Glycine- and arginine-rich (GAR) motifs with different combinations of RG/RGG repeats are present in many proteins. The nucleolar rRNA 2′-O-methyltransferase fibrillarin (FBL) contains a conserved long N-terminal GAR domain with more than 10 RGG plus RG repeats separated by specific amino acids, mostly phenylanalines. We developed a GAR motif finder (GMF) program based on the features of the GAR domain of FBL. The G-X-R-G-X-G-X-R-G pattern allows the accommodation of extra-long GAR motifs with continuous RG/RGG interrupted by polyglycine or other amino acids. The program has a graphic interface and can easily output the results as .csv and .txt files. We used GMF to show the characteristics of the long GAR domains in FBL and two other nucleolar proteins, nucleolin and GAR1. GMF analyses can illustrate the similarities and also differences between the long GAR domains in the three nucleolar proteins and motifs in other typical RG/RGG-repeat-containing proteins, specifically the FET family members FUS, EWS, and TAF15 in position, motif length, RG/RGG number, and amino acid composition. We also used GMF to analyze the human proteome and focused on the ones with at least 10 RGG plus RG repeats. We showed the classification of the long GAR motifs and their putative correlation with protein/RNA interactions and liquid–liquid phase separation. The GMF algorithm can facilitate further systematic analyses of the GAR motifs in proteins and proteomes. Eukaryotic protein-coding genes may acquire some novel features to accommodate the encoded proteins in the enormously large and complicated cellular environment. Fibrillarin (FBL), an rRNA 2′-O-methyltransferase (MTase), has a long N-terminal GAR domain with diverse combinations of arginine–glycine–glycine (RGG) or arginine–glycine (RG) repeats in eukaryotes but not Archae . On the Membrane-less organelles (MLOs) or numerous RNP bodies organize and function through the liquid–liquid phase separation (LLPS) mechanism to coordinate thousands of simultaneous molecular reactions spatiotemporally . NucleolIn addition to FBL, two other nucleolar proteins, nucleolin (NCL or C23) and GAR1 , also contain long GAR domains . Human NG, NGN-dimethylarginines (ADMA) surrounded by glycine residues in FBL and NCL, indicating post-translational modification of arginines in GAR domains , di-RGG[RGG(X0-4)RGG], tri-RG[RG(X0-4)RG(X0-4)RG], or di-RG[RG(X0-4)RG] motifs defined previously [The rRNA 2′-O-methyltransferase FBL is a major nucleolar protein for rRNA processing. We analyzed the N-terminal GAR domains in FBL from evolutionarily distant model organisms and showed their features . The loneviously . This paGMF analyses of FBL as well as two nucleolar proteins NCL and GAR1 in five vertebrate species showed the potential of the program to help inspect the domains through evolution. In Besides the FNG proteins, we analyzed other typical human RG/RGG-repeat-containing proteins listed in the review by Chong et al. . GMF anaIdentifications of long GAR domains in NCL or FBL are connected with arginine methylation in these domains ,11. GAR1The RG/RGG-repeat-containing proteins analyzed in Most of the GAR-motif-containing proteins listed in this study are components of different MLOs or RNPs. Different GAR motifs, together with other regions in the proteins, determine their subcellular distribution. Besides ionic interaction, the guanidino groups can also form π stacking and cation-π stacking. Glycine is the smallest and most flexible amino acid to tolerate a wide range of backbone arrangements. The unordered, extended, and flexible RGG/RG-rich motifs can provide multivalency for intra- or inter-molecular interactions for phase separation . Argininamyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) [We also explored the whole human proteome using GMF for more long GAR-motif-containing proteins. The six long GAR domains in FBL, NCL, GAR1 (GAR-C), EWS, TAF15, and Lsm14a with more RGG than RG repeats have all been analyzed in n (FTLD) . The lonn (FTLD) . Both hnn (FTLD) .Among the 10 other proteins containing more RG than RGG repeats, 3 are nuclear proteins containing zinc fingers. ZC3H4, containing two long GAR motifs, is an RNA-binding protein localized at chromatin to suppress transcription of non-coding RNAs . Both moA few other proteins show chromatin association and/or are related to epigenetic modification. CHTOP can bind to PRMT1, as its full name is “chromatin target of PRMT1 protein” , and proRGL/(M)DDDRG repeats within a region with 25 approximate tandem repeats. This specific long GAR motif with RG repeats separated by multiple negative-charged Ds is also a mixed charge domain (MCD). MCDs with multiple RD repeats promote nuclear speckle condensation [Two cytosolic RG-rich proteins are involved in translation. The long GAR motif in initiation factor 3 subunit A (eIF-3A) contains 5 tandem PRensation . Whetherensation ,47.In summary, GMF can show the pattern, the position, the numbers of RG/RGG repeats, the non-GR amino acids in the motifs, the coverage, the G/R ratios, and the percentages of G, R, and other amino acids in the motifs and thus can provide critical information for further evaluation of the motifs in LLPS. The GMF program can be a starting tool to facilitate the analyses of GAR motifs in proteins through evolution as well as to design putative therapeutic targets focusing on the motifs. Further modification of the GMF program, for example, to include the analyses of the FGG/FG repeats and other elements, can improve and expand the application of the program.


Antibiotic resistance is an important public health problem. One potential solution is the development of synergistic antibiotic combinations, in which the combination is more effective than the component drugs. However, experimental progress in this direction is severely limited by the number of samples required to exhaustively test for synergy, which grows exponentially with the number of drugs combined. We introduce a new metric for antibiotic synergy, motivated by the popular Fractional Inhibitory Concentration Index and the Highest Single Agent model. We also propose a new experimental design that samples along all appropriately normalized diagonals in concentration space, and prove that this design identifies all synergies among a set of drugs while only sampling a small fraction of the possible combinations. We applied our method to screen two- through eight-way combinations of eight antibiotics at 10 concentrations each, which requires sampling only 2,560 unique combinations of antibiotic concentrations. d drugs at m different combinations requires m ⋅ 2d samples under our design as opposed to md under exhaustive screening, while provably identifying all synergies under mild assumptions about antibiotic behavior. Scientists can use our design to quickly screen for antibiotic interactions, accelerating the pace of combination therapy development.Antibiotic resistance is a growing public health concern, and there is an increasing need for methods to combat it. One potential approach is the development of synergistic antibiotic combinations, in which a mixture of drugs is more effective than any individual component. Unfortunately, the search for clinically beneficial drug combinations is severely restricted by the pace at which drugs can be screened. To date, most studies of combination therapies have been limited to testing only pairs or triples of drugs. These studies have identified primarily antagonistic drug interactions, in which the combination is less effective than the individual components. There is an acute need for methodologies that enable screening of higher-order drug combinations, both to identify synergies among many drugs and to understand the behavior of higher-order combinations. In this work we introduce a new paradigm for combination testing, the normalized diagonal sampling design, that makes identifying interactions among eight or more drugs feasible for the first time. Screening  PLOS Computational Biology Methods paper.This is a 5 experiments, which limits the search space even when employing robotics to facilitate experimentation [Antibiotic resistance poses a clinical problem for which there are few available solutions. One promising strategy is the use of synergistic antibiotic pairings whose collective potency is greater than expected . Commercnull model, i.e., a prior belief about the effectiveness of antibiotics in combination. Measures of antibiotic performance include the absolute amount of cells  [rate at which cells grow [energy released by the cells [A at a concentration that yields a 50% reduction in growth with antibiotic B at a concentration that yields an 80% reduction in growth should result in a 90% reduction in growth (the probability of AorB independently killing the bacteria); if the combination has an efficacy greater than 90%, then it is called synergistic. In contrast, the HSA model posits that the effect of a drug combination is equivalent to the maximum of the effects of each drug used by itself. In the preceding example, B is the highest single agent, with an 80% individual reduction in growth, so any combined effect above 80% is considered synergy. Under the Loewe model, antibiotic doses combine linearly, so that combining antibiotic A at half of its minimum inhibitory concentration (MIC) and antibiotic B at half of its MIC should result in an inhibitory drug . If the combination is inhibitory at a lower concentration, it is considered synergistic under the Loewe model. We direct the reader to Foucquier and Guedj [Many methods have been developed to search this space. Much of the existing work focuses on identifying combinations with performance exceeding their “expected performance” under some 8 hours) , 7, the he cells . The thrhe cells , Highesthe cells , and Loehe cells . Under tnd Guedj  for a coCI of a dose combination measures a deviation from the null model, so that CI = 1 implies the combination follows the null model, and CI < 1 implies synergy. For effect-based null models, such as Bliss or HSA, the CI is naturally defined as the ratio of the prediction of the null model on a combination of drugs to the true effect of that combination. For dose-effect models, such as Loewe, the CI is defined relative to underlying isoboles of the same growth level. The Fractional Inhibitory Concentration Index (FICI) is the CI associated with Loewe synergy; an FICI of 1 means the drugs interact according to the Loewe Model [A at B at A + B is therefore no greater than A complementary approach is to define an appropriate combination index (CI) on the space of antibiotic combinations at specific concentrations , 13, 14. synergy . The FICtotal synergy, which captures the combination’s performance relative to its individual components, and emergent