Pure self-compacting concrete has many disadvantages, such as early shrinkage and cracking. The addition of fibers can effectively improve the properties of resistance to tension and cracking of self-compacting concrete, thereby the effect of improving its strength and toughness can be achieved. Basalt fiber is a “new green industrial material” that has unique advantages, such as high crack resistance and being lightweight compared with other fiber materials. In order to study the mechanical properties and crack resistance of basalt fiber self-compacting high-strength concrete intensively, the self-compacting high-strength concrete of C50 was designed and obtained using the absolute volume method with multiple proportions. Orthogonal experimental methods were used to study the influence of the water binder ratio, fiber volume fraction, fiber length, and fly ash content on the mechanical properties of the basalt fiber self-compacting high-strength concrete. Meanwhile, the efficiency coefficient method was used to determine the best experiment plan , and the effect of fiber volume fraction and fiber length on the crack resistance of the self-compacting high-performance concrete was investigated using improved plate confinement experiments. The results show that (1) the water binder ratio had the greatest impact on the compressive strength of basalt fiber self-compacting high-strength concrete, and as the fiber volume fraction increased, the splitting tensile strength and flexural strength both increased; (2) there was an optimal value for the effect of the fiber length on the mechanical properties; (3) with the increase in fiber volume fraction, the total crack area of the fiber self-compacting high-strength concrete significantly decreased. When the fiber length increased, the maximum crack width first decreased and then slowly increased. The best crack resistance effect was achieved when the fiber volume fraction was 0.3% and the fiber length was 12 mm. Therefore, basalt fiber self-compacting high-strength concrete can be widely used in engineering fields, such as national defense construction, transportation, and building structure reinforcement and repair, due to its excellent mechanical and crack resistance properties. Self-compacting concrete offers numerous advantages, including high fluidity, uniformity, stability, and the ability to fill template space without requiring external vibration during pouring. It can flow and fill the desired space under the action of its weight. However, in the early stages, it will produce a series of microcracks, which will lead to stress concentration when the concrete is subjected to external loads, thereby reducing the strength of the concrete ,2,3,4. IThe workability and mechanical properties of concrete can be affected by fiber type, length, diameter, doping method, and dosage. Previously, research was often limited to the workability of fiber-reinforced concrete, such as the influence of fiber distribution on concrete fluidity and the influence of fiber length on concrete cohesion. Furthermore, mechanical properties are important in terms of whether materials or structures can meet the usage requirements, and thus, many experts have started to study the impact of various fibers on the basic mechanical properties of concrete ,11,12. MIn summary, basalt fiber not only has the performance of other fibers, such as steel fiber and polypropylene fiber, but is also a new type of green building material. Therefore, it is necessary to conduct thorough research on the mechanical properties and crack resistance performance of basalt fiber self-compacting high-strength concrete. It is worth noting that the research on the crack resistance performance of basalt fiber self-compacting high-strength concrete is not yet mature, and the idea of combining innovation was used to comprehensively apply mathematical combination theory to orthogonal design experiments under multiple factors and levels, as well as the efficacy coefficient method to determine the optimal mix ratio in experimental research, which could improve the scientificity and rationality of experimental research. Therefore, the results of this research can provide reference values for future research on the application of basalt fiber self-compacting high-strength concrete in practical concrete structures, such as pavement, bridge decks, and building structure reinforcement and repair.When using cement, the main consideration is to ensure the early fluidity of freshly mixed mortar and the long-term stability of the later hardening of the slurry. This experiment used P•O 42.5 R ordinary Portland cement , as shown in Coarse aggregate has a significant impact on the physical and mechanical properties and durability of self-compacting concrete. When preparing self-compacting concrete, it is advisable to use hard and rough-surfaced crushed stone as the coarse aggregate with a maximum particle size of less than 25 mm to ensure good bonding strength between the aggregate and the cement slurry. The experiment used crushed stones with a continuous grading of 5–20 mm, as shown in The sand content has a significant impact on self-compacting concrete. If coarse sand is used, it is not conducive to the cohesion of the mixture; if fine sand is selected, it will increase the water required for the mixture, thereby reducing the workability of the concrete. Therefore, sand is usually chosen, where the sand grade is divided into grades Ⅰ, Ⅱ, and Ⅲ grade; choosing grade Ⅱ sand can not only ensure the fluidity of the mix but also reduce the water demand of the concrete mix. This test used the grade Ⅱ sand, as shown in 3 (produced at the Harbin Third Power Plant), as shown in For high-strength self-compacting concrete, the incorporation of a certain amount of mineral admixture is beneficial to improve the compactness and workability of concrete, while the combination of mineral admixture and cement can enhance the late strength and durability of concrete. This experiment used class I fly ash with a density of 2200 kg/mTo achieve high flowability, gap permeability, filling ability, and high stability of self-compacting concrete, admixtures are added. The selection requirements of additives are as follows: good compatibility with cement, high water-reducing ability, and a retarding effect. This experiment used a polycarboxylic acid high-performance water-reducing agent , as shown in This experiment used three different lengths of short-cut basalt fibers, as shown in This study adopted the absolute volume method for the mix design of self-compacting high-strength concrete with a level 1 performance. According to the relevant provisions of the “Technical specification for the application of self compacting concrete” (JGJ/T283-2012) , the spegM:(1) The weight of coarse aggregate per unit volume g—apparent density of the coarse aggregate (kg/m3).ρgV of the coarse aggregate per unit volume is determined according to the self-compacting performance class of the concrete in accordance with gV = 0.30 m3 was used.The absolute volume mV:(2) Mortar volume sV and mass sM per unit volume:(3) The sand volume s—the volume fraction of sand, taken as 0.42~0.45;ϕs—apparent density of sand (kg/m3).ρpV:(4) Slurry volume bρ:(5) Apparent density of cementitious materials m—ρ3);apparent density of admixtures (kg/mc—ρ3);apparent density of cement .(6) Preparation strength of self-compacting high-strength concrete:cu,k—the standard value of concrete cube compressive strength, where our test took the design strength of 50 MPa;fδ—standard deviation (6.0 was taken as the standard deviation).(7) Water/binder ratio:b—weight of cementitious material in a unit volume of concrete (kg);mw—water weight in a unit volume of concrete (kg);mβ—unit volume of concrete admixture as a percentage of the mass of the cementitious material (%);ce—the 28 d measured compressive strength of cement (MPa), which can be taken as 1.1 times the cement strength value when it is unknown;fγ—the cementation coefficient of mineral admixture; fly ash (β ≤ 0.3) can be taken as 0.4.bm:(8) Mass per unit volume of cementitious material a—the volume of air introduced into a unit volume of concrete (L), we took Va to be 15 L;Vw—we used 1000 kg/m3.ρmm, the mass of cement mc, and the mass of water wm:(9) The mass of mineral admixture per unit volume (10) The dosage of additives can be calculated using the following formula:ca—mass of the admixture in a unit volume of concrete (kg);mα—admixture per unit volume of concrete as a percentage of the total cementitious material (%).Through theoretical calculations and repeated trial formulations, the C50 self-compacting high-strength concrete ratio was obtained, and the specific parameters are shown in 4) orthogonal table was selected for the orthogonal test based on the factor levels, as shown in Orthogonal experimentation is a design method that uses mathematical combination theory to study the situation of multiple factors and levels. This method involves selecting representative test points from comprehensive tests through orthogonality. There are many factors that affect the strength of concrete, such as cement strength, aggregate particle size, admixtures, mineral admixtures, and curing temperature. This study considered the water binder ratio , fiber volume fraction , fiber length , and fly ash content  as the main influencing factors, denoted as A, B, C, and D, respectively. Three levels of factors were taken for each experimental factor, and the factor level table is shown in We conducted tests in accordance with relevant concrete specifications ,46, inclAfter the fiber concrete was mixed, it was loaded into the mold, the surface was smoothed, and the concrete was placed in a 20 ± 5 °C environment. After 24 h of curing, the mold was removed and the test blocks were numbered. Then, the test blocks were placed in a curing box, controlled at a temperature of 20 ± 3 °C, and the relative humidity was controlled to be not less than 95%. After 28 days of curing, the test pieces were taken out and tested sequentially. The size and number of test pieces required for each test are shown in The compressive strength test of the basalt fiber self-compacting high-strength concrete adopted a screen display hydraulic pressure testing machine, where the testing equipment is shown in The loading steps for this experiment were as follows:(1) We took out the specimen whose maintenance age reached 28 d and wiped the surface dry.