Plasmodium-infected models, have rarely been studied. The Plasmodium species parasitize inside RBC, and these cells should be the final place where DHA performs its activity. In this study, the profile of DHA metabolites in biosample  of the infected and healthy mice was investigated with UPLC-Q-TOF-MS and UNIFI platform to gain insight into DHA metabolism. Results show that a total of 25 metabolites were successfully identified in infected  blood, 27 in infected  plasma, and 15 in infected  RBC. Results show that hydroxylation, OH-dehydration, and glucuronidation reactions were important in the metabolic pathway in vivo. Significantly, DHA metabolites inside RBC were identified for the first time. 8-Hydroxy (8-OH) DHA, 4α-OH deoxy ART, and 6β-OH deoxy ART were identified in vivo for the first time.Dihydroartemisinin (DHA) and its’ derivatives have been employed as the most powerful first-line drugs for malarial treatment for several decades. The metabolism of DHA has not been studied clearly. Previous reports were focused on the pharmacokinetics procedure of DHA in healthy rats. The metabolites of DHA in red blood cells (RBC), especially in the RBC from  Artemisia annua L. (qinghao) and displays highly antimalarial activity. Later, a more powerful dihydroartemisinin (DHA) was developed by Tu in 1973 by introducing a hydroxyl group into the structure of ART (in vivo rapidly (Artemisinin (ART), a sesquiterpene lactone containing a peroxide group, was first discovered by Tu et al. in 1972. It is derived from the leaves of e of ART . Nowadaye of ART  , and these cells are the final place where DHA performs its activity. Early studies have shown that radioisotope-labeled 3H-DHA accumulates from the culture medium into healthy and infected RBC (h-RBC and i-RBC); especially, the partitioning of radioactivity inside i-RBC was >300-fold higher than the concentration measured in the medium  of infected and healthy mice were investigated with UPLC-Q-TOF-MS to obtain insight into DHA metabolism. A combination of MSE data acquisition technology and the integrated data processing functions of the UNIFI platform was applied for the rapid detection and structural characterization of unknown metabolites. Furthermore, DHA metabolites inside RBC were firstly identified from blood and RBC of mouse. This study provides the experimental basis for further exploration of the antimalarial mechanism of DHA, particularly inside RBC.Our group has been devoted to studying ART drugs for decades . In thisα-Hydroxy deoxy DHA was provided by Professor J.Y. Wang . The reagents used were of high-performance liquid chromatography (HPLC) grade. Acetonitrile and methanol were purchased from Fisher ; formic acid and ethyl acetate were purchased from Beijing Chemical Works . Sodium pentobarbital was purchased from Merck . Water was prepared using a Milli-Q system operating at 18.2 MΩ . All other chemicals used were purchased from Fisher Scientiﬁc or Beijing Chemical Works and were of the highest purity available. Potassium dichromate was obtained from Sinopharm Chemical Reagent Co., Ltd . Ethylenediaminetetraacetic acid disodium salt (EDTA-Na2) was purchased from Beijing Solaria Science & Technology Co., Ltd .ART and DHA were obtained from the Chongqing Wuling Mountain Pharmaceutical, Kunming Pharmaceutical Group . The compound had a purity of ≥99%. 3E system consisted of a Waters ACQUITY I-class UPLC and Xevo G2-XS Q-TOF Mass Spectrometer , equipped with an electrospray ionization (ESI) source . Chromatographic separation was achieved using an ACQUITY UPLC BEH C18 . The mobile phase consisted of solvent A  and solvent B . The gradient program for biosamples included three segments: 5%–100% B from 0 to 15 min, followed by 100%–5% B from 15 to 17 min, followed by a postrun of 3 min for column equilibration. The ﬂow rate was 0.4 ml/min, and the temperature was at 30°C throughout the analysis.The UPLC-ESI-Q-TOF-MSm/z 50 to 1,000, with a scan time of 0.2 s. Source parameters were as follows: source temperature, 150°C; cone gas, 50 L/h; desolvation temperature, 450°C; desolvation gas ﬂow, 800 L/h. Argon (99.95%) was used for collision-induced dissociation, and N2 was used as the drift gas. The low collision energy was set to 6 eV, and the high collision energy was ramped from 12 to 25 eV. MSE analysis was employed for simultaneous acquisition of the exact mass of small molecules at high and low collision energy. The MS was calibrated daily by Waters calibration standard. Leucine enkephalin was used for lock mass correction with m/z 556.2771 at an interval of 0.5 min to ensure robust and accurate mass measurements.The MS was operated in positive ionization mode across a scan range of E scan function using MassLynx4.1 . The components were identiﬁed in a nontargeted manner by spectral deconvolution in UNIFI 1.9  with the following parameters: three-dimensional peak detection mode; low-energy limits of 150 counts and high-energy limits of 20 counts; isotope clustering; drift peak with a mass accuracy of ±2 mDa; the maximum number of allowed fragment ions per match set at 10. Furthermore, the detection of metabolites was accomplished using data processing tools, such as mass defect filter, common fragment filter, common neutral loss fragment filter, and binary comparison.In this analysis, data acquisition was performed with the MSMale C57BL/6J mice (weighing 18–22 g) were supplied by Beijing Vital River Laboratory Animal Technology Corporation . The experimental protocol was approved by the Ethics Committee of the China Academy of Chinese Medical Sciences . Mice were randomly divided into a healthy group  and an infected group . Corresponding control groups were set up separately (n = 2). Mice were fasted for 12 h prior to drug administration and for an additional 1 h after dosing. The mice had ad libitum access to water during the experiments.Plasmodium berghei ANKA strain (chloroquine-sensitive) was stored at Artemisinin Research Center, China Academy of Chinese Medical Sciences . A vial of Plasmodium berghei ANKA was retrieved from liquid nitrogen storage, thawed in a water bath at 37°C, and intraperitoneally inoculated into two mice. Subsequent passage to maintain the parasites was performed by intraperitoneal inoculation of a normal mouse with infected blood (i-blood) from a donor mouse. I-blood was diluted with sterile, nonpyrogenic 0.85% saline to provide 1 × 107 i-RBC in an injection volume of 0.2 ml. The experiment was only performed when the levels of parasitemia reached 30%.The rodent malaria parasite A drop of i-blood was collected from the mouse by venesection of the tail and transferred onto the edge of a microscope slide . The blood was drawn evenly across a second slide to produce a thin blood film, fixed with methanol, and then allowed to dry at room temperature before staining with Giemsa’s stain solution . The slides were viewed using light microscopy  with oil immersion . The percentage of parasitemia was calculated by counting the number of i-RBC in 1,000 cells in a thin blood film.bw; intraperitoneally). Subsequently, all mice were sacrificed by cervical dislocation. This time point was selected based on a preliminary study showing that tmax of DHA in blood was 0.5 h and further drug metabolism also requires some time. Plasma and RBC were separated by centrifugation  at 3,500 rpm for 15 min, at 4°C. In this study, potassium dichromate was employed to deactivate the Fe2+ ion in hemoglobin in blood samples, while ethylenediaminetetraacetic acid disodium salt (EDTA-Na2) could simultaneously chelate Fe2+ and Fe3+ to protect the peroxide group of DHA . The mixture was vortex-mixed for 1 min on ice. After freezing at −80°C and rapid thawing at 37°C for three freeze-thaw cycles, the mixture was subjected to ultrasonication for 5 min in ice water. The supernatants of samples were loaded onto pretreated SPE cartridges . The cartridges were washed with 1 ml of water, and analytes were eluted with 1 ml of methanol. The methanol fractions were dried using a vacuum freeze concentrator . All samples were stored at −80°C until reconstitution with 100 µL of the initial mobile phase and immediate analysis. Aliquots (4 µL) of the reconstituted solutions were injected into the LC-MS.DHA was formulated as a suspension in 0.5% sodium carboxymethylcellulose. Groups H and I (n = 5) received a single oral dose of DHA (200 mg/kg). The blank control received 0.5% sodium carboxymethylcellulose only. The blood samples were collected into EDTA tubes at 1.0 h after administration by eye removal under anesthesia state  were evaluated by the extraction of metabolites. Protein precipitation was achieved by adding four times the volume of acetonitrile to remove the protein . Liquid-α-hydroxy (3α-OH) deoxy DHA were used to establish the standard MS fragmentation patterns.The reference substances DHA, ART, and 3m/z 307.1515 [M + Na]+ and m/z 323.1251 [M + K]+. Fragments m/z 267.1597, 249.1491, 231.1387, and 213.1282 were generated by the successive loss of H2O from m/z 307.1515. Fragment m/z 221.1543 was generated by the loss of HCOOH from m/z 267.1597. Moreover, fragment m/z 261.1476 was generated by the loss of HCOOH from m/z 307.1515. Fragments m/z 163.1125 and 145.1021 were generated by the successive loss of C6H8O2 and H2O from m/z 261.1476. Mass spectra and the MS fragmentation pattern of DHA are shown in DHA was eluted at 7.28 min. The quasimolecular ions were m/z 283.1545 [M + H]+, m/z 305.1361 [M + Na]+, and m/z 321.1092 [M + K]+. Fragments m/z 265.1447, 247.1335, and 229.1230 were obtained by successive loss of H2O from m/z 283.1545. Moreover, the fragment ion at m/z 237.1490 was generated by the loss of HCOOH from m/z 283.1545. Fragments m/z 219.1386 and 201.1281 were generated by the successive loss of H2O from m/z 237.1490. Mass spectra and the MS fragmentation pattern for ART are shown in ART was eluted at 8.64 min. The quasimolecular ions were α-OH deoxy DHA was eluted at 4.17 min. The quasimolecular ions were m/z 307.1540 [M + Na]+ and 323.1265 [M + K]+. The MS fragmentation pattern was similar to that of DHA. Fragments m/z 267.1602, 249.1534, 231.1395, and 213.1285 were generated by the successive loss of H2O from m/z 307.1540. Fragments m/z 221.1546 and 203.1441 were generated by the successive loss of HCOOH and H2O from m/z 267.1602. Mass spectra and the MS fragmentation pattern for 3α-OH deoxy DHA are shown in 3in vivo, metabolites in blood, plasma, and RBC of infected and healthy mice were acquired by UPLC-electrospray ionization-Q-TOF MS operating in MSE mode and identified using the UNIFI 1.9 platform . Metabolites were identified based on retention time and characteristic behavior of MS, including the exact mass, quasimolecular ions, in-source fragmentation, and characteristic fragments of metabolites. Compared with the peaks in the corresponding blank sample, a total of 34 peaks were observed and identified as DHA metabolites in blood samples of infected and healthy mice.To evaluate the metabolism of DHA The metabolites were generated by multiple enzymatic reactions, such as monohydroxylation, deoxygenation, OH-deoxygenation, dehydrogenation, OH-dehydrogenation, dehydration, OH-dehydration, glucuronidation, dehydro-glucuronidation, and OH-glucuronidation. All identified DHA metabolites are listed in m/z 323 [M + Na]+ and m/z 339 [M + K]+. They showed a similar MS fragmentation pattern to that of DHA, except for a 16 Da mass shift (an oxygen atom). Fragment m/z 283 was generated by the loss of H2O from m/z 323 [M + Na]+. High-energy spectra showed that fragments m/z 265 and 247 were generated by the successive loss of H2O from m/z 