapy required CGmin,A = Gmin,B and HillA = HillB) for scenarios without CS as well as in the presence of one-directional and reciprocal CS in the magnitude of 50% or 90% (2 or 10-fold) reduction of the sensitive MIC (Supplementary Table ss) to the MICWT, we simulated different dosing levels resulting in a range of Css of 0.5–4 × MICWT  development for different treatments. An overview of all simulated scenarios can be found in Supplementary Table n), thus representing 500 virtual patients for which the within-patient resistance development was assessed. For each scenario we evaluated different multi-drug treatments regimens, including within-patient cycling and simultaneous administration. We note that most previously conducted studies investigating the clinical utility of antibiotic cycling and mixing to suppress AMR have evaluated stewardship strategies at a community level49, e.g., between patients within a hospital ward. However, community-level strategies are conceptually different from the within-patient multi-drug treatment strategies we investigate in this analysis. Therefore, the results we derive from our simulations are not directly comparable to the findings from such epidemiological studies.Each simulated scenario was realized 500 times , which was defined as resistant bacteria reaching, or exceeding, the initial bacterial density of 10ely (Eq. )13\document (Eq. ):14\docuAny).We also calculated the PoR for the case where any, i.e., one or more, resistant subpopulation(s) exceeded the resistance cut-off (RThe standard error (SE) of the PoR was calculated according to Eq. .15\docum51. The associated model code is available at https://github.com/vanhasseltlab/CS-PKPD)52.All analyses were conducted in R version 4.0.5, using the ODE solver package RxODE (version 1.0.0-0)Further information on research design is available in the Supplementary informationDescription of Additional Supplementary FilesSupplementary SoftwareReporting Summary


Pseudomonas aeruginosa (PA), multidrug-resistant (MDR) metallo-beta-lactamase (MBL)-negative-PA, MBL-positive-PA, carbapenem-susceptible Acinetobacter baumannii (AB), and carbapenem-resistant AB. (3) Results: Piperacillin–tazobactam or fourth-generation cephalosporins represent the first therapeutic choice in IVACs caused by multi-susceptible PA. A carbapenem-sparing approach favouring the administration of novel beta-lactam/beta-lactamase inhibitors should be pursued in the management of MDR-MBL-negative PA infections. Cefiderocol should be used as first-line therapy for the management of IVACs caused by MBL-producing-PA or carbapenem-resistant AB. Fosfomycin-based combination therapy, as well as inhaled colistin, could be considered as a reasonable alternative for the management of IVACs due to MDR-PA and carbapenem-resistant AB. (4) Conclusions: The implementation of algorithms focused on prompt revision of antibiotic regimens guided by results of conventional and rapid diagnostic methodologies, appropriate place in therapy of novel beta-lactams, implementation of strategies for sparing the broadest-spectrum antibiotics, and pharmacokinetic/pharmacodynamic optimization of antibiotic dosing regimens is strongly suggested.(1) Background: To develop evidence-based algorithms for targeted antibiotic therapy of infection-related ventilator-associated complications (IVACs) caused by non-fermenting Gram-negative pathogens. (2) Methods: A multidisciplinary team of four experts had several rounds of assessments for developing algorithms devoted to targeted antimicrobial therapy of IVACs caused by two non-fermenting Gram-negative pathogens. A literature search was performed on PubMed-MEDLINE (until September 2021) to provide evidence for supporting therapeutic choices. Quality and strength of evidence was established according to a hierarchical scale of the study design. Six different algorithms with associated recommendations in terms of therapeutic choice and dosing optimization were suggested according to the susceptibility pattern of two non-fermenting Gram-negative pathogens: multi-susceptible  Pseudomonas aeruginosa and Acinetobacter baumannii) are responsible for a remarkable amount of IVACs in critically ill patients, second only to Staphylococcus aureus in terms of prevalence  or FiO2 followed by a rise in PEEP of 3 cm H2O or a rise in FiO2 of 0.2 sustained for 48 h) coupled with the occurrence of body temperature <36 °C or >38 °C and the start of at least one antibiotic agent continued for over 96 h. VAP was considered a subgroup of IVACs, consisting in the presence of at least 25 neutrophils/field coupled with positive semi-quantitative/quantitative culture for pathogenic organisms at bronchoalveolar lavage [Pseudomonas aeruginosa, MDR metallo-beta-lactamase-negative Pseudomonas aeruginosa, MDR metallo-beta-lactamase-positive Pseudomonas aeruginosa, carbapenem-susceptible Acinetobacter baumannii, and carbapenem-resistant Acinetobacter baumannii). MDR Pseudomonas aeruginosa isolates were defined according to the classification proposed by Magiorakos et al. [A multidisciplinary task force, composed by one intensive care physician (B.V.), one infectious disease consultant (P.V.), one clinical