(2) The pressure-bearing surface of the test piece was placed perpendicular to the top surface during molding on the lower pressing plate. The center position of the test piece was aligned with the center of the lower pressing plate. We started the testing machine, and when the upper pressing plate was close to the test piece, we pressed the ball seat to ensure that it evenly touched the test piece.(3) In this study, the strength grade of the concrete was C50, the test loading was continuous, and the loading rate used was 0.5~0.8 MPa per second.(4) When the specimen was deformed, the accelerator of the testing machine was controlled until the specimen is damaged, and then the load should be recorded. The compressive failure morphology of the specimen is shown in (1) Calculation of the compressive strength of concrete:cu—compressive strength value (MPa);ƒF—destructive load value (N);2).A—pressure-bearing surface area (mm(2) The compressive strength value met the following requirements:① The result was accurate to 0.1 MPa.② The strength value of this group was the average value of three specimens.③ If the maximum or minimum value of the test block was compared with the middle value and one of the extremum values varied from the middle value by 15%, the middle value was taken as the compressive strength value; if both the extremum values varied by more than 15% from the middle value, the group results were invalid.④ This test selected the dimension side length of a 100 mm non-standard cube specimen, and thus, the results were multiplied by the size conversion factor of 0.95.The results of the experimental data are listed in From As the fiber volume fraction increased, the compressive strength first increased and then decreased. When the volume fraction was 0.2%, the maximum strength reached 55.23 MPa, and a turning point occurred. When the fiber volume fraction was 0.3%, the strength decreased by 1.5%, indicating that the optimal fiber volume fraction affected the 28 d compressive strength of the fiber self-compacting high-strength concrete. The fiber length also had an impact on the compressive strength of concrete, when the fiber length increased from 6 mm to 12 mm, the 28 d compressive strength showed a slow growth trend, but when the fiber length was 18 mm, the compressive strength slightly decreased, indicating that adding too long fibers had an adverse effect on the compressive strength of concrete.The influence of fly ash content on the compressive strength was relatively small, and the 28 d compressive strength of basalt fiber self-compacting high-strength concrete slowly increased with the addition of the fly ash content.1B2C2D3.From The splitting tensile strength testing equipment for basalt fiber self-compacting high-strength concrete was the same as the compressive strength, but it was necessary to place cushion blocks and strips on and below the pressure-bearing plate of the press. The cushion blocks were made of steel material with a radius of 75 mm, the width of the cushion strips was 20 mm, and the thickness was 3–4 mm. The lengths of the cushion blocks and strips should not be less than the side length of the test piece, and the cross-sectional dimensions are shown in The specific test steps were as follows:We took out the specimens with a curing age of 28 days and wiped their surfaces clean. Then, we placed the test piece in the center of the lower pressing plate of the testing machine and aligned the cushion block and strip with the centerline of the upper and lower surfaces of the test piece. Then, the testing machine was started, and we maintained continuity in the loading process, where it was controlled between 0.05 and 0.08 MPa/s. When the specimen was about to break, we adjusted the throttle until the specimen broke and recorded the load value at this time. The splitting tensile failure morphology of the specimen is shown in (1) The formula for the concrete splitting tensile strength is as follows:ts—splitting tensile strength value (MPa);fF—failure load value (N);2).A—splitting surface area (mm(2) The splitting tensile strength value met the following requirements:① The result was accurate to 0.01 MPa;② The value requirements were the same as the compressive strength;③ This experiment selected non-standard cubic specimens with a side length of 100 mm, and the results were multiplied by a size conversion factor of 0.85.The experimental data results are listed in From the test results in 1B3C2D2.From The bending strength test of the basalt fiber self-compacting high-strength concrete was conducted using a screen display hydraulic universal testing machine, where the bending test device is shown in The specific test steps were as follows:We removed the specimens after a curing period of 28 days and dried their surfaces. Then, we selected the side of the specimen during molding as the testing surface, placed the specimen according to the device diagram, and installed it with a deviation of no more than 1 mm on the left and right. We ensured that the cylindrical contact surface was stable on the support and testing surface.When applying the load, it was necessary to accelerate uniformly and continuously, which was controlled to be between 0.05 and 0.08 MPa/s. When the specimen was damaged, the throttle was controlled until the specimen was completely damaged, and then the load value was recorded. The flexural failure morphology of the specimen is shown in (1) If the fracture position of the lower edge of the specimen is between two concentrated load action lines, the flexural strength is calculated as follows:f—flexural strength value (MPa);fF—failure load value (N);L—span between supports (mm);h—section height (mm);b—section width (mm).(2) The flexural strength value met the following requirements:① The result was accurate to 0.1 MPa.② If the fracture position of one specimen was not between the two concentrated loads, the results of the other two specimens were used for the strength value. If the difference between these two measured values was less than 15% of the smaller value, the average value of the two specimens was taken as the flexural strength of the group. Otherwise, the results were considered invalid.③ The selected size for this experiment was 100 mm × 100 mm × 400 mm. The result of a 400 mm non-standard specimen was multiplied by a size conversion factor of 0.85.The experimental data results are listed in From 2B2C2D3.According to According to the efficacy coefficient method, the overall evaluation of the performance indicators of basalt fiber self-compacting high-strength concrete was carried out. Based on the results of the previous mechanical performance tests, the corresponding efficacy coefficients and total efficacy coefficients d of each assessment indicator were calculated to obtain the optimal mix proportion of basalt fiber self-compacting high-strength concrete with a comprehensive performance.id , and each efficacy coefficient id is the ratio of the indicator value to the optimal indicator value of the group’s experimental results. The total efficacy coefficient d is used to represent the advantages and disadvantages of m assessment indicators. The larger d is, the more favorable the efficacy of the group of experiments on m indicators.The efficacy coefficient of each assessment indicator is d = 0.988 of test BF-2 was the highest, and the corresponding test condition was A1B2C2D2. From the magnitudes of the range R and K values in 1B2C2D3. In summary, the optimal experimental plan for the comprehensive performance of the basalt fiber self-compacting high-strength concrete was as follows: a water binder ratio of 0.3, basalt fiber volume ratio of 0.2%, fiber length of 12 mm, and fly ash content of 30%.From This study selected an improved plate constraint method, namely, the knife-edge-induced constraint method. Based on the testing results of the mechanical properties of the basalt fiber self-compacting high-strength concrete in the early stage, the optimal mix ratio was obtained as A1B2C2D3. Therefore, under the conditions of a water binder ratio of 0.3 and a fly ash content of 30%, the early crack resistance performance of the C50 basalt fiber self-compacting concrete with basalt fiber volume ratios of 0.1%, 0.2%, and 0.3% and basalt fiber lengths of 6 mm, 12 mm, and 18 mm was studied.The test mold used for the edge induction constraint method was an 800 mm × 600 mm × 100 mm steel mold welded with channel steel on all four sides and embedded with bolts on the bottom plate. The mold was equipped with seven crack inducers, which were parallel to the short side of the mold. The bottom plate was laid with steel plates (plate thickness > 5 mm), and a plastic film was placed on top of it as an isolation layer. The experimental setup is shown in The test steps were as follows:We applied template oil evenly on the inside and bottom of the mold, poured the mixed self-compacting concrete into the mold, leveled the concrete, and the surface was slightly higher than the mold frame. The curing conditions of the specimen were as follows: temperature 20 ± 2 °C and relative humidity 60 ± 5%.After the specimen had formed for 30 min, we immediately adjusted a fan to blow directly onto the surface of the specimen so that the wind direction was parallel to 100 mm above the center of the specimen surface and adjusted the wind speed to 5 ± 0.5 m/s along the blade direction.After 24 h, we identified the cracks on the specimen, measured the lengths of the cracks with a steel ruler, and took the straight distance between the two ends of the crack as the crack length. When there were two cracks on a knife edge, the lengths of the two cracks were added together to convert them into one crack.The maximum width of each crack was measured using a reading microscope that was 100 times the width of the crack.When measuring the development of cracks after 24 h, the main tests were the number of cracks, maximum crack width, and total crack area. Based on the above test results and crack reduction coefficient as evaluation indicators, we explored the crack resistance effect of the fiber-reinforced self-compacting concrete.