283. Fragment m/z 219 was generated by the loss of HCOOH from m/z 265 (All metabolites were detected within 16 min through a chromatographic method. Metabolites M1–M7 (DHA + O), eluted from 3.22 to 5.79 min, were proposed to be the result of hydroxylation of DHA. The quasimolecular ions were  m/z 265 .m/z 291 [M + Na]+ and m/z 307 [M + K]+. This metabolite showed a similar MS fragmentation pattern to that of DHA. Fragments m/z 251 and 233 were generated by the successive loss of H2O from m/z 291. Fragment m/z 205 was generated by the loss of HCOOH from m/z 251 (Metabolite M8 (DHA-O), eluted at 7.09 min, was identified as 1 deoxy DHA. It was a known metabolite of DHA; the quasimolecular ions were  m/z 251 .m/z 307 [M + Na]+ and m/z 323 [M + K]+. These were isomers of DHA and exhibited the same fragments as DHA, such as m/z 267, 249, 231, 221, and 203 (Metabolites M9-M10 (DHA-O + O), eluted from 4.17 to 6.04 min, were proposed to be the result of hydroxy-deoxygenation of DHA. Their quasimolecular ions were  and 203 .2), eluted at 8.63 min, was identified as ART. It was a known metabolite of DHA; the quasimolecular ions were m/z 283 [M + H]+, m/z 305 [M + Na]+, and m/z 321 [M + K]+. Fragments m/z 265 and 247 were consistent with the reference substance (Metabolite M11 (DHA-Hubstance .2+O), eluted from 2.48 to 5.10 min, were proposed to be the result of OH-dehydrogenation of DHA. Their quasimolecular ions were m/z 337 [M + K]+, m/z 321 [M + Na]+, and m/z 299 [M + H]+. Fragments m/z 281 and 263 were generated by the successive loss of H2O from m/z 299. Fragment m/z 235 was generated from m/z 281 following the loss of HCOOH (Metabolites M12-M18 (DHA-Hof HCOOH .2-O), eluted at 8.64 min, was identified as 1 deoxy ART. The quasimolecular ions were m/z 305 [M + K]+, m/z 289 [M + Na]+, and m/z 267 [M + H]+. Fragments m/z 249 and 231 were generated by the successive loss of H2O from m/z 267. Fragment m/z 221 was generated from m/z 267 following the loss of HCOOH (Metabolite M19 (DHA-Hof HCOOH .2-O + O), eluted from 3.21 to 5.75 min, were proposed to be the result of OH-dehydration of DHA. Their quasimolecular ions were m/z 305 [M + Na]+ and 283 [M + H]+. They were isomers of ART, and their MS fragmentation pattern was consistent with that of ART. Fragments m/z 265, 247, and 229 were generated by the successive loss of H2O from m/z 283. In addition, fragment m/z 237 was generated by loss of HCOOH from m/z 283. Fragments m/z 219 and 201 were generated by the successive loss of H2O from m/z 237 (Metabolites M20-–M28 (DHA-H m/z 237 .6H8O6), eluted at 6.03 min, was predicted to be the result of glucuronidation of DHA. The quasimolecular ion was m/z 478 [M + NH4]+. Except for a 176 Da mass shift (a glucuronic acid molecular), fragments m/z 267, 249, 231, 221, and 203 were consistent with those of DHA (Metabolite M29 (DHA + Ce of DHA .6H8O6), eluted from 3.21 to 3.37 min, were predicted to be the result of glucuronidation of hydroxy-DHA. The quasimolecular ions were m/z 499 [M + Na]+ and m/z 494 [M + NH4]+. Except for a 176 Da mass shift (a glucuronic acid molecular), fragments m/z 283, 265, and 247 were consistent with the DHA-hydroxylated products (M1–M7)  .2+C6H8O6), eluted from 3.23 to 3.88 min, were predicted to be the result of glucuronidation of dehydro-DHA. The quasimolecular ions were m/z 459 [M + H]+ and m/z 481 [M + Na]+. Except for a 176 Da mass shift (a glucuronic acid molecular), fragments m/z 265, 247, and 237 were consistent with ART (M11) and OH-dehydration of DHA (M20–M28) (Metabolites M32–M34 (DHA-HM20–M28) .2+O, 1 (1) 1 deoxy ART, and 7 (8) DHA-H2-O + O; and phase II metabolites: 1 (1) DHA + C6H8O6, 0 (2) DHA + O + C6H8O6, and 1 (2) DHA-H2+C6H8O6  putative metabolites were identified in infected blood  [i-blood (h-blood)]. These comprised phase I metabolites: 7 (7) DHA + O, 1 (1) 1 deoxy DHA, 2 (2) DHA-O + O, 1 (1) ART, 4 (5) DHA-H2+C6H8O6 .α-OH deoxy DHA, ART, 1 deoxy ART, 4α-OH deoxy ART, and 6β-OH deoxy ART  1 deoxy ART, and 8 (8) DHA-H2-O + O; and phase II metabolites: 1 (1) DHA + C6H8O6, 2 (2) DHA + O + C6H8O6, and 1 (1) DHA-H2+C6H8O6  putative metabolites were identified in infected plasma . These comprised phase I metabolites: 7 (6) DHA + O, 1 (1) 1 deoxy DHA, 2 (2) DHA-O + O, 4 (5) DHA-H2+C6H8O6 .α-OH deoxy DHA, 1 deoxy ART, 4α-OH deoxy ART, and 6β-OH deoxy ART  1 deoxy ART, and 4 (7) DHA-H2-O + O; phase II metabolites: 1 (1) DHA + C6H8O6 and 1 (1) DHA-H2+C6H8O6  putative metabolites were identified in i-RBC (h-RBC). These comprised phase I metabolites: 4 (7) DHA + O, 0 (1) 1 deoxy DHA, 2 (2) DHA-O + O, 2 (2) DHA-H2+C6H8O6 .α-OH deoxy DHA, 1 deoxy ART, 4α-OH deoxy ART, and 6β-OH deoxy ART. Moreover, 8-OH DHA and 1 deoxy DHA were identified inside h-RBC , which are digested from hemoglobin by Plasmodium. Following entry into i-RBC, the drug is easily reduced by heme, free iron ions, and other components (2+ and Fe3+ to protect the structures of DHA metabolite. This is the first attempt to identify DHA metabolites inside RBC and blood samples. The results showed that the established method successfully identified 15 (22) putative metabolites in i-RBC (h-RBC). Previous studies have demonstrated that radioisotope-labeled 3H-DHA was accumulated from the culture medium into RBC, especially in i-RBC. However, the number of DHA metabolites and the relative content (peak area) of main metabolites inside i-RBC were significantly lower than those recorded in h-RBC, especially the products of hydroxylation of DHA (DHA + O) and OH-dehydration of DHA (DHA-H2-O + O). Combined with our results, it was hypothesized that DHA and bioactive metabolites immediately bind to the target, result in nonenzymatic biotransformation, or disrupt the metabolic balance of Plasmodium, after entering i-RBC and exerting their effect. Therefore, further qualitative and quantitative analyses of DHA and its metabolites inside RBC are warranted.It is known that the us study  has showmponents . It is din vivo, the hydroxylation, OH-dehydration, and glucuronidation reactions were found to be important in the metabolic pathway, and the metabolic pathway of DHA was constructed  possess antimalarial activity. Collectively, the results laid a solid foundation for further pharmacological research and offered new insight into the antimalarial mechanism of ART drugs.In summary, a C57 mouse model infected by The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by the Ethics Committee of the China Academy of Chinese Medical Sciences .LY and DZ conceived and designed the experiments. YZ and PS performed the experiment. YM and YB prepared the reference substances. XQC, XYC, and XJ analyzed the data. All the authors gave the final approval of the version to be submitted.This work was supported by the Emergency Management Program of National Natural Science Foundation of China (Grant No. 81841001) and major science and technology project for “Signiﬁcant New Drugs Creation” (Grant No. 2017ZX09101002-002).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Tetragonula carbonaria and Tetragonula hockingsi species in Australia, from Geniotrigona thoracica and Heterotrigona itama in Malaysia and from Tetragonisca angustula in Brazil. The previously unrecognised abundance of trehalulose in stingless bee honeys is concrete evidence that supports some of the reported health attributes of this product. This is the first identification of trehalulose as a major component within a food commodity. This study allows the exploration of the expanded use of stingless bee honey in foods and identifies a bioactive marker for authentication of this honey in associated food standards.Stingless bee (Meliponini) honey has long been considered a high-value functional food, but the perceived therapeutic value has lacked attribution to specific bioactive components. Examination of honey from five different stingless bee species across Neotropical and Indo-Australian regions has enabled for the first time the identification of the unusual disaccharide trehalulose as a major component representing between 13 and 44 g per 100 g of each of these honeys. Trehalulose is an isomer of sucrose with an unusual α-(1 → 1) glucose-fructose glycosidic linkage and known acariogenic and low glycemic index properties. NMR and UPLC-MS/MS analysis unambiguously confirmed the identity of trehalulose isolated from stingless bee honeys sourced across three continents, from  Like the more well-recognised Apis mellifera honeybees, stingless bees live in permanent colonies made up of a single queen and workers, who collect pollen and nectar to feed larvae within the colony and likewise store honey in the hive for this purpose. Honey produced by stingless bees is known by various names such as Meliponine honey, pot-honey, sugarbag honey , and Kelulut honey . Under these and other names, stingless bee honey has a long history of traditional indigenous use with a range of purported therapeutic properties2, including antidiabetic and antioxidant activity4. Various studies have been conducted of physicochemical and nutritional composition of stingless bee honey5, but to date few bioactive components have been identified2. While these studies all acknowledged that the composition of stingless bee honey is different to that of European bee honey, no rigorous identification of the major components and potential therapeutically active compounds has been reported. In addition to the importance of identifying the potential therapeutic components of stingless bee honey, the rapidly increasing consumer demand for stingless bee honey derived products has highlighted the need to produce food standards to enable establishment of authenticity and provenance of such products6.Stingless bees (Meliponini) occur in most tropical and sub-tropical regions, with over 500 species of these eusocial bees distributed across Neotropical, Afrotropical and Indo-Australian regions1) −) m/z 341.1082  was clearly a disaccharide, but did not match any of our initially available disaccharide standards. Previous analysis of stingless bee honeys have suggested that the disaccharide present was the glucose-glucose disaccharide maltose (2)18. However, the improved resolution and mass spectral data provided by our UPLC-MS/MS method demonstrated that the disaccharide present in all five stingless bee honeys, was in fact not maltose. This enigmatic disaccharide eluted with a slightly shorter UPLC retention time compared to a maltose standard  1a) and (1b). Tentative structural assignments were compared with literature enabling the unambiguous assignment of the unknown honey disaccharide as trehalulose  being present at a higher level than 1-O-α-d-glucosylpyranosyl-β-d-fructofuranose tautomer (1b)19. Trehalulose was previously isolated from excrement of sweet potato whitefly Bemisia tabaci by Bates et al.20 These authors reported both 13C and 1H NMR assignments in D2O of three tautomers present in 20:4:1 ratio. Their NMR data were similar to incomplete details reported previously by Cookson19, who had isolated trehalulose from a mixture of glucose, fructose and isomaltulose produced by immobolised microbial cells, with the isolated disaccharide reported to be a 2:1 mixture of fructopyranose and fructofuranose forms by 13C NMR and other methods.1D and 2D NMR analysis of the isolated disaccharide suggested a 1,1-linkage between glucose and fructose monosaccharides with evidence of major/minor tautomers for the fructose ring (1a) and (1b), which were present in a 3.6:1 ratio by integration of the anomeric proton signals for the glucose rings (Table 1a) were irradiated in separate 1D TOCSY experiments to identify the proton signals