synergy, which captures the incremental benefit over any subset of the combination; these notions have been defined relative to both the Bliss [data-driven predictive models trained only on pairs of drugs and then evaluated on three or more drugs, such as the dose model [Recent research has focused on identifying synergy among more than two drugs. When moving to higher order interactions, a distinction emerges between he Bliss , 16, 17 he Bliss  null modhe Bliss . In respse model , pairs mse model , 21, andse model , 22, 23.8 measurements are required to exhaustively test eight drugs at 10 concentrations each. Strategies to overcome exhaustive sampling fall into two categories: parametric modeling and experimental design. The former approach applies concepts from machine learning to build parametric models that can potentially predict all possible drug combinations accurately but can be learned using only a fixed number of parameters. Models of this form include the previously mentioned dose [Given a specific definition of synergy, a second major challenge is the high measurement burden of identifying synergistic combinations. For example, 10ned dose  and pairned dose  models, ned dose  or gene ned dose ; and thened dose , which ldiagonal sampling, where the relative proportions of the antibiotics remain fixed but the absolute quantities vary [The experimental design approach is a complementary strategy that reduces the amount of data to be collected, sometimes at the cost of data fidelity. For example, some studies severely restrict the number of doses per antibiotic combination  in orderies vary , 18, 27.ies vary , 23, to normalized diagonal sampling (NDS). The MECI has dual advantages over previously proposed metrics. It can be efficiently identified in high dimensions using the NDS design; under realistic assumptions about the behavior of antibiotics in combination, we prove that the NDS design finds the MECI with exponentially fewer samples than the full factorial experiment that samples all drugs at all combinations of concentrations. Finding the MECI of an 8-drug combination using 10 concentrations requires only 10 ⋅ 28 ≈ 2500 samples, whereas finding the FICI in the same setting via the full factorial design would require an infeasible 108 samples. The second advantage of the MECI is the flexibility it gives the experimentalist to capture clinically relevant drug combinations. The definition of the MECI includes a normalization factor for each drug, and the choice of normalization can be tailored to the goals of the synergy study at hand. We present two examples of the normalization factor in Section 2.3.This work makes three major contributions: (1) we develop a novel CI, the Minimax Effective Concentration Index (MECI), which naturally extends the FICI and HSA models; (2) we present a theoretical framework for determining total and emergent synergies based on the MECI; and (3) we propose a new experimental design for provably identifying the MECI, called MECI, which captures the idea of avoiding high doses by minimizing the highest single antibiotic’s concentration  among antibiotic combinations that are “effective” at inhibiting growth. The precise definition of an “effective combination” is specified by the practitioner but could, for example, represent whether or not growth at a predefined time point remains below a pre-specified threshold.In clinical practice the goal is to administer antibiotic combinations that are effective while avoiding high doses, which may cause adverse effects. Antibiotic doses are measured relative to various metrics, such as the strain-specific MIC or species-specific breakpoints, determined by bodies such as the European Committee on Antimicrobial Susceptibility Testing (EUCAST) . In thisd} index a set of d drugs, where drug i will be tested at m − 1 concentrations χi = {xi,1, xi,2, …, xi,m−1}. The concentrations of drug i are normalized to concentration Ni for analysis purposes so all drugs can be compared on a similar scale. In our experiments, we chose to test each drug at the same set of normalized ratios Given a definition of an effective drug combination, we can now define the MECI. Let Ω = {1, 2, 3, …, d drugs in Ω at their m − 1 concentrations. A single xi encoding the concentration of drug i (or xi = 0 if drug i is absent). The set md experimental conditions that would be tested in the full-factorial experimental design.Define minimax concentration of any Minimax Effective Concentration Index (MECI) is the smallest minimax concentration among all effective combinations i}) of a single antibiotic i is the normalized concentration at which i is individually effective. For example, if Ni is the MIC of drug i and a drug is considered “effective” if it completely inhibits growth, then MECI({i}) = 1.We define the TSS measures the reduction in maximum concentration attainable by the combination as compared to each individual drug. For any combination of drugs Ω, it can be expressed mathematically asNi is the MIC of each drug, then the denominator mini ∈ ΩMECI({i}) = 1, and the TSS is identical to the MECI. However, if the normalization can potentially be very far from the MIC, reporting the TSS ensures that a combination must improve upon its best single ingredient in order to be considered synergistic.When screening for synergy, it is important to identify combinations where each antibiotic’s inclusion is justified by the effectiveness it brings to the combination. Indeed, synergies among lower order antibiotic combinations are likely to be detected in higher order combinations that include those same drugs; therefore, finding clinically useful combinations requires determining whether all antibiotics in a combination are necessary to achieve a synergistic effect. To this end, we develop two scores for interpreting whether a drug combination provides a meaningful improvement over its components: the Total Synergy Score (TSS) and the Emergent Synergy Score (ESS). The ESS to capture the improvement offered by the combination when compared to any of its subsets, following the intuition that the combination must significantly improve upon any subset of its ingredients to justify the use of additional drugs. The ESS is defined asTSS(Ω) ≤ ESS(Ω) ≤ 1. An ESS score of 1 indicates that some proper subset of Ω has an MECI at least as small as Ω itself; this can occur in instances of indifference or antagonism. The TSS and ESS scores identify only synergy, not antagonism; for a discussion of antagonism, see Section 4.We further define the synergy be restricted to combinations with an ESS of 0.25 or below, while combinations with an ESS between 0.25 and 1 should be interpreted as evidence of weak synergy. These interpretive criteria are consistent with the FICI interpretation of weak synergy when two drugs are tested according to the NDS design, since the cutoff FICI of 0.5 and the cutoff ESS of 0.25 both occur when two drugs are combined at While any ESS less than 1 indicates emergent synergy, we suggest as interpretive criteria that conclusions of For comparison to an established metric, we note that the FICI, like the MECI, can be written as the solution to an optimization problem. The FICI of combination Ω is given byWe conclude by observing that the MECI corresponds to a dose-effect interpretation of the HSA model. Intuitively, the MECI minimizes the minimax concentration among effective combinations, where the minimax concentration is exactly the highest  concentration of a single agent. This connection is made precise in Ni, which allows the experimentalist to tailor the choice of Ni to the goals of the investigation. In particular, different choices of Ni lead to different interpretations of synergy. For example, a natural choice of normalization Ni is the MIC for each drug i. With this choice, a low ESS or TSS indicates that the combination is effective at concentrations far below the individual drugs’ MICs, which aligns with the Loewe  conceptions of synergy.The MECI provides flexibility in the choice of normalizing metric Ni could be a strain-independent metric like the EUCAST breakpoint, which is the highest concentration at which the organism is considered sensitive to the antibiotic [MECI ≤ 1.Another meaningful choice of tibiotic . For exaNi but not another, or for the strength of the interaction to depend upon the choice of normalization. As a result, it is important for the choice of Ni to reflect the scientific or clinical goal of the experiment and for this choice to be reported along with the synergy scores.We observe that it is possible for a drug combination to be synergistic with respect to one normalization NDS design, an experimental design that samples all combinations of drugs in Ω at equal concentrations relative to the normalization Ni. We begin with a set of ratios at which each drug will be tested, cj = 2j−, in which case the drugs are tested on a two-fold dilution gradient. The spacing and number of concentrations should be chosen to balance the resolution of the synergies detected with the number of experiments required, while testing a sufficient range of concentrations so that all drug combinations can be observed at both effective and ineffective concentrations. For all subsets Ω′ ⊆ Ω, the NDS design evaluates the combination Ω′ at all m − 1 normalized concentrations {c11, c21, …, cm−11}, where 1 represents a vector of all ones of size |Ω′|. In Section 3.1 we prove that, under mild assumptions about the behavior of antibiotic combinations, NDS provides strong theoretical guarantees on the detection of synergy. In particular, the design provably identifies the MECI from a collection Ω of d antibiotics without having to sample all We introduce the md wells to screen d drugs at m concentrations each. The NDS design significantly reduces the required number of wells by testing along the “diagonal” − testing each combination with all drugs present at the highest concentration, then at the second-highest concentration, and so on. Under the NDS design, each of the 2d drug combinations requires only m wells, for a total requirement of m ⋅ 2d wells. For eight drugs and 10 concentrations per drug, this requires m ⋅ 2d = 10 ⋅ 28 = 2, 560 wells, or about twenty six 96-well plates. This is experimentally feasible, whereas md = 108 wells (requiring approximately 106 plates) is not.Exhaustive tests for synergy are conducted with checkerboard assays see  requirineffectiveness metric that specifies whether the antibiotics tested were effective or ineffective at the given concentrations x. For our experiments, we considered an antibiotic combination effective in inhibiting bacterial growth if the area under the growth curve (AUGC) was less than a predefined threshold. The AUGC measures the area under the curve of optical density (at 600nm) over time after