(1) Average cracking area per crack:(2) Number of cracks per unit area:(3) Total cracking area per unit area:(4) Crack reduction coefficient:i—maximum width of the i-th crack (0.01 mm);ωi—length of the i-th crack (0.01 mm);lN—total number of cracks (pieces);2);A—plate area ;b—number of cracks per unit area (0.1/m2/m2);c—total cracking area per unit area ;Amcr—nominal total area of cracks in specimens without fibers (mm2).AThe experimental data results calculated based on the above formula are listed in From η, with the increase in fiber volume fraction, there was a continuous growth trend, and when the fiber volume fraction was 0.3%, η ≈ 1. Early cracks in concrete specimens were almost invisible. From the above analysis of results, it can be concluded that the addition of basalt fibers could improve the generation of cracks in cement-based materials. This was due to the fiber adsorbing a large amount of cement slurry. This can improve the gripping force between fibers and concrete, thereby enhancing the interfacial adhesion of the fiber matrix, leading to the fibers being able to fully suppress concrete cracking.According to the variation pattern of the total crack length in 2, which was 58.7% lower than the benchmark concrete and the crack reduction coefficient η reached approximately 0.6; the self-compacting high-strength concrete specimens with fiber lengths of 12 mm and 18 mm were added, and the total cracking area decreased by 83.5% and 92.7%, respectively, with a crack reduction coefficient η ≈ 1. Overall, the addition of basalt fibers of different lengths significantly improved the crack resistance performance of self-compacting high-strength concrete. From the experimental phenomenon, it can be observed that excessive fiber length also had a certain adverse effect on concrete cracking. Therefore, there was an optimal range of fiber length effects on the cracking performance of the self-compacting concrete.As shown in Through experimental research on the basic mechanical properties and crack resistance performance of basalt fiber self-compacting high-strength concrete, the main conclusions were as follows:(1) The fiber volume fraction was the main factor that affected the compressive and flexural strengths of the self-compacting high-strength concrete. When an appropriate amount of basalt fiber material was added to the self-compacting high-strength concrete, it significantly improve the compressive and flexural strength of the concrete. However, when the fiber content exceeded or is less than the appropriate amount, it reduced the compressive and flexural strength of the concrete.(2) The fiber length was the main factor that affected the splitting tensile strength of the self-compacting high-strength concrete. When a suitable length of basalt fiber material was added to the self-compacting high-strength concrete, the splitting tensile strength of the concrete was significantly improved. However, when the fiber length exceeded or was less than the appropriate length, the splitting tensile strength of the concrete was reduced.(3) There was an optimal value or range for the influence of fiber length and fiber volume ratio on the performance of concrete.(4) Adding appropriate fiber length and fiber volume fraction could effectively suppress the spread and penetration of crack width, thereby improving the plasticity and toughness of the self-compacting high-strength concrete.The above conclusions are basically consistent with the results found in the literature ,7,22,35,


This study established a comprehensive framework for evaluating the lifetime performance of precast prestressed concrete frames exposed to chloride environments. The proposed analytical framework enabled a scientifically grounded and rational assessment of both the service life and residual load-carrying capacity of precast prestressed concrete frames in chloride environments. It further served as the foundational basis for making informed decisions regarding the repair and maintenance of pertinent structures. Based on Fick’s second law, this evaluation framework established the probability distribution of the corrosion initiation time and cracking time of reinforced concrete structures due to corrosion expansion in a chloride environment. Additionally, based on the fragility analysis model and results of a precast prestressed concrete frame in a chloride environment, a practical method for evaluating the time-varying seismic performance of the precast structure considering the influence of corrosion was proposed. Furthermore, by employing the path probability model and reliability theory, time-varying reliability models were proposed to predict the three limit states of the precast prestressed concrete frame. According to the analysis results of a four-story planar frame, it could be seen that the corrosion initiation time and normal service limit state were highly sensitive to the chloride ion diffusion coefficient of the composite layer in precast concrete structures. Compared to cast-in-place structures, the presence of a composite layer in precast concrete structures could lead to more severe degradation of the time-varying seismic performance of the precast prestressed concrete frame. The corrosion of reinforced concrete structures leads to a notable decline in the mechanical properties of the reinforcing steel, as well as a reduction in the bond strength between the reinforcement and concrete. In recent years, researchers worldwide have conducted extensive experimental investigations into the mechanical properties of corroded steel reinforcement ,2,3. TheRebar corrosion leads to a reduction in the cross-sectional area and mechanical property degradation, resulting in a deterioration of the steel–concrete bond strength, as well as the occurrence of cracking and potential spalling of the concrete cover. These combined effects contribute to a degradation in the seismic performance and a shift in the failure modes of the structure. Yang et al. ,9 conducPresently, experimental studies on corroded concrete structures often concentrate on specimens with specific corrosion ratios, potentially limiting the representation of the structure’s complete lifetime degradation process. Additionally, due to the considerable uncertainty associated with seismic forces, employing simple cyclic loading may not offer a comprehensive assessment of the structure’s seismic performance. Consequently, scholars have introduced seismic vulnerability analysis methods to provide a holistic evaluation of structural seismic performance . Choe etSome scholars have conducted research on prediction methods for corroded materials or structures using statistical or machine learning approaches. Weyers proposed a model to estimate the service life of corrosion protection systems, and the model consisted of three serial phases . DarmawaOver the past decades, research on the seismic performance of precast prestressed concrete frame structures has been conducted worldwide, including theoretical analyses and cyclic loading/vibration table tests ,18,19,20The corrosion of steel reinforcement is one of the significant factors leading to the degradation of concrete structure performance . Figure To construct a time-dependent reliability analysis model based on reliability theory, it is imperative to initially ascertain the time-varying probability models for the structure at each corrosion stage. Subsequently, predictive time-varying models for the three limit states of precast prestressed concrete frame structures can be established using path probability models. These predictive time-varying models for the three limit states encompass time-varying reliability models for the rebar depassivation state, time-varying reliability models for the normal service limit state, and time-varying reliability models for the load-bearing capacity limit state under varying performance level requirements. The specific framework is illustrated in Z, is defined as the difference between the resistance R against “failure” and the environmental load F, i.e., Z = R − F. The probability of structural failure fP is defined as the maximum target probability targetP, and is represented as follows:When employing probabilistic statistical methods for the design calculation of the lifetime of a structure, the structural performance function, denoted as F is Ff(f) and the cumulative distribution function is FF(f), the probability density function of R is Rf(r), and the cumulative distribution function is RF(r). If the variables F and R are independent of each other, then the probability of structural failure fP is:Assuming the probability density function of Or,β is the reliability index, indicating the acceptable level of failure for various limit states of the structure.For a normal distribution, the failure probability can be expressed as:c(x)) reaching the critical concentration that induces rebar corrosion at the depth of the protective layer. In other words, the surface chloride ion concentration on the rebar reaches a threshold (crc). Consequently, the resistance R against this “failure” is represented by the thickness of the concrete protective layer x. The environmental load serves as the driving force for chloride ion migration within the concrete. Therefore, the probability of structural failure fP in this phase can be expressed as:According to the aforementioned definition, when calculating the service life of a concrete structure at the corrosion initiation stage, the state of “failure” is defined as the chloride ion concentration (crw) on the surface of the component is used as the criterion for structural failure, the probability of structural failure fP can be expressed as:At the corrosion propagation stage, if the critical crack width  will be employed to formulate a time-dependent reliability model for the ultimate limit state of bearing capacity, tailored to the varying performance level requirements during the corrosion failure stage.At the corrosion failure stage, the probability of structural failure varies due to different requirements for structural performance levels. In this phase, a time-dependent probability model for the ultimate limit state of bearing capacity will be established based on Equation (7). According to Equations (2) and (3), it can be observed that the limit state equation for concrete durability assessment in a chloride environment involves highly nonlinear and complex partial derivatives, making the solution of high-order equations a formidable task. The application of direct integration methods is particularly challenging in this context. Currently, the Monte-Carlo simulation is one of the most effective methods for conducting reliability assessments of complex structures.t) and depth (x) from the concrete surface can be calculated using Equation (8).sC represents the surface concentration of chloride ions in