in each monosaccharide spin system. This allowed full elucidation of the pyranose tautomer of fructose (β-d-Frup) predominant in trehalulose (1), with assigned 13C and 1H NMR data of (1a) shown to be in close agreement to that previously reported by Bates et al.20 for this compound  were partly obscured by the more dominant fructopyranose tautomer (1a) in the isolated trehalulose. Only the anomeric glucosyl proton doublet  could be clearly distinguished. Based on 2D HSQC, TOCSY and COSY experiments, all other protons and carbon shifts of the minor fructofuranose conformer (1b) were assigned as shown in Table 20. A third more minor tautomer with anomeric glucosyl proton doublet  could be seen in our trehalulose NMR spectra, but due to the low concentration and overlap with the other anomeric signals it is not possible to report full data for this compound. This is presumably the component speculated to be the α-furanose tautomer by Bates et al.20.1) with minor disaccharides tentatively identified as sucrose, maltulose and turanose by comparison of NMR chemical shifts with literature22. Isomaltulose (3)22 was not detected in these NMR spectra of trehalulose isolated from stingless bee honey.Close examination of NMR spectra demonstrated that the disaccharide isolated from each of the five stingless bees comprised > 90% trehalulose  MS/MS fragmentation for trehalulose (1) has not previously been reported. UPLC-MS/MS analysis of trehalulose isolated from each of the stingless bee species showed a single unresolved peak for (1a) and (1b) tautomers  structure. Glycosidic bond cleavage of the molecular ion ([M-H]−) m/z 341 of trehalulose (1) produces a dominant m/z 179, with fragmentation of this ion to m/z 161, 143, 131, 119 and 113  differed markedly from that of maltose. Most notably, the m/z 221 peak corresponding to the glucosyl-glycoaldehyde anion observed in the mass spectra of maltose (2) and isomaltulose (3)26, was not observed in the 1 → 1-linked trehalulose (1) spectrum , but the authentic standard erroneously contained a second minor disaccharide peak which proved by UPLC-MS/MS analysis to be an isomaltulose  (3) contaminant. This second peak had identical retention time and MS/MS fragmentation to authentic isomaltulose (3) 24. Isomaltulose (3) and trehalulose (1) are regioisomeric disaccharides which occur concomitantly in reported biological sources of these disaccharides27, and the presence of isomaltulose (3) as a 5% contaminant in the commercial trehalulose standard is understandable. Industrial trehalulose production has been achieved from sucrose using immobilised enzymes, with differing ratios of (3) to (1) produced depending on the enzyme used28.The authentic standard of trehalulose obtained for confirmatory comparison exhibited a major UPLC peak with the same retention time and MS/MS fragmentation as our isolated disaccharide 3) Figs. , 3, incl Figs. , 1) isolated by preparative HPLC from each of our stingless bee honeys contains no evidence of co-occurring isomaltulose (3) in either UPLC-MS/MS chromatograms . This observation highlights the potential of stingless bee honey as a novel source of pure trehalulose (1).It is worth noting that trehalulose  as a major component representing between 13 and 44 g per 100 g of each stingless bee honeys. The highest proportion of trehalulose was present in the sample of Malaysian Geniotrigona thoracica honey in which it represented 84% (w/w) of the total sugar content. The only other sugars present at significant levels were the monosaccharides glucose and fructose.UPLC-MS/MS quantitative analysis of the sugars present in the same five stingless bee honey samples employed in preparative HPLC isolations confirmed the presence of trehalulose  glycosidic bond  as a distinguishing disaccharide in these stingless bee honeys thus provides a ready marker for authenticity, in the same way that specific marker compounds are used to authenticate high value mānuka honey34. Trehalulose therefore represents an ideal indicator of authenticity to be incorporated in the development of relevant stingless bee honey standards6. Previous attempts to develop a fast FTIR-ATR analysis of sugars in H. itama honey were unfortunately ill-founded in the belief that the major disaccharide present in this stingless bee honey was maltose (2)16. However, it is likely that the chemometric PLS regression analysis presented by these authors will still hold true for quantitation against trehalulose , presenting the ready opportunity for the development of a fast FTIR-ATR analysis method for trehalulose (1) in stingless bee honey. This would facilitate the development of a rapid method for the authentication of stingless bee honey products.This is the first isolation of trehalulose from a food source, namely stingless bee honey. Stingless bee honey represents a highly valued food with accredited biological activity, and this reported activity may in part be attributable to the previously unrecognised abundance of trehalulose in these honeys. The presence of trehalulose Tetragonula hockingsi (syn. Trigona hockingsi)35 and Tetragonula carbonaria (syn. Trigona carbonaria)35 honey samples were collected from hives located in suburban backyards in Brisbane, Queensland Australia. Geniotrigona thoracica (syn. Trigona thoracica)35 honey was purchased from a producer in Kampung Rinching Hilir, Selangor, Malaysia. Heterotrigona itama (syn. Trigona itama)35 honey was purchased from a producer in Batang Kali, Selangor, Malaysia. Tetragonisca angustula (syn. Trigona angustula)35 honey (Brazil) was provided as a gift. All stingless bee honey samples were stored in a refrigerator (4 °C) before analysis.Authentic trehalulose (specified by supplier > 90% purity) was purchased from Biosynth Carbosynth . Maltose, sucrose, glucose and fructose were purchased from Sigma Aldrich , and isomaltulose from Myopure .4OH and Mobile Phase B: 20% RO water/80% acetonitrile with 0.1% NH4OH, utilising a gradient as follows: 0–1 min, 100% B; 1–13 min, 100% B to 50% B; 13—16 min, 50% B to 100% B; 16–20 min, 100% B.Honey samples (0.5 g) were dissolved in ultrapure water (50 mL) and further diluted 1:10 in water and then 1:4 in acetonitrile. Sugar standards were similarly dissolved in Millipore water and diluted sequentially in aqueous acetonitrile to provide a concentration range of glucose 1–204 µg/mL, fructose 1–195 µg/mL, sucrose 1–198 µg/mL and trehalulose 1–203 µg/mL. Analysis of sugars in individual honey samples was conducted on a Shimadzu Nexera ultra high-performance liquid chromatograph (UHPLC) coupled with a Shimadzu 8045 MS/MS detector with Lab Solutions software and a CTO-20AC column oven was operated at 35 °C. Separations were conducted on a Waters Acquity UPLC BEH Amide 1.7 µm, 2.1 × 100 mm column eluted at a flowrate of 0.2 mL/min with Mobile Phase A: 70% RO water/30% acetonitrile with 0.1% NH2) typically in the range of 0.98–0.99. Percentage recoveries of standard additions to five honeys at four levels for each of glucose, fructose, sucrose and trehalulose were calculated, with values for spiked samples calculated by subtraction of the endogenous, no-spike value. Recoveries for spiked samples were calculated by using the expected value and averaged 93–119% with standard deviations of 2–4% at the highest spike level, 4–15% at the intermediary spike levels and 18–40% at the lowest spike level.Method validation was conducted by comparing the results for calibration using external sugar standards to a standard additions method for determining sugar concentrations. For standard additions, squared linear correlation coefficients (R−) m/z 341.1 was fragmented at both 20 V and 8 V to examine differences in fragmentation of individual eluted disaccharides. Selected reaction monitoring (SRM) transitions of m/z 341.2 → 179.2 were used for quantitation of trehalulose in each of the analysed honeys with confirmation transitions of m/z 341.2 → 251.2 and m/z 341.2 → 161.2. Sucrose was quantitated using m/z 341.2 → 179.2, with m/z 341.2 → 161.2 and m/z 341.2 → 119.1 used for confirmation. Similarly, glucose and fructose were analysed based on SRMs of m/z 179.2 → 89.0 (quantitation) with m/z 179.2 → 101.1 and m/z 179.2 → 113.1 (confirmation).The disaccharide molecular ion  using full-scan ddMSMS mode using an inclusion list of 341.1089 ([M-H]−) and 387.1144 (M + HCOO−). The normalized collision energy (NCE) was set to 20%. Xcalibur  was used for instrumental control and spectral inspection.High resolution mass spectral data was conducted on a Thermo Dionex Ultimate 3000 ultra high-performance liquid chromatograph (UHPLC) coupled with a Q Exactive Orbitrap high resolution accurate-mass (HRAM) spectrometry system. LC separation was carried out on a Waters Acquity UPLC BEH Amide column  at 35 °C using a flowrate of 0.2 mL/min with mobile phase A: 70% RO water/30% acetonitrile with 0.1% NH2 100 Å 250 × 4.6 mm column with an isocratic mobile phase comprised of 85% acetonitrile and 15% RO water at a flow rate of 2.5 mL/min. Eluted sugars were monitored with a Shimadzu ELSD- LT (Low Temperature) detector operated at 350 kPa and 45 °C. The elution flow was diverted to a collection tube when the target peak emerged and 5 mL (2 min) fractions collected before reconnection of the column eluant to the ELSD detector (to see the tail end of the peak). Collected fractions were analysed ‘as is’ by UPLC-MS/MS (as above), and a second portion freeze-dried and dissolved in D2O for NMR analysis.To enable separation of individual disaccharides, the honey samples were chromatographed on a Shimadzu HPLC-ELSD system consisting of a Shimadzu Class VP Pump LC-10AD VP/Valve FCL-10AL VP/Degasser DGU-14A with a Class VP Software/ SCL-10A VP controller, SIL-10AD VP autosampler and a CTO-10A VP column oven operated at 40 °C. Separations were performed on a Phenomenex Luna 5 µm NH1H nuclear magnetic resonance (NMR) analysis performed on an AV500 (500.13 MHz) Bruker Avance system using 5 mm SEI Probe. A zg45 pulse experiment at 298 K with 64 scans and a spectral width of 12.0 ppm  was applied. Spectra were recorded in D2O, with chemical shifts (δ) values recorded in ppm. Residual protonated solvent signals were used as internal standard (δ 4.80). NMR data presented as: chemical shift, multiplicity , coupling constant (J Hz), assignment. Multiplicities, and hence coupling constants, reported are apparent values. 13C NMR spectra were recorded on a Bruker Avance 500 (125.77 MHz) spectrometer with complete proton decoupling. Spectra were recorded in D2O with added 1% 1,4-dioxane (δ 67.40) used as reference. 2D COSY, TOCSY, HSQC, HMBC (500 MHz) spectra were used to confirm spectral assignments. Trehalulose exists in aqueous solution as a mixture of both pyranose and furanose forms (3.6:1) with both tautomers assigned as below.The purified sugar was analysed via O-α-d-glucopyranosyl-β-d-fructopyranose (1a). 1H NMR  δ 4.98 , 4.08 , 4.02 , 3.94 , 3.92 , 3.88 , 3.85, 3.79 , 3.80–3.76 , 3.73 , 3.72 , 3.58 , 3.48 , 3.44 ppm . 13C NMR  δ 99.32 (C-1′), 98.64 (C-2), 73.81 (C-3′), 72.73 (C-5′), 72.28 (C-2′), 70.41 (C-4′), 70.34 (C-4), 69.93 (C-1), 69.89 (C-5), 68.70 (C-3), 64.35 (C-6), 61.31 ppm (C-6′).1-O-α-d-glucosylpyranosyl-β-d-fructofuranose (1b). 1H NMR  δ 5.01 , 4.13 (H-4), 4.15 (H-3), 3.89 (H-6′), 3.88 (H-5), 3.81 (H-6), 3.76 (H-3′), 3.72 (H-5′), 3.68 (H-6′), 3.59 (H-2′), 3.56 ppm (H-1). 13C NMR  δ 101.69 (C-2), 81.49 (C-5), 77.11 (C-3), 75.19 (C-4), 72.91 (C-5′), 72.23 (C-2′), 69.29 (C-1), 63.13 (C-6), 61.35 ppm (C-6′).1-1a) and (1b).NMR analysis of authentic trehalulose  provided matching NMR data for both tautomers (Supplementary Information.