subtracting the background optical density reading. The area was approximated using a trapezoidal Riemann sum, taken in 15 minute increments over the 24 hours following inoculation. We also considered quantifying effectiveness using the maximum growth rate, computed as the maximum slope of a five-point moving average of the log optical density versus time curve; since this technique agreed with the AUGC, we did not include it in our results. Any measurement that captures the notion of antibiotic effectiveness could be used to compute the MECI.Computing the MECI requires the analyst to specify an E. coli strain MG-1655  in BBL Mueller Hinton II Broth (Cation-Adjusted) . All experiments were performed in duplicate in 96 well plates and were fully randomized across well, plate and day of experimentation with the use of the OT-2 liquid handling robot . In each well, antibiotics were diluted into 200 μL of media, then 50 μL of a 10−4 dilution of E. coli overnight culture, incubated at 37°C in BBL Mueller Hinton II Broth (Cation-Adjusted), was added. A fresh preparation of overnight culture was used for each day of experimentation. Plates were sealed with a gas-permeable sealing membrane  and incubated at 37°C for 24 hours, during which time optical density readings (600nm) were taken at 15 minute increments using a Biotek BioStack II coupled to a Biotek Epoch II Microplate Spectrophotometer. Plates were orbitally shaken for 15 seconds prior to each reading.Experiments were performed using the wild-type https://journals.asm.org/journal/aac/abbreviations), and MICs determined experimentally.Eight antibiotics were chosen for their diversity of class and mechanism of action: ampicillin, aztreonam, ceftazidime, chloramphenicol, ciprofloxacin, gentamicin, trimethoprim, and tobramycin. Antibiotics were dissolved in water with the exception of aztreonam, ceftazidime and trimethoprim, which were dissolved in DMSO, and chloramphenicol, which was dissolved in ethanol. The full-factorial sampling design is intractable beyond a small number of antibiotics, which motivates the need for a more efficient design. We begin with a proof of correctness for the NDS design, showing that it identifies the MECI using significantly fewer measurements than the full factorial design. The NDS design samples along the diagonal in multi-antibiotic concentration space, letting us find all synergies among combinations of up to eight antibiotics at 10 concentrations with only 2,560 samples. This scale of experiment can be effectively pipetted by hand or using robotics, as we did here. Using robotics enabled us to perform complete pipetting randomization, minimizing plate position effects. In combination, the NDS design and robotics let us confidently identify synergies while mitigating the influence of experimental artifacts that complicate large-scale experiments.We now show that the NDS design provably identifies the MECI of a set of drugs using significantly fewer samples than the full factorial design. Since the NDS design for a set of drugs Ω also involves performing the NDS design for all sets Ω′ ⊂ Ω, it correctly identifies the MECI, TSS, and ESS for each Ω′ ⊆ Ω.A to a fixed concentration of antibiotic B does not exhibit paradoxical growth, that is, once increasing the amount of A reduces the level of the measured response , further increasing A cannot increase the response. Next, we observe that a fixed-ratio combination of drugs itself behaves like an antibiotic, with its own dose response curve and its own interactions with other (combination) antibiotics. This perspective lets us extend the assumption to the general case where A and B are themselves antibiotic combinations, stated formally in Definition 3.1. When the effectiveness measure in the definition of MECI behaves according to Definition 3.1, we can declare many combinations ineffective without ever measuring them because they lie between points already measured to be ineffective. Without such an assumption, we would have no way to know whether a point x is effective without testing it. The formal theorem statement is provided in Theorem 3.2; the proof is available in The proof begins with an assumption that adding an antibiotic Definition 3.1 . Let Ω be a set of antibiotics. Let the vectorrepresent a fixed background concentration of antibiotics to which we add increasing amounts of another antibiotic combinationWe say the set of drugs Ω does not exhibit paradoxical growth if, for allc3 > c2 > c1 ≥ 0, the responsesatisfiesA is added to the base combination B. We specifically note that this assumption does not preclude so-called “hyper-antagonism,” where the addition of A to B yields a less effective response than B alone. Such behavior is allowed under our assumption as long as the following condition holds: once increasing concentration of A starts reducing the response r, further increasing the concentration continues to reduce the response.Eagle effect, first observed by Eagle and Musselman [How plausible is the assumption of non-paradoxical growth? When antibiotic effectiveness is measured in a broth dilution assay, as in our experiments, we are aware of no published evidence of paradoxical growth. When effectiveness is measured using a survival assay, in which bacteria are first treated with antibiotics for a specified time and then the culture is grown in the absence of antibiotics, paradoxical growth is known as the usselman  and reviusselman . If any x as effective whenever the response falls below some threshold (r(x) ≤ t). Then, as long as the response behaves according to Definition 3.1, we can identify entire regions of the antibiotic combination space as ineffective using only measurements on the boundary of the space. This leads to our main result: the correctness of the NDS design in the absence of paradoxical growth.Suppose we define a combination of drugs at a given concentration Theorem 3.2Assume the set of drugs Ω does not exhibit paradoxical growth (Definition 3.1). Then, the NDS design applied to Ω identifies MECI(Ω′) for all Ω′ ⊆ Ω.MECI(Ω) with significantly fewer samples than the naive full factorial design: the full factorial design requires md samples, while the NDS design requires only m ⋅ 2d.The proof of Theorem 3.2 is deferred to 8 combinations of the 8 drugs shown in Enterobacterales.Using the NDS design, we performed experiments to screen all 2Ni for the first experiment, used for both the NDS design and for calculating the TSS and ESS, was the EUCAST susceptible breakpoint [Enterobacterales. As motivated in Section 2.3, normalization relative to the breakpoint provides a strain-independent measure of antibiotic interactions, which may be more relevant to how drugs are prescribed in combination clinically. We tested concentrations across 10 steps of a two-fold dilution gradient so that any interactions could be identified within a power of two.Effectiveness was specified as complete inhibition of growth, measured by AUGC (as described in Section 2.5). The normalization constant eakpoint  for Ente2 ESS score of 0 indicates the absence of synergy). Among all 28 combinations tested, no combination met our synergy threshold of a log2 ESS of −2 or lower (4-fold synergies), although several combinations exhibited weak synergy with a log2 ESS of −1. This indicates only weak synergy among all combinations of these eight antibiotics, consistent with previous studies that found synergy to be rare [2 emergent effect was zero. 8 combinations and a Loewe analysis showing the absence of strong Loewe synergy along the diagonals tested, is available in We computed MECI, ESS and TSS for each combination of two through eight antibiotics. Histograms of the ESS and TSS scores across all combinations, plotted by the number of drugs combined, are shown in  be rare , 23, 31.guarantees that, among these eight drugs, no combination has a log2 ESS score of −2 or less when ESS measures synergy relative to the EUCAST breakpoint. In particular, the result guarantees that performing the full factorial experiment would result in the same ESS and TSS scores that we found with the NDS design. If the goal is to minimize the maximum amount of drug applied relative to the EUCAST breakpoint, we therefore conclude that no significant gains are possible by combining this set of drugs against the strain we tested and under our experimental conditions.We emphasize that our results come with strong guarantees under the assumption that the drugs do not exhibit paradoxical growth. Since our experiments were conducted according to the NDS design, Theorem 3.2 Ni. To demonstrate the utility of normalization, we repeated the preceding experiment but with all concentrations normalized to the MIC of the individual drugs , not to maximizing the minimax ineffective concentration (identifying the greatest antagonism). The difference is due to an asymmetry in Definition 3.1; it is possible for the response to increase and then decrease as antibiotic B is added to a fixed concentration of A , but it is not possible for the response to decrease and then increase . Consequently, while an ESS of 1 indicates a lack of synergy, an ESS of less than 1 does not rule out the existence of antagonism in some part of the antibiotic combination space. Notwithstanding this limitation, we believe synergies are typically the most clinically relevant, so the inability to find antagonisms is therefore not too limiting in practice.While the NDS design provably identifies all synergies relative to a given normalization, it is limited in that it cannot provably identify all antagonisms. Recall that the MECI quantifies the smallest minimax concentration among drug combinations measured to be effective. Another perspective on this optimization problem is to consider multiple rays representing different concentration ratios , which The NDS design makes provably identifying high-order interactions experimentally feasible for the first time. With this new method, it is now possible to screen for interactions among more antibiotics, across additional strains, and on multiple media, providing information on whether synergies are conserved across these variables. The NDS design is simple to implement: given a definition of antibiotic normalization , it samples along the diagonals in multi-antibiotic space. We conclude by noting that the interaction among biologically active agents is not only of interest for antibiotics, but also for many other biologically active agents, such as immunosuppressants , environS1 Appendix(PDF)Click here for additional data file.S2 Appendix(PDF)Click here for additional data file.S3 Appendix(PDF)Click here for additional data file.S4 Appendix(PDF)Click here for additional data file.S1 Data and Code(ZIP)Click here for additional data file.S1 Text(PDF)Click here for additional data file.