concrete, erf(⋅) stands for the error formula, and D denotes the diffusion coefficient of chloride ions.The research suggests that, among various chloride ion erosion mechanisms, diffusion plays a notably more significant role. The diffusion of chloride ions in concrete is commonly modeled by Fick’s second law ,26. Collek, lk, and ck represent the modification coefficients for the environmental influence, the testing method, and the curing conditions, respectively. D0 stands for the reference chloride ion diffusion coefficient at a concrete age of t0.Based on the classical diffusion theory, the Duracrete model  not onlyChloride ions continuously infiltrate into concrete, gradually accumulating on the surface of the steel bars. When the chloride ion concentration on the surface of the steel bars reaches a critical level, corrosion of the steel bars initiates. This signifies the onset of the corrosion progression stage, which persists until corrosion-induced cracks ultimately reaches the critical crack width. This denotes the end of the corrosion progression stage. Generally, steel corrosion includes two forms: uniform corrosion and non-uniform corrosion ,30,31.t after corrosion initiation, the remaining cross-sectional area of the steel bar can be determined using Equations (10)–(12).sd(t) represents the remaining diameter of the reinforcing bar at time t, sd0 is the initial diameter of the reinforcing bar, λ is the corrosion rate of the reinforcing bar, corT is the start time of the corrosion of the reinforcing bar, and endT is the end time of the corrosion of the reinforcing bar.Uniform corrosion leads to a reduction in the diameter of the steel bar. At time cori). Generally, the average corrosion rate of the reinforcing bars can be determined using Equation (13) [Because of the generation of corrosion current during the corrosion process for the reinforcing bars, most corrosion models are predicated on the corrosion current density (ion (13) .(13)λ=0cori(t) represents the corrosion current density at time t.Sung et al.  proposedcor,i0 represents the corrosion current density at the beginning of corrosion, and w/c stands for the water–cement ratio.Based on the experimental results of Liu et al. , Vu et aP(t) represents the depth of the pitting corrosion, typically calculated by adjusting the uniform corrosion depth, as shown in Equation (21).Under the erosion of chloride ions, steel bars will also undergo non-uniform corrosion , which first leads to the appearance of corrosion expansion cracks in the concrete at the site of severe non-uniform corrosion. According to the investigation by Val et al. , the geoω represents the crack width (mm) and K is the fitting parameter.This study employs the model provided in reference  to prediRelying solely on pseudo-static tests and related numerical simulations may not comprehensively reflect the response of structures under seismic action. Therefore, this study employs the incremental dynamic analysis (IDA) method to conduct nonlinear dynamic time history analysis on prestressed concrete-assembled integral frames with varying degrees of corrosion. By statistically analyzing the IDA data, seismic vulnerability curves for the structures are derived, allowing for the assessment of the time-dependent seismic performance of prestressed concrete-assembled integral frames.a as the seismic intensity indicator and utilizes the maximum inter-story drift angle (maxθ) as the structural damage indicator. In accordance with [maxθ = 0.5%), immediate occupancy , life safety , and collapse prevention .This study, referencing , employsnce with ,39, fourTo accurately conduct earthquake vulnerability analysis and comprehensively capture the structural response under seismic forces, it is imperative to establish precise and efficient numerical models. In pursuit of this objective, a multi-scale modeling method of “material–component–structure” is proposed, as illustrated in 2, and the roof floor live load was 7.0 kN/m2. The live load was taken as 2.0 kN/m2. The specific construction and reinforcement details are shown in This study selected a four-story precast prestressed concrete frame structure as the case study, as selected in the paper by Yang et al. . The buiReferring to the relevant literatures, the input parameters adopted in this study are shown in η) was determined using Equation (24). After entering the corrosion progression stage, the cumulative probability density curve of corrosion expansion cracks reaching the critical crack width is shown in A0 represents the original cross-sectional area of the uncorroded steel reinforcement.In this study, a critical crack width of 0.2 mm was utilized as the endpoint for the corrosion progression stage. According to previous studies, the duration of the corrosion progression stage is relatively short compared to the entire service life of concrete structures. Typically, following the onset of the corrosion initiation stage, concrete spalling due to corrosion-induced expansion occurs within a short period of time. Therefore, in this study, Equation (14) was used for the calculation of the corrosion ratio during both the corrosion progression stage and corrosion failure stage. Statistical analysis was performed using Monte-Carlo simulation, and the simulation was implemented using MATLAB software, as illustrated in η) under different performance level requirements were formulated, as shown in Equations (25)–(28). Here, FE denotes frequent earthquakes, DBE stands for design basis earthquakes, and MCE represents maximum credible earthquakes. In subsequent analyses, the reliability index of the structural ultimate limit state, under varying conditions, would be determined based on the failure probability models presented in Equations (25)–(28).A schematic diagram of the multi-scale vulnerability analysis model is shown in t, the corrosion can only occur within the interval [0, t). Otherwise, the event probability is zero. By dividing the interval [0, t) into n sub-intervals, (n − 1) paths are formed. For each path, it is assumed that the corrosion initiation period ends at time it and enters the corrosion progression period, with corrosion progressing over the remaining time. All paths are mutually exclusive, and according to the law of total probability, the contributions of each path can be summed to calculate the corrosion level distribution at time t.The degradation process of concrete structures in chloride environments exhibits distinct stages, and each stage has significantly different deterioration models. To improve analysis efficiency, Monte-Carlo simulation can be used to independently calculate the conditional probability of failure at each stage or the conditional probability distribution of each key parameter. Subsequently, the path probability model  is used init represents the moment when the corrosion initiation period ends , the probability density of crack width ω at time t is given as following equation:p(init) is the probability that the corrosion initiation stage  would end exactly at the moment init.Therefore, assuming Similarly, the corrosion ratio distribution at any given moment can be calculated using Equation (30).Based on Equation (30) and In accordance with Equation (30) and in conjunction with The initial corrosion time of reinforcement was highly sensitive to the chloride ion diffusion coefficient. In the composite layer between the precast part and the cast-in-place part, the higher chloride ion diffusion coefficient would lead to early corrosion in the precast prestressed concrete frame, consequently reducing the durability of the structural system.Both the depassivation of reinforcement and the limit state of normal service was highly sensitive to the chloride ion diffusion coefficient in the composite layer. For structures adopting these two limit states as design failure criteria, it was crucial to focus on improving the waterproofing performance of the joint area to extend the service life of the structure.Using the time-dependent reliability model curves of structural capacity limit states under different performance levels, it was observed that the seismic performance of the precast prestressed concrete frame structures gradually decreased with the development of corrosion. The presence of the composite layer led to a more severe deterioration in the time-dependent seismic performance of the precast prestressed concrete frame structure compared to the cast-in-place structure.Based on reliability theory, this study established a framework for evaluating the lifetime performance of a precast prestressed concrete frame in chloride environments. By applying the path probability model, time-varying reliability models for predicting the three limit states of the precast prestressed concrete structure were proposed, and a method for predicting the service life of the structure in chloride environments was developed. An example of a four-story planar frame was analyzed and studied. Based on the analysis results, the following conclusions were drawn:


Proteobacteria) showed statistically significant association with behavioral changes (increase in anxiety). There were no consistent findings with statistical significance for the potential biomarkers . Results of the meta-analysis revealed a significant association between symptoms of negative valence system (including anxiety and depression) and cognitive system  with antibiotic intake (p < 0.05). However, between-study heterogeneity and publication bias were statistically significant (p < 0.05). Risk of bias was evaluated to be high in the majority of the studies. We identified and discussed several reasons that could contribute to the heterogeneity between the results of the studies examined. The results of the meta-analysis provide promising evidence that there is indeed an association between antibiotic-induced gut dysbiosis and psychopathologies. However, inconsistencies in the implemented methodologies make generalizing these results difficult. Gut microbiota depletion using antibiotics may be a useful strategy to evaluate if and how gut microbes influence cognition, emotion, and behavior, but the heterogeneity in methodologies used precludes any definitive interpretations for a translational impact on clinical practice.There are previous epidemiological studies reporting associations between antibiotic use and psychiatric symptoms. Antibiotic-induced gut dysbiosis and alteration of microbiota-gut-brain axis communication has been proposed to play a role in this association. In this systematic review and meta-analysis, we reviewed published articles that have presented results on changes in cognition, emotion, and behavior in rodents (rats and mice) after antibiotic-induced gut dysbiosis. We searched three databases—PubMed, Web of Science, and SCOPUS to identify such articles using dedicated search strings and extracted data from 48 articles. Increase in anxiety and depression-like behavior was reported in 32.7 and 40.7 percent of the study-populations, respectively. Decrease in sociability, social novelty preference, recognition memory and spatial cognition was found in 18.1, 35.3, 26.1, and 62.5 percent of the study-populations, respectively. Only one bacterial taxon (increase in gut  Antibiotics are “miracle” drugs that have saved the lives of countless humans suffering from infectious diseases. However, the side-effects of these drugs are not fully known. In particular, the relationship between antibiotic intake and onset of neuro-psychiatric symptoms/syndromes such as depression and anxiety has been postulated based on large scale epidemiological studies in humans. An association between antibiotic use and higher risk for depression and anxiety was found in a nested case–control study in the United Kingdom . A studyThe gut microbiome is comprised of all the microorganisms in the gut including bacteria, viruses, and fungi and the bi-directional communication between the gut and brain mediated via actions of bacteria is referred to as the “microbiota-gut-brain axis” . Gut dysAntibiotics could potentially create the most potent disruption of the microbiota-gut-brain axis, which has significant implications in both basic and translational research . The mecThere has been a spurt of articles linking antibiotics with cognitive, emotional, and behavioral changes in rodents in recent years. However, the results reported in these studies lack consensus and are often contradictory . In thisA dedicated search string was created for three different databases .Strains of rodents used were created to model a specific disease .Details of the behavioral outcomes.Molecular mechanisms potentially associated with changes in behavior after antibiotic-induced gut dysbiosis .Antibiotics used, route and duration of antibiotic administration, time between antibiotic administration, and behavioral assessment.Rodent species, strain, sex, and age.Some studies described results of experiments conducted on multiple populations such as those differentiated by mice strains, sexes, age-groups or antibiotics used within the same study. Hence, for the purpose of this review, the unit of analysis is the “population” within an article.The tests included in this review are open field test (OFT), elevated plus maze test (EPM), light–dark box test (L/D), forced swim test (FST), tail suspension test (TST), Morris water maze test (MWM), novel object recognition test (NOR), three-chambered sociability test , and sucrose preference test (SPT). We have provided a brief description of the tests  and theiWe generated a behavioral phenotype  after assessing each behavioral outcome carefully for each study population. Some of the studies utilized multiple tests to study the same phenotype. For example, OFT, EPM, and L/D box test the unconditioned, exploratory behavior of the rodents, which is used to assess “anxiety-like” behavior. If a population was evaluated for the same phenotype using multiple tests, then such population was considered to be positive for said phenotype even if only one of the tests were positive.Risk of bias assessment was conducted by modifying the SYRCLE’s risk of bias tool . The folSummary statistics of the behavioral assessments were usually not provided in the articles selected. We extracted the mean and variance estimates (standard deviation and standard error) from the figures using WebPlotDigitizer version 4.6 online . Data waSubgroup analysis was conducted to evaluate the impact of age at which antibiotic administration was initiated , duration of antibiotic treatment (less than 14  days vs. more than 14  days), number of antibiotics administered (single vs. multiple), and time between antibiotic treatment and behavioral assessment . Publication bias was assessed using Egger’s test .Formal meta-analysis of microbiome data was not conducted because the data were not extractable from the graphs reported in the articles and raw reads were often not available in the public repositories. Hence, we conducted a semi-quantitative analysis to check if the direction of significant changes in gut microbiome  were associated with behavioral changes  using Fisher’s exact test (2 × 2 tables) or Freeman–Halton extension of Fischer’s exact test (3 × 3 or 3 × 2 tables). A meta-analysis of molecular mechanisms was not conducted because these were secondary outcomes and were not part of the search strings.The details of the literature search conducted are presented in n = 31, 42.5%) were tested with a single antibiotic. Oral route of antibiotic administration was by far the most common route of antibiotic administration . Fifty-seven (78.1%) of these populations were comprised of male rodents only, and 10 (13.7%) and six (8.2%) populations were made up of female rodents only and rodents of both sexes, respectively. Antibiotics were administered on an average for 22.4 days (range: 1–150 days). The average time between the last day of antibiotic administration and start of behavioral testing was 14.3 days (range: 0–98 days). None of the articles reported an increase in anhedonia after antibiotic administration  and 7 (9.6%) of these populations, respectively. C57BL/6 J was the most common strain of mice used (34 populations), followed by BALB/C (13 populations). Cocktails consisting of several antibiotics were tested on 42 (57.5%) populations and the rest of the populations (oC without any additives.The average risk of bias score was 3.67 (range: 2–7) out of a possible highest score of 7. Behavioral outcomes and husbandry descriptions  were adequately reported in 48 (100%) and 46 (95.8%) articles, respectively. Randomization, microbiome data availability, baseline characteristics, blinding, and attrition bias were explained in only 54.2, 43.8, 12.5, 29.2, and 31.3% of the articles, respectively. Fecal and cecal contents were sampled in 32 (66.7%) and 16 (33.3%) of the articles, respectively. Storage temperatures or time between sample collection and DNA extraction of fecal/cecal contents was not provided in 25 (52.1%) articles. When provided, fecal samples were stored at −20 or −80Decrease in sociability and social novelty preference was reported in 18.1% (4/22) and 35.3% (6/17) populations, respectively. Increase in anxiety was reported in 32.7% (19/58) populations. Increase in depression-like behavior was reported in 40.7% (11/27) populations. Decreased recognition memory and spatial cognition was observed in 26.1% (6/23) and 62.5% (10/16) populations based on NOR and MWM tests, respectively. Interestingly, a decrease in anxiety was also reported in 17.2% (10/58) of the populations.Antibiotics were administered to mice in the early postnatal phase of life in seven articles . However, the data was usually too scant to evaluate associations between bacterial taxa and changes in behavior.Notably, the data at a behavior-taxa combination were very scant. However, some patterns were still evident. For example, levels of gut ognition . Conversognition . At a ba anxiety . However anxiety . There wLactobacillus spp. However, these studies differed in the dosage of ampicillin used. Gut Firmicutes levels increased after penicillin V administration only in 14 days old male mice, but not in females  gene expression in the hippocampus, circulating levels of IL-6 and IL-1β and serum corticosterone were the three most common molecular mechanisms studied  toward statistical significance in case of time spent in open arm (EPM), and discrimination index (NOR). Sensitivity analysis was conducted by removing outliers but the results of OFT, FST, and TST remained statistically significant. Meta-analysis on the results of male mice administered orally revealed that time in center (OFT), immobility time (TST), and escape latency (MWM) remained significantly associated with changes in behavior, but the results of FST were not significant.Decrease in time spent in center (OFT), increased immobility time during FST and TST and increased escape latency (MWM) were significantly associated with antibiotic administration (p < 0.05) was reported in all the meta-analytic models. There was a significant publication bias (p < 0.05) in the meta-analysis of all the behaviors tested, with the exception of escape latency in MWM.Based on subgroup analysis, number of antibiotics (single vs. multiple), age , days of antibiotic administration (14 days vs. more than 14  days), and time between antibiotic administration and behavioral analysis  did not influence associations between changes in behavior during OFT, FST, and TST and antibiotic consumption. Significant between-study heterogeneity , depression-like behavior (FST and TST), and decrease in spatial cognition (MWM) after antibiotic use were the most outstanding results of this meta-analysis. These results should aid in strengthening the hypothesis that antibiotic-induced dysbiosis can manifest as cognitive and behavioral disturbances in rodents. Meta-analysis of the results of other behavioral tests, although not significant, also favored the hypothesis that antibiotic use can have deleterious effects on cognitive and behavioral functions in rodents. The discrepancy between the results of narrative review and meta-analysis can be explained by the likelihood that the studies were under-powered and there was a high chance of committing type II errors , leadingAlthough these results are promising, caution should be exercised while interpreting these results. A significant publication bias indicates that results were more likely to be published if they were significant. This is consistent with the results of other systematic reviews published on rodent studies . Under-rProteobacteria in the gut after antibiotic intake and an increase in anxiety was the most significant association between gut bacteria and behavioral changes. Proteobacteria  launched the Research Domain Criteria (RDoC) in 2013 . The RDoThis study was limited by the various methodological variations, biases, incomplete reporting, and heterogeneity of the rodent populations studied. We limited search to the English language and did not search gray literature such as dissertations or preprint repositories, which might have led to the exclusion of some studies. We did not conduct a meta-analysis of the molecular mechanisms because these were not part of the original search string. Some of the terms such as anxiety or depression might not have direct translational value and this topic is debated among neuroscientists . HoweverThe results of this systematic review meta-analysis provide some evidence that antibiotic-induced gut dysbiosis can indeed cause some behavioral changes in rodents. However, the heterogeneity between study populations, behavioral testing and microbiome evaluation makes it difficult to generalize these results. We are still far from establishing a model of antibiotic-induced gut dysbiosis and behavioral change in rodent models that can consistently reproduce the same results.The original contributions presented in the study are included in the article/SHa: conceptualization, conducting review, data analysis, and writing. SHw: writing. JC: conceptualization and writing. All authors contributed to the article and approved the submitted version.This research was supported by startup funds provided by the University of Nebraska at Omaha and the Nebraska Food for Health Center to JC. Research reported in this publication was supported by the Office of the Director, National Institutes of Health of the National Institutes of Health under Award Number K01OD030514 awarded to JC. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Multiplex stool polymerase chain reaction (PCR) panels offer rapid comprehensive testing for patients with infectious diarrhea. We compared antibiotic utilization among hospitalized patients with suspected infectious diarrhea who underwent diagnostic testing with either a stool culture or stool PCR panel. No significant differences in antibiotic utilization were identified. However, evidence suggests that the low proportion of stool cultures that grow pathogenic bacteria and the lower sensitivity associated with this diagnostic test limit its clinical utility. Stool cultures are used for bacterial identification and require 24–96 hours for adequate incubation and microbial growth. Importantly, other etiologic agents of infectious diarrhea, such as viruses and parasites, may not be captured by stool culture. Recently, molecular diagnostic tests, such as multiplex polymerase chain reaction (PCR) panels, have emerged as valuable diagnostic tools given their rapid turnaround time, higher test sensitivity, and ability to detect various pathogens.Pathogen identification plays a critical role in determining appropriate therapeutic measures in patients with suspected infectious diarrhea. Routine diagnostic evaluations traditionally include stool culture. Results from stool PCR testing allow clinicians to promptly adjust therapies, offering the potential for judicious and precise antimicrobial use among patients with suspected infectious diarrhea.With the ongoing emergence of drug-resistant organisms, efforts to enhance antimicrobial stewardship are increasingly essential.We evaluated the impact of multiplex stool PCR testing versus stool culture on the utilization of antibiotics administered for suspected infectious diarrhea in hospitalized adult patients.The study population included hospitalized adult patients at a single quaternary-care center who underwent stool microbiologic testing, either culture or multiplex PCR , for suspected infectious diarrhea. Stool cultures were routinely collected from these patients in the preintervention period (October–November 2021). Stool PCR orders were available in that period but were restricted to gastrointestinal and infectious disease providers. All orders for stool culture in the electronic health record (EHR) were converted to a multiplex stool PCR test in December 2021. The postintervention period included January–February 2022; December 2021 was excluded as a washout. LOT was defined as the total number of days of antibiotic therapy for infectious diarrhea, regardless of how many antibiotics were administered per day. The EHR at our institution is designed such that an indication is required to be selected when ordering antibiotics. When determining DOT and LOT, only ordered antibiotics with an indication for “infectious diarrhea,” “diarrhea,” or “colitis” were included.Primary outcomes included antibiotic days of therapy (DOT) and length of therapy (LOT) for the following antibiotics: ceftriaxone, cefepime, ampicillin-sulbactam, piperacillin-tazobactam, amoxicillin-clavulanic, ertapenem, meropenem, metronidazole, ciprofloxacin, levofloxacin, azithromycin. DOT was defined as the summation of days of each antibiotic administered for infectious diarrhea.2 test, and the incidence rate ratio comparison test were used for continuous variables (DOT and LOT), categorical variables (stool positivity), and incidence rate ratios, respectively. R Studio version 4.1.1 software  was used for statistical analysis. This study was approved under IRB protocol H-50891 at our institution.To compare variables across the pre- and postintervention groups, the Wilcoxon rank-sum test, the χP < .001) in the postintervention group. In the preintervention group, the median DOT and LOT were both 0 days, with ranges of 0–10 and 0–5 days, respectively. In the postintervention group, the median DOT and LOT were both 0 days, with ranges of 0–8 days and 0–5 days, respectively. There was no statistically significant difference in DOT (P = .967) or LOT (P = .993) after the intervention  of 75 patients, compared to negative stool PCR panels in 58 (71.6%) of 81 patients  compared to the postintervention cohort . This may have limited our ability to detect a difference in DOT and LOT after introducing the intervention. This lack of initial antibiotic administration may reflect our institution’s existing culture of excellent antimicrobial stewardship. Furthermore, the study’s small sample size (n = 156) might diminish the generalizability of these findings. Additionally, clinical information, such as patient demographics, severity, and presenting symptoms, was not collected. reflects a similar conclusion. In their retrospective analysis of over 300 patients, they found no significant change in antibiotics between those who received stool PCR (84.9%) compared to stool culture (84.1%). Notably, among patients who received a stool PCR test, those identified as having a viral infection were observed to have a lower rate of antibiotics than patients with bacterial or parasitic infections. Although this second observation was not directly measured in our study, the overall conclusions from Singh et al demonstrated a similar lack of impact on overall antibiotic use with two different stool testing techniques.A study by Singh et al By contrast, in a randomized control trial of 74 patients in the emergency department by Meltzer et al, PCR testing was associated with higher antibiotic utilization compared to traditional or no stool testing among patients with bacterial or parasitic pathogens causing diarrhea. However, the higher antibiotic utilization observed in that particular study likely reflects a rise in appropriate antimicrobial prescriptions informed by PCR detection.However, conclusions from other studies differ from the findings presented here. In a retrospective investigation published in 2019 that included >15,000 patients, stool multiplex PCR panels were associated with significantly lower antibiotic use than traditional stool testing. raise another limitation of the generalizability of our study, which is that we investigated total antibiotic usage rather than appropriate antimicrobial prescription. Future initiatives to examine this issue would include expanding the sample size, including multiple hospitals, comparing patient length of stay, and measuring appropriate antibiotic administration compared to unnecessary antimicrobial usage. Additional efforts could incorporate simultaneous interventions, such as formalized education to all providers ordering stool tests and assessing cost comparisons between tests. Future research investigating the impact of stool PCR testing on antimicrobial use may help inform clinical decision making or the development of clinical decision-support tools within EHRs. As antibiotic stewardship becomes increasingly essential with the advent of drug-resistant pathogens, diagnostic stewardship must be considered in patient evaluation and treatment, including the turnaround time and result sensitivity.The results of the trial by Meltzer et al


Self-assembled H-shaped Lewis acid–base adduct 2d proved to be effective in forming thermally stable host–guest complexes, 2d × solvent, with aromatic hydrocarbon solvents such as benzene, toluene, mesitylene, aniline, and m-, p-, and o-xylene. Crystallographic analysis of these solvent adducts revealed host–guest interactions to primarily occur via π···π contacts between the 4,4′-bipyridyl linker and the aromatic solvents, resulting in the formation of 1:1 and 1:2 host–guest complexes. Thermogravimetric analysis of the isolated complexes 2d × solvent revealed their high thermal stability with peak temperatures associated with the loss of solvent ranging from 122 to 147 °C. 2d, when self-assembled in an equimolar mixture of m-, p-, and o-xylene (1:1:1), preferentially binds to o-xylene. Collectively, these results demonstrate the ability of 1,8-dihydroxy naphthalene to serve as an effective building block in the selective self-assembly to supramolecular aggregates through dative covalent N→B bonds.The new Lewis acid–base adducts of general formula X(nad)B←NC The last decades have witnessed increased interest in the rational design of supramolecular architectures based on the self-assembly of various suitable building blocks ,10,11,121a–e), where nad = 1,8-naphthtalenediolate  to form stable Lewis acid–base adducts with 4,4′-bipyridine  showed a signal at around 29 ppm, which is close to the 11B NMR chemical shift of 1a (δ = 27 ppm in CDCl3) [2a. For the system 4,4′-bipyridine/1b (1:2), two distinct signals at ca. 27 ppm and 7 ppm were observed; the former can be assigned to ester 1b, while the latter is due to the desired Lewis acid–base adduct 2b. In contrast, mixtures of 4,4′-bipyridine with 1c, 1d, and 1e, respectively, showed up-field shifted signals at ca. 12 ppm (1c), 6 ppm (1d), and 4 ppm (1e), indicating the formation of the respective adducts 2c, 2d, and 2e.At the outset, we investigated the ability of our recently prepared boronic esters of general formula R-Bnad  , showing2a–e. The results for 2a, 2b, and 2d are shown in 2a and 2b can structurally be described as double-tweezers. 