Here, we report optimization of the pharmacokinetic and antibiotic properties of the acylaminooxadiazoles, producing MBX-4132, which clears multiple-drug resistant Neisseria gonorrhoeae infection in mice after a single oral dose. Single particle cryogenic-EM studies of non-stop ribosomes show that acylaminooxadiazoles bind to a unique site near the peptidyl-transfer center and significantly alter the conformation of ribosomal protein bL27, suggesting a novel mechanism for specific inhibition of trans-translation by these molecules. These results show that trans-translation is a viable therapeutic target and reveal a new conformation within the bacterial ribosome that may be critical for ribosome rescue pathways.Bacterial ribosome rescue pathways that remove ribosomes stalled on mRNAs during translation have been proposed as novel antibiotic targets because they are essential in bacteria and are not conserved in humans. We previously reported the discovery of a family of acylaminooxadiazoles that selectively inhibit  N. gonorrhoeae infection in mice.Antibiotic-resistant bacterial pathogens pose a substantial threat to human health. Here, aided by structural analyses, the authors describe the molecular mechanism behind the activity of a series of compounds that inhibit trans-translation and are effective in eradicating  Among the five most dangerous “Urgent Threats” identified by the CDC is drug-resistant Neisseria gonorrhoeae, which infects >500,000 people per year in the US2. New antibiotics must be developed to treat these drug-resistant infections. Bacterial ribosome rescue pathways have been proposed as potential antibiotic targets because these pathways are essential in bacterial pathogens but are highly dissimilar from cytoplasmic mechanisms to disassemble non-stop ribosomes in eukaryotes3.Antibiotic-resistant bacterial pathogens pose a substantial threat to human health and are projected to cause up to 10 million deaths per year by 2050 if new antibiotics are not developed4. These “non-stop” ribosomes must be rescued to maintain protein synthesis capacity and cell viability4. All bacterial species that have been studied use trans-translation as the primary ribosome rescue pathway. During trans-translation, transfer-messenger RNA (tmRNA) and the protein SmpB recognize non-stop ribosomes and use tRNA-like and mRNA-like properties of tmRNA to add a short sequence to the nascent polypeptide and terminate translation at a stop codon within tmRNA4. In some bacteria, including N. gonorrhoeae, tmRNA and SmpB are essential6. Other species have an alternative ribosome rescue factor  that acts as a backup system for rescuing ribosomes when trans-translation activity is not sufficient10. Deletions of the alternative ribosome rescue factors and tmRNA or SmpB are synthetically lethal, indicating that at least one mechanism for ribosome rescue is required for bacterial viability5.Bacterial ribosomes frequently stall at the 3′ end of mRNAs lacking an in-frame stop codon due to physical or nucleolytic damage to the mRNA or premature termination of transcriptiontrans-translation in Escherichia coli has broad-spectrum antibiotic activity in vitro11. Experiments in E. coli and Mycobacterium smegmatis showed that KKL-2098, a cross-linkable acylaminooxadiazole derivative, bound 23S rRNA near the peptidyl-transfer center (PTC), suggesting that these molecules inhibit trans-translation by binding the ribosome11. Based on these data, we sought to optimize the acylaminooxadiazole activity against N. gonorrhoeae and establish the basis for selective inhibition of trans-translation.A family of acylaminooxadiazoles identified in a high-throughput screen for inhibitors of N. gonorrhoeae and activity (EC50) in a trans-translation luciferase reporter assay3, was responsive to structural changes, consistent with specific binding of the molecule to the target  and murine serum (>99.8% remaining after 1 h)  but did not inhibit translation in vitro , half-life (t1/2), and a low clearance rate . Efficacy was monitored by quantitative culture of N. gonorrhoeae from vaginal swabs, and clearance of infection from a mouse was defined as three consecutive days with no detectable N. gonorrhoeae  to determine the structure of KKL-2098 cross-linked to a non-stop ribosome Fig. . In prevE. coli3. The resolution of KKL-2098 was not high enough to distinguish one end of the molecule from the other, but the molecule could be oriented with high confidence based on the following considerations. First, Zone 4 of KKL-2098 contains the moiety that crosslinks to C24523, and in its current refined position this end of KKL-2098 is within 2.1 Å of C2452 . Other molecular interactions between KKL-2098 and the ribosome include the amide oxygen in Zone 3 with the 3′ end of the terminal A76 from the P-site tRNA. Overall, these interactions explain why minor changes in Zones 2 and 3 dramatically reduced potency  move ~180° from the PTC  and the acceptor stem of the P-site tRNA. In this position bL27 would not be able to participate in the peptidyl transferase reaction when tmRNA is presented in the A site. The two distinct positions of bL27 suggest that its N terminus is mobile and its movement may be required for optimal trans-translation activity.Although no major rearrangements in the rRNA core of the PTC were observed, the N-terminal 7 residues of ribosomal protein bL27  in manual mode, and are uncorrected. Thin-layer chromatography was performed on silica gel GHLF plates from Analtech , and the chromatograms were visualized under UV light at 254 nm. 5-(4-fluorophenyl)-1,3,4-oxadiazol-2-amine, 3-phenyl-1,2,4-oxadiazol-5-amine were purchased from Enamine ; 5-phenyl-1,2,4-oxadiazol-3-amine was purchased from Chembridge ; 5-cyclohexyl-1,3,4-oxadiazol-2-amine, 1,3,4-oxadiazol-2-amine were purchased from Life Chemicals ; p-Toluenesulfonyl Chloride, 1,1’-Carbonyldiimidazole were purchased from Thermo Fisher Scientific (Acros Organics) ; 4-Chlorobenzoyl chloride was purchased from Thermo Fisher Scientific (Alfa Aesar) ; 2-amino-5-phenyl-1,3,4-oxadiazole amine, 4-Chlorobenzoic acid, Cyclohexanecarboxylic acid, 4-Chlorobenzaldehyde, Pyrrolidine, Piperidine, Hexamethyleneimine, Morpholine, Methyl Iodide, Sodium Triacetoxyborohydride, Diisopropylethyl amine, Triethylamine, and all solvents were purchased from Millipore-Sigma ; 1,2,3,4-tetrahydro-isoquinoline and 4-chlorobenzene sulfonyl chloride were purchased from Combi-Blocks ; 4-methyl-1,2,3,6-tetrahydropyridine hydrochloride was purchased from Pharmablock ; HATU was purchased from GenScript .All commercially obtained reagents and solvents were used as received. 2O + 0.1% TFA).Heteroaryl amine (1.1eq) was dissolved in NMP (0.29 M) and triethylamine (1.2 eq) stirred for 10 min at room temperature; to this solution, acid chloride (1 eq) was added dropwise via pipette. The reaction mixture was allowed to continue stirring at room temperature for 16–20 h. If the reaction did not reach completion, the mixture was warmed to 50 °C for an additional 16–20 h. Upon completion, reaction mixture was added to water, and the resulting precipitate was filtered and dried. Crude precipitate purified with HPLC (5–95% MeCN/H2O + 0.1% TFA).Carboxylic acid (1.1 eq) and HATU/HBTU (1.2 eq) were dissolved in NMP (0.28 M), to which N,N-diisopropylethylamine (1.2 eq) and heteroaryl amine (1 eq) were added. The reaction was stirred at room temperature for 16–20 h. If the reaction did not reach completion, the mixture was warmed to 50 °C for an additional 16–20 h. Upon completion, reaction mixture was added to water, and the resulting precipitate was filtered and dried. Crude precipitate purified with HPLC (5–95% MeCN/H2O + 0.1% TFA).To oxadiazole amine (eq) and 1,1’-Carbonyldiimidazole (1 eq) in N-methyl imidazole (0.56 M) was added 3 Å molecular sieves (1.6 mm pellets: ~4 pellets/mmol). Reaction was stirred at room temperature for 3–16 h. Then, the second amine (1.1 eq) was added to the reaction and continued stirring at room temperature for 2–18 h. Upon completion, reaction mixture was added to water, and the resulting precipitate was filtered and dried. Crude precipitate was purified with HPLC (5–95% MeCN/H38. 15.0 mg (7%); mottled tan powder; 1H NMR (DMSO): 12.35 , 8.08–8.01 , 7.65 , 7.47 ; LC/MS: 318.0 (M + 1); mp: >240 °C (decomp.); Rf: 0.25 (50% EtOAc/hexanes).Prepared according to General Method A to provide material consistent with prior reports1H NMR (DMSO): 12.75 , 8.07–7.99 , 7.67–7.58 ; LC/MS: 300.0 (M + 1); mp: 182–188 °C; Rf: 0.64 (50% EtOAc/hexanes).Prepared according to General Method A. 26.0 mg (14%); off-white solid; 1H NMR (DMSO): 11.77–11.68 , 8.14–7.91 , 7.76–7.53 ; LC/MS: 300.2 (M + 1); mp: >102 °C (slow); Rf: 0.65 (50% EtOAc/hexanes).Prepared according to General Method A. 12.0 mg (6%); white solid; 39. 30.0 mg (16%); white solid; 1H NMR (DMSO): 12.26 , 8.08–7.96 , 7.67–7.62 ; LC/MS: 300.2 (M + 1); mp: 250–259 °C; Rf: 0.34 (50% EtOAc/hexanes).Prepared according to General Method A to provide material consistent with prior reports38. 26.0 mg (28%); White solid; 1H NMR (DMSO): 11.95 , 8.02–8.00 , 7.64–7.61 , 2.94 , 2.02–1.98 , 1.77–1.41 ; LC/MS: 306.2 (M + 1); mp: 204–206 °C; Rf: 0.72 (5% MeOH/DCM).Prepared according to General Method A to provide material consistent with prior reports1H NMR (DMSO): 12.12 , 9.10 , 8.06–7.98 , 7.65–7.59 ; LC/MS: 224.0 (M + 1); mp: 212–214 °C; Rf: 0.32 (5% MeOH/DCM).Prepared according to General Method A. 17.0 mg (13%); white solid; Material was purchased and tested as received from Life Chemicals, Inc.1H NMR (DMSO): 11.66 , 7.99–7.95 , 7.47–7.41 , 1.87–1.66 , 1.41–1.22 ; LC/MS: 290.0 (M + 1); mp: >205 °C (slow); Rf: 0.73 (3.75:46.25:50 MeOH/EtOAc/DCM).Prepared according to General Method A. 150 mg (97%); light brown solid; 40, by dissolving (E/Z)-N-(4-chlorobenzylidene)-5-(4-fluorophenyl)-1,3,4-oxadiazol-2-amine , and NaHB(OAc)3  in dichloromethane (1 ml), stirred at room temperature for 18 h. Adsorbed material onto Celite and isolated product from column chromatography eluted with linear gradient of 0–50% EtOAc in Hexanes. 27.0 mg (27%); White solid; 1H NMR (DMSO): 8.39 , 7.87–7.82 , 7.41–7.34 , 4.43 ; LC/MS: 304.1 (M + 1); mp: 165–167 °C; Rf: 0.42 (50% EtOAc/hexanes).Prepared in a manner analogous to that previously described2CO3  was added and the mixture was stirred at room temperature for 2 h. Then methyl iodide  was added and continued to stir at room temperature for an additional 65 h. The reaction was diluted with water (~30 ml), solid precipitate was filtered and dried under high vacuum. Product was purified by HPLC (20–100% MeCN/H2O + 0.1% TFA) and freeze dried to solid. 13.0 mg (18%); White solid; 1H NMR (CDCl3): 8.21 , 8.01–7.97 , 7.40 , 7.22 , 3.74 ; LC/MS: 332.2 (M + 1); mp: >148 °C (slow); Rf: 0.66 (50% EtOAc/hexanes).Prepared by dissolving 4-chloro-N-(5-(4-fluorophenyl)-1,3,4-oxadiazol-2-yl)benzamide  in DMF (2 ml), to which K1H NMR (CDCl3): 7.96–7.86 , 7.34–7.16 , 2.42 ; LC/MS: 334.1 (M + 1); mp: 218–221 °C; Rf: 0.14 (50% EtOAc/hexanes).Prepared according to modified General Method A; used solvent mixture of Pyridine/Dichloromethane (1/1 mixture) instead of NMP and trietheylamine. 33.0 mg (18%); white solid; 1H NMR (CDCl3): 7.98–7.95 , 7.20–7.14 , 3.57 , 1.96 ; LC/MS: 277.1 (M + 1); mp: 197–199 °C; Rf: 0.94 (10% MeOH/DCM).Prepared according to General Method C. 15.0 mg (20%); light yellow solid; 1H NMR (CDCl3): 7.97–7.92 , 7.21–7.15 , 3.65 , 1.62 ; LC/MS: 291.5 (M + 1); mp: 200–203 °C; Rf: 0.64 (10% MeOH/DCM).Prepared according to General Method C. 13.0 mg (9%); white solid; 1H NMR (CDCl3 + MeOD): 7.92–7.88 , 7.13–7.07 , 3.48 , 1.69 , 1.52–1.50 ; LC/MS: 305.7 (M + 1); mp: 191–194 °C; Rf: 0.63 (10% MeOH/DCM).Prepared according to General Method C. 15.0 mg (33%); white solid; 1H NMR (CDCl3 + MeOD): 7.93–7.89 , 7.18–7.12 , 3.66 ; LC/MS: 293.9 (M + 1); mp: 211–216 °C; Rf: 0.55 (10% MeOH/DCM).Prepared according to General Method C. 8.9 mg (15%); white solid; 1H NMR (CDCl3): 7.98–7.93 , 7.21–7.16 , 5.41 , 4.11 , 3.78 , 2.11 , 1.73 ; LC/MS: 303.0 (M + 1); mp: 180–181 °C; Rf: 0.74 (5% MeOH/DCM).Prepared according to General Method C. 19.0 mg (23%); white solid; 1H NMR (DMSO): 7.98–7.94 , 7.46–7.40 , 7.19 , 4.69 , 3.75 , 2.85 ; LC/MS: 339.1 (M + 1); mp: >190 °C (slow); Rf: 0.51 (50% EtOAc/hexanes).Prepared according to General Method C; dried precipitate solids were triturated in MeOH (~50 mL) yielded pure product. 