This systematic review aims at providing an overview of the state of the art regarding smart wearable systems (SWS) applications to monitor the status of patients suffering from vascular disorders of the lower extremity. Peer-reviewed literature has been analyzed to identify employed data collection methods, system characteristics, and functionalities, and research challenges and limitations to be addressed. The Medline (PubMed) and SCOPUS databases were considered to search for publications describing SWS for remote or continuous monitoring of patients suffering from intermittent claudication, venous ulcers, and diabetic foot ulcers. Publications were first screened based on whether they describe an SWS applicable to the three selected vascular disorders of the lower extremity, including data processing and output to users. Information extracted from publications included targeted disease, clinical parameters to be measured and wearable devices used; system outputs to the user; system characteristics, including capabilities of remote or continuous monitoring or functionalities resulting from advanced data analyses, such as coaching, recommendations, or alerts; challenges and limitations reported; and research outputs. A total of 128 publications were considered in the full-text analysis, and 54 were finally included after eligibility criteria assessment by four independent reviewers. Our results were structured and discussed according to three main topics consisting of data collection, system functionalities, and limitations and challenges. The aging of populations has prompted increasing challenges for health systems around the world due to the higher demand for care and assistance, driven by the growing prevalence of chronic conditions, multimorbidity patterns, and disability . On the Wearable devices for health research are increasing as more options become accessible and affordable, and rates of clinical approval of respective regulatory bodies increase . AmongstThe pathophysiology of the diabetic foot is caused by neuropathy, arterial occlusive disease, and trauma with secondary infection. Peripheral neuropathy leads to intrinsic muscle atrophy, leading to functional anatomical changes in hammertoe formation and the development of high-pressure zones on the plantar surface of the metatarsal heads. Repetitive trauma with walking, together with decreased sensitivity, leads to skin damage and consequent displacement of the protective plantar fat pads, leading to ulceration . AlthougVenous leg ulcers are the last and most severe stage of chronic venous disease according to the C5 and C6 classes within the Clinical Etiological Anatomical Pathophysiological (CEAP) classification, resulting from failures of the valves that connect the superficial and deeper veins, manifesting as superficial venous hypertension. Capillaries cannot withstand this high pressure for a long time, leading to a decrease in oxygen distribution and consequent ulcer development . If timeIntermittent claudication (IC) is usually associated with peripheral arterial disease (PAD), which is a highly prevalent and debilitating condition affecting around 6% of patients above 60 years of age . Lower eStudies show that the continuous monitoring of physiological parameters of patients leads to an improvement in their health condition ,24,25 anWe conducted a literature search in databases of PubMed and SCOPUS in order to identify relevant studies describing SWS focusing on the monitoring of the previously described vascular disorders of the lower extremity. We searched from inception to the date of the last search, which was performed on 25 May 2022. To improve query recall, the search queries were defined considering the terms in titles, abstracts, and author-identified keywords. Queries fundamentally included terms to identify the intended system, referencing telemedicine, sensor, and device, among other relevant reference words to find articles of interest and adding wide-ranging terms for each one of the vascular disorders, which correspond to publications addressing diabetic foot ulcer, venous ulcers, and intermittent claudication. The final queries, after refining the query and performing sensitivity analysis, are reported below. PubMed Search Query:  AND ). Scopus Search Query:  AND ).Only studies written in English and published in peer-reviewed journals or conference proceedings were considered. Considering both screening and full-text analysis phases, documents were included if they (1) present a Smart Wearable System (SWS) applicable to any of the three selected vascular disorders of the lower extremity and that have been applied with real users; (2) include the use of a wearable or portable device; (3) and contain data processing and provide output to users. Exclusion criteria include non-English publications, documents with no abstract available, letters, editorials, comments, abstract-only publications, and study protocols. In the full-text analysis, an additional exclusion criterion was considered: other reviews or documents that comprise the analysis of several works and that are not original research publications.Screening and full-text analysis phases were performed by four independent reviewers following the same strategy: the list of retrieved publications was divided into four batches with an equivalent number of publications and each batch was assessed by two different reviewers. Disagreements were resolved through consensus involving the assessment of all four reviewers. The complete list of included articles is presented in the References section ,77,78,79Regarding the data extraction phase, all articles that passed through a full-text analysis were divided into four groups and extraction occurred independently by each researcher. A random sample of 4 publications were extracted by all researchers to compare the similarity of the information extracted and to make the extraction process as homogeneous as possible. Information extracted from publications is reported in The included publications were independently reviewed by three researchers. Information extracted from publications included targeted disease; data collection ; system objectives; system outputs to the user; data science approaches to infer and predict the patient’s state and/or to deliver coaching interventions, recommendations or alerts; challenges and limitations reported; and authors’ conclusions. Analyses were carried out by three relevant thematic areas: (a) data collection through the remote monitoring of patients via wearable devices and clinical parameters; (b) system characteristics, including remote or continuous monitoring capabilities, as well as functionalities derived from basic or more advanced data processing, enabling patients and healthcare professionals with means to visualize, interpret and communicate the processed information, or receive coaching and personalized recommendations; and (c) current research challenges and limitations to be addressed.n = 2287 duplicates). In the title and abstract screening phase, a total of 3457 studies did not meet our inclusion criteria and were excluded. A total of 54 articles were finally included and analyzed.In n = 31), followed by IC (n = 17) and venous ulcers (n = 6). Original research articles published in international journals comprised the majority of the included publications (n = 50), as only four documents were conference papers [n = 9)  .In Data collection typically occurred from different types of sensors integrated into distinct wearable, implantable or portable devices. n = 31), data was still not being transmitted directly to medical centers or end-users, but rather raw measurements were downloaded from devices or visualized through software’s Graphical User Interface [In most publications   describeIn the works described by Gardner et al. (2014)  and Gardn = 19)  see . These s 19) see .n = 15), as well as the amount of time spent doing exercises, often analyzed by type and intensity of exercises or activity (n = 6)  see . PhysicaWearable technology most frequently employed in these applications included pedometers and tri-axial accelerometers in devices placed at distinct body sites, such as ankle ,45,46,47Regarding venous ulcers, force sensors placed under bandaging were used to determine the interface pressure applied by compression products that are typically applied in the ulcer area, providing means to adjust or change bandaging in an adequate time . The useGenerally, applications described in the peer-reviewed publications employed wearable devices to facilitate patient follow-up, without major data processing by Artificial Intelligence (AI) algorithms. Most projects for the targeted diseases address continuous monitoring through technology, but only nearly half of the DFU and VU-related publications described remote monitoring of patients, whereas this feature was present in only a minority of IC-related publications . A few DWearable devices used in the context of IC were implemented to help to motivate the patients to achieve their daily step goals, as