2a exhibits an almost perfect double-tweezer-shaped structure with nearly planar bipyridine units, while 2b is markedly twisted with a twisting angle of the bipyridine moiety of about 35°. Adduct 2d, on the other hand, is composed of a more H-shaped structure with a nearly planar bipyridine unit (twisting angle ~10°). The bond parameters for all three adducts are similar, with B-N and B-O distances ranging from 1.61 to 1.67 Å and 1.45–1.47 Å, respectively. The central boron atoms in 2a, 2b, and 2d have slightly distorted tetrahedral coordination environments, with O-B-O and N-B-O angles ranging from 111–116° to 102–105°. Unfortunately, it was not possible to obtain suitable single crystals of 2c and 2e from acetone as the solvent. Not only was 2e highly soluble in acetone, but it also slowly degraded to a second product exhibiting a relatively sharp signal in the 11B NMR with a chemical shift of ca. 0 ppm  and average B-O and B-N distances of 1.45 and 1.67 Å, respectively. Notably, 2c × benzene co-crystallizes with two molecules of benzene, both being entrapped via π–π stacking with the 4,4′-bipyridine moiety and C-H…π contacts with both the phenyl and the naphthalene substituents.To confirm our structural assignments, efforts were undertaken to grow single crystals suitable for X-ray analysis from concentrated acetone solutions of 4,4′-bipyridine and see also . This nesee also . However benzene . Similar2c and 2d via a one-pot procedure in excellent yields starting from the respective boronic acids, without the need of preparing the respective esters 1c and 1d ethylene gave— upon reaction with 1,8-dihydroxy naphthalene and 1,4-phenylene diboronic acid in acetone—an orange microcrystalline precipitate, from which single crystals suitable for X-ray analysis could be obtained. The results revealed the compound to be polymeric Lewis acid–base adduct  fashion a. Due to4 (yield 94%) was formed as confirmed by single-crystal X-ray analysis  were heated until clear solutions were obtained. Upon slowly cooling to room temperature, crystalline solids were obtained in isolated yields ranging from 34–81%. In addition to being characterized by 1H NMR spectroscopy and combustion analysis, all compounds were analyzed by X-ray crystallography.Encouraged by the ability of dertaken . 2d was 2d is capable of forming various stable host–guest complexes with all aromatic hydrocarbon solvents used in this study via π–π stacking between the 4,4′-bipyridyl unit of 2d and the respective aromatic solvent. Thus, in benzene as a solvent, 2d × benzene is formed . Interestingly, crystallization experiments in meta-xylene gave two crystallographically distinct single crystals of 2d × m-xylene; the results for one revealed a classical 1:1 host–guest complex  associated with the liberation of the guest were found to be 131 °C and 147 °C, respectively, suggesting stronger host–guest interactions in 2d × toluene, and consistent with the results of DSC analysis (2d × m-xylene), 133 °C (2d × o-xylene), and 136 °C (2d × p-xylene). The slightly higher peak temperatures for 2d × o-xylene and 2d × p-xylene suggest somewhat stronger host–guest interactions compared to 2d × m-xylene, which is supported by DSC measurements , 71 °C (o-xylene), 76 °C (p-xylene), 121 °C (toluene), 139 °C (benzene), and 100 °C (mesitylene). Except for benzene, these values are significantly lower than what was measured for our 1,8-dihydroxy naphthalene-based host–guest complexes 2d × solvent . The obtained crystalline material was collected and analyzed by 1H NMR spectroscopy using DMSO-D6 as the solvent (see 2d for o-xylene (ca. 57%), with an m-, p-, to o-xylene ratio of about 2:1:4, respectively, which is similar to those of the respective catechol-based host–guest complexes reported by Hőpfl and Morales-Rojas [p-xylene appears to be surprising but perhaps can be attributed to kinetic effects during the crystallization process.Based on the results from the host–guest chemistry with es-Rojas . Conside5 and 6 could be obtained from acetone solutions and were characterized by single-crystal X-ray crystallography ethane was employed in reactions with 1,8-dihydroxy naphthalene and various boronic acids. Unfortunately, in none of the cases could host–guest complexes with aromatic hydrocarbon solvents be crystallized and structurally determined. Nonetheless, single crystals of the solvent-free double-tweezers lography a,b.2d × solvent, was prepared via reactions of 4,4′-bipyridine, 1,8-dihydroxy naphthalene, and 3,4,5-trifluorophenyl boronic acid with various aromatic hydrocarbons. SCXRD analysis of these solvent adducts revealed host–guest interactions to primarily occur via π···π contacts between the 4,4′-bipyridyl linker and the aromatic solvents to give 1:1 and 1:2 host–guest complexes, which was confirmed by 1H NMR spectroscopic analysis of the bulk samples. TGA measurements of the bulk samples showed well-defined weight losses at peak temperatures ranging from 122 to 147 °C, which in every case could be attributed to the complete loss of solvent (guest). Self-assembled Lewis acid–base adduct 2d, when recrystallized from an equimolar mixture of m-, p-, and o-xylene (1:1:1), preferentially binds to o-xylene, generating 2d × o-xylene as the major component, similar to what was reported for structurally related catechol-based host–guest complexes [We have demonstrated the ability of 1,8-dihydroxy naphthalene to self-assemble with various aryl boronic acids and 4,4′-bipyridine as a linker to give double-tweezer and H-shaped Lewis acid–base adducts in very good isolated yields by means of N→B bond formation. In addition, a series of host–guest complexes, omplexes . Collect


To determine antibiotic prescribing appropriateness for respiratory tract diagnoses (RTD) by season.Retrospective cohort study.Primary care practices in a university health system.Patients who were seen at an office visit with diagnostic code for RTD.Office visits for the entire cohort were categorized based on ICD-10 codes by the likelihood that an antibiotic was indicated . Medical records were reviewed for 1,200 randomly selected office visits to determine appropriateness. Based on this reference standard, metrics and prescriber characteristics associated with inappropriate antibiotic prescribing were determined. Characteristics of antibiotic prescribing were compared between winter and summer months.P < .01).A significantly greater proportion of RTD visits had an antibiotic prescribed in winter  compared to summer months [standardized difference (SD) = 0.21]. A significantly greater proportion of winter compared to summer visits was associated with tier 2 RTDs , but less tier 3 RTDs . A greater proportion of visits in winter compared to summer months had an antibiotic prescribed for tier 2 RTDs  and tier 3 RTDs . The proportion of inappropriate antibiotic prescribing was higher in winter compared to summer months (72.4% vs 62.0%, Increases in antibiotic prescribing for RTD visits from summer to winter were likely driven by shifts in diagnoses as well as increases in prescribing for certain diagnoses. At least some of this increased prescribing was inappropriate. Respiratory tract diagnoses (RTD) are the most common indication for ambulatory antibiotic prescriptions, up to 50% of which are estimated to be inappropriate.Most antibiotics in the United States are prescribed in the outpatient setting. At least some of the increased prescribing for RTDs in the winter months is likely inappropriate. Because these increases in antibiotic prescribing may drive antibiotic resistance, further understanding of seasonal prescribing patterns is vital to antibiotic stewardship efforts broadly.Seasonal fluctuations in prescribing have been demonstrated with wintertime peaks and summertime nadirs for certain diagnoses, including for RTDs. On a national level, increased total antibiotic use is associated with greater seasonal fluctuations in antibiotic prescribing. As such, seasonal variation in antibiotic prescribing at the individual prescriber level may also be correlated with inappropriate use.Of additional interest is the development of metrics that can serve as proxies for inappropriate antibiotic prescribing in the outpatient setting. For individual prescribers, the proportion of antibiotics prescribed for all RTDs and for the subset of RTDs for which antibiotics are rarely indicated correlates with inappropriate use.The primary objective of this study was to determine the appropriateness of antibiotic prescribing by season. Secondary objectives were to describe seasonal variations in prescribing patterns by antibiotic class and diagnosis and to determine whether seasonal variation in rate of prescribing is associated with inappropriate use and with certain prescriber characteristics.entire cohort.A retrospective cohort study was conducted from July 1, 2016, through June 30, 2017, at 32 primary care practices in the University of Pennsylvania Health System, which included 227 primary care providers. These practices serve a diverse population in urban and suburban settings in southeastern Pennsylvania and southern New Jersey with over 90,000 RTD office visits annually. Office visits were eligible for inclusion if: (1) there was an ICD-10 code for at least one RTD; (2) the patient was ≥18 years of age; and (3) the clinician was either an attending physician or advanced practice provider (APP). Only adults were included because only a minority of prescribers saw children. Although teaching practices were included in this study, only office visits in which a patient was seen primarily by an attending physician or APP were included, given that residents were not present in all practices. Office visits were excluded if there was an infection other than an RTD coded in the same encounter. These resulting office visits are subsequently referred to as the  Each visit occurring during a fall or winter month (October through March) was characterized as winter and during a spring or summer month (April through September) was characterized as summer. Prescriber demographics were collected, and ambulatory care practices were characterized as either teaching or nonteaching depending on whether residents saw patients at the clinic and as either urban or nonurban.Antibiotic(s) prescribed and ICD-10 code(s) for each office visit were collected. Demographics and relevant comorbidities using ICD-10 codes were collected. Charlson comorbidity index for each patient was calculated using methods previously described.1).Each RTD was further characterized by diagnostic grouping  and by prescribing tier based on the likelihood of that diagnosis to require an antibiotic   or intramuscular penicillin prescribed. Sixty prescribers were randomly selected from prescribers with at least 20 RTD visits in the summer months and at least 20 RTD visits in the winter months. Then, 20 office visits for each of these prescribers were randomly selected for a total of 1,200 office visits. Visits were intentionally sampled so that each prescriber had 10 visits in the summer months and 10 visits in the winter months. These office visits are subsequently referred to as the 2).To determine the appropriateness of antibiotic prescribing, clinical documentation and diagnostic testing from each office visit in the random subset were reviewed in the electronic health record (EHR) by at least one member of the research team. Diagnostic criteria for determination of appropriateness were adapted from relevant professional society and public health guidelines  with SD≥0.1 considered a significant difference. Significance for other analyses was reported using Data were analyzed using STATA v15.0 . This study was approved by the Institutional Review Board at the University of Pennsylvania.Over the course of the study period, 95,773 office visits were identified, and 6,146 office visits were excluded because another infection other than an RTD was coded. A total of 89,627 unique RTD visits were analyzed as the entire cohort. Demographic characteristics and comorbidities of patients in the entire cohort and random cohort are shown in Table The frequency of antibiotic prescribing for all RTD visits and by tier and diagnostic groupings for the entire cohort in winter compared to summer months is shown in Table For diagnostic groupings in the entire cohort, a greater proportion of visits with a diagnosis of bronchitis  and sinusitis  occurred in the winter relative to summer months. By contrast, a greater proportion of visits with “other RTDs” was noted in the summer relative to the winter months . Other diagnoses did not vary seasonally. Greater proportions of antibiotic prescribing were observed in the winter relative to summer months for the diagnoses of sinusitis  and “other RTDs” . No seasonal difference in the proportions of antibiotic prescribing for other diagnostic groupings was observed.1. For a majority of prescribers, there was an increase in percent prescribing for RTDs from summer to winter. In linear regression analyses, seasonal change in percent prescribing on an individual prescriber level was most strongly correlated with absolute increase in RTD visits from summer to winter , followed by total winter RTD visits  and percent change in RTD visits .Overall, 182 prescribers in the entire cohort met the inclusion criteria of having at least 20 RTD visits in the summer months and 20 RTD visits in the winter months. A histogram showing the prescribers’ seasonal change in percent prescribing is shown in Supplemental Figure 3. Family medicine specialty, nonteaching practice, nonurban practice, and board certification ≤15 years were associated with a greater increase in percent prescribing from summer to winter months.Associations between prescriber characteristics and seasonal variation in percent prescribing from summer to winter months in the entire cohort are reported in Supplemental Table P < .01). Certain prescriber characteristics were associated with greater inappropriate prescribing, including family medicine specialty, nonteaching practice, nonurban practice, and APP degree .For the random cohort, there was 94% observed agreement and kappa of 0.90 in the determination of the appropriateness of antibiotic prescribing among raters. Overall, the proportion of inappropriate prescribing was 72.4% in the winter months and 62.0% in the summer months   and for all respiratory visits .Seasonal change in percent prescribing was positively correlated with inappropriate prescribing on a prescriber level even after controlling for prescriber characteristics : percent prescribing for tier 3 RTDs, percent prescribing for all RTDs, and seasonal prescribing variance for RTDs. However, the pseudo- By focusing our analysis on RTDs alone, we likely mitigated this effect and consequently saw no substantial shifts in antibiotic classes.We observed no significant changes in prescribing for antibiotics by class from summer to winter months. Though seasonal fluctuations in antibiotic prescribing have previously been shown to be driven by increased prescribing of aminopenicillins and macrolides in the winter months, the observed wintertime increase likely reflects the contribution of seasonal prescribing for RTDs. Decision fatigue may be exacerbated by emotional exhaustion arising from countering patient demand for unnecessary antibiotics. A similar phenomenon has been observed during individual clinic sessions with clinicians prescribing antibiotics more frequently at the end of a clinic session relative to the beginning. In this study, there was a significant association between a clinician’s inappropriate antibiotic prescribing and the difference in their total RTD visits from summer to winter, their percent increase in total RTD visits from summer to winter, and their total number of RTD visits in the winter, suggesting the possibility of decision fatigue. However, additional investigation is needed to understand seasonal variation in clinical decision-making about antibiotics.One possible explanation for the increase in inappropriate prescribing in winter months is decision fatigue, the phenomenon where a person’s ability to make decisions declines in quality after a long period of decision making. As visits for RTDs increase in winter months and clinicians must make more decisions about prescribing antibiotics, the quality of these decisions may deteriorate over time. It is clear that clinicians see a greater number of patients with RTDs in the winter months, and it is also possible that they see more infections where antibiotics are warranted as well. More visits with bacterial infections may, in turn, drive inappropriate prescribing through recency bias. In this study, there was a decrease in tier 3 diagnoses and an increase in tier 2 diagnoses from summer to winter months. These changes could reflect accurate differences in patient presentations, but clinicians may also be primed to expect a diagnosis that may require antibiotics in the winter months and so are more likely to assign a tier 2 RTD instead of a tier 3 RTD. Alternatively, having decided to prescribe an antibiotic a priori, they may adjust their coding to justify the prescription.Another possible contributing factor is recency bias, a cognitive bias that causes decisions to be disproportionately impacted by the most recent events. Anxiety and depression may be expected to peak in the winter months due to the contribution of seasonal affective disorder.Finally, it is possible that individual clinician well-being may play a role in the increased antibiotic prescribing observed in the winter months. A retrospective cohort study found that clinicians’ self-reported level of anxiety and depression was positively associated with proportions of inappropriate prescribing for acute respiratory tract infections. These potential differences in how symptoms are communicated by the patient and perceived by the prescriber could also drive differences in coding more or less specific diagnoses. Additional studies are necessary to investigate the language around patients’ descriptions of symptoms, suggested diagnoses, or requests for antibiotics.In addition to prescriber factors, patient factors may also contribute to increased proportions of antibiotic prescribing in winter months. It is possible that patients’ expression of the number and/or severity of symptoms may influence clinicians’ perceptions of the likelihood of bacterial infection. Similarly, patients may be more likely to specifically appeal for antibiotics in the winter months. Many of these characteristics were also associated with greater inappropriate prescribing in this study that intentionally sampled visits in summer and winter months, specifically family medicine specialty, APP degree, nonteaching practice, and nonurban practice. Additional investigation is needed to determine how prescriber characteristics impact the appropriateness of antibiotic prescribing and how antibiotic stewardship interventions targeted at these specific groups impact antibiotic prescribing.It was previously observed that certain prescriber characteristics were associated with greater inappropriate prescribing, specifically APP degree, family medicine specialty, fewer years in practice, nonteaching practice, and nonurban practice.This study has several limitations. First, it was a retrospective single health-system study, possibly limiting the generalizability of results. Second, RTD metrics and analyses were based on diagnostic codes, which may not be accurate representations of actual diagnoses. Although the determination of appropriateness was based on manual chart review, many of the analyses still depended on diagnostic codes. Third, in determining the association of appropriate prescribing with various characteristics, the small number of prescribers in the random subset precluded multivariate analysis and investigation of the association of different characteristics with each other. Fourth, this study included only adult patients so results should not be applied to pediatric patient populations.In conclusion, there was a greater proportion of tier 2 compared to tier 3 RTDs in winter months; there were greater proportions of inappropriate prescribing overall in the winter months; and variation in prescribing from summer to winter months was positively correlated with inappropriate prescribing at the level of the prescriber. More investigation is needed to determine the factors influencing seasonal variations in diagnosis coding and in antibiotic prescribing patterns. A better understanding of seasonal variation in antibiotic prescribing for RTDs may facilitate antibiotic stewardship interventions to reduce inappropriate prescribing in these settings.Serletti et al. supplementary material