375 mg (40%); white solid; E. coli strains expressing bL27  were constructed by transducing a tolC::cat allele into IW312 strains using a P1 vir phage. These strains were grown in LB medium containing 1 mM IPTG. To quantify the in vitro antibacterial activity of acylaminooxadiazole analogs against various bacterial strains, the minimum inhibitory concentration (MIC) was measured using microbroth dilution assays as described in the CLSI guidelines (M7-A7)41, except that liquid G77L medium42 was used for Neisseria gonorrhoeae MIC assays. Each assay comprised three technical replicates, and each assay was repeated at least once. The reported MIC is the geometric mean of at least 5 technical replicates. H041(STMR) is a streptomycin-resistant derivative of the multi-drug resistant (MDR), ceftriaxone-resistant strain H041 (Ohnishi) and was cultured as previously described43.Bacterial strains, plasmids, and synthetic sequences are shown in Supplementary Table 44 with the following modifications for N. gonorrhoeae. The bacterial inoculum for the assays was prepared by suspending colonies of N. gonorrhoeae ATCC 49226 grown on a chocolate agar plate for >24 h (37 °C with 5% CO2) in G77L medium. The cell suspension was adjusted to an OD600 of 0.1 and was diluted 1:10 in G77L media  containing various concentrations of MBX-4132. The resulting cultures were incubated at 37 °C (5% CO2), and viability was monitored over 24 h by removing samples at various time points, making serial 10-fold dilutions in G77L, and spotting 5 µl of each dilution onto the surface of a chocolate agar plate in triplicate. Colonies were counted after the plates were incubated at 37 °C (5% CO2) for 18–18 h, colony forming units (cfu) per ml were calculated, and the average and standard deviation for the three replicates was determined. The lower limit of detection of this assay was determined to be 100–200 cfu/ml. This experiment was repeated three times, and the results of a representative experiment are shown.The time kill assay was performed essentially as describedtrans-translation assay is designed to produce the first 157 amino acids of nano-luciferase from a non-stop mRNA (nanoluc-ns) and add the C-terminal peptide AAVSGWRLFKKIS via a mutant version of E. coli tmRNA (tmRNA-nl) to reconstitute an active nano-luciferase45. In this assay, the tagged nano-luciferase gene has >30,000-fold increase in activity over the peptide made in the absence of tmRNA-nl.The in vitro 46. Briefly, a culture of E. coli BL21 (DE3) cells containing a pET28 plasmid carrying the E. coli T7 polymerase gene was grown at 37 °C to an OD600 = 0.8, induced with 1 mM IPTG and grown for an additional 3 h. Cells were harvested by centrifugation at 20,000 × g for 10 min at 4 °C and the pellet was resuspended in buffer A (20 mM Tris-acetate (pH 8.2), 14 mM Mg(OAc)2, 60 mM potassium glutamate, 1 mM DTT). Cells were lysed by sonication, the lysate was clarified by centrifugation at 12,000 × g for 10 min, and the supernatant was stored at −80 °C.S12 lysates were made according to the procedure of Kim, et al.E. coli SmpB was purified as previously described3. tmRNA-nl, a variant of E. coli tmRNA encoding the final 11 residues of nano-luciferase, was transcribed from the tmRNA-nl synthetic DNA sequence in vitro, purified, and folded as previously described for wild-type E. coli tmRNA3. The nanoluc-stop template DNA was prepared as previously described3 by PCR amplification from pMC1 using T7 universal and nanoluc-stop primers. The nanoluc-ns was prepared in a similar manner using pMC1 with T7 universal and nanoluc-ns primers.trans-translation, tmRNA-nl and SmpB were premixed and stored on ice. S12 lysate (2 μl), freshly made polymix buffer (2 μl)47 , nanoluc-ns template  and 2 µl water were mixed and incubated at 37 °C for 5 min. This solution was dispensed to tubes containing 0.5 μl of different concentrations of an inhibitor prepared in 75% acetonitrile, 25% water, and incubated at 37 °C for 5 min. The tmRNA-nl/SmpB mixture  was added to each tube and the samples were incubated at 37 °C for 1.5 h. NanoLuc substrate (Promega) was prepared according to the manufacturer’s instructions, one volume of this substrate solution was added to each sample tube, and the reactions transferred to a white 96-well plate. Luminescence readings were obtained using the SpectraMax i3 microplate reader. Data analysis was performed using GraphPad Prism 8.For in vitro 48. N. gonorrhoeae strain 49226 (ATCC) was suspended to the equivalent of a 5 McFarland standard in G77L broth and then diluted to generate the final inoculum (1.5 × 105). The bacterial cell suspension was then transferred to wells in a stainless-steel replicator block which was used to inoculate the test plates. After the inoculum had dried, all plates were incubated at 35 °C in 5% CO2. The MIC was read post-incubation per CLSI guidelines48. To determine the frequency of resistance, stock solutions of MBX-4132 were prepared at 100X the final test concentrations of 4× and 8× the predetermined MIC value. A 0.5 mL aliquot of the 100X stock was mixed with 49.5 mL of molten GC Medium agar/1% IsoVitaleX to produce an agar/drug mixture that was either 4- or 8-fold the MIC and dispensed into sterile 150 × 15 mm plates (VWR) at a volume of 50 mL per plate. A dense cell suspension equivalent to 5 McFarland was prepared using bacterial growth from 48 h chocolate agar plates of N. gonorrhoeae (ATCC 49226). The viable count of each suspension was determined by plating serial ten-fold dilutions onto GC Medium agar/1% IsoVitaleX in duplicate. A 0.25 ml aliquot of inoculum was spread onto the surface of duplicate 150 × 15 mm test plates. After allowing the inoculum to dry on the surface of the plate, the plates were inverted and incubated at 35 °C (with 5% CO2) for 48 h. Colony counts were determined manually and the spontaneous mutation frequency was calculated using the following equation:First, MIC values were determined for MBX-4132 using the reference agar dilution methodIf there were no colonies on the antibiotic selection plates, the spontaneous mutation frequency was calculated as 1/inoculum to indicate that the spontaneous mutation frequency was less than the limit of detection (one cfu).50) of each compound against HeLa cells (ATCC CCL-2) was measured as previously described49. Each assay comprised three technical replicates, and each assay was repeated at least once. The mean values for each biological replicate were averaged, and the CC50 was determined using a 4-parameter nonlinear curve fitting algorithm (GraphPad Prism). The average of the CC50s from two biological replicates was calculated and reported.The half maximal cytotoxic concentration  was measured using the method of Kuhnz, et al.52. Caco-2 permeability values (Papp) > 1 × 10−6 cm/sec are predictive of oral bioavailability. The observation that Papp A→B > Papp B→A indicates that efflux from the basolateral compartment does not occur.To evaluate the potential for oral bioavailability, the ability of prioritized compounds to permeate a monolayer of Caco-2 (ATCC HTB-37) intestinal epithelial cells was determined as described53. The amount of compound in each chamber (buffer and serum) was measured using methods for reverse-phase liquid chromatography/mass spectroscopy methods that were customized for each compound.Serum protein binding was determined using an equilibrium dialysis method as described54. Each assay comprised three technical replicates, and each assay was repeated at least once. The reported solubility is the average of at least 5 technical replicates.The maximum aqueous solubility of each compound was determined using a nephelometric method as describedtrans-translation, we measured its dose-dependent activity against the non-stop luciferase reporter assay strain E. coli SB75 ΔtolC::kan (pluc-trpAt) essentially as described3, with modifications. Briefly, serial 1.5-fold dilutions of MBX-4132 in DMSO were transferred to 96-well assay plates (Costar 3195), followed by the addition of 50 µl of an overnight culture of SB75 ΔtolC::kan (pluc-trpAt) that had been diluted to a final OD600 of 0.4 with LB media supplemented with 100 µg ampicillin/ml and 1 mM IPTG. The final concentrations of MBX-4132 ranged from 0.05 to 1.5 µM, and the final concentration of DMSO was 2%. The assay plates were incubated at room temperature for 2 h, and 50 µl of BrightGlo (Promega) bioluminescence reagent was added to each well. After 10 min incubation, bioluminescence intensity was measured using an Envision multi-label plate reader (Perkin Elmer). Each assay comprised three technical replicates, and the experiment was repeated three times. The fold induction for each MBX-4132 treated sample as compared to the DMSO-only sample was calculated for each technical replicate, and the average and standard deviation of the three technical was calculated. The IC50 was determined using a 4-parameter nonlinear curve fitting algorithm (GraphPad Prism).To verify that MBX-4132 retains activity as an inhibitor of Several in vitro selectivity assays were performed at Eurofins Discovery Services using established methods and controls that behaved as expected . MBX-4132 was tested from a 5 mg/mL DMSO stock solution (the solubility limit), which provided plate concentrations up to 500 µg/plate, with serial dilutions accessing doses as low as 5 µg/plate. MBX-4132 precipitated at the two highest dose levels (500 and 100 µg/plate), but at 50 µg/plate, no precipitation was observed. Precipitation did not interfere with colony counts or analysis. Test articles were considered mutagenic when the mean number of revertant colonies increased in a dose-dependent manner. Some cytotoxicity was observed, but sufficient colonies were formed to allow analysis. As shown in Supplementary Table The Ames assay was performed at SRI Biosciences, following the standard protocols established there2 atmosphere at 37 °C. Cells were incubated in the presence of MBX-4132 at 10 concentrations starting a 100 µM and serially diluted 3.16-fold for 24 h at 37 °C, incubated for 30 min with multiplexed fluorescent dyes  and imaged to allow visualization of nuclei, reactive oxygen species generation, and mitochondrial oxidation. A >3.5-fold induction of ROS was considered consistent with formation of ROS and a >2-fold change in TMRE signal indicated an increase or decrease in mitochondrial membrane potential58.Multiplexed cytotoxicity assay — Human primary hepatocytes were grown on collagen I coated optical plates, cultured in hepatocytes culture media in a humidified 5% CO59. Assays were performed at Eurofins Cerep Panlabs.Mitochondrial toxicity assay — HepG2 cells (ATCC) were seeded and cultured in media containing either glucose or galactose overnight. Test compounds were added at 8 concentrations  and incubated with the cells for 24 h. Cell viability was measured by the alamarBlue method. The data in Supplementary Table ®, 0.45% hydroxypropylmethylcellulose, 0.45% alginic acid, 22.5% hydroxy-betacyclodextrin). At 0.25, 0.5, 1, 2, 4, 8, and 24 h post dose, 3 mice from each group were euthanized by CO2 inhalation, blood was collected by cardiac puncture into K2EDTA collection tubes, and protein was precipitated and analysed by LC/MS-MS for plasma concentrations of MBX-4132. Data were analysed using WinNonLin.Female CD-1 mice as above were fasted for 2 h prior, and 4 h after dosing. MBX-4132 was administered at 10 mL/kg via oral gavage with a 1.0, 2.5, or 10.0 mg/ml suspension in vehicle A  or subcutaneously to the intrascapular region (SC) in a 2 mg/ml 10% DMSO/80% PEG-400/10% water formulation. At 0.083, 0.5, 1, 4, 8 and 24 h post dose, blood was collected from 3 mice/group by tail vein or facial bleed into KSingle dose tolerability studies — Female CD-1 mice were fasted for 2 h prior, and 4 h after dosing. MBX-4132 was administered at 10 ml/kg via oral gavage with a 0.0 (vehicle control), 1.0, 2.5, or 10.0 mg/ml suspension in vehicle A. Mice were observed at 0.083, 0.25, 0.5, 1, 2, 5, 8, and 24 h post dosing, and any abnormal observations  were noted. No abnormal observations of any dosing group were made during the 24 h course of this study. 