part of their treatment plans defined by clinicians. No coaching or recommendation systems have been described in the assessed publications see . In factDFU was the condition for which most coaching functionalities have been implemented. Killeen et al. (2018)  developeSome enhanced functionalities comprising alerts and recommendations were found in half of the publications addressing venous ulcers. Henricson et al. (2021)  implemenIn what concerns the limitations of the reviewed publications, most studies reported small sample sizes, with difficulty in generalizing the results. In nearly all studies, the lack of robustness of the control group is highlighted, having only veterans in the study or most of the study population was male. The fact that patients volunteered was also a commonly mentioned limitation, referred to as self-selection bias regarding the interest and adherence to exercises, potentially influencing the results. Moreover, several studies drew conclusions based on results obtained using proof of concept or were carried out over a very short period.Less frequent limitations, but also reported, include lack of control over room temperature (in studies whose sensors measure this variable), sensors that record activity but do not account for the time that participants are resting or practicing sedentary activities, and results that cannot be generalized to all patients, since individuals in the sample considered in the study may be in more or less advanced stages of the disease.Furthermore, barriers were also reported in terms of adherence to the use of sensors, and technical limitations in terms of the sensors used, such as the non-accounting of asymmetries in gait or measurement failures. Lauret et al. (2014)  pointed As future challenges, recommendations to carry out more in-depth studies in the future, with larger samples and longer study times have been extensively highlighted.Concerning the quality assessment of the included publications, we employed the STARE-HI checklist. This list includes a comprehensive set of relevant principles for properly describing health informatics evaluations. The assumption is that when manuscripts submitted to health informatics journals and general medical journals adhere to these aspects, studies would be placed in a proper context and their validity and generalizability would be better judged, including the degree to which publications fit in the scope of meta-analyses in specific health informatics interventions .Vascular disorders affecting lower extremities considerably affect mobility and quality of life, and they tend to become more prevalent as populations age. The management of these diseases relies on medical appointments where treatment plans are defined according to the patient’s condition, comprising pharmacological interventions and physical activities that the patient needs to perform to control and improve their health status. The evolution of information technologies in the health sector, such as monitoring sensors embedded in wearable devices, has opened a possibility for a shift towards personalized healthcare, based on the remote and continuous monitoring of patient parameters. The use of smart coaching techniques to guide and motivate patients to adopt healthy behaviors, and support healthcare professionals during decision-making, are potential gains that may be associated with the use of wearable technology.Two main sub-sections characterize a complete wearable medical device : the harResearch on SWS applied to diseases has shown an increased trend in recent years see . This isMost of the reviewed publications presents novel devices for research purposes and are at proof-of-concept stage. However, in recent years, a variety of commercial products have been introduced and a considerable number of publications described the reuse of such commercially available devices. For instance, devices dedicated to fitness monitoring, such as wrist or arm bands and smart watches, namely Fitbit, which can provide real-time activity data under minimum hardware and computing abilities, thereby constituting cost-effective solutions for monitoring patients suffering from vascular disorders of the lower extremity. Moreover, these devices are usually capable of performing many other functions related to the smart phone .A substantial share of the examined studies described technologies that allow continuous monitoring, although the minority enabled remote access to patient data. This occurs because several projects are still in the proof-of-concept stage or at most mention a follow-up provided by healthcare professionals based upon the data measured by the monitoring sensors, such as integrating wearable devices into exercise programs for IC patients for monitoring physical activity, but without major data processing. Automated recommendations, coaching, or alert feedback are still scarce. Applications addressing DFU and VU described some functionalities implemented at this level, usually carried out by smartphones or sent directly from wearable devices, warning the patient on moments to reduce walking or when there is a risk of ulcer development, such as abnormal plantar pressure or temperature patterns, displaying useful information to patients and clinicians. Nevertheless, the assessed publications indicate that clinical knowledge and evidence on IC and DFU is robust enough to support future initiatives and thus improve the current technologies, especially with regard to the effects of clinical parameters, behaviors, and risk factors associated with the evolution of these conditions. VU remains an underexplored field, and there is a plethora of opportunities to develop innovative SWS in this field, namely, to guide compression therapy and help clinicians to check whether patients are properly following medical recommendations.Finally, published research lacks clinical validation and evaluation of the impact on health outcomes and well-being. In fact, Macdonald et al. (2021)  reportedThere is a rising need for sustainable healthcare, with personalized treatment and management of patients, with increased proactivity of individuals regarding their own health condition. To address these needs by means of SWS and achieve a desirable efficacy, a robust infrastructure needs to be implemented for large-scale deployment of wearable devices integrated to conventional healthcare facilities. This integration requires challenges to be overcome at both clinical and operational levels. In terms of hardware, wearable devices may not be easily maintained, and they are affected by battery issues . In termFrom a clinical point of view, as future challenges, we highlight the recommendations to carry out more in-depth studies in the future, with larger samples and longer study times. Future work perspectives presented by the reviewed articles included mostly the refinement of current technologies and further evaluation and clinical validation of existing projects.We reviewed the current state-of-the art on SWS for monitoring vascular disorders affecting lower extremities, summarizing aspects of data collection, existing wearable devices and sensing solutions, system features, limitations, challenges and future needs. Although this is still and emerging field that have been growing just recently, important achievements have been made, mostly due to progresses in areas such as wearable sensors, embedded systems, material science, IoT communication and cloud computing. Most publications presented novel devices enabling continuous monitoring, but systems allowing remote monitoring and smart coaching and recommendations are still less common in the field of vascular disorders affecting the lower limb. Several projects concerning IC employed novel or commercially available sensing devices to perform follow-up and manage exercise programs based upon the measured activity data, without using or implementing advanced analytics. Recommendations or coaching feedback, whenever available, were usually carried out by smartphone applications, warning diabetic foot patients when they should offload or whenever abnormal temperature patterns indicating elevated risk of ulcer development are detected. Clinical knowledge and evidence regarding the association between physiological and motion parameters and disease progression are robust for DFU and IC, proving evidence and clinical knowledge that can be used as basis for further developing recommendations and coaching level functionalities. Research on VU monitoring is still scare, and the available projects focused mostly on monitoring pressure under compression apparatus and wound moisture. Overall, most projects lack clinical validation, as works are mostly at proof-of-concept stage, focusing on pilots or small-scale preliminary studies. Future work tends to focus on the refinement of existing technologies and further clinical validation, providing evidence on the efficacy of such devices in providing actual gains in health outcomes, which in turn is critical to increase general acceptance by patients and clinicians.


