The mutation resulted in a reduced muscle fibre number, in particular in the pectoral abductor, and in a disturbed pectoral fin function. Other MMP derived muscles, such as the sternohyoid muscle and posterior hypaxial muscle were also affected in met mutants. This indicates that the role of met in MMP function and appendicular myogenesis is conserved within vertebrates.The hepatocyte growth factor receptor C-met plays an important role in cellular migration, which is crucial for many developmental processes as well as for cancer cell metastasis. C-met has been linked to the development of mammalian appendicular muscle, which are derived from migrating muscle progenitor cells (MMPs) from within the somite. Mammalian limbs are homologous to the teleost pectoral and pelvic fins. In this study we used Crispr/Cas9 to mutate the zebrafish  Cellular migration is one of the corner stones of the processes that forms the structure and organisation of the multicellular organism and has important implications for development and disease. The migratory muscle progenitor cells (MMPs) are a group of cells which originally reside within the embryonic somite and upon inductive signals the MMPs delaminate from the somite and migrate laterally, giving rise to hypaxial muscle groups –3. MMPs Myf5 and MyoD expression [C-met [The formation of muscle cells in mammals is initiated in the presomitic mesoderm where inductive signals, such as HH and FGF from the midline and surrounding embryonic structures initiates a myogenic programme in the somites and expression of the myogenic regulatory factors  results in the subsequent differentiation of muscle fibres. In the early stages of mammalian somitic compartmentalization, the transcription factor Pax3 is expressed throughout the mesodermal cells in the whole somite . As the pression , 10. Paxpression , 12, in n [C-met , 14. C-mn [C-met . C-met an [C-met –17. The n [C-met . Lbx1 pln [C-met . The RASn [C-met . The MMPn [C-met –23. The n [C-met –27. Foren [C-met , 29. Durn [C-met .The similarities between the appendicular structures limbs and fins are many, including several of the genes that orchestrate their respective developmental processes. The zebrafish pectoral fins are homologous to amniote forelimbs and its muscles are, like in the amniote limbs, derived from MMPs with somitic origin , 31, 32.C-met orthologue met is expressed in various cell types during embryogenesis, including cells in the hypaxial myotome region and the developing pectoral fins [met in myogenesis, using morpholino experiments, indicate that the lack of met leads to disturbed hypaxial and appendicular myogenesis, although met is not needed for the initial specification of these cells [met gene during the migration of MMPs in the formation of pelvic fin and pectoral fin musculature.The zebrafish ral fins . Functiose cells . In thismet during myogenesis, and particularly in the formation of muscles deriving from MMPs, we generated zebrafish strains carrying mutations in the met gene using Crispr/Cas9. Several mutations were identified and versions resulting in frameshifts and early premature stop codons were used to generate F2 generations, which were kept for further analysis , likely due to a combination of non-sense mediated decay and a failure of MMP migration  due to impaired pectoral fin function  expression in adult zebrafish. As expected, the formation of differentiated muscle fibres within the pectoral fins as well as pelvic fins in met-/- mutants was disturbed  , even though the average number of fibres within the adductor was significantly reduced compared to wt siblings i135 [Tg(pax3a:EGFP)i150 [Mutant line used was GFP)i135  and Tg(pGFP)i150 . Zebrafimet zebrafish mutants were generated using methods previously described [met, gRNA targeting exon 2 was synthesized using the sequence CCTTCACTGCGGGGGAACTATCC. One frame-shift mutation was identified carrying a 2 bp deletion (met mutant zebrafish (escribed . In shordeletion . Genotypebrafish .in situ hybridization was performed as described previously [myoD (gene bank accession number: NM_131262.2), myogenin (NM_131006) and pax3a (NM_131277). All comparisons between different expression levels and areas were performed within the same experimental groups.Zebrafish embryos were fixed in 4% paraformaldehyde overnight at desired stages. To prevent pigmentation embryos older than 24 hpf, embryos were reared in 0.003% phenothiourea in embryo medium from 26 ss. Whole-mount eviously  with min2O, and successively cleared in 20% glycerol with 0.25% KOH and 50% glycerol with 0.25% KOH before imaging.To detect cartilage, Alcian blue staining was performed. Zebrafish embryos were fixed in 4% paraformaldehyde overnight and then stored in 100% methanol at −20°C. Embryos were dehydrated and washed in PBT before being transferred to Alcian blue solution  and incubated overnight. Embryos were washed in acidic alcohol , stepwise rehydrated to H5 dpf larvae were fed with 0.0026% Fluoresbrite® YG microspheres 1.00 μm  in embryo medium for 1h, washed extensively and fixed in 4% PFA. Larvae were photographed and the number of fluorescent microspheres in the stomach was counted.Embryos were dechorionated and incubated in 10 mM 5-Bromo-2′-deoxyuridine  in embryo medium from 26 ss to 48 hpf, fixed in 4% PFA overnight, dehydrated in 100% methanol and stored at −20°C until analysis using immunohistochemistry. For brdU detection, a mouse anti-brdU antibody conjugated to Alexa Fluor 555 was used , to increase antibody penetrance embryos were treated with 2N HCl and digested with proteinase k before anti-brdU incubation.Zebrafish embryos at the desired stage were sedated using tricaine mesylate and mounted in 1% low melt agarose and a z-stack was run every 45 min, after 48 hours the experiment was terminated.S1 Movie(MP4)Click here for additional data file.S2 Movie(MP4)Click here for additional data file.S3 Movie(MOV)Click here for additional data file.S4 Movie(MOV)Click here for additional data file.S5 Movie(MOV)Click here for additional data file.S6 Movie(MOV)Click here for additional data file.S1 Figin situ showing the expression of met in met+/+ siblings (n = 7) and met-/- (n = 5) mutant embryos at 48 hpf. Scale bar: 100 μm. (B) Lateral view of whole mount in situ showing the expression of myoD and myogenin in met+/+ siblings (n = 7 for myoD and 5 for myogenin) and met-/- (n = 5 for myoD and 5 for myogenin) mutant embryos at 24 hpf. Abbreviation: fb: fin bud. Scale bar: 100 μm.(A) Dorsal view of whole mount (TIF)Click here for additional data file.S1 File(XLSX)Click here for additional data file.


Febrile illness caused by viral and bacterial diseases  often have similar symptoms and are difficult to differentiate without diagnostic tests. If not treated appropriately, patients may experience serious complications. The question of what diagnostic tests to make available to providers in order to inform antibiotic therapy remains an open problem for health services facing limited resources.We formulated the problem of minimizing the weighted average of antibiotic underuse and overuse to inform the optimal diagnostic test and antibiotic treatment options for given occurrence probabilities of several bacterial and viral infections. We modeled the weight of antibiotic overuse as a monetary penalty per unnecessarily administered course, which we varied in both the base case and sensitivity analysis. Detailed Markov cohort models of febrile illness progression were used to estimate the weight of antibiotic underuse. The model accounted for multiple infections simultaneously and incorporated test, treatment, and other direct and indirect costs, as well as the effect of delays in seeking care and test turnaround times. We used the Markov models to numerically estimate disability-adjusted life years (DALYs), pre-penalty costs, and likelihood of antibiotics overuse per patient for fifteen different strategies in two example settings in Thailand, one with a higher probability of bacterial infections  and one with a higher probability of viral infections . We found that empirical antibiotic treatment to all patients always incurs the lowest pre-penalty cost , and the lowest DALYs, . However, such strategy resulted in the highest proportion of antibiotic overuse per patient . Consequently, empirical antibiotic treatment became suboptimal with antibiotic overuse penalties above $12,800/course, $18,400/course, $23,900/course for patients presenting on day one, day four, and day ten in Scenario A and above $1,100/course, $1,500/course, $1,600/course for patients presenting on day one, day four, and day ten in Scenario B.Empirical antibiotic treatment to all patients provided the best outcomes if antibiotic overuse was not the primary concern or if presenting with viral disease (such as dengue) was unlikely. Empirical antibiotic treatment to severe patients only was in most cases not beneficial. Otherwise, strategies involving diagnostic tests became optimal. In particular, our results indicated that single test strategies  were optimal in regions with a greater probability of presenting with viral infection. PCR-led strategies  are robust under parameter uncertainty . Clinical manifestations such as the sudden onset of acute fever, chills, and headache are the common features among several tropical and emerging diseases, including dengue, Zika, yellow fever, leptospirosis and scrub typhus . DependiThere are currently no evidence-based guidelines to inform diagnostic and treatment strategies and the necessary health care investments . Early dNevertheless, antibiotic overuse has been recognized as a key driver of antibiotic resistance development, which is an increasingly pressing public health issue. In the U.S. alone, antibiotic resistance causes more than 2 million infections and 23,000 deaths per year . A U.S. As pointed out by Crump et al. , the litThe objective of this study was to inform the optimal diagnosis and antibiotic treatment strategies for patients with undifferentiated febrile illnesses. We determined the optimal decision by considering the tradeoff between antibiotic underuse  and health care cost) and antibiotic overuse . We selected Thailand as an exemplary setting because it is endemic for several pathogens of interest, including dengue, leptospirosis, and scrub typhus at varying occurrence probabilities and immediate availability of published data for model development , 21.To understand the degree to which different strategies achieve the balance between antibiotic overuse and underuse, we seek to quantify the expected consequences and proportions of patients falling in both categories for each strategy. To capture the consequences of antibiotic underuse, we developed a Markov cohort model that describes febrile disease progression with and without treatment. The long-term consequences of antibiotic overuse, such as the development of bacterial resistance, were much more challenging to estimate. Consequently, we assigned a monetary penalty (weight) to every patient unnecessarily prescribed a course of antibiotics, given the disease etiology, in order to capture how different values for this weight might drive optimal decision-making.We first considered a simplified setting where patients presenting with fever had one of four possible disease etiologies: 1) a specific bacterial infection for which a diagnostic test exists and is treatable with a commonly prescribed antibiotic ; 2)In this setting, we considered three strategies: 1) empirical antibiotic treatment ; 2) testing all patients using the bacterial infection test, and prescribing antibiotics to patients with positive results; 3) testing all patients using the viral infection test, and prescribing antibiotics to patients with negative results.wunder, and the penalty (weight) for each patient with non-antibiotic-treatable (NAT) disease who is prescribed antibiotics is wover, then we choose a strategy that minimizes the expected total penalty per patient:If the penalty (weight) for each patient with antibiotic-treatable (AT) bacterial disease who is not prescribed antibiotics is The first and second term corresponds to antibiotic underuse and overuse penalty, respectively, associated with each strategy. We rewrite this objective aswunder/ wover that guarantee that administering a specific test leads to a lower total penalty than administering the other test or no test at all .We derived analytical expressions of antibiotic overuse and underuse probabilities for each strategy, estimated the weights  in orderAfter gaining intuition from analyzing the simplified version of the balancing problem, we turned to a more realistic setting in order to account for multiple disease scenarios, incorporate test, treatment and other direct and indirect costs, as well as the effect of delays in seeking care and in test turnaround times (TAT).We categorized sources of infections into the following five types based on whether they are bacterial or viral, and whether they are treatable with antibiotic: 1) Leptospirosis ; 2) Scrub typhus ; 3) “Other bacterial”, treatable with antibiotic, such as spotted