4–6 weeks-old CD-1 female mice were received from Charles River laboratories and acclimated for at least 5 days prior to the start of the study. Apart from specific instances of fasting described in the experimental, the mice had free access to food and water. The animals were housed 3–6 per cage in a temperature and humidity-controlled room with a 12 h light cycle. All procedures described are in compliance with the Animal Welfare Act, the Guide for the Care and Use of Laboratory Animals, and the Office of Laboratory Animal Welfare. These studies conform to the NeoSome IACUC policies and Operational Guidelines as approved by the IACUC membership, NeoSome Safety Officers, or Attending Veterinarian. All testing was performed at Neosome LLC.Multidose tolerability studies — In preparation for this study, an abbreviated version of the above murine PK study using the same formulation (A) examined fasted mice vs. fed mice was performed, with plasma samples taken at 1 and 4 h post dosing and analyses as described in the PK section. No significant variation in exposure was observed at either timepoint.Female CD-1 mice were given free access to food and water. MBX-4132 was administered to two groups of 3 mice for 7 d either QD (with compound) or BID, with an additional two groups of mice given only vehicle at 10 ml/kg via oral gavage with a 1.0 mg/ml suspension in vehicle A. Mice were observed visually twice daily for 10 d , additionally, mice were weighed once daily. Any abnormal observations  were noted. No abnormal observations of any dosing group were made during the 24 h course of this study. One mouse in the vehicle only group did exhibit a slight weight loss but had recovered weight by the end of the study.N. gonorrhoeae infection as described15. Mice were inoculated vaginally with N. gonorrhoeae strain H041 (104 cfu/mouse) two days after estradiol pellet implantation and vaginal swabs were cultured for 2 days post-bacterial inoculation to confirm infection. On the afternoon of the second culture day (day 0), mice were given MBX-4132, GEN or the vehicle (n = 20–21 mice/group). Doses of MBX-4132 were prepared fresh in vehicle at the time of treatment and administered as a single oral dose (dose volume 10 ml/kg). The positive control GEN (48 mg/kg) was prepared and administered intraperitoneally as 5 daily doses as previously described15. Vaginal swabs were collected on 8 consecutive days following treatment and quantitatively cultured for N. gonorrhoeae to assess efficacy. The data are expressed as CFU/ml of vaginal swab suspension. Clearance was shown by Kaplan-Meier curves with log-rank (Mantel-Cox) statistical analysis. The average cfu/ml over time was compared by 2-way ANOVA with Bonferroni post-hoc analysis. Statistics were performed in GraphPad Prism Software. Mice were housed in Allentown cage units with 2–5 animals per cage at 20–26 °C with relative humidity 30–70% and a minimum of 10 air changes/h and 12 h light/12 h dark cycle. At the study endpoint (10 days post-inoculation), mice were euthanized using compressed CO2 gas in a CO2 gas chamber in the Laboratory Animal Medicine Facility. All animal experiments were conducted at the Uniformed Services University of the Health Sciences, a facility fully accredited by the Association for the Assessment and Accreditation of Laboratory Animal Care, under a protocol that was approved by the university’s Institutional Animal Care and Use Committee.Groups of female BALB/cAnNCr mice (Charles River Laboratories) (6–7 weeks old) were treated with 17β-estradiol and antibiotics (streptomycin and trimethoprim) to increase susceptibility to long-term E. coli arfA gene was synthesized and assembled into pET28 that had been digested with NcoI and HindIII60. The sequence from arfA contains the RNase III cleavage site62. Translation of the cleaved mRNA produces a 59 amino acid peptide with 10 histidines at the N terminus.To construct pET28-H10arfArnc, a DNA cassette encoding 10 histidine residues, the M2 epitope, 3 glycine residues, and 20 arbitrary codons followed by 71 base pairs from the 3ʹ end of the E. coli 70S ribosomes were purified as described previously63. E. coli BL21(DE3) pET28-H10arfArnc cells were grown to an A600 of ∼0.5 in Luria broth (LB) medium at 37 °C and induced with 1 μM IPTG and 1 μM KKL-2098 (synthesized as previously described11) and continued to grow for an additional hour at 37 °C then cooled on ice for 20 min. All centrifugation steps were performed at 4 °C. Cells were pelleted by centrifugation and washed with buffer 1 ) twice and then resuspended in buffer 2 . The cells were crosslinked under ultraviolet light (254 nm) for 10 min, then lysed using an EmulsiFlex-C5 high-pressure homogenizer (Avestin). Cell debris was removed by centrifuging at 13,000 × g for 15 min. The lysate was further centrifuged at 27,000 × g for 30 min to obtain the S30 fraction. Ribosomes were pelleted by centrifuging at 42,000 × g for 17 h. The pellets were resuspended in buffer 2 and bound to a 1 mL IMAC gravity column, washed with 10 column volumes of Buffer 2 and eluted with Buffer 2 supplemented with 500 μM imidazole. Ribosomes were further purified over a 10–40% sucrose gradient in buffer 2 at 70,000 × g for 12 h. 70S ribosomes were separated from polysomes and subunits using a Brandel gradient fractionator. The 70S fractions were pooled, pelleted, resuspended in buffer 2, and stored at −80 °C.® grids  were glow-discharged for 20 s with a Solarus 950 (Gatan). In total, 3 μl of 70S complexes at 100 nM were placed on grids at 8 °C in 100% humidity and blotted for 3.5 s using a Vitrobot Mark IV (FEI).UltrAuFoil_/A°2 at a magnification of 59,000X  with a DE-64 direct electron detector in counting mode64 using Leginon65 for automatic data acquisition. Images were recorded with a total exposure time of 19.3 s, and intermediate frames were recorded every 0.2 s giving a total of 78 frames per image. Defocus values ranged from −1.3 to −3 μm.Two independent datasets of 2,394 micrographs total  were collected on a Titan Krios (FEI) microscope operated at 300 kV with a C2 aperture diameter of 70 μm. Movie frames were recorded at an accumulated dose of 58 e66. All frames of each micrograph were aligned using MotionCor267. Contrast transfer function (CTF) parameters were estimated on all motion-corrected micrographs using CTFFIND468 and GCTF67 and the best estimate chosen using resolution evaluation in Appion69. 197 micrographs were excluded after manual inspection of corresponding power spectra displayed ice contamination, exposure to the shifted beam, or low-resolution Thon ring profiles. An initial set of ~2000 particles were picked using DoG (Difference of Gaussian) Picker70. A rotational average was generated from these picks, and this was used as a template for template-based picking using FindEM71. A total of 474,382 particles  were picked. Particles were extracted with a box size of 384 × 384 pixels in Appion.Pre-processing — All processing steps were carried out using Appion72 73, with a 5-voxel expansion and a 7-voxel soft edge. This resulted in a class of 70S particles with P-site tRNA. These particles were unbinned, refined, then underwent focused classification with an A site mask, created as stated, using a model of the 70S ribosome with A-site tRNA (PDB 4V5D)23. Classes with P-site tRNA but no A-site tRNA were refined and post-processed.Initial 3D refinement occurred against a 60 Å low-pass filtered empty 74. The graphs of directional 3D FSC and global resolution of the maps were plotted using 3DFSC Processing Server75. Local resolution was estimated using blocres in Bsoft76.The resultant map was post-processed in RELION-3 using a solvent mask generated from the final reconstruction low-pass filtered to 40 Å with a 7-pixel extension and 10-pixel soft edge. Beam-tilt estimation and correction was performed (without per-particle refinement of CTF parameters) using CTF refinement followed by 3D reconstruction. These steps were repeated iteratively until the highest resolution was achieved, and the final map post-processed with a solvent mask. Resolution estimations were calculated from Fourier shell correlations (FSC) at 0.143 between the two independently refined half-maps. Maps were sharpened in PHENIXE. coli 70S ribosome (PDB 5MDV) were removed of P-site tRNA, E-site tRNA and mRNA and rigid-docked into cryo-EM maps using UCSF Chimera77. Ligand coordinates were initially generated in COOT using Lidia79. Ligand restraints were generated and edited in PHENIX eLBOW and REEL respectively80. P-site tRNA, mRNA, the N-terminus of bL27 and KKL-2098 coordinates were manually fit using COOT79. The P-site tRNA in PDB 5MDV was manually mutated to tRNAGly, the last codon in the mRNA sequence. The assembled complex was then subjected to real space rigid body refinement followed by validation in PHENIX 1.17.180.For initial model building, the coordinates of 11. At the other end of the molecule, Zone 1 was the most tolerant of substitutions .For the figures that show segmented maps (Supplementary Figs. Further information on research design is available in the Nature Research Reporting Summary linked to this article.Supplementary InformationDescription of Additional Supplementary FilesSupplementary Movie 1Reporting Summary


We reviewed relevant studies published up to July 2020, using three English databases  and two Chinese databases . The OHAT tool, with some modification, was applied to evaluate risk of bias. Meta-analyses were conducted with random-effects models for calculating the pooled estimate of markers. To assess the potential effect modifiers and the source of heterogeneity, we conducted subgroup analyses and meta-regression analyses where appropriate. The assessment and correction of publication bias were based on Begg’s and Egger’s test and “trim-and-fill” analysis. We identified 44 eligible studies. For short-term PM exposure, the percent change of a 10 μg/m3 PM2.5 increase on TNF-α and fibrinogen was 3.51% : 1.21%, 5.81%) and 0.54% : 0.21%, 0.86%) respectively. We also found a significant short-term association between PM10 and fibrinogen . Overall analysis showed that long-term associations of fibrinogen with PM2.5 and PM10 were not significant. Subgroup analysis showed that long-term associations of fibrinogen with PM2.5 and PM10 were significant only found in studies conducted in Asia. Our findings support significant short-term associations of PM with TNF-α and fibrinogen. Future epidemiological studies should address the role long-term PM exposure plays in inflammation and blood coagulation markers level change.Inflammation and the coagulation cascade are considered to be the potential mechanisms of ambient particulate matter (PM) exposure-induced adverse cardiovascular events. Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-8 (IL-8), and fibrinogen are arguably the four most commonly assayed markers to reflect the relationships of PM with inflammation and blood coagulation. This review summarized and quantitatively analyzed the existing studies reporting short- and long-term associations of PM  •The first review about associations of PM with TNF-α, IL-6, IL-8, and fibrinogen.•Short-term PM exposure was significantly associated with TNF-α and fibrinogen.•Short-term PM exposure was associated with IL-6 in studies conducted in Asia. This is the first review about associations of PM with TNF-α, IL-6, IL-8 and fibrinogen. Short-term PM exposure was associated with TNF-α and fibrinogen. TNF-α .There are close links between inflammation and blood coagulation. Inflammation is thought to regulate blood coagulation and activate the fibrinolytic system . For exaFibrinogen is regarded as a risk factor and predictor of cardiovascular disease . Studies2.5 and PM10 on the above markers. Among 6589 nonsmoking subjects in South Korea, for short-term PM exposure, Lee et al. reported 0.44%  higher fibrinogen levels with 10.4 μg/m3 increment of PM2.5 and 0.61%  higher fibrinogen levels with 20.1 μg/m3 increment of PM10  and 4.4% , respectively  with inflammation and blood coagulation markers . To fill this gap, this review summarized and quantitatively analyzed the existed studies, which could provide healthcare professionals and researchers with a comprehensive overview of the effect of short-term and long-term exposure to particulate air pollution on TNF, IL-6, IL-8, and fibrinogen.To date, there has been no meta-analysis to summarize associations of PM  “fibrinogen”, “blood coagulation factor I"; (3) “tumor necrosis factor-alpha”, “tumor necrosis factor alpha”, “tumor necrosis factor”, “TNFalpha”, “TNF-alpha”; (4) “Interleukin-6”, “IL-6”, “Interleukin 6”, “IL6”, “Interleukin-8”, “IL-8”, “Interleukin 8”, “IL8”. Also, synonyms of relative markers and particulate matter were searched using Medical Subjects Headings terms. Search strings were summarized in the supplementary material.We searched three English databases  and two Chinese databases  to identify epidemiological studies that examined the short-term and long-term associations of PM2.2in vivo studies, in vitro studies, case reports, summaries, reviews, editorials, commentaries, and studies that reported inflammation and coagulation markers in nasal lavage, induced sputum and exhaled breath condensate (EBC). Studies restricted to pregnant women   and longnt women  and focu2.3We downloaded all studies identified from five databases into a reference manager (Endnote X8) and removed duplicates. The remaining studies were screened for eligibility by two investigators. First, two investigators screened titles and abstracts to select eligible studies. Then, the remaining studies were reviewed in full texts. Two investigators selected studies independently, and a third investigator adjudicated disagreements. References of included studies were searched to find more relevant studies.2.4Two investigators extracted data from each study, including authors, publication year, characters of subjects , sample size, study design, study location, study period, an average of markers level , average levels of PM, exposure assessment methods, effect estimates , relative change, fold change) and standard error or a 95% confidence interval. The data extraction was performed by two investigators and any disagreements were adjudicated by a third investigator.3 PM increase. Beta-coefficients from linear regression models were normalized using an equation We used the percent change as effect estimates. All estimates were converted into percent change of a 10 μg/mls (CIs) , where β2.5The OHAT tool, with some modification, was applied to evaluate risk of bias . We cons2.62.6.1Meta-analyses were conducted only when four or more eligible studies examined the association between the same pollutant and the same marker . When st2, representing the proportion of heterogeneity in the total variation of effect, was used to quantify the heterogeneity among included studies. I2 values in the range of 50–100% indicate large or extreme heterogeneity  , age <6, gender 2.6.3To investigate the source of heterogeneity, we performed a meta-regression analysis . FactorsEach study was removed in turn to investigate the sensitivity of pooled results. The assessment and correction of publication bias were based on Begg’s and Egger’s test  and “tri33.13.2The evaluation for risk of bias was shown in 3.33.3.12.5 exposure  and 0.54% . Fibrinogen was not significantly associated with long-term PM2.5 exposure (3 PM2.5 increase on TNF-α (n = 4 studies) and fibrinogen (n = 12 studies) were 4.19%  and 0.26%  at lag 1 day respectively , while an insignificant association in studies conducted in Europe   .Table 1S3.3.32.5 exposure with TNF-α . The pooled estimate of IL-6 with short-term PM10 exposure was not significant , followed by general population .Sub-stratified analysis by exposure assessment technique, subjects, study location, and study design showed that a significant or stronger short-term association between PMl design . For exa3.4.310 exposure with TNF-α  . Trim-and-fill analysis shows no change in the overall analysis for studies reporting the long-term association for PM2.5-fibrinogen  . For shobrinogen .Table 2M42.5/PM10 with key inflammation and blood coagulation markers. Our meta-analysis showed significant short-term associations between PM2.5 and fibrinogen  and PM10-fibrinogen . For short-term PM exposure, the overall analysis showed the percent change of a 10 μg/m3 PM2.5 increase on TNF-α was 3.67% . However, in long-term studies, the pooled estimates of fibrinogen with PM2.5, and PM10 were insignificant.To our knowledge, we conducted this first review to comprehensively summarize and quantitatively analyze short- and long-term association of PMGiven the important role of TNF-α and fibrinogen for inflammation and coagulation cascade in cardiovascular disease, our results support that short-term PM exposure might cause adverse effects on the human body through inflammation and coagulation cascade. When human bodies are exposed to particulate air pollution, particles can cause an acute-phase response and inflammation indicated by increments of fibrinogen and inflammatory cytokines . Particl2.5 exposure during commuting, which may be due to exercise  at lag 1 day   at lag 2 day  and 1.8%  at lag 3 day and lag 4 day, respectively  and 0.26%  at lag 1 day respectively, and 0.08%  higher fibrinogen levels per 10 μg/m3 exposure to PM10 at lag 0 day.The short-term associations of exposure to PM with inflammation and blood coagulation markers are different at lag length, and such effects might be different in populations. A study conducted in COPD patients reported that the percent change of a 10.8 μg/mag 1 day . Among h, 7.13%) . Also, sag 2 day . Study oectively . Rückerlsubjects . To inve2.5 exposure with TNF-α and IL-6 in higher PM levels. Interestingly, it was found significant associations of short-term PM2.5 and PM10 exposure with fibrinogen in lower PM levels. Liang et al. also reported that the change of von Willebrand factor was more sensitive in the subgroup with PM2.5 < 25 μg/m3 , but an insignificant association in studies conducted in Europe  or North America . We also found significant pooled estimates of fibrinogen with PM2.5 and PM10 exposure in studies conducted in Asia, but not in Europe or North America. A study conducted in 10 cities around the world found that the cities located in Europe (except Milan) all met the EU PM2.5 annual mean standard (25 μg/m3), while the cites located in Asia have the highest PM2.5 annual mean concentrations , while the lowest source is heavy oil combustion (4%)  . A study exhaust . Moreove exhaust .3 exposure to the iron of PM2.5 at lag 1 day among healthy adults  , but an insignificant association for PM2.5 mass (3 exposure to black carbon at lag 4 day among patients with diabetes (2.5 (The variation of components in different regions may be a reason for inconsistent findings among studies . In Chiny adults . Lei et  99.10%) . A meta-2.5 mass . A revie2.5 mass . These f2.5 mass . Fang etdiabetes . Delfinodiabetes . In an etes   . However%, 7.7%) .2.5 and PM10, which leads to lower statistical power. Second, most studies used a single-pollutant model, although there may be interactions between pollutants (Our study had some limitations. First, few studies investigated long-term associations of PM with TNF-α, IL-6, and IL-8. Also, there are few reports on long-term associations of fibrinogen with PMllutants . It is d5Our meta-analysis showed fibrinogen and TNF-α were significantly associated with short-term PM exposure. The current study is too limited to draw an appropriate conclusion about long-term associations of PM with the above markers. Future epidemiological studies should address the role long-term PM exposure plays in inflammation and blood coagulation markers level change.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


This study aimed to investigate the feasibility of generating pseudo dual‐energy CT (DECT) from one 120‐kVp CT by using convolutional neural network (CNN) to derive additional information for quantitative image analysis through phantom study.Dual‐energy scans (80/140 kVp) and single‐energy scans (120 kVp) were performed for five calibration phantoms and two evaluation phantoms on a dual‐source DECT scanner. The calibration phantoms were used to generate training dataset for CNN optimization, while the evaluation phantoms were used to generate testing dataset. A CNN model which takes 120‐kVp images as input and creates 80/140‐kVp images as output was built, trained, and tested by using Caffe CNN platform. An in‐house software to quantify contrast enhancement and synthesize virtual monochromatic CT (VMCT) for CNN‐generated pseudo DECT was implemented and evaluated.The CT numbers in 80‐kVp pseudo images generated by CNN are differed from the truth by 11.57, 16.67, 13.92, 12.23, 10.69 HU for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. The corresponding results for 140‐kVp CT are 3.09, 9.10, 7.08, 9.81, 7.59 HU. The estimates of iodine concentration calculated based on the proposed method are differed from the truth by 0.104, 0.603, 0.478, 0.698, 0.795 mg/ml for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. With regards to image quality enhancement, VMCT synthesized by using pseudo DECT shows the best contrast‐to‐noise ratio at 40 keV.In conclusion, the proposed method should be a practicable strategy for iodine quantification in contrast enhanced 120‐kVp CT without using specific scanner or scanning procedure. The image contrast of CT depends on the differences in photon attenuation of various materials that constitute human body, whereas the degree of photon attenuation is related to tissue composition and photon energy. Dual‐energy CT (DECT) acquires two images at different energy levels to use the attenuation difference at different energies for deriving additional information, such as virtual monochromatic CT (VMCT) and iodine image.22.A18cm) to 23 cm (Cphan23cm), 28 cm (Cphan28cm), 33 cm (Cphan33cm), and 38 cm (Cphan38cm). The electron density phantom is made of soft tissue equivalent epoxy resin and houses 4 rod inserts + 5 syringes. The rod inserts simulate four different soft tissues, including adipose (0.96 g/cc), breast (0.991 g/cc), muscle (1.062 g/cc), and liver (1.072 g/cc). The plastic syringes  were filled with iodine solution at concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml.A calibration phantom set which consists of an electron density phantom and additional annuluses was used to generate training dataset for CNN optimization Fig. . The ele2.B3. The elliptical, epoxy resin‐based phantom houses 17 rod inserts simulating lung , adipose (0.96 g/cc), breast (0.991 g/cc), plastic water (1.016 g/cc), muscle (1.062 g/cc), liver (1.072 g/cc), trabecular bone (1.161 g/cc), dense bone (1.53 g/cc). The second evaluation phantom (Ephan2) shown in ]i, bj ci2.Freal) and pseudo CT images (Ipseudo) generated by CNN was quantified by using RMSE and PSNR:BG and SDBG are the average and standard deviation of CT numbers of tissue equivalent background material, respectively.The difference between real CT images ]]i, bj ciL/I0)) are shown in [Fig. Figures 3.B18cm, Cphan23cm, Cphan28cm, Cphan33cm, Cphan38cm obtained from real DECT scans. For these acquired images, the CT numbers of iodine syringes at 80 and 140 kVp are depicted in [Figs. Figure 3.C7 iterations are compared with real DECT images in Fig. 7 iterations are differed from the truth by 11.57, 16.67, 13.92, 12.23, 10.69 HU for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. The corresponding results for 140‐kVp CT are 3.09, 9.10, 7.08, 9.81, 7.59 HU. As for the iodine concentration estimated by the in‐house software with pseudo DECT generated by CNN after 107 iterations, the estimates are differed from the truth by 0.104, 0.603, 0.478, 0.698, 0.795 mg/ml for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. With regards to the efficacy of our proposed method on image quality enhancement, the CNR of VMCT synthesized by the in‐house software with real and pseudo DECT are demonstrated in [Figs. Figure 4Contrast material enhancement for CT has been used since the mid‐1970s. Besides providing visual enhancement between a lesion and the normal surrounding structures, contrast enhanced CT can also be used for estimating iodine concentration through DECT. Since CT contrast enhancement in the lesion has close relationship with the vascular density, the iodine volume is associated with tumor differentiation.In this work, the feasibility of using deep learning method to generate pseudo DECT based on one 120‐kVp SECT scan for quantitative image analysis has been investigated through phantom study. According to Fig. Several limitations to this study need to be acknowledged. First, the data acquisition, processing and reconstruction approaches can influence the study results. The protocol parameters used in this study are suggested by the manufacturers and are currently employed in many centers equipped with the same scanners. Additional studies assessing the proposed workflow for different DECT scanners will be needed and valuable. Second, CT images were acquired either with the calibration phantoms or with the evaluation phantoms. When the proposed workflow is translated to clinical use, it is expected that the accuracy of CNN‐generated pseudo DECT determines the performance of the proposed method. Challenges arise because tissue heterogeneity is not modeled in this phantom study. In clinical implementation, transfer learning should be performed to retrain the CNN model by using CT images obtained from patient DECT and SECT scans. The efficacy of the proposed workflow on clinical patient data needs to be further investigated.5This study investigated the feasibility of generating pseudo DECT from one 120‐kVp CT by using deep learning method to quantify iodine concentration and synthesize VMCT through phantom study. Based on our results, the accuracy of iodine concentration estimated by the in‐house software with CNN‐generated pseudo DECT imaging was comparable to the commercial software with real DECT imaging. Moreover, the VMCT synthesized by the proposed method could provide better image contrast than 120‐kVp SECT after energy optimization. In conclusion, the proposed method should be a practicable strategy for iodine quantification in contrast enhanced 120‐kVp SECT without using specific scanner or scanning procedure.


BCR-ABL1 molecular detection using quantitative PCR (qPCR) methods is the golden standard of chronic myeloid leukemia (CML) monitoring. However, due to variable sensitivity of qPCR assays across laboratories, alternative methods are tested. Digital PCR (dPCR) has been suggested as a robust and reproducible option. Here we present a comparison of droplet dPCR with routinely used reverse-transcription qPCR (RT-qPCR) and automated GeneXpert systems. Detection limit of dPCR was above 3 BCR-ABL1 copies, although due to background amplification the resulting sensitivity was 0.01% BCR-ABL1 (MR4.0). Nevertheless, in comparison with GeneXpert, dPCR categorized more than 50% of the patients into different MR groups, showing a potential for improved BCR-ABL1 detection. •-ABL1 copies.dPCR assays attain MR4.0 sensitivity due to a blank amplification 3 BCR•Quantification principle of RT-qPCR and dPCR introduces bias in copy numbers.•BCR-ABL1 measurement in >50% MR3.0-MR4.5 CML patients.dPCR provides more sensitive  However, it often shows insufficient sensitivity and inconsistent detection of minimal BCR-ABL1 levels [Specific targeting of the Bcr-Abl1 enzyme by tyrosine kinase inhibitors (TKI) revolutionized the management of chronic myeloid leukemia (CML) to the point that TKIs can offer near normal life expectancy for CML patients . Current1 levels . Despite1 levels ,4.BCR-ABL1 monitoring suggest that dPCR has increased sensitivity up to MR5.5, although higher false positivity rate (FPR) could lower the detection limit of this method [Digital PCR (dPCR) offers high reproducibility, precision and increased sensitivity for rare target detection . Recent s method . TherefoBCR-ABL1 and ABL1 assays and to evaluate the suitability of dPCR for molecular monitoring of CML patients with low or undetectable levels of BCR-ABL1 in comparison with routinely used methods.The objectives of our study were to evaluate the performance of droplet dPCR using the Europe Against Cancer (EAC) standardized 22.1BCR-ABL1 negative controls. All samples were obtained from the Department of Internal Medicine, Haematology and Oncology, University Hospital Brno. Characteristics of CML patients are listed in A retrospective analysis was performed on 70 clinical samples from chronic phase CML patients and 15 samples from healthy volunteers used as 2.2BCR-ABL1 transcript by RT-qPCR in accordance with the manufacturer’s recommendations.ERM AD623 BCR-ABL pDNA (Sigma-Aldrich) plasmid set  was used2.3All qPCR measurements were performed at the Centre of Molecular Biology and Gene Therapy, University Hospital Brno. Two methods, routinely performed to assess treatment response, were used: conventional RT-qPCR and the GeneXpert-based assay.BCR-ABL1 in K562 cells was performed on an Applied Biosystems 7300 Real-Time PCR System. Cepheid Xpert BCR-ABL Monitor test was used for quantification of BCR-ABL1 in clinical CML samples, according to the manufacturer’s recommendations. Reverse transcription and qPCR reaction conditions are described in detail in Supplementary Data and RT-qPCR quantification of 2.4All dPCR measurements were performed at the Central European Institute of Technology of Masaryk University Brno, Department of Molecular Medicine on Bio-Rad QX200 Droplet Digital PCR System (dPCR) according to the manufacturer’s recommendations. Reaction conditions are described in Supplementary Data and 2.5The formulae for calculation of FPR, limit of blank (LOB) and limit of detection (LOD) are concluded in Supplementary Data. Statistical analyses were generated using GraphPad Prism v.9 software. P values < 0.05 were considered significant.33.1BCR-ABL1 and ABL1 copies across the dilution range of the ERM AD623 standard down to 10 copies, with R2BCR-ABL1 = 0.998 and R2ABL1 = 0.999, respectively  was 4% with LOB = 1.4 copies/sample, and the FPR of BCR-ABL1 negative controls  was 6% with LOB = 3.2 copies/sample , and the samples from s/sample . A detecBCR-ABL1 in 3 independent dilution series. We used a cDNA sample from a CML patient with 10% BCR-ABL1IS, which was serially diluted into BCR ABL1 negative control. Digital PCR detected BCR-ABL1 transcript all sample dilutions down to 0.0001% BCR-ABL1IS, however after correction to LOD (3.3 copies/sample), the final sensitivity was corresponding to MR4.0 (0.01% BCR-ABL1IS)  .Fig. 1Se3.2BCR-ABL1IS. Despite overall correlation of ratios (BCR-ABL1IS), RT-qPCR detected significantly more BCR-ABL1 copies than dPCR (P < 0.0001). Conversely, in the sample with low transcript levels (0.0032% BCR-ABL1IS), RT-qPCR quantified significantly less BCR-ABL1 copies compared to dPCR (P = 0.0477). Moreover, in all sample categories dPCR detected significantly less ABL1 copies (P < 0.0001)  . As a reR ratios .ABL1 copies than dPCR in these samples   (n = 12). RT-qPCR still quantified significantly more by dPCR) . The BCR3.3BCR-ABL1IS transcript level as follows: ≤10% (n = 3), ≤1% (n = 3), ≤0.1% (n = 14), ≤0.01% (n = 11) and ≤0.0032% (n = 13). We observed significant differences in the ratios measured by dPCR and GeneXpert in the patients with low transcript levels   , which a 2=0.49; C. OveralBCR-ABL1IS) 3-way comparison of BCR-ABL1 rations was performed as shown in RT-qPCR = 0.0049; PdPCR = 0.0010).In addition, in 12/44 patients .Finally, in 40% (10/25) of CML patients, evaluated by GeneXpert as anscript . However4BCR-ABL1 quantification has already been demonstrated, showing its superiority compared to RT-qPCR (LOD up to MR5.5) [BCR-ABL1 negative controls, not distinguishable from the lowest copy numbers in positive samples. Therefore, final sensitivity was decreased to MR4.0.The sensitivity of dPCR for o MR5.5) . In our BCR-ABL1 detection have been validated on dPCR in the studies of Franke and Maier [GUS and BCR control gene assays, or GUS alone, resulted in sensitivity of MR5.5 [BCR-ABL1 and ABL1 dPCR assays with low-background, 98% specificity, and sensitivity of MR5.0 [The assessment of the false positivity and the detection limit is especially important for the assays, monitoring minimal residual disease. The EAC assays for nd Maier ,10, revend Maier  describend Maier ,8,13. Inof MR5.5 . Most reBCR-ABL1 and ABL1 copy numbers quantified in K562 cell line and in CML patients by dPCR significantly differed from those detected by RT-qPCR. Franke et al. obtained similar results for samples with ≤0.1 BCR-ABL1% measured by dPCR, with significant redistribution of the patients into MR categories relative to RT-qPCR [ABL1 copies measured by two methods  [-ABL1% and BCR-ABL1 negative samples dPCR yielded more sensitive measurements, GeneXpert assay used for this comparison was validated to MR4.0 [BCR-ABL1IS). Still, more than half of the patients in MR3.0 - MR4.0 were categorized into different MR classes by dPCR. Similarly, Folta reported consistent MR levels only in 29/50 samples in a comparison of dPCR with more sensitive GeneXpert Ultra kit with sensitivity of MR4.5. [Herein, the  RT-qPCR . In addiby dPCR) . Since tto MR4.0 , which mf MR4.5. -ABL1 copies/sample, which corresponded to sensitivity of conventional quantitative methods. Nevertheless, dPCR categorized more than 50% of the CML patients into different MR categories compared to quantitative GeneXpert. CML patients in deep molecular response considered for TKI cessation could benefit from more sensitive monitoring using well optimized dPCR assays, however an international standardization independent from RT-qPCR would be required to promote dPCR as an alternative method.Our study demonstrated that droplet dPCR, tested with standard EAC assays, provided a detection limit of above 3 BCRDagmar Smitalova: Investigation, Writing – original draft, preparation. Dana Dvorakova: Resources, Conceptualization. Zdenek Racil: Resources, Writing – review & editing. Marianna Romzova: Conceptualization, Methodology, Supervision.Authors DS, DD, ZR, and MR have no competing interests.


Decreases in muscle size and function are a general consequence of old age; the precise mechanisms of these changes remain unclear. Recent studies suggest that fat deposition in muscle may also contribute to dysfunction in older adults. Fat content was quantified in the quadriceps, and its effects on function in healthy young (21-45 y) and older (65-75 y) men and women (n=44) of comparable physical activity were compared. A subset of the young matched with the older group for muscle fat content were also examined. Peak fat-free whole muscle cross-sectional area , volume , fat content , specific torque (Nm/mCSA) and peak contraction velocity (Nm∙s-1) were determined using fat-water magnetic resonance imaging and dynamometry (0-300□∙s-1). To examine potential molecular mechanisms of muscle weakness, vastus lateralis biopsies were obtained (n=31) and cross-bridge kinetics of type I and II fibers were determined. FF was higher in older adults than young (8.4±1.2% (SE), 7.6±1.4; p=0.03), while mCSA (48.9±10.4 vs. 64.2±17.3), MV (1536±532 vs. 2112±708), specific torque (2.6±0.4 vs. 3.2±0.4), and peak voluntary contraction velocity (422±20 vs. 441±23) were lower in older than young (p<0.01). Type II fiber myosin attachment rate was slower and attachment time longer in older muscle (p<0.017), providing a potential mechanism for the slowing of peak contraction velocity with age. Notably, differences at the whole muscle and molecular levels remained for the subset of young and older groups matched for FF, suggesting that fat deposition in muscle does not exacerbate age-related changes in function.