Using coal gangue (CG) as a building material does not only reduce the disposal of industrial waste and promote the resource utilization of solid waste, but also solves the excessive consumption of sand and stone in construction. This study experimentally investigated calcining ceramisites from CG raw materials and the mechanical properties of CG ceramsite concrete were studied. Additionally, the physical, chemical and composition changes of CG before and after calcination were observed using scanning electron microscopy and X-ray diffraction analysis (XRD). The experimental results reveal that calcination can reduce the density, increase the strength, increase the porosity of CG, and change the microstructure and mineral composition of CG. Finally, there are great differences between coal gangue ceramsite concrete and ordinary concrete in the variation of compressive strength with time and the relationship between elastic modulus and compressive strength. In this paper, the existing formula is modified according to the experimental data. Generally, one ton of CG is discarded for every 10 tons of produced coal5. Statistics show that 5–6 billion tons of CG are now stored, and the accumulation increases at the rate of 150–200 million tons per year in China7. Presently, most CG is disposed by simple stacking, and there are approximately 2600 large-scale CG hills in China, which amount to approximately 15,000 hectares10. This does not only result in resource wastage, but also causes environmental pollution and threatens the health and well being of local communities11. With the implementation of China’s green and sustainable development strategy, the rational and comprehensive utilization of CG will bring remarkable economic, environmental, and social benefits.Coal gangue (CG) is a type of industrial solid waste produced by the process of coal excavation and separation13. Although there are different types of CG with different properties owing to the different origins of CG, most chemical and mineral components are similar to natural aggregates (NAs). Therefore, a more direct and effective method of using CG is to use it as a coarse or fine aggregate in concrete after crushing16. However, CG aggregates (CGAs) have looser structure and exhibit lower physical properties compared with NAs. Therefore, the strength of concrete with CG as the aggregate is lower than that of concrete with NA as the aggregate under the same mix proportion19. Therefore, to improve the mechanical properties of CGA concrete and enable its adoption in more construction fields, it is necessary to improve the physical and mechanical properties of CGA.Existing research on the main application methods of CG in building materials includes research on the production of cement, burning bricks, concrete hollow blocks, and aerated concrete2, Al2O3, Fe2O3, CaO, MgO, NaO, and K2O22. Calcined CG is an effective method for improving the aggregate properties. Carbon and various other components in CG can be removed during calcination at the temperature range of 500–800 °C, and the kaolinite in CG can also be gradually transformed into metakaolin24. Zhang et al.25, Cao et al.13, and Guo et al.26 pointed out that CG has high activity after calcination at the temperature of 700–800 °C. The secondary hydration reaction of metakaolin and cement hydration products  can improve the mechanical properties of CGA concrete. Yang et al.27 found that high temperature calcination can cause the internal chemical reaction of CG, eliminate unstable components in CG, generate stable substances, and cause corresponding changes to the physical properties of CG. By calcination, CGA can be converted into a lightweight and high-strength ceramsite aggregate28. Compared with ordinary concrete, ceramsite lightweight aggregate concrete has excellent properties, such as low density, high cylinder compressive strength, high porosity, high softening coefficient, good frost resistance, and excellent alkali-aggregate resistance31. Many studies36 have investigated the preparation and performance of ceramsite concrete with the objective of further improving its performance. To improve the performance of CG ceramsite lightweight aggregate concrete (CGCLAC), it is necessary to improve the physical and mechanical properties of coal gangue ceramsites. However, research on the preparation of high-strength ceramsite from CG raw materials is still relatively rare, and studies on the constitutive properties of CGCLAC are even fewer.Although the chemical composition of CG is complex, CG is mainly composed of silicon and aluminum, and contains more than a dozen elements. Generally, CG is mainly composed of oxides, such as SiOThis study experimentally investigated the production of calcining ceramisite from CG raw materials. The raw material formula and experimental process used in this study can be used as the preliminary basis for the experimental investigation of CGC. The physical, chemical, and composition changes of CG before and after calcination were observed by scanning electron microscopy (SEM) and X-ray diffraction analysis (XRD). Coal gangue ceramsite (CGC) made by this method has high strength. Moreover, this study conducted mechanical tests on concrete prepared using CGC. The variation law of strength is explored and the relationship between elastic modulus and compressive strength is put forward.37 obtained by the investigation of calcined ceramsite, the chemical composition of raw materials that is appropriate for the production of ceramsite is presented in Table 2 and Al2O3 form glass melt at high temperature, and their interaction in the liquid phase promotes the formation and growth of 3Al2O3·2SiO2. If the SiO2 and Al2O3 content in the raw material increases, the melting temperature increases, the viscosity of the liquid phase increases, the expansion becomes lower, and the strength of the raw material becomes greater. With a higher content of SiO2 and Al2O3 in ceramsite raw materials, higher temperature is required to reach a certain viscosity. The K2O, Na2O, CaO, MgO, and so on, are cosolvent, which is beneficial for reducing the melting point of raw materials. For example, when SiO2 and Al2O3 generate eutectic compounds, the melting temperature is 1713 °C; when K2O is added, the melting temperature is 976 °C; when Na2O is added, the melting temperature is 874 °C. At high temperature, Fe2O3 and C produce gas substances such as H2O, CO, CO2, and other gas substances, which are the force driving the pore expansion of ceramsite.According to Riley’s resultsThe main components of CG are clay minerals, mainly kaolinite and hydromica, and also quartz, feldspar, pyrite, carbonate, and other secondary minerals. Table Chemical reaction at 400–800 °C:Chemical reactions at 800–1100 °C:The production process of CGC includes raw material processing, granulation, and thermal processing. The CG was broken by a jaw crusher and milled by a ball mill. The raw material was screened using a 100 mesh sieve. Various raw materials were mixed according to a certain ratio to prepare pellets with a diameter of 10–20 mm. Then, the formed CGC was put into a drying box and heated to 105 °C for 1–2 h. Preheating was carried out at 300 °C for 30 min to further remove the surface moisture so as to eliminate surface cracking and bursting of CG in the calcination process caused by a sharp increase in temperature. The preheating and calcination of the sample were carried out in a preheating furnace and calcination furnace, respectively. When the CG raw material reached the preheating time at the design preheating temperature, it was immediately removed from the preheating furnace and put into the calcination furnace, which had reached the design calcination temperature of 1150 °C, and the calcination time was 30 min. The rapid cooling method was used to quickly decrease the surface temperature of ceramsite below 400 °C. When the ceramic was calcined, as the temperature changed, the internal material composition of the ball resulted in the following reaction process:2 and SO2 gas overflow, and the carbonate compounds (CaCO3 and MgCO3) and sulfides are thermally decomposed. In the calcination process, various unstable substances are gradually decomposed and discharged, and the remaining substances are not easy to decompose, which results in the more stable properties of ceramsite.The above reactions indicate that the combustion of elements such as S and C form CO2. These gases are bound by the liquid phase formed by the matrix, which results in the formation of voids during the expansion of the ceramsite volume. The amount of expansive gas and the uniformity of pores are not only related to CG, but are also directly related to the calcination temperature. When the surface produces a higher amount of viscous liquid, the amount of bound gas and the pores in the ceramsite increase, and the uniformity improves, which decreases the density of ceramsite while increasing its strength.The macroscopic and microscopic morphologies of CG before and after calcination are shown in Figs. Part 2: Test methods for lightweight aggregates (GB/T17431.2-2010)38, the physical and mechanical properties of CG should be tested before and after calcination. The performance indicators are listed in Table According to the testing methods for lightweight aggregates specified in s GB/T1741.2-20103Technical standard for application of lightweight aggregate concrete (JGJ/T12-2019)39 and Pebble and crushed stone for construction (GB/T14685-2011)40. The CG ceramsite satisfies the requirements of Class II coarse aggregates, while CG only satisfies the requirements of Class III coarse aggregates. The grade of CG used in construction can be improved by calcining.The quality of the CGC was evaluated based on the the specification of the X-ray diffractometer (JB/T 9400-2010)41 and the analysis method for clay minerals and ordinary non-clay minerals in sedimentary rocks using X-ray diffraction (SY/T 5163-2018)42. A quantitative analysis scanning method, namely, step scanning, was used in this test; the sample interval and scanning speed were set to 0.01 and 0.25 /min, respectively. The XRD test results are shown in Fig. The mineral composition of CG before and after Calcination was determined by XRD , according to  SY/T 516-201842. Quartz and