fever group rickettsioses ; 4) DengWe selected two contrasting settings in Thailand with varying infection occurrence probabilities : NortherWe developed detailed Markov cohort models to capture disease progression for each febrile disease and used the model outcomes to evaluate alternative strategies for diagnosis and antibiotic treatment. We modeled a hypothetical cohort of 40-year-old adult patients  with acute, undifferentiated fever since symptom onset. We set the time horizon to 45 days since most patients would be either recovered or deceased by then. We tracked patient health states daily. On each day, patients may recover, progress to severe disease stage or die. We considered patients presenting to hospitals on their first, fourth or tenth day of illness, which captures the minimum, average, and maximum of time for patients presenting to hospitals seeking care. We simplified the health states for any infection type to four core states: Mild, Severe, Recovered and Death. The exact daily transition probabilities depended upon the specific infection etiology and treatment . We assumed that all Severe patients were immediately hospitalized and assigned to a diagnostic and treatment strategy if it was the first hospital visit (no prior testing). We also assumed that deaths during the 45-day time horizon were caused only by severe complications of infections.In the two Thai settings, we evaluated fifteen strategies with different test and treatment options towards febrile disease management . TreatmeWe assumed all Mild state patients received outpatient care (with or without antibiotic prescription), where practices such as follow-up of patients, adequate bed rest and fluid intake are common. Patients who progressed to Severe state  were hospitalized. The current protocol recommended by the WHO in resource-limited settings is empirical antibiotic treatment to patients presenting with severe illness . For comOutcome measures included:Costs and health outcomes: direct and indirect healthcare costs incurred and health burden  and Prob(under)).Antibiotics underuse and overuse. For a given strategy, we tracked the proportion of patients over- and under-treated with antibiotics (Prob(over) instead of the standard two-dimensional outcome space consisting of only DALYs and costs. Secondly, for each strategy, we assigned a penalty per unnecessarily prescribed course of antibiotics (wover), and monetized DALYs by assigning a willingness-to-pay (WTP) per DALY averted. DALYs averted, incremental costs and the incremental Prob(over) for a given strategy is the difference between the DALYs, costs, and Prob(over) incurred by the strategy and those incurred by the “No tests/No Antibiotics” strategy  is 1.We denoted by Our metric for evaluation was the total weighted penalty of antibiotic under- and overuse (Eq ) in the wunder or wover is the penalty per patient under- or over- treated with antibiotics, respectively. This condition states that, if the probability of presenting with bacterial disease is low , or the penalty for overuse of antibiotics is large, then using a strategy that tests for either viral or bacterial disease before prescribing antibiotics is preferred to the strategy that distributes antibiotic treatment to all patients.If If If Prob(over)), underuse (Prob(under)) for each strategy are shown in wover) for patients presenting on day one of illness  and viral-endemic setting (Scenario B) in Thailand. The per-patient costs incurred (in USD), health burden (in DALY), and antibiotics overuse  to be equal to the WTP (Thailand’s GDP per capita), we found that empirical antibiotic treatment (Strategy 2) was only optimal in Scenario A (not in Scenario B), which is consistent with the analytical results  . In ScenStrategy 3  was optimal in two settings and had very small optimal regions at low WTP and low penalty. In Scenario A on day four , StrategCompared to Scenario A, we observed that single test strategies  had the highest NMB for a much wider range of WTP and penalty values in Scenario B than in Scenario A. For example, when we fixed the WTP to Thailand’s GDP per capita, and presentation day as the first day of illness , Dengue Policies with highest NMB for patients presenting on the fourth day of illness  are simiThe flexibility of the model allows us to consider multiple additional strategies. For example, in settings where viral disease is more prevalent, healthcare decision-makers and administrators might consider sequential test strategies that include viral disease tests. We described in supplementary material  four addThe general structure of the optimal strategy sequence when varying antibiotic overuse penalty while setting the WTP to Thailand’s GDP per capita did not change when considering: 1) two additional disease probability distribution scenarios in Thailand (wover). In the average day-of-presentation (day four) scenario and the high bacterial disease prevalence setting  less preferable: For example, in Scenario A, when fixing the WTP to Thailand’s GDP per capita and assuming patients present on day four , StrategWe performed one-way sensitivity analysis for all variables while fixing the disease occurrence probabilities to the ones in Scenario A, and assumed that patients presented on the average day of presentation (day four) to hospitals , S5 Fig.Lastly, we conducted a probabilistic sensitivity analysis (PSA) by varying all model parameters simultaneously using Monte Carlo simulation . Our anaFebrile illness causing diseases is a significant public health burden worldwide , 28, 29.In this study, we first proposed a simple framework to evaluate the effectiveness of different strategies for diagnosis and treatment by balancing antibiotic overuse and underuse. Our framework produced three highly generalizable sufficient conditions that ensured pairwise strategy dominance in terms of a weighted overall penalty of antibiotics under- and overtreatment. We then built detailed Markov models of disease progression in order to capture relevant, practical impacts, such as test costs and turnaround times and delays in seeking care. In both the simple framework and a more realistic setting where more strategies were available, we found that empirical antibiotic treatment to all patients incurred the least DALYs and healthcare costs when the reduction of unnecessary antibiotic use was not a concern. This is because, for patients with a bacterial disease, early antibiotic treatment decreased illness duration in Mild state patients and effectively prevented patients in Mild state from progressing to Severe state which accrued significantly higher DALYs .Considering the limitations in diagnostic laboratory access, empirical treatment is often recommended to patients suspected of a specific bacterial illness, in particular if severe , 33. In Our three-dimensional cost-effectiveness analysis with case studies in Thailand showed that disease occurrence probabilities, test sensitivity and specificity, and patient illness duration at the time of seeking care are highly influential to the choice of an optimal strategy. Empirical antibiotic administration was less preferred in settings where the probability of viral infections was higher than that of bacterial infections since antibiotics were not effective for viral infections. Among all strategies considered in Increasing patients’ delay in seeking care from 1 day to 10 days increased costs threefold, and DALYs sevenfold . This isWhen all model parameters were varied simultaneously in PSA, PCR-led strategies were more likely to be optimal than RDT-led strategies . Nevertheless, our model framework is capable of evaluating any potential strategies. Lastly, quantifying the effects of antibiotics overuse is difficult due to the long-term nature of such effects . To mitigate the difficulty in quantifying the consequences of antibiotics overuse, in our analysis, we provided a wide range of monetary penalties per course of antibiotics unnecessarily prescribed, which resulted in a sequence of optimal policies.Laboratory disease diagnosis plays a key role in the provision of care, but it requires investments in financial and human resources. There are an increasing number of tests at the disposal of hospitals and providers, making the decision of which test to use non-trivial. Clinical trials have been the gold standard in evaluating candidate strategies, but oftentimes such trials cannot be carried out due to ethical, logistical or cost reasons . MathemaS1 CHEERS Checklist(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableWe fixed the disease occurrence probabilities to the ones in Scenario A, and set the WTP to Thailand GDP per capita. We assumed that patients presented to hospitals on day four (average day of illness). Strategy 2: Empirical to all; Strategy 5: Dengue PCR; Strategy 9: S: Lepto PCR, typhus RDT; Strategy 13: P: Lepto PCR, typhus RDT; Strategy 15: Multiplex PCR.(DOCX)Click here for additional data file.S3 TableFor each scenario, we identified the strategies that were on the three-dimensional effectiveness frontier, where the three dimensions are DALY, cost and antibiotic overuse. * = strategies on the effectiveness frontier  for Scenario A ; º = strategies on the effectiveness frontier  for Scenario B .(DOCX)Click here for additional data file.S4 TableFor each scenario, we identified the strategies that were on the three-dimensional effectiveness frontier, where the three dimensions are DALY, cost and antibiotic overuse. * = strategies on the effectiveness frontier  for Scenario A ; º = strategies on the effectiveness frontier  for Scenario B .(DOCX)Click here for additional data file.S5 TableValues obtained from (DOCX)Click here for additional data file.S6 Table* = strategies on the effectiveness frontier  for Scenario A ; º = strategies on the effectiveness frontier  for Scenario B .(DOCX)Click here for additional data file.S7 Table* = strategies on the effectiveness frontier  for Scenario A ; º = strategies on the effectiveness frontier  for Scenario B .(DOCX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S9 Table* = strategies on the effectiveness frontier  for Scenario A ; º = strategies on the effectiveness frontier  for Scenario B .(DOCX)Click here for additional data file.S1 Fig(TIFF)Click here for additional data file.S2 FigPatients enter the model in Mild state, during the 45-day horizon, they could progress to Severe state, become recovered, or dead.(TIF)Click here for additional data file.S3 Figover = antibiotic overuse penalty.We fixed disease occurrence probability vector as Set 1 in (TIF)Click here for additional data file.S4 Figover = antibiotic overuse penalty.We fixed disease occurrence probability as Set 2 in (TIF)Click here for additional data file.S5 Figover; DALY = disability-adjusted life year; PCR = Polymerase Chain Reaction tests.One-way sensitivity analysis, each row (bar) displays the range of Augmented ICER between the empirical antibiotic to all strategy and the Multiplex PCR strategy . We only displayed leptospirosis-specific disease parameters, but all other disease categories share the same structure in the range of ICER change. Augmented ICER = augmented incremental cost-effectiveness ratio, calculated by the ratio of DALY difference and augmented cost difference. Augmented cost = cost + penalty * w(TIFF)Click here for additional data file.S6 FigWe fixed WTP = Thailand GDP per capita. The optimal strategy for a given penalty, is the strategy with the highest NMB value.(TIF)Click here for additional data file.S7 Figover) on the x-axis. (A): 100% antibiotic effectiveness (B): 75% antibiotic effectiveness (C): 50% antibiotic effectiveness.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S8 Figover) on the x-axis. (A): 100% antibiotic effectiveness (B): 75% antibiotic effectiveness (C): 50% antibiotic effectiveness.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S9 Figover) on the x-axis. (A): 100% antibiotic effectiveness (B): 75% antibiotic effectiveness (C): 50% antibiotic effectiveness.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S10 Figover) on the x-axis. (A): 100% antibiotic effectiveness (B): 75% antibiotic effectiveness (C): 50% antibiotic effectiveness.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S11 Figover) on the x-axis. (A): 100% antibiotic effectiveness (B): 75% antibiotic effectiveness (C): 50% antibiotic effectiveness.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S12 Figover) on the x-axis. (A): 100% antibiotic effectiveness (B): 75% antibiotic effectiveness (C): 50% antibiotic effectiveness.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S13 Figover) on the x-axis. (A): Bacterial-endemic Scenario A (B): Viral-endemic Scenario B.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S14 Figover) on the x-axis. (A): Bacterial-endemic Scenario A (B): Viral-endemic Scenario B.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.S15 Figover) on the x-axis. (A): Bacterial-endemic Scenario A (B): Viral-endemic Scenario B.We vary willingness-to-pay (WTP) on the y-axis and penalty (w(TIF)Click here for additional data file.


In order to investigate the fracture behavior of concrete mesostructure and reveal the inner failure mechanisms which are hard to obtain from experiments, we develop a 3D numerical model based on the Voronoi tessellation and cohesive elements. Specifically, the Voronoi tessellation is used to generate the aggregates, and the cohesive elements are applied to the interface transition zone (ITZ) and the potential fracture surfaces in the cement matrix. Meanwhile, the mechanical behavior of the fracture surfaces is described by a modified constitutive which considers the slips and friction between fracture surfaces. Through comparing with the experiments, the simulated results show that our model can accurately characterize the fracture pattern, fracture propagation path, and mechanical behaviors of concrete. In addition, we found that the friction on the loading surfaces has a significant effect on the fracture pattern and the strength of concrete. The specimens with low-friction loading surfaces are crushed into separate fragments whereas those with high-friction loading surfaces still remain relatively complete. Also, the strength of concrete decreases with the increase of the specimen height in the high friction-loading surfaces condition. Further, the energy analysis was applied to estimate the restraint impact of loading surfaces restraint on the compressive strength of concrete. It shows that the proportion of the friction work increases with the increase of the restraint degree of loading surfaces, which finally causes a higher compressive strength. Generally, based on the proposed model, we can characterize the complicated fracture behavior of concrete mesostructure, and estimate the inner fracture mode through extracting and analyzing the energies inside the cohesive elements.  Concrete is a composite material consisting of aggregates, cement matrix, interface transition zone (ITZ) and some other content such as pores. These mesoscopic components determine the macro mechanical behaviour of concrete. In order to research the effect of these mesoscopic components on the mechanical behaviors, researchers have presented many modelling and simulation methods.In terms of the modelling, there are two typical methods to rebuild the concrete mesostructure. One is to generate the aggregates and pores in a random way such as randomly throwing circles/spheres ,2,3,4 orIn recent years, more researchers have adopted the model with cohesive elements to simulate the fracture process of concrete ,33,34,35The fracture behaviour of concrete under uniaxial compression has been studied by several methods, which includes the traditional FEM method such as the homogeneous model  and the In this paper, we present a 3D numerical model based on 3D Voronoi tessellation and zero thickness cohesive elements. Based on the modified constitutive that takes into account the effect of the norm-tangential coupling and the friction between cracks, the proposed model can characterize the complicated fracture behavior of concrete mesostructure. Moreover, this model can also be used to estimate the inner fracture mode through extracting energies inside the cohesive elements. The fracture process of concrete specimens under compression is simulated through the ABAQUS  with subBased on Voronoi polyhedron tessellation ,44,45, aOn the basis of the simplified polyhedrons, the whole process  to generStep1: randomly throw the spheres in a specified region (the spheres should have no overlap and satisfy the size distribution of aggregates), and then take the centers of the spheres as the seeds to generate Voronoi polyhedrons.Step2: generate the Voronoi polyhedrons based on the generated seeds.Step3: simplify the polyhedrons by reducing the vertices and determine the convex hull of the reduced vertices.Step4: zoom the simplified polyhedrons through the scaling ratio of the sphere volume to the polyhedron one which shares the same seed. The scaling ratio is normally less than 1 . The ratio can be calculated by:After the generation of aggregates in concrete, a two-phase mesostructure of concrete can be generated easily by merging the cement matrix and aggregates as shown in Based on the method in Ref. , the zerThe none-linear mechanical behavior is defined in the cohesive elements according to the previous work ,33,34,35A modified constitutive with the consideration of the friction stress is established based on the bilinear damage model. The constitutive is given by the relation of stresses and displacements. In the case of 3D model, one normal stress  elastic phase, (2) damage phase. In elastic phase, the relation between the stresses and displacements can be expressed as:The element initiates the damage phase  once:The stress-displacement relationship in a single direction is shown in The normal  initial damage displacement The initial damage and failure surfaces controlled by normal and tangential displacements are established , which cAs shown in The coordinate value of the point C can also be similarly calculated by:So the relative displacements can be expressed as:According to the bilinear damage model in During the damage phase in the loading process, the friction stresses would occur when the cohesive element (fracture surface) is under compressive conditions. In the damaged area, the friction stress The tangential deformation displacement After the calculation of the friction stress, the orthogonal slip displacements should be updated when the slip of the crack occurs:According to the direction of the tangential deformation, the frictional stress components  exist in the cohesive element, three corresponding energies should be extracted respectively. These three energies are: (1) the normal stress work The energies of the cohesive elements in whole concrete structure can be calculated through:3, and the gradation of aggregate size distribution based on Ref. [Square concrete specimens of 10 cm side are chosen for simulation. The density of the aggregates is assumed as 2800 kg/m on Ref.  is listeWithout the consideration of interfaces inside the aggregates, the mesh of the concrete specimen is shown in E = 70 GPa, v = 0.2, ρ = 2800 kg/m3 for aggregate; E = 25 GPa, v = 0.2, ρ = 2400 kg/m3 for cement matrix. The material parameters value applied in the cohesive elements of concrete are 6 GPa, ρ = 2400 kg/m3, f = 0.45 for cement matrix; 6 GPa, ρ = 2400 kg/m3, f = 0.45 for ITZ. According to the previous works about cohesive element model ,29,30, rd = 1 mm, corresponding to the macro strain ε = 0.01. The models are solved in ABAQUS/EXPLICIT solver, with the user subroutine VUMAT [The simulations all end when the displacement ne VUMAT  in whichThe numerical experiments of concrete under uniaxial compression in the LF condition are carried out. The average stress–strain curve of concrete is shown in −3) and is shown in light blue (−4) and is shown in red. These two parts are separated by cracks with highly discontinuous. Thus, we can obtain the shape of these two parts by extracting the elements with the displacement value higher than 1e−3 and smaller than 1.2e−4 in the loading direction  20 times as shown in The average stress-strain curve in the HF condition is shown in The fracture pattern (deformation is magnified 5 times) and the fracture surfaces of concrete in four different states are shown in By observing the nephogram of displacement whose direction is vertical to the loading one , the conThe fracture modes of concrete under compression are investigated through the energy analysis. The energy evolution of concrete specimens during the loading process are shown in For comparison purposes, we have carried out a group of numerical experiments of concrete specimens under uniaxial tension. The final fracture pattern and the energy evolution of concrete specimens are shown in To investigate the effect of loading condition  on the compressive strength of concrete in terms of energy, the energy increments at the pre-peak stage  are extrd = 1 mm.To investigate the effect of the specimen height on the fracture pattern and the mechanical behavior of concrete, three kinds of the concrete specimen with different height  were chosen for the numerical experiments in the HF condition as shown in The evolution of concrete fracture pattern (deformation is magnified 5 times) with the specimen height = 200 mm is shown in The evolution of concrete fracture pattern (deformation is magnified 5 times) with the specimen height = 50 mm is shown in The fracture modes of concrete with different height are investigated through the energy analysis. The energy evolution of the concrete specimens with different heights  are shown in The energies increment at the pre-peak stage  were extA 3D numerical model of concrete mesostructure is proposed based on Voronoi tessellation and cohesive elements. A modified constitutive is established to characterize the complex behavior of the potential fracture surfaces. Based on the proposed model, the effect of the loading condition and the height of the concrete specimens under uniaxial compression were investigated by analyzing the fracture patterns and the energy increments proportion. Several conclusions can be obtained as follows:(1) The mechanical behavior and the fracture patterns of concrete under compression obtained from the numerical results shows an agreement with that obtained from experiments, which means the proposed model in this paper is suitable for the mesoscopic study of concrete.(2) The energy consumption proportion can be used to identify the fracture mode of concrete during the fracture process. The compressive fracture of concrete is always accompanied by high shear and friction stress work, and the tensile fracture is accompanied by high normal stress work.(3) The effect of loading surfaces restraint on the compressive strength can be estimated by the proportion of the energies increment at the pre-peak stage: a higher proportion of the friction stress work and a lower proportion of the shear stress always cause a higher compressive strength.In this study, we have established a 3D numerical model and used it to analyze the fracture behavior of concrete under compression. However, there are still many things worth studying based on this research. First, the aggregate generated in this paper is based on pure theory, and we can try to replace it with more realistic aggregates reconstructed by CT scanning in further studies. Secondly, there are still many factors that can affect the mechanical behavior of concrete such as the loading form, the loading rate, the aggregate/cement content, and the strength range of concrete. These factors are meaningful to the design of concrete and worth investigating in further studies.


Urinary tract infections (UTIs) are among the most common bacterial infections. Traditionally, all symptomatic UTIs are tested and treated. The use of antibiotics has resulted in an antibiotic resistance crisis, and we have limited options for managing UTIs. Currently, we live in the era of antimicrobial resistance and may live in other eras like the era of the microbiome. New insights might provide an opportunity to prevent the overuse and misuse of antibiotics and could enable the development of innovate managing strategies. Several decades ago, the first antibiotic saved our lives from bacterial infection, but now bacterial infections have again become a threat. The overuse and misuse of antibiotics, along with the development of few new drugs by the pharmaceutical industry, are the most important causes of the antibiotic resistance crisis2.The world is changing rapidly; there is hardly anything in life that is not changing. Technological advancements have enriched our lives, but others have created fear and anxiety. The number of antibiotic-resistant pathogens is rapidly increasing, and many pathogens are becoming multidrug resistant (MDR) with the attendant increased risk of failure of standard therapies3. Traditionally, a UTI is defined as microbial infiltration of the normally sterile urinary tract, and most clinicians think all symptomatic UTIs should be treated5. Recently, however, the paradigm for the management of infectious diseases started to shift as the concept of the microbiome has been established6.Urinary tract infections (UTIs) are among the most common bacterial infections managed by clinicians8. In older residents of long-term care facilities, diagnostic testing and the initiation of antibiotics should be reserved for residents with fever, dysuria, gross hematuria, worsening urinary frequency and incontinence, costovertebral angle tenderness, or suspected bacteremia. Non-specific symptoms and altered mental status are no longer part of the recommended evaluation for a possible UTI10. Asymptomatic bacteriuria also occurs in an estimated 1–5% of healthy pre-menopausal females, increasing to 0.7–27% of patients with diabetes, 2–10% of pregnant women, and 23–89% of patients with spinal cord injuries12. Asymptomatic bacteriuria does not cause systemic disorders, such as renal damage13. Thus, the treatment of asymptomatic bacteriuria is not recommended in patients without risk factors11. Avoiding antibiotic administration in cases where the urine culture does not indicate UTI may be the first step to decreasing antibiotic misuse14.Asymptomatic pyuria and bacteriuria are very common in the elderly, especially in women residing in long-term care facilities or in patients who use a urinary catheter, with a prevalence of 25–50%16. Delaying antibiotic treatment with a back-up prescription to see if symptoms will resolve without antibiotic treatment, or delaying the antibiotic until microbiological results are available, may be an option for antibiotic sparing17.For patients with non-febrile uncomplicated UTIs, active pain control and minimal use of antibiotics should be prioritized. Uncomplicated cystitis can be a self-limiting disease in some cases. Pain in acute cystitis is a natural consequence of the inflammatory response, and pain-mediated urinary frequency or urgency is the chief complaint of patients. Therefore, for this self-limited disease, painkillers, including NSAIDs, may be a good option for symptomatic care as well as reducing the consumption of antibiotics20. However, the use of unnecessary antibiotics has increased by including strains other than “true” STIs such asMycoplasma hominis,Ureaplasma urealyticum , andUreaplasma parvum 21.M. hominis,U. urealyticum, andU. parvum are commonly detected in the urogenital tract of both healthy and symptomatic individuals23. Testing forM. hominis andU. parvum and subsequent antimicrobial treatment of positive men or women are currently not recommended. Instead, “true” STIs and bacterial vaginosis in symptomatic women should be diagnosed and treated21. Bacterial vaginosis, sexually transmitted diseases (STDs), and pelvic inflammatory disease can mimic symptoms of UTIs. In fact, a recent study showed that approximately one-third of STD cases were misdiagnosed as UTIs24.Recently, multiplex PCR assays for the detection of sexually transmitted infection (STI) agents became commonplace in Eastern Europe, Western Europe, South America, and AsiaEscherichia coli to this drug has markedly increased. According to the literature published in the past decade, the resistance rates ofE. coli to co-trimoxazole varied but were usually over 15–30%28. However, there was an interesting report wherein the authors emphasized the role of co-trimoxazole in empirical antibiotics because of the recent decrease in the resistance rate to co-trimoxazole in several European countries owing to its low prescription rate29. Nevertheless, it may not be possible to reuse the drug worldwide within the next few years, and close observation of surveillance data will be required.There are limited oral options for the treatment of antibiotic-resistant uropathogens associated with lower UTIs (acute cystitis). Co-trimoxazole was a typical antibiotic used to treat UTIs, but the resistance of28. Fluoroquinolones are no longer recommended as first-line therapy for uncomplicated UTIs11. Similar to what was seen with co-trimoxazole, there is evidence that escape from exposure to this antibiotic will increase antimicrobial susceptibility in UTIs. According to Leeet al., the susceptibility of Gram-negative bacteria to ciprofloxacin was much higher in patients younger than 20 years old than in patients older than 20 years old. The reason for this observation may be the lower exposure to fluoroquinolones in young individuals because these drugs are not recommended for use in those under 20 years old30.With respect to fluoroquinolones, the increase of resistance in uropathogens has occurred at an alarming rate in relation to increased prescribing practicesE. coli, whereas the prevalence exceeded 10% in the local communities of many countries after 201035. Therefore, the increase in ESBL-producingE. coli is no different to that of co-trimoxazole-resistantE. coli or fluoroquinolone-resistantE. coli, and the prevalence of ESBL-producingE. coli is likely to increase soon.One recent issue of importance is the increasing prevalence of extended spectrum beta lactamase (ESBL)-producing uropathogens. Before 2010, the vast majority of countries showed less than a 5–10% prevalence of ESBL-producingE. coli. Fosfomycin prevents peptidoglycan synthesis earlier than do beta-lactam or glycopeptide antibiotics and is broadly active against several Gram-positive and Gram-negative organisms, including methicillin-resistantStaphylococcus aureus and vancomycin-resistantEnterococcus spp.. Fosfomycin has been shown to have advantages in the treatment of UTIs owing to its high concentration in the urinary tract, which exceeds 2,000 mg/L after the initial administration and remains at high levels for a prolonged period, over 24 hours. However, oral fosfomycin should not be used for pyelonephritis or in patients with bacteremia because of inadequate concentrations within the bloodstream37. Fosfomycin susceptibility in uropathogens, includingE. coli, is currently greater than 90%, even in ESBL-producingE. coli40. It is safe to use in pregnancy41. The drug is likely to be excreted in low levels in breast milk, but would not be expected to cause any adverse effects in breastfed infants, especially if the infant is older than two months.42.Fosfomycin is an oral antibiotic agent that has broad activity against MDR uropathogens including ESBL-producingE. coli cystitis is nitrofurantoin. Nitrofurantoin is a drug that has been used since the 1950s to treat uncomplicated UTIs and works by damaging bacterial DNA in its highly active reduced form. Now, and even in earlier eras of widespread use, the baseline resistance to nitrofurantoin is low (0–10%)44. Nitrofurantoin should be used only for lower UTIs, and its use should be avoided in patients with a creatinine clearance of less than 60 mL/minute, as reduced renal function results in decreased active drug within the urine45. Nitrofurantoin is one of the few drugs that can be used during pregnancy46. A recent retrospective, matched-cohort study in older adults concluded that long-term use of nitrofurantoin is associated with greater risk of lung injury than acute exposure47.Another oral antimicrobial agent that can be considered for the treatment of ESBL-producingLactobacillus spp.), cranberry-based products, D-mannose, methenamine hippurate, hormonal replacement , and other options have been studied as non-antimicrobial prophylaxis53. Evidence for the use of non-antimicrobial prophylaxis is hampered by considerable heterogeneity, and further placebo-controlled randomized trials of these agents are needed. However, trials investigating these options have produced promising results and combining these agents may offer the best route to lowering the rate of recurrent UTIs without needing to use antimicrobials54.The active use of non-antimicrobial prophylaxis is often indicated and does not result in an increase in antimicrobial resistance of the commensal flora. Immunoactive agents, probiotics , an extract of 18 different serotypes of heat-killed uropathogenicE. coli, stimulates innate immunity by increasing non-specific and specific humoral and cellular immune responses via the induction of interferon-γ and tumor necrosis factor-γ production as well as the activities of lymphocytes and macrophages57. Uro-Vaxom® is a safe and effective medicine that can reduce recurrent UTI episodes60 and can effectively reduce the repeated use of antibiotics61. Uromune® is a sublingual spray consisting of equal amounts of four common UTI-causing bacteria in a suspension of 109 inactivated whole bacteria/mL:E. coli;Klebsiella pneumoniae,Proteus vulgaris, andEnterococcus faecalis54. The data from European prospective and retrospective studies suggest that Uromune® is a viable alternative therapy for treating recurrent UTIs in women63.Among these modalities, the urinary immunopotentiator is now well documented and strongly recommended in the guidelinesLactobacillus and the loss of the acidic pH microenvironment within the vagina. Although specific mechanisms are still poorly understood, estrogen plays a key role in modulating the natural defense of the lower urinary tract against UTIs64. The role for topical  estrogen in averting recurrent UTIs in postmenopausal women compared with placebo is clear, and guidelines for this population recommend their use66. Currently, there is evidence that CO2 ablative vaginal lasers may help rejuvenate this microenvironment, much like topical estrogen therapy, restoring the lactic acid synthesis of commensal bacteria and the innate vaginal defense against UTIs69. For postmenopausal women, vaginal estrogen therapy has been considered often as an adjunct to antimicrobial-based prophylaxis70. However, combination therapy with both immunostimulants and vaginal therapy (laser rejuvenation or estrogen) may provide better effectiveness at preventing UTI recurrence in postmenopausal women and is a potentially novel avenue for further research.The lower estrogen state found in postmenopausal women is linked with decreased innate immunity via the loss of the commensal bacteria71. Recently, more sensitive diagnostic tests demonstrated that urine is not sterile72. The urinary tract is inhabited by a unique urinary microbiota, and standard bacteriuria represents a fraction of the diverse microbiota hosted by the urinary tract73. In the past, the notion that UTI was the detection of organisms as a standard culture in sterile urine has changed in the era of the microbiome. The fact that we diagnosed UTIs through standard culture and antibiotic susceptibility ignored the dozens of bacterial species and intracellular bacterial colonies known to reside in the urinary tract72. As expected, in the era of the microbiome, stable bacterial communities are generally beneficial and this condition is referred to as symbiosis. In this sense, patients with urinary tract symptoms would be more likely to be classified as having urinary tract dysbiosis rather than a UTI73. If the full array of microbes resident in the human urinary tract is identified in the near future, some treatment of UTIs by antibiotics may turn into a correction of dysbiosis. In the gut microbiome, treatments ofClostridium difficile infections through fecal transplants have been investigated75. In the urinary tract, the instillation of non-pathogenicE. coli safely reduced the risk of symptomatic UTI in patients with spinal cord injury. All of these efforts are ultimately related to preventing the overuse and misuse of antibiotics. The paradigm of managing UTIs has shifted from diagnosing UTIs and antibiotic treatment to screening for patients who really need antibiotics.The microbiota is defined as the microorganisms in a particular environment. The microbiome refers to their genomes that are revealed using molecular techniques such as 16S ribosomal RNA (rRNA) sequencingA clear achievement in recent oncology is the emergence of immunotherapy, a type of treatment that helps our immune system fight cancer and that marks an entirely different way of treating cancer by targeting the immune system, not the tumor itself. If the immune system also helps our body fight infections, why not use our body’s immune system instead of antibiotics to treat UTIs? This paradigm shift seems to be beginning in the management of UTIs. Further understanding of the microbiome in the urogenital system is expected to stimulate this shift. Eventually, the spread of antibiotic resistance can be reduced if antibiotics are used only when they are needed.


A single-phase homogeneous formulation of PTX with the mixture of the MPC-ran-C2H5-POSS and polyvinylpyrrolidone (PVP) was prepared by a solvent method. The formulation of MPC-ran-C2H5-POSS/PVP/PTX enhanced the dissolution rate and the dissolved amount (approximately 90% within 40 min) without precipitation. The X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC) analysis confirmed the presence of PTX as an amorphous state. The amphiphilic nature of the MPC-ran-C2H5-POSS contributed to enhancing the aqueous solubility of PTX. The new formulation is applicable for solid dispersion technique via the supersaturation of PTX in an aqueous media.Suitable polymers for the homogeneous formulation of drug/polymer mixtures should be selected to correct the structural and physicochemical nature with a rapid dissolution rate. This study aimed to evaluate a copolymer prepared by the radical polymerization of 2-methacryloyloxyethyl phosphorylcholine (MPC) and a polyhedral oligomeric silsesquioxane (POSS) methacrylate bearing an ethyl (C Ⓡ) and micelles  have been used in clinical studies ) has been prepared [co-BMA] was also applied for the solid dispersion of tranilast  anthranilic acid), an anti-allergic biopharmaceutics classification system (BSC) class II drug [co-BMA] markedly improved the dissolution rate by the attractive interaction between the polymer and tranilast. Historically, polyvinylpyrrolidone (PVP) has been extensively used for solid dispersions to improve the dissolution rate without recrystallization due to the enhanced interaction in the solid state  as mentioned above is not optimized for controlling the interaction with PTX. In a previous study, a random copolymer was synthesized by using the MPC and ethyl (C2H5) group-modified polyhedral oligomeric silsesquioxane (POSS) methacrylate (MA) as a hydrophobic monomer . Th. Thran-Cspectrum . PTX andran-C2H5-POSS, PVP and PTX (MPC-ran-C2H5-POSS/PVP/PTX) was prepared using a solvent method. The MPC-ran-C2H5-POSS, PVP and PTX were dissolved in dehydrated ethanol (MPC-ran-C2H5-POSS:PVP:PTX = 44:44:12 wt. %) with continuous stirring. The solvent was removed under vacuum at room temperature. The MPC-ran-C2H5-POSS/PTX (C2H5-POSS-MA MPC:PTX = 88:12 wt. %) and the PTX/PVP (PVP:PTX = 88:12 wt. %) were also prepared in the same manner.The formulation of MPC-The dissolution of the solid formulation was tested according to the European Pharmacopoeia, using a type 2 (paddle) dissolution apparatus . The dissolution study was performed in 500 mL of 2nd Fluid for dissolution test mixed with 1% Tween 80 as a dissolution medium. The temperature was kept at 37 °C during the study with a stirring speed of 100 rpm. The solid dose form of 10 mg was used in this dissolution study, which contained 1.1 mg equivalent of PTX. The sample solutions (25 mL) were collected at 5, 10, 20, 30, 40, 50, 60, 90, 120 and 180 min time points and an equivalent amount of fresh media was added to maintain a constant dissolution volume. The concentration of PTX in the dissolution medium was determined by HPLC  equipped with a UV-vis detector , two pumps , a mixer  and a column (TSKgel ODS-100S (Φ 4.6 nm × 150 mm)) from TOSOH Co., Tokyo, Japan). Before the measurements were taken, all the samples were filtered through 0.45 µm Polyvinylidene difluoride (PVDF) membrane filters. A methanol and water (70:30 v/v) mixed solution was used as the mobile phase, and a 1 mL/min flow rate was maintained during the measurements. The detection was performed at a wavelength of 227 nm. PTX release in the dissolution medium at different time intervals was calculated using the PTX standard curve. The standard solutions of concentrations 100, 50, 10, 1 and 0.1 µg/mL were prepared in methanol and the standard curve was prepared by plotting the area under the peak vs. concentration. The resulting standard curve was linear with −1.Powder X-ray diffraction was carried out using an X-Ray diffractometer  with monochromatic CuKα radiation and a generator working at 40 kV and 20 mA. Scattering intensity was measured in the range of 2 < 2θ < 60° with scan steps of 1° min−1. KBr was used for the attenuated total reflectance crystal. The spectra were recorded from KBr pellets, prepared by mixing the formulation with KBr at room temperature. The spectrum resolution was 4 cm−1, and 2 mm s−1 scans were accumulated to determine one spectrum.The chemical bonds of the solid formulation were characterized using a Fourier transform infrared spectroscopy (FT-IR) apparatus . The scanning wave numbers ranged from 4000 to 400 cm−1  within the temperature range of 20–185 °C. The glass transition temperature (gT) was obtained at the midpoint of change in the baseline of DSC thermograms during the second heating. The gT of the solid formulation  apparatus . The scan rate was 10 °C minequation ,(1)1/Tgran-C2H5-POSS:PVP:PTX = 44:44:12 wt. % (MPC-ran-C2H5-POSS/PVP/PTX), MPC-ran-C2H5-POSS:PTX = 88:12 wt. % (MPC-ran-C2H5-POSS/PTX) and PVP:PTX = 88:12 wt. % (PVP/PTX). In order to characterize the crystalline and amorphous states of PTX and polymers in those solid formulations, XRD, DSC and FT-IR measurements were carried out.Three different formulations of PTX were prepared in this study at the same weight percentage of PTX in all the formulations: MPC-ran-C2H5-POSS, PVP, PTX and the three different formulations are shown in ran-C2H5-POSS/PTX, PVP/PTX or the MPC-ran-C2H5-POSS/PVP/PTX formulations , 156 °C (429 K) and 106 °C (379 K), respectively. The detailed calculation of gT is shown in gT of PVP was consistent with the findings of a previous study [gT values from the second heating curves was reliable. It is known that PTX exhibits a melting point at 213–217 °C as a semi-crystal [gT in an amorphous state [ran-C2H5-POSS/PVP/PTX solid formulation showed a single gT at 91 °C (364 K)  . gTmix of the MPC-ran-C2H5-POSS/PVP/PTX was calculated to be ca. 98 °C (381 K). Equation (1) only allows the prediction from the properties of pure components; the asymmetric entropic and enthalpic contribution are not reflected in this equation. In addition, the Equation (1) does not reflect the strength of intercomponent and intracomponent interaction, the composition-dependent energetic contribution from hetero-contact, the entropic effect, or the structural heterogeneity term. Taking the limitation of the Equation (1) into account, it is difficult to directly compare gT with gTmix.According to the Fox equation (Equation (1)), ran-C2H5-POSS/PVP/PTX system) [gT that characterizes the binary systems as polymer blends or copolymers depending on their composition [ix is the mass fraction of component i and gT values and the predicted values calculated by the Equation (1) is evidence of the increased complexity; the parameters of co-vinyl acetate), and the results agreed well with the experimental data [In the case of amorphous binary systems, the microstructure is closely related to the glass transition temperature, and the microstructural characteristics become evident in miscibility studies of binary polymer and drug/polymer mixtures  ,26. Broseneities . The BCKtal data . gT estimation, the BCKV equation was applied to evaluate the formulation of the MPC-ran-C2H5-POSS/PVP/PTX. gT values; the gDSCT was determined by the DSC measurements , the 0a–a2 . Since the parameters of ia reflected the differences of the interaction energies and the structural heterogeneities as mentioned previously, those solid formulations exhibited some energetic matters of the interactions between the MPC-ran-C2H5-POSS, PVP and PTX. However, the smaller ran-C2H5-POSS/PTX and the MPC-ran-C2H5-POSS/PVP/PTX compared to those of the PVP/PTX suggest that the MPC-ran-C2H5-POSS contributed to the increased miscibility of PTX. According to the abovementioned perspectives of the complicated ents see , and thegT of the binary polymer and drug/polymer mixture is dependent on the mass fraction, the observed single gT at 91 °C, which was higher than the value for the MPC-ran-C2H5-POSS (70 °C), follows conventional miscible organic blends [gT value suggests the miscibility and strong interaction between PTX, PVP and polymers in the single homogeneous phase [gT of the MPC-ran-C2H5-POSS (70 °C) to 91 °C suggests the increased stability of PTX by the strong interaction in the MPC-ran-C2H5-POSS/PVP/PTX homogeneous formulation [Since the c blends . In otheus phase . In addimulation . −1  and 1734 cm−1 ((C=O)-O-, ester) in addition to 1644 cm−1 (aromatics) and 1070 cm−1 (C-O-C). For the MPC-ran-C2H5-POSS, the corresponding ester bonds resulted in the appearance of the peaks at 1724 cm−1 ((C=O)-O-, ester) and 1080 cm−1 (P-O) in the MPC part [ran-C2H5-POSS/PTX , many jagged peaks around 1705–1740 cm−1 were observed  and 1734 cm−1 ((C=O)-O-, ester) in addition to 1644 cm−1 (aromatics) and 1070 cm−1 (C-O-C) at 12 wt. %  over 40 min. A similar phenomenon was observed in the case of the MPC-ran-C2H5-POSS/PTX, where the solubility of PTX was ~1.5 µg/mL. It is noted that the dissolved concentration percentage slowly decreased after reaching the maximum percentage. The general phenomenon of the homogeneous solid formulation was as follows—the decrease in the PTX concentration after a certain time was due to the fact that the crystal nucleation rate of PTX rises according to the ratio of the supersaturated solubility to the solubility of the crystal [Dissolution tests were carried out in order to assess the dissolution of PTX from the MPC- crystal . ran-C2H5-POSS/PVP/PTX was caused by several factors such as the amorphous state of PTX in the formulations, ran-C2H5-POSS (PTX solubility in the MPC-ran-C2H5-POSS 100 mg mL-1 solution was found to be 75.5 ± 8.8 µg) [ran-C2H5-POSS exhibited an amphiphilic nature [ran-C2H5-POSS could prevent the immediate recrystallization of amorphous PTX at the water interface to reduce interfacial tension between PTX and water [ran-C2H5-POSS/PVP/PTX and the MPC-ran-C2H5-POSS/PTX, suggesting that the absence of hydrophobic moieties in the hydrophilic PVP matrix somewhat induced the recrystallization of PTX. Thus, the incorporation of the MPC-ran-C2H5-POSS in the solid formulation of PTX plays an important role in modulating the dissolution behavior of PTX, which leads to PTX supersaturation throughout the media [The increase in the apparent dissolution from the MPC- 8.8 µg) , the inhc nature , the prend water . In the he media .ran-C2H5-POSS was incorporated into a solid formulation of PTX with PVP. The MPC-ran-C2H5-POSS/PVP/PTX single-phase homogeneous formulation was found to enhance the dissolution rate of PTX. The improved wetting of the formulation accompanied by the amphiphilic nature of the MPC-ran-C2H5-POSS facilitated rapid and complete drug release (approximately 90% within 40 min). The increased interaction between PTX and the polymeric matrix of the MPC-ran-C2H5-POSS/PVP/PTX formulation is likely to reduce the mobility of amorphous PTX, which results in the enhanced dissolution of PTX. Therefore, the formulation of PTX in combination with MPC-ran-C2H5-POSS and PVP would be a promising approach to enhance the physicochemical properties of PTX. The results obtained encourage further investigation of the pharmacokinetic parameters in an animal model.MPC-


Compared with the ARIMA model based on AIDS surveillance data, the ARIMAX model with Baidu Composite Index had the minimal an Akaike information criterion  and the most exact prediction (MAPE of 6.11%). We showed that there are close correlations of the same trends between BDI and HIV/AIDS reports cases for both increasing and decreasing AIDS epidemic. Therefore, the Baidu search query data may be a good useful indicator for reliably monitoring and predicting HIV/AIDS epidemic in China.China’s reported cases of Human Immunodeficiency Virus (HIV) and AIDS increased from over 50000 in 2011 to more than 130000 in 2017, while AIDS related search indices on Baidu from 2.1 million to 3.7 million in the same time periods. In China, people seek AIDS related knowledge from Baidu which one of the world’s largest search engine. We study the relationship of national HIV surveillance data with the Baidu index (BDI) and use it to monitor AIDS epidemic and inform targeted intervention. After screening keywords and making index composition, we used seasonal autoregressive integrated moving average (ARIMA) modeling. The most correlated search engine query data was obtained by using ARIMA with external variables (ARIMAX) model for epidemic prediction. A significant correlation between monthly HIV/AIDS report cases and Baidu Composite Index ( The severity of the AIDS epidemic and its perniciousness is also a social problem that needs an urgent solution. In recent years, the epidemic pattern of HIV/AIDS in China has gradually diversified and the scope of surveillance is continuously expanding. The traditional way of monitoring disease is to count the number of cases over a period of time by setting up sentinel hospitals throughout the country. A more modern way of monitoring diseases is to access the monitoring data that is released by the health department after sorting out the statistics. This method is collected by artificial means, covering a large area and for a period of time, which usually takes a lot of manpower, materials and time. Moreover, some HIV-infected patients may not be willing to report their symptoms to a doctor because of private issues and official data are usually released after two weeks of reported illness2. This lag in AIDS data collection and reporting is an impediment to the control of the epidemic.Since the first AIDS case was reported in 1981, the virus has caused more than 60 million infections and more than 30 million deaths worldwide, making it the greatest threat to human health5, but also in medical research and epidemic analysis of infectious diseases. It can provide health authorities with important information regarding the emergence and spread of diseases in the city to complement traditional epidemic surveillance systems6. Google Trends was used to obtain a global search of Ebola during the Ebola outbreak from November 1st to December 27th, 20147, and applied provided real-time tracking of the flu outbreaks11. Data from different search engines have also been utilized in tracking diseases such as malaria and breast cancer successfully13. Moreover, the real-time monitoring of disease trends using the Internet-based Google Insights has been explored on dengue fever in Singapore and Bangkok from 2004 to 201114. Diseases such as AIDS, due to a variety of reasons, patients often remain silent in front of relatives, friends and even doctors about their own status, and turn to self-diagnosis through Internet searches. While providing convenience, it also has the advantage of user private information confidentiality. There is little research on Internet data analysis for HIV/AIDS in China, with biological indicators, treatment methods, epidemiology and demographic indicators principally applied to evaluate and monitor the local epidemics16. The Baidu index launched by the Baidu Inc is the main Internet search tool used in China. In March 2018, its market share in China was 73.02% which is far higher than search engine markets such as Google18. We therefore use the internet search data provided by the Baidu index to survey the HIV/AIDS epidemics in China.The Internet search engine has become an important platform for public access to information as well as data archive, with the latter serving as research source in various disciplines. Research objects based on Internet data have not only been developed in the fields of economy, finance, and marketing such as products sales, trend of gas prices and stock market19. Our method will provide new reference approaches for the analysis, monitoring, and prevention of the AIDS epidemic.We compare the internet data to the number of conventional epidemic reports in the same period to determine the relevance of Internet search behavior. Spatial difference analysis of the data is also performed to find the differences in spatial distribution of the AIDS-related search data. Lastly, we developed an Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model based on the keyword search index of the Internet and examined whether it improved the model’s forecasting abilityThis describes the parameters and tools used in this study, including the Baidu search engine and its daily search amounts and wide coverage to all of China, Baidu search index, etc. what does Fig. Spearman’s rank analysis on the correlation between Baidu Search index and HIV/AIDS reported cases found that 11 out of the 50 keywords are not related to epidemic, 20 keywords have weak sequential time-series correlation. Only 19 search keywords have significantly correlated to the reported cases, of which correlation coefficient is greater than 0.6 (Table P < 0.001). We also displayed AIDS related Baidu Composite Index (Baidu CI) trends in both annual and monthly time dimensions, and found a constant increase of it from 2011 to 2016 , two provinces (Xinjiang and Chongqing) with middle level epidemic and two major cities  with low level epidemic . Residual autocorrelation test shows that the residual series belong to the white noise sequence  and partial autocorrelation coefficient (PACF)  and the output sequence (y1t) are stationary. Establishing co-correlation coefficient plots for different delay orders, we can see that differencing Baidu CI has a significant lag effect with differencing HIV/AIDS report cases and the parameters obtained after estimating the model are significantly non-zero, moreover, the residual autocorrelation test shows a random distribution that there is no autocorrelation in the residual  in 2017, the rural Internet penetration rate reached only 35.4%. Finally, although we found that search engine data have spatial differences and there are also deviations in provincial network data. However, the selected provinces are still insufficient, as well as not found a pattern on different provincial relationships. Moreover, the ARIMAX model is based on nationwide data, does not take into account geographical disparities within the province. Further studies to account for the search index from a larger number of provinces and regions may be more effective.However, there are some limitations of this current study. First of all, the search index of each keyword is easily influenced by the continuous change in search behavior of the individual, and Baidu Inc still has some related keywords not included, which may result in an underestimation of the correlationIn conclusion, the keywords for AIDS used in this study can provide some reference value for the collection, screening, analysis and forecasting process of search engine data. Moreover, the prediction model based on Baidu Index can accurately predict infectious disease outbreaks. Current monitoring and detection procedures for infectious disease epidemics are complicated and inefficient. Exploitation of the internet-based surveillance system by Baidu search index in disease surveillance is therefore timely. With the rapid development of the Internet services and search engine today, the combination of network data analysis may be considered as an adjunct for traditional monitoring of diseases. The real-time and low-cost Internet Big Data can improve the timeliness of monitoring and mitigate the low efficiency in the bureaucratic hierarchy, as well as help public health officials to identify and predict more accurately which people are at risk of potential HIV/AIDS spread to take effective interventions.Official case counts. This study used monthly aggregated HIV/AIDS new case counts from January 2011 to June 2017  for China. The data is publicly available on China Centre for Disease Control and Prevention’s (China CDC) monthly status report of HIV/AIDS. In addition, it is typically released 1–2 week after the end of each month.http://index.baidu.com). The search’s database includes search query volumes for many keywords keyed in by Baidu search users. Moreover, Baidu index is available on a daily basis, at cities and towns, provinces and national level. Considering the HIV/AIDS category keywords are available in the Baidu’s search database from January 2011, therefore, we collected the data from January 2011 to June 2017. Since Baidu’s search index is available on a daily basis, so the index is converted to monthly counts for analysis.Daily search engine query data were obtained for the same period from Baidu index  was used for further obtaining correlative keywords and did some statistical analysis of collected numbers34. In addition, due to different people typing in entirely different words when searching the same information, especially when searching in Chinese language, where one meaning can be expressed in several ways, hence, some of the keywords represent the same meaning37. Other keywords were dug by using semantic correlation analysis from Microblog, Post Bar, and online Encyclopedia31. Finally, we initially acquired 100 related keywords about AIDS search behavior. However, some researches had indicated that more keywords do not necessarily assure better model fit and it’s not easily reproducible by research fellows with a finite resource38. Consequently, we collected a variety of HIV/AIDS core keywords and screened it following three steps:The core keywords should be principal factors that perhaps influence the genesis and development of the disease.We picked out each of the more than one million search frequent keywords by analyzing the total number of website inclusions and then 50 keywords remained.The selected keywords were divided into five categories, namely HIV/AIDS Etiology, General, Diagnosis, Symptom, and Treatment.In the Baidu’s search index, the keywords have different search frequencies at different times and regions. Consequently, diverse search behavior can be reflected the attention of people from different periods. Although the significance of this is, however, there are no rules or standards for directionIn order to further screen out high relevance keywords and guarantee the number of keywords in our analysis. Therefore, in the monthly HIV/AIDS new case count and monthly keyword BDI Spearman’s correlations analysis (two-tailed test), we considered the Spearman’s rank correlation coefficients 0.6 as the threshold.40. The lag value with the maximum correlation coefficient for each keyword was selected for inclusion in subsequent AIDS Search Index composition analysis. Then, considering the remaining keyword numbers and strength of the Spearman’s correlations coefficient, we deleted the words with maximum correlation coefficients less than 0.5 in each time lag and those correlations that were statistically insignificant. Finally, 17 keywords were detected with distinct non-lag in results of the cross-correlation analysis  with specific time lag(k), keywordki and weightki denotes the ith keyword monthly Baidu Index and the weight of it with specific time lag(k).In the above formulae, k denotes the potential time lag, n represents the number of keywords included at each time lag, In order to better observe the network search behavior of different types of people, it is necessary to carefully analyze the spatial distribution of each type of keyword.Firstly, we selected Chongqing and Sichuan areas which with significantly increased AIDS epidemic, the Beijing and Shanghai regions where the epidemic progressed tardily, and the Xinjiang and Guangxi provinces with reduced epidemics as an example. Furthermore, according to the components of the national search index composition and the actual inclusion of Baidu search engine data in each region, a total of five categories of 17 keywords were selected for analysis. Thirdly, for better visualization of these data, we used the Search intensity indicator, which is calculated the total number of each keyword search indices and divided by number of Internet users in each provinces. Ultimately, we respectively analyzed the correlation between the actual number of cases in each province with the Internet users’ search intensity and the search index of keyword of five categories.44. However, it is merely a univariate model, which also has limitations in predicting disease. The ARIMAX model is an extension of the Autoregressive Integrated Moving Average (ARIMA) model. More information  can be utilized by the ARIMAX model than the ARIMA model, it makes use of multiple regression analysis and time series analysis that could improve the forecasting ability45. Therefore, we used the ARIMA model that combines Baidu Composite Index (AIDS search index) and can examine the relationship between keywords and AIDS. The following equation was used to obtain the predicting disease series:Time series models use the past tendency of variables so as to predict its future values. Most time series can be shown by Autoregressive Integrated Moving Average Model (ARIMA) model. The ARIMA model is also widely used to predict infectious diseases incidence through the use of historically surveillance cases data, such as malaria and hepatitis A, dengue fever and hepatitis incidenceith input variables respectively; k; 47.In the formula 50, equation was as follow:The predicting precision of the model was checked by the goodness of fit between the observed and predicted of HIV/AIDS report cases using the mean absolute percentage error (MAPE)It means that predicted cases from the models have a better accuracy for the reported case when the MAPE values are small.P<0.05 were considered to be significant in the analysis and construction process.The modeling process of ARIMA and ARIMAX was analyzed by SAS 9.4 statistical software and the rest of the statistical analysis were performed using IBM SPSS 19.0. Furthermore, each variable with Supplementary Figure S1-S4


Overwhelming antibiotic use poses a serious challenge today to the public-health policymakers worldwide. Many empirical studies pointed out this ever-increasing antibiotic consumption as primary driver of the community-acquired antibiotic drug-resistance, especially in the middle- and lower-income countries. The association is well documented across spatio-temporal gradients in many parts of the world, but there is rarely any study that emphasizes the mechanism of the association, which is important for combating drug-resistance. Formulating a mathematical model of emergence and transmission of drug-resistance, we in this paper, present how amalgamating three components: socio-economic growth, population ecology of infectious disease, and antibiotic misuse can instinctively incite proliferation of resistance in the society. We show that combined impact of economy, infections, and self-medication yield synergistic interactions through feedbacks on each other, presenting the emergence of drug-resistance as a self-reinforcing cycle in the population. Analysis of our model not only determines the threshold of antibiotic use beyond which the emergence of resistance may occur, but also characterizes how fast it develops depending on economic growth, and lack of education and awareness of the population. Our model illustrates that proper and timely government aid in population health can break the self-reinforcing process and reduce the burden of drug-resistance in the community. It is described as the primary threat to public health in the 21st century, and agencies around the globe have underlined the urgent need for actions4. There is high resistance to Cotrimoxazole (68.5%) and Ampicillin (84.5%) among the Gram-negative bacilli in Zimbabwe5. In the same country, Gram-positive cocci is also resistant to Cotrimoxazole (69%) and Nalidixic acid (81%). E. coli is another pathogen that shows 84% resistance to ampicillin6. A recent report has documented the non-susceptibility pattern of key Gram-negative  and Gram-positive pathogens  to the most common antibiotics in Sub-Saharan Africa7. However, antibiotic resistance is worldwide, and the effects of resistance are more severe in lower- and upper middle-income countries  have estimated the economic cost of resistance per antibiotic by drug class and compared those in developing and developed countries, like in Thailand and United States11. Moreover, mortality and morbidity are the indirect consequences of resistance that incur a huge loss in income leading the sufferer and family to the poor economic condition13.The rapid emergence and dissemination of resistant bacteria is occurring globally, threatening the potency of antibiotics, which saves millions of livesies Fig. 8,9. This15. Several countries already have taken steps to reduce the misuse of antimicrobials. World Health Organization (WHO) already has launched a Global Action Plan in 2015 to initiate evidence based prescribing through effective, rapid, and low-cost diagnostic tools to optimize use of antimicrobials16. In spite of these efforts, the volume of antibiotic use is ever-increasing worldwide, especially in developing countries. A recent report indicates that the global antibiotic consumption increased by 65% (rate increased by 39%) between 2000 and 2015, from 21.1 to 34.8 billion Daily Defined Doses (DDDs), and the global increase was primarily driven by increased consumption in Lower Middle Income Countries  are developing nations, which show the highest drug consumption from 2000 to 2010 with India as the first and China is in the second position17.Antibiotic resistance may occur naturally, but irrational use of antibiotics accelerate the process leading to expulsion of sensitive strain, and procreation and propagation of the resistant bacteria in the communityies Fig. 9. Countr21. Over-the-counter (OTC) sales – which is more ubiquitous in more economically destitute society – is one of the source of self-medication22. It is a very common practice in countries like Bangladesh23, Addis Ababa and Central Ethiopia24, and North West Ethiopia25. Avoiding expenditure of treatment, inability to access medical facilities, less education and lack of awareness are utmost challenges for self-medication26. Also, perceived patient expectation, lack of knowledge and diagnostics, incentives and advertising from industry, and financial benefits are major factors for irrational antibiotic prescription by physicians in most of the developing countries27.Self-medication plays a major role in ever-increasing antibiotic consumptionet al. (1993) studied coexistence of sensitive and resistant strains in hospital infection28. Austin et al.  developed model to understand influence of drug use on transmission of resistance29. In the past few years, various antibiotic drug-resistance models have been developed that discuss usage of antibiotics and emergence of resistance34. For example, Levin et al. (2014) have shown by developing simple epidemiological model that burden of resistance can be maintained under certain acceptable level if the use of specific antibiotics declines with the frequency of resistance to these drugs35. Developing game theoretic model, Fu and Chen (2018) have shown how social learning may help prescribing behavior of physicians to promote social optimum of antibiotic consumption36. However, there is rarely any modelling work that integrate socio-economic growth, antibiotic use and transmission dynamics to understand this ever-increasing antibiotic consumptions in middle and lower income countries.The relation between antimicrobial use and emergence of resistance is a complex association. While most of the recent research focus on understanding microbiology of drug-resistance, there are only few modelling studies that emphasize transmission dynamics and coexistence of strains under volume of antibiotic use. For example, Massad SIS) model, where individuals can have recurrent infections over the course of their lifetime. This kind of general framework of reinfection is considered to represent the repeated threat of infection that individuals face in most of developing tropical countries. However, our model can demonstrate the emergence of antibiotic drug-resistance in the population as a self-reinforcing system where these three components interact through positive feedbacks on each other use by individuals. Although these three aspects are dynamic in nature and canonical in their respective disciplines, combining them may explain the evolution of drug-resistance in the population. Below, we describe model formulation in these three parts separately, and then develop the integrated model. Detailed model development of separate components are discussed in the Supplementary Information.Our drug-resistance model connects three domains of human population: 39. The relationship between the labor and capital determines the output , thus the model provides a basis for economic growth in the canonical framework by defining a process that describes capital conversion and accumulation in population over time40. This is a macro-oriented approach that dictate patterns of capital accumulation as an inevitable outcome of normal market processes driven by savings and technological progress. The patterns of accumulation converges over time leading to a steady economic growth across countries40.We consider the model of economic growth based upon three driving forces namely, capital , labor and technology. This is described as Neoclassical growth theory in economics that layouts how steady economic growth rate can be accomplished with these three forcesConstant-elasiticity-of-substitution (CES) production model, which is one of the massively used function in economic analysis41. Thus, the rate of change of capital is given by:h(t) is the capital (income) at time t scaled to the labour supply. rh and rl determines the share in total output from capital and labor respectively, so rh + rl = 1. δ1 is the rate of capital depreciation. Detailed discussion and derivation of the linear form is given in the Supplementary Information (SI).We use a linear formulation of 42. For instance, resistance to the rifampicin drug in M.tuberculosis emerges through mutation whereas resistance to antibiotic β-lactam in E. coli was by plasmid transfer43. However, the key issue in this epidemiological model framework is to analyze the role of antibiotic consumption in the onset and propagation of resistance in the population. We assume that the drug-resistant strain is already present and circulating in the population. For simplicity, we also assume that individual in population are either colonized by sensitive strains or by drug-resistant strains. Colonization may result in the morbidity, and people undergo treatment also. We also consider that a susceptible individual may even consume antibiotics without having any prior knowledge of underlined infection, but the drug has no effect if individual is colonized by resistant strain.Acquired resistance may emerge from several biological mechanisms such as through mutation within the existing genome or through the plasmid transferSIS framework, where individuals become susceptible once recovered from an infection. Based on these assumptions, we compartmentalize the total population based on whether individuals are using antibiotics or not, and further based on individual infection status – by the sensitive or the drug-resistant strain. Figure We consider a general 38:Transmission potential of the commensal bacteria is measured by basic reproduction number  is low, then self-medication is high and reaches a maximum level m is determined byAntibiotic consumptions in developing and underdeveloped countries are strongly correlated with the economic growth of the populations. Several studies pointed out that poor economy fosters self-medication practice in individuals, especially through over-the-counter (OTC) salesho determines the effect of education and awareness of the community on antibiotic consumption. A schematic of the function is given in Fig. ho, lower the level of awareness and hence higher the antibiotic consumption.The parameter In reality, the association between the behavioral aspects of individual medical practice and socio-economic growth of population is more complex and nonlinear, and there is rarely any empirical contribution in support of this. Here, we intentionally consider a simpler approach, not to discount complexity, but to illustrate the complex outcomes as emergent properties of parsimonious integrated models.s + S + y + z = 1.We integrate the three components and construct the conceptual framework that describes the feedback from one part to the other. The following coupled differential equations governs the dynamics:rh and rl are linear function of y and z as follows: ρczz denotes the depreciation, where ρ is probability of maximum individual treated, and cz is per capita cost of treatment of severe infections. The variables and parameters descriptions are given in the Table For simplicity, we assume that mentclass2pt{minimy = 0 or z = 0) is much simpler than that of complete model given by (8). Here, we aim to discuss the effect of antibiotic consumption on the dynamics of both sensitive and resistant strains in the population, and hence, mainly consider the existence of endemic equilibrium when both pathogens exist in the system. Discussion of the endemic equilibrium provides us a framework to address interesting issues such as invasiveness of resistance in the community, and also defines parametric regime related to antibiotic use when resistant strains will come to dominate over sensitive strains, once present in the population.The dynamics of the system with either of strains  at higher ah.Condition (3) provides a parametric regime where both sensitive and resistant strains coexist in the system. While ah) and duration (1/δ2) of antibiotic consumption, level of awareness and education (h0). In absence of drug-resistant strain, the sensitive strain will be eradicated from the system if the antibiotic use reaches the threshold δ2 i.e., the average duration of antibiotics consumption. However, in presence of drug-resistant strain, the eradication of sensitive commensal is much easier, as the value of the threshold ah is increasing. Thus, it will be easier to eradicate sensitive strain with high volume of antibiotic use in presence of resistant strain.Conditions (1–3) discuss pathogen biology such as invasiveness and dominance of one strain on the other under different parameters such as rate . Increasing antibiotic consumption rate ah increases the range by extending h0, see Fig. If drug-resistant strains have a transmission fitness advantage (which may be induced by antibiotic consumption), then its population will grow and system will evolve towards coexistence. The relative fitness of both strains determines the span of coexistence and it also depends on the niche created by antibiotic consumption rate In the numerical simulation, we mostly focus on the transient dynamics of the model system to see how the integrated model (8) connecting three domains of human population, creates a reinforcing cycle to initiate the development of resistance in population. Figure mentclass2pt{minimh, i.e. h(0), which indicates economic status of the population in the beginning, and h0 which signifies education and awareness-level of individuals in the population. For example, low h(0) represents a population with poor economic status, but lower h0 represents relatively higher education and public health awareness in the population  together with lower h0 characterizes richer or developed countries, whereas lower h(0) together with high h0 represents underdeveloped countries.To investigate how socio-economic growth factors can promote the drug-resistance in the population, we assume that the resistant strain is already circulating in the population. In our model framework, we also differentiate populations based on socio-economic growth characterized by two important parameters in our model: the initial value of the variable see Fig.  in SI. Tz(t) for different values of h(0). As this shows, the population with higher h(0) (representing relatively developed country), it takes 4 to 5 times longer duration to stabilize the resistant commensal compare to population with lower h(0). Moreover, this has equal effect on the economy and volume of antibiotic use by individuals in the population. This same scenario we have observed in many countries today – countries with lower-middle (LMIC) and upper-middle (UMIC) income , and the area bounded by curves of h(t) and antibiotic use ah(t) for different values of h(0)  increases. However, the the amount capital reduction also decreases with higher economy . Taken together, these results clearly explain how countries with lower economy can quickly develop a huge burden of community-acquired drug-resistance by increasing the volume of antibiotic misuse, and damaging the socio-economic growth.Figure ome Fig.  accumulasee Fig. , and stesee Fig.  as h(0) omy Fig. , but theh0) accumulates the resistance much faster than population with higher education level (lower h0), though altogether the effect is less compare to economy h(0)  antibiotic consumption. Figure To characterize the relation between development of drug-resistance and antibiotic consumption, we also plot the stabilization time of resistant strain with the volume and the duration of antibiotic use. As the Fig. cz in model equations  in all three time series for different values of amount of aid and time-to-aid. As observed in the Fig. Our theoretical framework explores the development of community-acquired antibiotic resistance as a consequence of antibiotic use, and discuss the implication of feedbacks in the dynamics from socioeconomic factors such as income, education and awareness. The model puts together population ecology of infection disease, antibiotic consumption and economic growth forming a vicious cycle, and predicts that the population acquires high burden of resistance in the long period of time that eventually leads the population to poverty. Empirical testing of such feedback loops or parameter estimation of such reinforcing dynamics among different components requires high-resolution data on transmission of resistance, antibiotic use, and impact of disease on the economic growth at both population- and individua-level. To our knowledge, there is rarely such data available in public repositories, and thus it becomes a serious challenge to test our theory. Instead, we allow our model to test for a more approachable goal of determining the plausibility, that is, can our model predicts a long term trajectory to reflect the empirical pattern observed in such population-level data?Klebsiella sp. and E. coli across different countries and the per capita gross national income (GNIP). As easily observed, the burden of resistance is negatively correlated with the gross income across countries, and this highly nonlinear negative correlation suggests that there is a possible interaction between these two components through some feedback loop such as one described above. To characterize empirical pattern in the data, we first perform a clustering analysis using Gaussian Mixture Model (GMM), which is commonly used technique in statistical data analysis for grouping data points or set of objects in such a way that data points in the same group are similar to one another in some sense and distinct from point in other groups. Detailed discussion on algorithm and results from the analysis are given in the supplementary information. The posterior probability obtained from the GMM indicates two components in spatial distribution of the dataset, where contours define the measure of dispersion of data points from the centroid of clusters under different confidence interval use, that not only have the potential to demonstrate the divergence in drug-resistance profile among different populations, but also explains the ever-growing disparity in the global economy. The nonlinear interactions between income and health, and its consequence have been pointed out in many literatures, but how feedbacks between economy and health can generate self-reinforcing process by altering individuals behavior has been demonstrated in the present study. Empirical studies suggest that individuals from LMICs choose self-medication to avoid high treatment cost, and thus pointing towards a consistent increase in the gradient of antibiotic consumption. Our model also exhibits a similar pattern showing a negative relationship of drug-resistance with gross income or capital of populations. Low education and lack of awareness are other factors that promote self-medication. Currently, it has been observed that even the educated population of developing countries are indulged into this defective practice such as in India59, although the impact and effectiveness of foreign aid in developing countries depend on optimal allocation and coordination of the budget60.Theory from physics states that a self-reinforcing process – which is made of chain of complex events – continue in the direction of their momentum until an external factor intervenes and breaks the cycle. Our simple model also suggests that economic aid from government of countries or funding agencies can improve the present situation of drug resistance by perturbing the self-reinforcing feedback loop, although a late response may not be very effective. More the amount of aid and earlier the response, slower the development of resistance, and hence better the economic growth in population. Thus, providing monetary aid in the form of reduced treatment cost, inexpensive medicines and diagnostics are necessary for middle and low income countries, but that too before the establishment of resistant strain in community. Development aids can yield everlasting economic and health boon for the developing countries. Several international funding agencies such as GHIT, MOFA and MHLW in Japan, and Bill & Melinda Gates foundation in US are working to combat drug-resistance in developing countries. They are providing fund for development of new medicines, vaccines, and diagnostic tools to combat multi-drug resistant disease like HIV/AIDS, tuberculosis, malaria61. Here we consider linear production production function, which is a simpler approximation of actual constant-elasticity substitution (CES) function. Human behavior and social interactions are other issues that influence the antibiotic consumption in community36. Our study also motivates those who are readily curious to examine the interdependence of antibiotic resistance and economic by incorporating other socio-economic parameters like nutrition, hygienic level, lifestyle, living conditions, which serve as potential transmission factors of infection, along with migration, reproduction, and climate change that may expand the practicality of the model.While our theory provides a framework to explore such a complex system like antibiotic resistance, the model has been simplified in several aspects. There are scopes for further improvement. We examine the model in the absence of two biological mechanisms – mutation and plasmid transfer – which are important components for the selection and emergence of multi-drug resistant pathogens in population. Also, the transmission mechanisms of different pathogens are different – for example, malaria (vector-borne), HIV/AIDS (exposure to body fluid) and tuberculosis (Airborne). Our basic model may be improved and analyzed by integrating those specific characteristics of the pathogens. The model can also analyze the effect of the poor drug quality, which is another critical issue in selection and emergence of drug-resistant strainsSupplementary InformationSupplementary Dataset 1