microbiologist (G.M.R.), and one MD clinical pharmacologist (F.P.) met virtually on several occasions with the intent of developing algorithms for targeted antimicrobial therapy of IVACs caused by r lavage . The defs et al. . A hieraA researcher (M.G.) retrieved the scientific evidence needed for supporting the specific choices included in the algorithms by means of a PubMed-MEDLINE literature search (until October 2021). Key terms were selected antibiotics, HAP, VAP, IVACs, and bacterial pathogens with genotype of resistance and/or antibiotic susceptibility pattern. Quality of evidence was established according to a hierarchical scale of the study design, as reported in the evidence pyramid : randomiIn an era characterized by widespread diffusion of MDR Gram-negative pathogens and continuous increase in antibiotic resistance, the implementation of a multidisciplinary taskforce focusing on targeted therapy in critically ill patients has become a real need. Our approach is focused on prompt revision of inappropriate/unnecessary antibiotic therapy, implementation of “carbapenem-sparing” strategies, and PK/PD optimization of antibiotic exposure hopefully guided by real-time TDM whenever feasible. Rational use of broad-spectrum antibiotics, especially carbapenems, could represent a powerful strategy for tackling resistance spread in the ICU setting . We beli


These findings highlight the central role of T cells in sustaining IgG4‐RD and open novel avenues for targeted therapies.IgG4‐related disease (IgG4‐RD) is a fibroinflammatory disorder signified by aberrant infiltration of IgG4‐restricted plasma cells into a variety of organs. Clinical presentation is heterogeneous, and pathophysiological mechanisms of IgG4‐RD remain elusive. There are very few cases of IgG4‐RD with isolated central nervous system manifestation. By leveraging single‐cell sequencing of the cerebrospinal fluid (CSF) of a patient with an inflammatory intracranial pseudotumor, we provide novel insights into the immunopathophysiology of IgG4‐RD. Our data illustrate an IgG4‐RD‐associated polyclonal T‐cell response in the CSF and an oligoclonal T‐cell response in the parenchymal lesions, the latter being the result of a multifaceted cell–cell interaction between immune cell subsets and pathogenic B cells. We demonstrate that CD8 This translational study demonstrates the potential of single‐cell profiling technologies to support clinicians in the diagnosis of rare autoimmune disorders while shedding new light into potential molecular pathomechanisms of intercellular communication in IgG4‐related disease. IgG4‐related disease (IgG4‐RD) is an autoimmune disorder signified by infiltration of pathological plasma cells into a variety of organs. Clinical symptoms are diverse, and the underlying mechanisms that lead to IgG4‐RD remain elusive. There are very few cases of IgG4‐RD with isolated central nervous system manifestation, and treatment is unspecific and often not very successful.This paper aims at shedding new light into potential molecular mechanisms of cell‐to‐cell communication in IgG4‐related disease. The authors propose the idea that the abnormal immune response in IgG4‐RD is driven by single T‐cell clonotypes.This paper demonstrates the potential of single‐cell profiling technologies to support clinicians in the diagnosis of rare autoimmune disorders. Future studies might incorporate results and hypotheses of this paper to develop new causal treatments against IgG4‐RD.et al, et al, et al, et al, et al, Immunoglobulin G4 (IgG4)‐related disease (IgG4‐RD) is the pathological consequence of aberrant infiltration of IgG4‐restricted plasma cells into a variety of organs, most commonly the pancreas and lymph nodes ‐associated cytokine profile including IL‐4, IL‐10, and IL‐21. Previous studies suggest that Th2 cells drive the class switch toward IgG4 via IL‐4 signaling  ‐like cells  as well as a direct T‐cell–T‐cell crosstalk between CD8 TEM and CD4+ memory cells, while plasmablasts did not show potent intercellular interactions  on CD8+ and CD4+ T cells, which has recently been described as B‐cell chemokine that might be responsible for the migration of pathogenic B cells to IgG4‐RD manifestation sites as well as their aberrant proliferation  on CD8 TEM binding to C‐C chemokine receptor type 4/5 (CCR4/5)‐expressing T cells that might facilitate recruitment of helper and cytotoxic CD4+ T cells that have been shown to mediate inflammation in IgG4‐RD  autoimmune pancreatitis .et al, et al, et al, et al, Patient CSF cells were sequenced in multiplexed libraries on an Illumina NovaSeq sequencing system at a depth of ∼130,000–200,000 reads per cell. MS and control datasets were obtained from GEO with the accession code GSM4104122. Libraries with a total of 38,203 cells  after quality control were integrated and analyzed using Seurat v4  and Deparaffinization Solution  as per the manufacturer’s instructions. TCR beta chain (TCRB) deep sequencing was performed to detect rearranged TCRβ gene sequences using hsTCRB Kit (Adaptive Biotechnologies) according to the manufacturer’s protocol. The prepared library was sequenced on an Illumina MiSeq by the Genomics & Proteomics Core Facility, German Cancer Research Center (DKFZ). Data processing  was done using the Adaptive Biotechnologies proprietary platform as previously described  was measured at 570 and 450 nm. Cytokine concentrations were calculated based on OD [450nm] – OD [570 nm] according to parallel serial dilutions of cytokine standards included in the respective ELISA kit. ELISA detection was used for the following human immunoglobulins and cytokines: IgG4 , total IgG  Human Uncoated ELISA Kit with Plates, #88‐50550‐22, Thermo Fisher), CXCL13 .Supernatants of IgG4‐RD CSF and control CSF from patients without any resulting neurological diagnosis were transferred to cytokine‐specific antibody‐coated or uncoated ultra‐low binding 96‐well plates (Corning), respectively, and immunoglobulin and cytokine ELISA based on horseradish‐peroxidase were performed according to the manufacturer’s instructions . Development process was stopped with 1 M HFor immunofluorescence stainings, formalin‐fixed paraffin‐embedded (FFPE) tissue was used. After deparaffination and rehydration, antigen retrieval was performed by boiling 10 µm sections in 10 mM citric acid buffer, pH 6.0. Sections were covered with blocking solution , followed by incubation with different primary antibodies overnight at 4°C: anti‐GFAP  and anti‐IgG4 . The secondary antibodies (Goat anti‐Mouse IgG (H + L) Highly Cross‐Adsorbed Secondary Antibody, Alexa Fluor Plus 488, Goat anti‐Rabbit IgG (H + L) Highly Cross‐Adsorbed Secondary Antibody, Alexa Fluor Plus 546, Thermo Fisher) were applied at 1 µg/ml to the sections in blocking buffer for 1h at RT. Tile scans (20×) and higher‐magnification images (40×) were acquired using a Carl Zeiss Cell Observer HS fluorescence microscope.Immunohistochemistry was conducted on 3 µm thick FFPE tissue sections mounted on StarFrost Advanced Adhesive slides  followed by drying at 80°C for 15 min. Immunohistochemistry was performed on a BenchMark Ultra immunostainer . Slides were pretreated with Cell Conditioning Solution CC1  for 32 min at room temperature. For DAB staining of IgG4 and IgG, anti‐human‐IgG4  and anti‐human‐IgG  were used as primary antibodies. Primary antibodies were incubated at 37°C for 32 min, followed by Ventana standard signal amplification, UltraWash, counter‐staining with one drop of hematoxylin for 4 min, and one drop of bluing reagent for 4 min. UltraView Universal DAB Detection Kit  was used for visualization. Tile scans (20×) and higher‐magnification images (40×) were acquired using a Carl Zeiss Cell Observer HS fluorescence microscope.et al, 2. Counting of IgG+ and IgG4+ cells was done semi‐automated using the CellCount plugin of the Fiji image analysis software. The number of IgG4+ and IgG+ cells from 3 areas of each slide were averaged for calculation of the IgG4/IgG ratio. Quantification results were validated by automatic quantification as per default DAB parameters of QuPath 0.2.3 software.DAP‐stained FFPE tissue slides were scanned using the Zeiss Axioscan™ slidescanner. For each resection tissue, areas with the highest IgG4 staining were analyzed in accordance with the consensus statement on the pathology of IgG4‐RD , control CSF , and MS patient‐derived CSF , were included in downstream analyses on a single‐cell basis in a similar procedure to other exploratory neuroinflammation studies. For functional experiments, CSF samples were blinded to the experiment performer.Data are represented as individual values or as median ± SD, as indicated. Group sizes (n) and applied statistical tests are indicated in figure legends. Significance was assessed by either unpaired ® database (https://doi.org/10.21417/MF2021EMBOMM). All additional datasets generated or analyzed during this study are included in this published article (and its supplementary information files). Imaging source data for this manuscript can be found via URL: https://doi.org/10.6084/m9.figshare.14522397.v1.Gene expression data that support the findings of this study have been deposited in the Gene Expression Omnibus repository (E‐MTAB‐10479). T‐cell receptor deep sequencing data have been deposited in the Adaptive Biotechnologies immuneACCESSStudy design, experiments, scRNA‐seq, VDJ‐seq, and experimental data analysis and interpretation, and writing the manuscript: MF scRNA‐seq data analysis and experiments: NK Lumbar punctures and blood sampling for diagnostics and translational analyses: NE, JK, and IM Single‐cell sequencing: KL Immunofluorescence tissue staining: PM. MR imaging data interpretation and provision: CG and AG Study design and data interpretation: MFa and NEt Diagnostic tissue staining: AvD and DR Study conceptualization, data interpretation, and writing the manuscript: MP and LB.The authors declare that they have no conflict of interest.●https://www.rheumatology.org/I‐Am‐A/Patient‐Caregiver/Diseases‐Conditions/IgG4‐Related‐Disease‐IgG4‐RDInformation for patients and caregivers: ●https://www.dkfz.de/en/neuroimmunologie/index.phpResearch group website: AppendixClick here for additional data file.Expanded View Figures PDFClick here for additional data file.Source Data for Expanded ViewClick here for additional data file.Review Process FileClick here for additional data file.


Antimicrobial resistance has been steadily increasing in prevalence, and combination therapy is commonly used to treat infections due to multidrug resistant bacteria. Under certain circumstances, combination therapy of three or more drugs may be necessary, which makes it necessary to simulate the pharmacokinetic profiles of more than two drugs concurrently in vitro. Recently, a general theoretical framework was developed to simulate three drugs with distinctly different half-lives. The objective of the study was to experimentally validate the theoretical model. Clinically relevant exposures of meropenem, ceftazidime, and ceftriaxone were simulated concurrently in a hollow-fiber infection model, with the corresponding half-lives of 1, 2.5, and 8 h, respectively. Serial samples were obtained over 24 h and drug concentrations were assayed using validated LC-MS/MS methods. A one-compartment model with zero-order input was used to characterize the observed concentration-time profiles. The experimentally observed half-lives corresponding to exponential decline of all three drugs were in good agreement with the respective values anticipated at the experiment design stage. These results were reproducible when the experiment was repeated on a different day. The validated benchtop setup can be used as a more flexible preclinical tool to explore the effectiveness of various drug combinations against multidrug resistant bacteria. The widespread use of antibiotics for decades has led to the emergence of antimicrobial resistance, which presents a significant threat to global public health. In 2019, the CDC reported that there are over 2.8 million infections and 35,000 deaths from antibiotic-resistant bacteria each year in the U.S. alone [The in vitro activity against a pathogen over time is most commonly determined using constant concentrations of an antibiotic . By using constant dilution of an isovolumetric system and repeated dosing, a fluctuating concentration-time profile mimicking clinical dosing in humans can be produced . This would allow more clinically relevant insights to be gained, guiding early drug development and transition to in vivo/clinical investigations . With a With an increasing demand of testing antibiotic combinations against multidrug resistant pathogens, a more advanced experimental setup is necessary. Multiple (three or more) antibiotics with different mechanisms of action and elimination half-lives may have to be used together in unique situations. We have previously reported a mathematical framework to mimic the concentration-time profiles of more than two antibiotics simultaneously , which sThe performance of the modified assay was deemed satisfactory. A typical chromatogram and the linear range of the assay are both shown in 24) for meropenem, ceftazidime, and ceftriaxone were 674.8, 1125.0, and 347.2 mg·h/L, respectively . Overall, the concurrent pharmacokinetic simulations were considered acceptable. The results were also reasonably reproducible on different days. The 80% confidence intervals of half-life observed on different days ranged from 0.83–1.3 h (meropenem), 0.99–3.6 h (ceftazidime), and 7.5–10.6 h (ceftriaxone), respectively (data not shown).Individual drug concentrations observed ranged from 72% to 135% (median 112%) of the target values. The correlation between target vs. observed antibiotic concentrations is shown in Novel treatment strategies are needed to solve an urgent healthcare crisis with broad spectrum antimicrobial resistance. Antimicrobial agent combinations are clinically used in the routine care of patients with HIV and tuberculosis infections. Relatively speaking, antibiotic combinations are not considered as the standard of care for many bacterial infections. However, with a growing prevalence of infections due to multidrug-resistant bacteria, antibiotic combinations are increasingly used by clinicians as a treatment of last resort. A robust system to evaluate the efficacy of antibiotic combinations in vitro would be of great value to advance medical care of these patients. Until recently, simulating more than two distinct pharmacokinetic profiles simultaneously in a dynamic infection model would not have been feasible. This is generally recognized as a technical gap of the field.max) by simple proportions , and the dosing frequencies are to emulate those of the clinical dosing regimens. The serial design is easier to set up, and it has been experimentally validated earlier [MEM = CLCAZ = CLCRO) was used in this study. Notably, different dilution rates to a constant supplemental volume (for each antibiotic) are also possible, depending on investigator preference and equipment availability.To simulate antibiotic exposures with three distinct elimination half-lives, we reported two feasible experimental designs . Both designs are based on the concept of using supplemental dosing ) to offset the rapid clearance implemented for the antibiotic with the shortest half-life. Theoretical details of the concept and complete mathematical formulas for design of the experimental setup have been described elsewhere . Doses t earlier . On the The simulated pharmacokinetic profiles were reasonably satisfactory. Despite a considerable difference , the best-fit half-lives of all three drugs were within the target ranges. Furthermore, these observations were fairly consistent when the experiment was performed on different days. The efficacy of specific antibiotic combination(s) against multidrug resistant bacteria is beyond the scope of this study, but it will be the focus of future studies once this pharmacokinetic simulation framework is established.Meropenem and ceftazidime powder were obtained from Tokyo Chemical Industry Co., Ltd. (TCI) . Ceftriaxone powder was purchased from Sigma-Aldrich, Inc. . Ertapenem was provided by Merck . Ammonium acetate was purchased from Sigma Life Sciences . LCMS-grade ammonium hydroxide, water, and methanol were obtained from EMD Millipore Corporation .central) were achieved by direct drug injections . Diluent was introduced to the central compartment to dilute the drugs over time at pre-determined rates; an equal volume of drug-containing fluid was removed from the central compartment to maintain an iso-volumetric system. To mimic different pharmacokinetic exposures concurrently, dosing (Dosesupp) into various supplemental compartments (Vsupp) would also be necessary. Meropenem and ceftazidime were dosed once every eight hours, whereas ceftriaxone was dosed only once to be consistent with clinical dosing in humans. All doses were given over 30 min. The schematics of the experimental setup  is shown in Specific pharmacokinetic parameters to mimic the unbound concentration-time profiles associated with clinical dosing in humans are shown in Antibiotic concentrations in the samples were assayed using validated liquid chromatography tandem mass spectroscopy (LC-MS/MS) methods. The method used to detect meropenem and ceftazidime has been reported previously . Using s® 5500 mass spectrometer  equipped with Turbo-Ion-Spray™ source. Mobile phase A consisted of 10 mM ammonium acetate and 0.2% (v/v) ammonium hydroxide. Mobile phase B was 100% methanol. The injection volume for ceftriaxone was 5 µL. The analyte was separated by a gradient elution at 45 °C, using a flow rate of 0.3 mL/min. The gradient was as follows: 0–0.5 min, 95% A; 0.5–2.5 min, 95–10% A; 2.5–4.0 min, 10% A; and 4.0–4.2, min 10–95% A. Multiple reaction monitoring (MRM) scan type in positive mode was used for the mass spectrum. The transitions of m/z 555.1→396.1 for ceftriaxone and 476.2→432.2 for ertapenem were used. The best-fit weighing was used to calculate the slope, intercept, and correlation coefficient of the linear regression equation. The linear range of the assay is 1–64 mg/L.A modified method was used to assay ceftriaxone. Briefly, 20 μL of thawed sample was added to 880 μL of water and 100 μL of ertapenem at a concentration of 320 ng/mL as the internal standard. The samples were mixed by vortexing for 10 s before injection. The LC-MS/MS system consisted of an Exion UHPLC  with a Kinetex 100 × 2.1 mm, a 5-μm EVO C18 100 Å column , and a QTRAP24) was derived by integrating the best-fit concentration-time profile with respect to time. The simulated concentration-time profiles were considered acceptable if the best-fit maximum concentrations and half-lives were both within 20% of target values.To characterize the pharmacokinetics, a one-compartmental model with zero-order infusion input was fitted to the observed drug concentration-time profiles using ADAPT 5 . The areConcurrent simulations of 3 clinically relevant antibiotic exposures were experimentally validated in a pre-clinical infection model. This framework could advance the field of antimicrobial pharmacokinetics/pharmacodynamics, and facilitate the in vitro efficacy of additional antibiotic combinations to be investigated against different pathogens. Future studies will extend the framework to four or more agents with different elimination half-lives.