kaolinite are the two major crystallized minerals in the uncalcined CG. Quartz is hard and wear resistant, which contributes to the high strength of CG, while kaolinite is a hydrous layer silicate clay mineral and a type of soil or lump with low hardness and poor stability, which is one of the reasons for CG being easy to break and having low strength. The CG contains easily-hydrolyzed and weathered chemical components, which account for approximately 15%. After calcination, the loss of original materials in CG greatly increases the proportion of quartz, which contributes to the improvement of the mechanical properties of CGC. The alumina silicate in kaolinite is calcined at high temperature to form mullite, which is a material with high strength that further improves the mechanical properties of calcined CGC. Additionally, with high temperature calcination, the unstable components in CG are transformed into stable substances in CGC. Therefore the physical and mechanical properties of CGC are qualitatively different to those of CG before calcination.In this test, 42.5R ordinary Portland cement was used as the concrete cementitious material, and an appropriate amount of fly ash was added. Local river sand was used as the fine aggregate of concrete with a fineness modulus of 3.26. The CGC with the particle size ranging from 5 to 20 mm was used as a coarse aggregate, and the water for mixing was ordinary tap water. A water reducing agent was added to the fresh concrete to ensure that the concrete slump satisfies the concrete mixing requirements. The water reducing agent dosage was 1.5–2.5% of the cement dosage, and the water reducing rate was 20–30%.Four different strength mix proportions were designed according to the needs of different engineering practices. The mix proportions of CGCLAC are presented in Table 43. A water reducing agent was added to the stirring water. Next, all CGCs, sand, and 70% water were mixed in a mixer for 10–20 s, and the cement and fly ash were then added over 30 s; the remaining 30% of water was added over 60 s. When the concrete was uniformly stirred, it was poured into the prepared mold, and then vibrated on a vibration table to be made dense. After 24 h, the mold was removed and the concrete was placed into a standard incubator with a temperature of 20 °C ± 2 °C and a relative humidity of 95% to cure for 28 days.The quantity of each raw material in concrete was calculated according to the mix proportion. According to a previous study, it is necessary to prewet CGC to avoid the difference in the fluidity of concrete caused by excessive water absorption in the mixing process of CGC. The general practice is to add 60% of water absorbed by CGC in one hour into the CGC before making the CGCLAC, such that the CGC can be fully wettedStandard for test methods of concrete physical and mechanical properties (GB/T 50081-2019)44, Standard for test method performance on ordinary fresh concrete(GB/T 50080-2016)45 and Technical standard for application of lightweight aggregate concrete (JGJ/T 12- 2019)39. The compressive strength, split tensile strength and elastic modulus were measured using a 200-ton electro-hydraulic servo hydraulic testing machine. The test device is shown in Fig. The mechanical properties of CGCLAC were tested according to ies GB/T 0081-2019General rules for measurement of length in micron scale by SEM (GB/T16594-2008)46, after the mechanical test, a test block with a surface area of up to 1 cm2 and thickness up to 1 cm was drilled from the surface of the damaged specimen using a hollow drill. The specimens were pumped into a vacuum for SEM analysis, and the microstructure of the failed specimen was observed using a scanning electron microscope .According to Ready-mixed concrete (GB/T14902-2012)47. The cohesion of cement slurry mainly depends on the dry-thin degree of cement slurry, that is, on the consistency of cement slurry, and the frictional resistance between the aggregates, mainly depends on the thickness of the cement slurry layer on the surface of the aggregates, that is, on the quantity of cement slurry. Considering the performance difference between the CGC and the natural aggregate, the traditional concrete mix design method considers that the strength increases as the sand ratio decreases, which obviously does not satisfy the requirements of the CGCLAC mixture. Therefore, in CGCLAC mix design under different conditions and the same circumstances, the selected sand ratio is larger compared with that of ordinary concrete.The slump mean values of series A, B, C, and D were 69 mm, 65 mm, 53 mm, and 42 mm, respectively. Additionally, the cohesion and water retention of concrete were satisfactory. The test results reveal that the slump satisfies the requirements of concrete construction specified in 3. The main reason for this is the fact that, in this study, the apparent density of CG was 1876.2 kg/m3, and the apparent density of NA was mostly above 2600 kg/m3. Therefore, CGC concrete is much lighter than NA concrete.Table The water absorption of CGCLAC is much higher than that of ordinary concrete (the water absorption of ordinary concrete is between 2 and 3%). Both the density and absorption are closely linked to the characteristics of the used aggregate. The CGC aggregates are less dense and more absorbent compared with natural aggregates. The reason for this is the existence of many pores on the surface of the CGC aggregate. This results in more mortar being attached to the aggregate surface, which in turn results in the CGC concrete having lower density and higher absorption rate.The compressive strength of concrete is an important index for determining the strength grade of concrete. The test results reveal that, the compressive strength steadily increased as the water–cement ratio of concrete decreased, similar to ordinary concrete. The compressive strength of concrete with a water–cement ratio 0.30 is slightly lower than that of concrete with a water–cement ratio of 0.35. As shown in Fig. The cube compressive strength of CGCLAC was measured at 3 days, 7 days, 14 days, 21 days, and 28 days, and the results are presented in Table From Table n is the age 48, when the compressive strength of concrete is 30–50 MPa, the corresponding elastic modulus is 30 GPa to 34.5 GPa. From the results in Table The elastic modulus of concrete is an important performance index in the design and calculation of concrete structures, and directly affects the calculation of the internal force and the deformation of the structure. The elastic modulus of concrete mainly depends on the elastic modulus of the cement mortar and aggregate and their relative content in concrete. Owing to the particularity of the CGCLAC composition, and the difference between the elastic modulus and the deformation performance of the CGC and mortar in the CGCLAC composition, the factors affecting the elastic modulus are more complex compared with those of ordinary concrete. The results obtained for the modulus of elasticity of different concretes are presented in Table 53, Smadi54, Yang55, JGJ/T12-201939, and ACI49 are 23.84%, 5.45%, 16.14%, 11.77%, and 14.74%, and the average deviations are 3.5, 0.95, 3.03, 1.31, and 1.32, respectively; the root mean square error (RMSE) is 3.24, 1.52, 1.54, 3.55, and 1.06, respectively. The comparison results reveal that the calculation formula proposed by ACI is more in line with the actual elastic modulus, and can be used to calculate the elastic modulus of ceramsite concrete.Based on a large number of theoretical studies and practical cases, the relationship between the compressive strength and elastic modulus of ordinary aggregate concrete and lightweight aggregate concrete was established. The formula for calculating the elastic modulus of the concrete’s compressive strength is provided in the building codes of some countries. The existing research results reveal that the elastic modulus of concrete is a function of the compressive strength and apparent density of concrete. Figure The physical properties, microstructure, and composition of CG changed after calcination, while the strength and water absorption increased. The apparent density of CGC concrete with different concrete mixes was lower than that of ordinary concrete, which essentially satisfies the requirements of lightweight aggregate concrete.Owing to the great difference between the physical and mechanical properties of CGC aggregate and natural aggregate, the early strength of CGCLAC developed rapidly, mainly because the water absorption of CGC is large and CG ceramsite absorbs a substantial amount of water. Therefore, the hydration reaction between the cement and aggregate is sufficient.Based on the experimental investigation of the cube compressive strength of CGCLAC at different ages, the empirical formula (the following equation) for predicting the early strength of CGCLAC was fitted.2 and RMSE given by this formula are 0.8521 and 2.6359, respectively. These values indicate that the performance of the novel formula for estimating the compressive strength is satisfactory. Therefore, the proposed formula can be used in practical projects to predict the compressive strength of CGCLAC.The RA formula describing the relationship between the splitting tensile strength and compressive strength specified in different national codes was established. The formulas in the GB50010-2010 and CEB-FIB specifications can satisfactorily predict the splitting tensile strength of CGCLAC.The 28-day flexural strength of CGCLAC is between 3.3 and 5.5 MPa, and the flexural strength is approximately one tenth of the cube compressive strength. In the flexural strength test, the CGC was directly damaged at the fracture surface, unlike ordinary concrete.The elastic modulus of CGCLAC is 25–35% lower than that of ordinary concrete with the same strength. The calculation formula proposed by ACI318-11 is more in line with the actual elastic modulus, and can be used to calculate the elastic modulus of ceramsite concrete.Coal gangue can be processed into ceramsite concrete by the above method, which solves the problem of solid waste treatment and alleviates the shortage of concrete raw materials. Based on the analysis of test results, the following conclusions were drawn by this study:


In the existing reinforced concrete columns where they are insufficient seismic details, critical failure mode such as shear failure can be observed under seismic loads. One strategy for the retrofitting of existing concrete columns is to use concrete jacketing. Concrete jacketing consists of a new concrete layer with longitudinal and transverse reinforcements, and can improve seismic resistance capacity. In this paper, a detail of concrete jacket that can be expected for easy construction and improved adhesion performance of longitudinal and transverse reinforcement was proposed. Additionally, a combined cyclic loading test was conducted to consider the seismic load with multiaxial characteristics. The concrete jacket details utilize three components: Steel Grid Reinforcement (SGR), Steel Wire Mesh (SWM), and Steel Fiber Non-Shrinkage Mortar (SFNM). One RC column with non-seismic details and two jacketed RC columns were fabricated to demonstrate the construction efficiencies and structural capacities of the jacketed columns. Two details of jacketed section were considered as variables. It was observed that the specimens retrofitted with concrete jacket resisted torsional load more than the un-retrofitted specimen in terms of crack and failure mode. The experimental results showed that the maximum load of retrofitted specimens was increased by more than 8 times compared to the un-retrofitted specimen, regardless of the jacket details. Newly designed concrete jacket effectively increased the strength. Compared with the un-retrofitted column, the columns retrofitted with the proposed details achieved significant increase in initial stiffness and energy dissipation. Non-seismically designed reinforced concrete (RC) columns need to be repaired or retrofitted because they do not possess adequate lateral strength and ductility. One typical retrofitting method, concrete jacketing, is to enlarge the cross section of the existing RC column with a new concrete layer, including longitudinal and transverse reinforcements. This method is known as a useful technique to improve the seismic performance of the column in terms of its axial strength, flexural strength, and ductility. In retrofitting RC columns, the usual practice consists of first assembling a jacketed reinforcement composed of longitudinal and transverse reinforcements, arranging the formwork, and then placing the concrete. To achieve the purpose of the retrofitting method, the treatment of the surface of the old columns must be carefully handled because the composite action between the old column and the new concrete layer can improve the structural performance. It is costly and time consuming ,2,3. JulThe arrangement, amount, and mechanical properties of steel reinforcement in the jacketed section are important parameters that impact the effectiveness of its load-carrying capacity and ductility. Sun et al.  fabricatFor the concrete jacketing to achieve the purpose of retrofitting, it is necessary to secure the confinement and load-carrying capacity. This depends on the bonding between the old column and the new concrete layer and the details of the jacketed section. The interface treatment to ensure bonding, installation of additional connectors, and welding of rebars to improve confinement effect have been proposed. Concrete jacket is a valuable technique in terms of cost and efficiency. Therefore, this study focused on concrete jacket details that ensured bonding without interface treatment, improved seismic performance, and easy construction. The simple combination of steel wire mesh and steel grid reinforcement allows for easy construction, as it can help practitioners in the site easily apply. The proposed details consist of two parts: steel wire mesh (SWM), which can replace interface treatment, and steel grid reinforcement (SGR), which can replace longitudinal and transverse reinforcement. The combination of these two parts can simplify the interface treatment process and the placing or welding reinforcement in the new concrete layer. It is also intended to be advantageous for crack control by pouring steel fiber non-shrinkage mortar (SFNM). In order to evaluate the structural performance of RC columns retrofitted with the proposed details of concrete jacket, a cyclic loading test was conducted under combined loading from a compression, including a bending and torsion moment. This is to consider the seismic excitations due to the multi-directional characteristics of earthquakes. Two different strengthening details are proposed as alternative methods to the existing concrete jacket. Both proposed reinforcement details of the concrete jacket consist of a combination of steel wire mesh (SWM) and steel grid reinforcement (SGR), as shown in Two different methods are proposed to install a combination of SWM and SGR. Type 1 makes a hole in the old column and inserts a dowel bar to fix the combination of SWM and SGR. Type 2 inserts a hook that couples the reinforcing bars placed transversely in the SGR instead of dowel bars. One non-retrofitted RC column specimen and two specimens retrofitted with each proposed detail were fabricated. The detailed drawings of the non-retrofitted RC specimen (CU) and two retrofitted specimens  are shown in The old column was designed with a cross-sectional size of 250 mm × 250 mm in consideration of the minimum reinforcement spacing and concrete cover thickness specified in ACI 318-19 [The sizes of the jacketing section of the retrofitted specimens of CJU1 and CJU2 were each set to 500 mm × 500 mm in consideration of the minimum thickness for the dowel bar, minimum thickness for reinforcement, and concrete cover thickness. In the jacketed section of CJU1 and CJU2, steel fibers are mixed with 40.09 MPa non-shrinkage mortar. The steel fiber mixing ratio was set to 1.5%. The steel fiber mixed in SFNM is shown in Three RC columns were tested to evaluate their behavior and capacity under combined cyclic load. Details of the loading setup are provided in CJU1 and CJU2 specimens retrofitted with the proposed concrete jacketing showed similar cracks and failure modes. At a drift ratio of 0.25%, flexural cracks occurred in the plastic hinge region. As the load increased, vertical splitting cracks were observed in the compression zone. Concrete spalling and crushing occurred at the bottom of the column in the CJU1 specimen at a drift ratio of 3.5% and in the CJU2 specimen at a drift ratio of 2.2%. Both specimens reached the maximum load at a drift ratio of 8%, and concrete crushing at the bottom of the column widened. Then, the load gradually decreased, and the experiment was terminated. In the CU specimen, more diagonal cracks appeared, and the angle of cracks became larger than for CJU1 and CJU2. This means that the failure modes of the CU specimens developed from flexural failure to torsional failure with the increase in torsional loading. Since the specimens retrofitted with a concrete jacket effectively resisted the torsional load, the specimens showed dominant flexural behavior. In addition, fewer cracks occur in the specimens retrofitted with concrete jacketing than in the CU specimen, which may be attributed to the contribution of the steel fiber to crack control. This is because the steel fiber acts as a bridge to mitigate an increase in crack width through pull-out resistance after cracks occur ,12.The hysteresis curves and skeleton curves are shown in The maximum load and displacement for the positive and negative directions are shown in nM of RC column is determined according to the ACI 318-19 [The predicted moment capacity It is presented that the ACI equation overestimates the experimental value because the lateral force with eccentricity was applied, and the torsion occurred. However, both CJU1 and CJU2 showed moment more than four times greater than the design moment. This means that the proposed concrete jacket can significantly improve the performance of the existing RC columns. In this study, the stiffness of each specimen was evaluated by Equation (3), referring to Vandoros et al. .(3)Ki= referring to Troung et al. , and it i-th drift ratio. i-th drift ratio. Here, The increase in the energy dissipation capacity of each specimen according to the increase in the drift ratio is shown in (1)In the case of CU, it was confirmed that many shear cracks due to torsion were distributed. On the other hand, for CJU1 and CJU2, transverse cracks were evenly distributed along the column. Concrete cover spalling and crushing at the bottom of the column occurred somewhat, but the increases in the widths of the cracks were insignificant because of confinement effect provided by the proposed concrete jacket. Therefore, it has been demonstrated that proposed details, in combination with SGR, SWM, and SFNM, effectively resisted combined loading.(2)The maximum load of CJU1 and CJU2 was about 8 times larger than that of CU and the initial stiffnesses of CJU1 and CJU2 were about 13 times larger than CU, respectively. It has been demonstrated that the strength and stiffness can be significantly improved by proposed concrete jacket details.(3)The yield of the longitudinal reinforcement of the old column of the CJU1 and CJU2 was confirmed. Additionally, the separation of the jacket from the old column was not observed even if there was no surface treatment, and the role of the contact interface between the old column and new concrete layer was performed by SWM.(4)RC columns retrofitted with the proposed details achieved significant increases in load carrying capacity, stiffness, and energy dissipation. The jacketed section with proposed details is constructed only by assembling the pre-fabricated reinforcement without surface treatment process. Simple details and easy installation can help practitioners to apply it easily. According to the current study, similar performance was exhibited regardless of the details. It is recommended to use concrete jacket details with hooked type without drilling and dowel fixing.In this study, two types of jacketing details that can improve both structural capacity and the constructability were proposed. In order to evaluate the structural performance of the RC columns retrofitted with the proposed concrete jacketing, cyclic loading tests were conducted in consideration of axial load, lateral load, and torsion. The following conclusions have been drawn: