DMS produced from the reduction of DMSO was not a significant process. Surface concentrations of total DMSO ranged from 2.3 to 102 nM with biological consumption of dissolved DMSO between 2.9 and 111 nM·d−1. Comparisons between 14C2-DMSO assimilation and dissimilation rates suggest that the majority of dissolved DMSO was respired (>94%). Radiotracer microbial consumption rates suggest that dissimilation of dissolved DMSO to CO2 can be a significant loss pathway in coastal waters, illustrating the significance of bacteria in controlling organic sulfur seawater concentrations.The marine trace gas dimethylsulfide (DMS) is the single most important biogenic source of atmospheric sulfur, accounting for up to 80% of global biogenic sulfur emissions. Approximately 300 million tons of DMS are produced annually, but the majority is degraded by microbes in seawater. The DMS precursor dimethylsulfoniopropionate (DMSP) and oxidation product dimethylsulphoxide (DMSO) are also important organic sulfur reservoirs. However, the marine sinks of dissolved DMSO remain unknown. We used a novel combination of stable and radiotracers to determine seasonal changes in multiple dissolved organic sulfur transformation rates to ascertain whether microbial uptake of dissolved DMSO was a significant loss pathway. Surface concentrations of DMS ranged from 0.5 to 17.0 nM with biological consumption rates between 2.4 and 40.8 nM·d It accorganisms ,11,12,13rganisms . Howeverp), which gets released into the dissolved phase through algal cell lysis caused by grazing, viral attack or autolysis, or exudation [d by bacteria, and some phytoplankton containing extracellular DMSP-lyases, typically maintains relatively low nano-molar concentrations [The dominant source of DMS is thought to be via the microbial (bacteria and/or phytoplankton) enzymatic cleavage of algal-derived DMSP ,16,17, axudation ,22. Rapitrations .d are attributed to photochemical and microbial oxidation of DMS [Roseobacter clade using an enzyme called trimethylamine monooxygenase [p) coupled with transformation to the dissolved phase via a number of pathways, including permeative diffusion, cell lysis, and as a byproduct of cell activity, have also been suggested [d remain essentially uncharacterised, although biological DMSOd consumption in seawater was previously observed [d loss pathways include bacterial consumption, reduction to DMS, oxidation to dimethylsulphone, and export via sinking particles [d [d to DMS during anaerobic respiration [Hyphomicrobium [Arthrobacter [Methylophaga [Dimethylsulfoxide is also an important ubiquitous reservoir of organic sulfur in the ocean, where the total pool of DMSO is often greater than that of DMS , and equn of DMS ,25. The xygenase ,27. Howeuggested . The funuggested . The marobserved ,31. Possarticles . Severalicles [d . DMSO reicles [d , and a vpiration ,35. Growicrobium , Arthrobrobacter ,37, and ylophaga . Howeverylophaga .d uptake and dissimilation to CO2 were significant DMSOd loss pathways. Our results suggest that dissimilation of dissolved DMSO to CO2 can be a significant loss pathway (for DMSOd) in coastal waters.Our objective was to employ a novel combination of stable and radiotracers in order to simultaneously determine seasonal changes in multiple dissolved organic matter sulfur transformation rates, and to ascertain whether microbial carbon DMSOSurface samples (≤10 m) were collected from the Western Channel Observatory long term monitoring station L4, situated ~13 km south west of Plymouth . Water samples were collected by the RV Plymouth Quest using 10 L Niskin bottles mounted on a rosette sampler, which also housed a Seabird 19 + CTD. Sub-samples were decanted into acid-washed brown glass bottles, sealed with ground glass stoppers with no headspace, and at in situ temperature for the ~2 h transit back to the laboratory. Temperature variability during transit was +1 °C, which is within the in situ diurnal variability at station L4.https://www.westernchannelobservatory.org.uk/). Chlorophyll a concentrations were determined through fluorometric analysis of acetone extracted pigments [Synechococcus sp. numbers were determined by flow cytometry (Accuri C6 instrument) on unstained samples based on their light scattering and autofluorescence properties [Seawater temperature was determined from the Seabird CTD, which has an accuracy of ±0.001 °C . The conpigments . Nutrienpigments ,42 and ppigments . Numbersoperties . Phytoploperties .−1 and cryogenically trapped in a PTFE sample loop submerged in liquid nitrogen before desorption using boiling water to GC). For dissolved DMSP (DMSPd), the purged DMS sample was transferred to a glass vial with 10 M NaOH and hydrolysed for 6–24 h (to convert DMSPd to DMS). Following hydrolysis, samples were analysed as above. For dissolved DMSO (DMSOd), ~10 mg cobalt-doped NaBH4 was added to the purged DMSPd sample (which reduces DMSOd to DMS) and purged for a further 10 min, with DMS analysis as previous.Concentrations of DMS, DMSP, and DMSO in seawater were analysed sequentially using a purge and cryotrapping system coupled with sulfur specific gas chromatography using a Varian 3800 gas chromatograph with a pulsed flame photometric detector (GC-PFPD) using methodology described by Simó et al. , Simó ant), which includes particulate DMSP (DMSPp) and a minor fraction from dissolved DMSP (DMSPd), 7 mL of whole seawater was pipetted into a glass vial with 1 mL 10 M NaOH, and left for 12–24 h for hydrolysis to convert DMSP to DMS. Then, 1 mL was carefully pipetted to a glass purge tower for extraction of DMS as above. For DMSPp, 7 mL of whole seawater was gravity filtered through a 25 mm GF/F filter. The filter was placed in a glass vial with 7 mL MQ and 1 mL 10 M NaOH, and left for 12–24 h for hydrolysis. Then, 1 mL was pipetted to the purge tower and analysed as previously. For particulate DMSO (DMSOp), ~10 mg cobalt-doped NaBH4 was added to the purged DMSPp sample to reduce DMSOp to DMS, and subsequently analysed by GC as above. The detection limit of the system was approximately 2.9 pmol S. The standard deviation of at least duplicate experimental samples was on average 6%, 10%, 9%, 9%, and 7% of the mean for DMS, DMSPt, DMSPp, DMSOp, and DMSOd, respectively. DMS standards for calibration were prepared from DMSP  in a 10 M NaOH solution in Milli-Q water. Typically, 4–5-point calibration curves were carried out twice per month during the sampling period, with an r2 for the resulting linear regression of ng sulfur versus square root of the peak area of typically ≥0.996.For total DMSP  by withdrawing ~30 mL and immediately gently filtering through a Millipore filtration unit containing a 25 mm GF/F filter directly into a 20 mL glass receiving syringe . This was immediately injected into a purge tower, and purged with high purity nitrogen at a flow rate of ~100 mL min−1 for 15 min directly into the proton transfer reaction mass spectrometer . This results in an exponentially decaying peak, allowing the total amount of DMS in a sample to be calculated by integration of the total peak area. Baseline levels were attained after 15 min of purging. Calibration curves were prepared using pure DMS . A primary DMS standard was prepared gravimetrically followed by dilution to produce a secondary standard, using gas tight vials. Five working (tertiary) standards were made up by dilution of the secondary standard in ultra-pure water in 100 mL glass syringes, to produce a 5-point calibration. For analysis, sub-samples of each standard were taken using 20 mL glass syringes without exposing the sample to the air, and purged and analyzed as above. Calibrations were performed on each sampling date. DMSPd and DMSOd were sequentially reduced to DMS after adding NaOH (DMSPd) and cobalt-doped NaBH4 (DMSOd) [n = 11, p < 0.001), suggesting that DMS concentrations derived from PTR-MS analysis were on average 4% lower than those from GC measurements.We report DMS, DMSP (DMSOd) ,47 into 3-DMS, 99 atom % d, Merck, Gillingham, Dorset, UK), DMSPd  and DMSOd  at ~10% of in situ concentrations into triplicate experimental bags. These and a control experimental bag (without any stable tracer additions) were incubated for 3–4 h in the dark at in situ temperature. During experiments, sub-samples were collected over 3–4 time points from each bag using a 50 mL glass syringe via the inlet on the Tedlar bag. Approximately 30 mL was withdrawn (ensuring no headspace or bubbles) at each time point and immediately gently filtered through a Millipore filtration unit containing a 25 mm GF/F filter directly into a 20 mL glass receiving syringe. This was immediately injected into a purge tower and analysed by PTR-MS as above. This technique allows the simultaneous quantification of DMS derived from DMSP cleavage and DMSO reduction, gross DMS loss , and net change in DMS concentrations . DMS production from DMS cleavage was determined as the rate of accumulation of d6-DMS from d6-DMSP, while DMS production from DMSO reduction was measured as the rate of accumulation of 13C2-DMS from 13C2-DMSO. Biological consumption of DMS was calculated from the rate of decrease in d3-DMS. Net change in DMS results from the rate of change of DMS, and thus gross DMS production, is calculated as net change in DMS plus biological consumption.Isotope tracer incubation experiments were also conducted using surface waters collected from station L4 between May and October 2014. On each date, approximately 350 mL seawater was siphoned directly into four acid washed and rinsed Tedlar bags without exposure to ambient air. We simultaneously added DMS , the biological consumption of DMSOd (from loss of 13C2-DMSO corrected for any conversion to 13C2-DMS), and the biological consumption of DMSPd (from loss of d6-DMSPd corrected for any conversion to d6-DMS and d6-DMSPd). For subsequent isotope DMSPd and DMSOd analysis at each time point, 20 mL was withdrawn from the Tedlar incubation bags using a glass syringe and placed immediately into a 20 mL serum vial containing two pellets of sodium hydroxide, which were immediately crimp sealed. These samples were stored in the dark at in situ temperature for between 4 and 8 weeks [d and DMSOd were sequentially reduced to DMS after adding NaOH (DMSPd) and cobalt-doped NaBH4 (DMSOd) into the purge tower and direct analysis by PTR-MS as previously. Concentrations of stable isotopes were determined via PTR-MS at m/z of 63, 65, 66, and 69 for unlabeled DMS, 13C2-DMS, d3-DMS, and d6-DMS, respectively (as this method of soft ionization within the PTR-MS adds a proton to each compound with no fragmentation of compounds). Final concentrations were calculated using standard curves. To scale the rate of tracer consumption or production to in situ values, the calculated rates were divided by the concentration of added tracer  and multiplied by the concentration of natural DMS, DMSPd, or DMSOd as appropriate [d, and DMSOd were calculated from the inverse of the rate constants for the loss of d3-DMS, d6-DMSPd, and 13C2-DMSOd, respectively.On two of the sampling dates (21 July and 26 August 2014), additional samples were also taken during the time course incubations for the determination of DMSO 8 weeks ,50,51. Bropriate . Biologi14C2-DMSO was added to each bottle and incubated in the dark at in situ temperature (no headspace). Tracer nano-molar  additions of 14C2-DMSOd (14CH3SO14CH3) were added to samples to determine microbial assimilation into biomass and dissimilation to 14CO2. Labelled 14C2-DMSO was purchased from American Radiolabeled Chemicals, Inc  with a specific activity of 30 mCi mmol−1 and a radiochemical purity of >99% (based on high performance liquid chromatography). A primary stock was made by diluting 52 µCi into 25 mL of 18 MΩ milli-Q water (2.1 µCi mL−1), and was stored in gas tight amber vials in the dark at 4 °C. Storage trials suggest <6% loss in activity over 12 months. Addition volumes of 14C2-DMSO to seawater samples were <1% of the sample volume incubation experiments.Seawater samples from the coastal station L4 were collected from Niskin bottles via acid washed Teflon tubing directly into the gas tight dark glass bottles . Labelled d carbon assimilation, a volume of 100 mL of the seawater sample was withdrawn from the bottom of the gas tight sampling bottles with a Teflon tube attached to a gas tight glass syringe. The tube was detached and the glass syringe attached to a Swinnex filter holder containing a 47 mm Supor 0.2 µm filter [n = 10, for ~34,000 DPM added per incubation). Samples and procedural blanks were filtered in a downward position with application of a very gentle pressure , so DMS release .d carbon microbial oxidation to 14CO2 (dissimilation) was determined in triplicate by pipetting 1 mL samples (each from replicate 305 mL gas tight incubation bottles) into 2 mL micro centrifuge tubes , and adding 0.5 mL of SrCl2.6H2O (1 M to precipitate the 14CO2 as Sr14CO3), 20 µL of NaOH , and 100 µL of Na2CO3  . The efficiency of the process assessed by mass balance of added 14C label was 96% ± 3% (n = 6). After centrifugation, the supernatant was aspirated and the pellet washed twice with ethanol (80%), resuspended in 1 mL of NaOH solution (~10 nM) that had been adjusted to a pH of 11.7, before addition of Optiphase HiSafe III scintillant to create a slurry. The samples were vortex mixed and stored in the dark for >24 h before being analysed on the scintillation counter. This period ensures that any chemiluminescence arising from interactions between the added NaOH and the Optiphase scintillant subsides [−1 .DMSOn et al.  for 14C subsides . Procedud were determined from linear time course experiments (refer to −1) was initially calculated from a ratio of the 14C counts collected on either the filter (assimilation) or as precipitated 14CO2  divided by the 14C2-DMSO spike (DPM mL−1). The apparent rate constant was multiplied by the in situ concentration of DMSOd to calculate DMSOd assimilation or dissimilation rates (nM d−1). All rate constants were corrected by subtracting killed sample counts. In addition, dissimilation rates were corrected to account for a minor  contribution from assimilation into particles entrained within the Sr14CO3 precipitate.Microbial assimilation and dissimilation rates of DMSOrefer to , where t−1 (3 cells mL−1), mainly comprising of Pseudo-nitzschia (0.8 × 103 cells mL−1) and large (≥4 µm) Thalassiosira phytoplankton cells  and Neoceratium lineatum , respectively. From flow cytometry analysis, the numbers of nanophytoplankton (2–20 µm), picophytoplankton (<2.0 µm), and Synechococcus ranged between 0.12 and 15.9, 1.46 and 41.5, and 0.15 and 62.0 × 103 cells mL−1, respectively, and showed peaks in abundance during September  and, ty−1 c, which eptember c. Total r months d.t concentrations averaged 13.5 ± 8.9 nM (June–October). However, there were noticeably higher concentrations during May . The total DMSO concentration in surface waters ranged between 2.3 and 102 nM, with on average ~56% in the dissolved phase , excluding the three maxima that occurred during June and September. Net DMS production (change in 12C-DMS with time) ranged between 0.0 and 10.5 nM d−1 (average 3.7 ± 3.4 nM d−1n = 12). Summing net DMS production and DMS BC yields gross DMS production rates of 2.7–42.9 nM d−1  ranged between 2.4 and 40.8 nM d−1 a. The av = 11 −1 b. DMS pr1 −1 −1, b, and wa6-DMSPd and 13C2-DMSOd on two dates in July and August (organic S transformations are summarized in d (loss of 12C-DMSPd) of 20.7 ± 8.8 and 29.2 ± 13.5 nM d−1 on 21 July and 26 August, respectively. We calculated biological consumption of DMSP as 75.7 ± 14.3 and 48.4 ± 15.6 nM d−1 for July and August, respectively  of at least 55.0 and 19.2 nM d−1 for July and August, respectively  of 8.1 ± 3.3 and 18.9 ± 11.3 nM d−1, and thus calculated that gross DMSOd production must be at least 15.1 ± 6.4 and 6.7 ± 16.2 nM d−1 for July and August, respectively  ranged between <0.01 and 0.49 nM d−1 during June–December July 2014, and was at a maximum during summer months (d to CO2 (dissimilation) was significantly higher and ranged between 2.7 and 111.0 nM d−1, with maximum rates during June . The ranges of DMS, DMSPt, and DMS/DMSPt presented here also agree with those found in a previously published seasonal cycle at L4 [Karenia mikimotoi , perhaps reflecting the ability of several species, for example, Scrippsiella trochoidea and Heterocapsa triquetra, to directly produce DMS by cleaving dissolved DMSP [Heterocapsa sp. on 23 June 2014 (118 cells mL−1), which may have also contributed to the DMS maxima observed at this time. The range in DMSPt concentrations found at the coastal L4 station is within the range often reported for a variety of other marine environments, including the North Sea, North Atlantic, Mediterranean, and subarctic Pacific [Phaeocystis sp. blooms (>200 nM) [p/DMSOp for our study was 5.4 ± 4.8, in agreement with the average reported in Simó & Vila-Costa [t concentrations remained lower than DMSPt concentrations, with maximum values not exceeding ~50 nM, as was similarly reported for coastal Antarctic waters [t values are within ranges reported globally [t , which corresponded to an over 140-fold increase in the number of dinoflagellate cells from a pre-bloom average of 0.91 to 131 cell mL−1. During this time, the dinoflagellate abundance was dominated (90%) by Heterocapsa cells, which were previously absent. We thus hypothesise that either there is direct production of DMSOd from the high-DMSP producing Heterocapsa [d  reduction under anaerobic conditions [d accounted for 55% of DMSOt and showed no obvious trends over the sampling period. The concentration of DMSOt in surface waters also showed a significant relationship with dinoflagellate abundance .The average surface DMS concentration found at L4 between May and October 2014 was 5.1 ± 4.0 nM, which compares well with the average found in U.K. shelf waters over the same monthly span of 5.4 ± 8.6 nM  and lowr et al. ). Surfacved DMSP ,58,59,60 Pacific , but did>200 nM) ,61,62. T>200 nM) ,30,56,62la-Costa . In compla-Costa . During globally ,30,32,47 to DMSO . This trseawater . The SARseawater , althougise DMSP . Growth nditions . Alternanditions  have rec−1), possibly because of lower temperatures minimizing bacterial activity [Scrippsiella trochoidea  and the diatoms Pseudo-nitzschia pungens  and Leptocylindrus danicus , where the numbers of phytoplankton cells varied between <0.04 and 7.68, <0.16 and 2.6, and <0.10 and 196.0 cells mL−1, respectively. The most noticeable was the peak in DMS BC during June, which coincided with an increase in the numbers of Scrippsiella trochoidea (from average background of 0.16 to 7.92 cells mL−1), which accounted for ~72% of all the dinoflagellates. Despite generally occurring in relatively low numbers . Generally, these rates are in the range previously reported for a variety of marine environments [d cleavage correlated with the abundance of the grazing ciliate Tontonia ovalis  and large flagellates , possibly suggesting enhanced DMSP lyase activity owing to grazing pressures, perhaps as some chemical “don’t eat me” cue [−1 of DMS could be excreted from biological particles  suggests a tight coupling in coastal waters.The biological consumption rates of DMS determined during this temperate coastal study were generally in the same range as those reported for coastal Antarctic  and subaactivity . Biologiactivity ,68,69. Or et al. ), Scrippllimolar  or 174–3t cell−1 . The bac to DMSO ,68, and ronments ,20,30,68 me” cue , or becad due to assimilation and dissimilation (determined using radiotracers) ranged between 2.9 and 111 nM d−1. However, the maximum loss rate was driven by the relatively high DMSOd concentration of 62 nM compared with the otherwise seasonal average of 9.2 ± 6.4 nM. Excluding the observed maxima, radiotracer-derived DMSOd biological consumption ranged between 2.9 and 24.3 nM d−1. Independent stable tracer experiments using 13C2-DMSO during July–August also suggest gross biological DMSO consumption rates of 23.3 ± 5.9 and 25.6 ± 11.6 nM d−1  at 0.6–1.9 d, which is comparable to 0.5–0.7 d derived from the 13C2-DMSO stable tracer experiments, and not dissimilar to previous literature estimates of 2–5 d [d turnover time of 7.4 d in coastal river plume stations, presumably because of their lower DMSOd oxidation rates. The majority of DMSOd utilized by the heterotrophic community was respired (>94%), like a variety of other low nano-molar organic methylated substrates in seawater such as methanol, methylamines, glycine betaine, and trimethylamine N-oxide [2 in the upper ocean [d respiration data lend support to this idea. Tyssebotyn et al. [Excluding the maxima, the biological DMSO loss rates (assimilation plus dissimilation) in coastal waters determined in our study averaged 11.9 ± 2.8 nM dubations ,76. By c9 nM d−1 , possiblof 2–5 d ,76. Howeof 2–5 d  report a N-oxide ,79,80,81 N-oxide . The micn et al.  similarld  and low DMS (1.0 nM) conditions  and 0.08 ± 0.04 (n = 3) µg C L−1·h−1 during July and August, respectively  to yield rates of 0.44 and 0.30 µmol C L−1 d−1 for July and August, respectively. This suggests that these three organic sulfur species could support 13%–17% of the estimated bacterial carbon demand during summer months. Bacterial carbon demand was converted to sulfur demand, assuming a carbon to sulfur ratio of 86 [−1·d−1 for July and August, respectively. Calculations suggest that DMSPd alone could supply all of the sulfur to meet microbial demand . Even if only ~50% of DMSPd sulfur used by bacteria was incorporated into biomass, that is, used for assimilatory rather than dissimilatory purposes, then the combined uptake of DMS, DMSPd, and DMSOd  would still meet bacterial sulfur demands. DMSPd is known to be a widespread substrate for heterotrophic bacteria, with literature suggesting that it can provide up to 15% and 100% of their carbon and sulfur requirements, respectively [d suggest that this compound alone could supply 60–126% and 1.4–2.9% of bacterial sulfur and carbon demand, respectively. Bacterial utilization of such reduced organic sulfur species over dissolved sulfate is thought to be energetically preferable for the synthesis of methionine [The rates of biological consumption of DMSPnditions . During pathways . Althougus cells c assimile et al. , where ue waters . DMS hasaters [d , with ou8 nM d−1 . We estit et al.  using a  al. [−1 ). Bacter−1 [0.58 . Bacteriio of 86 ,87, resuectively ,83. Simithionine .d, and its oxidation to DMSOd. Stable tracer experiments suggest that DMS produced from the reduction of DMSOd is not a common pathway in temperate coastal waters, which contrasts to Antarctic regions. Microbial consumption rates of organic sulfur species follow the order DMSPd > DMSOd > DMS, where the microbial dissimilation of DMSOd to CO2 can be a significant loss pathway for DMSOd in coastal waters. However, what controls the loss of DMSOd and the identification of bacteria responsible  in seawater largely remains elusive.In summary, these data demonstrate that, throughout the productive months of the year at a temperate coastal location, the biological consumption of DMS is highly variable, and largely decoupled from the amount of DMS produced from cleavage of DMSP


The present review discusses currently published papers that are related to the regulation of PPARs via lipid metabolism, glucose metabolism, and amino acid metabolism to affect trophoblast physiological conditions, including differentiation, maturation, secretion, fusion, proliferation, migration, and invasion. Recent pieces of evidence have proven that the dysfunctions of PPARs in trophoblast lead to several related pregnancy diseases such as recurrent miscarriage, preeclampsia, intrauterine growth restriction, and gestational diabetes mellitus. Moreover, the underlying mechanisms of PPARs in the control of these processes have been discussed as well. Finally, this review’s purposes are to provide more knowledge about the role of PPARs in normal and disturbed pregnancy with trophoblast, so as to find PPAR ligands as a potential therapeutic target in the treatment and prevention of adverse pregnancy outcomes.Peroxisome proliferator-activated receptors (PPARα, PPAR Peroxisome proliferator-activated receptors (PPARs) belong to the steroid receptor superfamily, and play roles in both physiological and pathological processes. PPARs regulate cellular biology functions, cell differentiation, metabolic homeostasis, inflammatory response, and immune tolerance ,2. PPARsβ/δ, and PPARγ, which are encoded by separate genes labeled PPARA, PPARD, and PPARG, respectively [PPARs, along with the retinoic acid receptors , the thyroid hormone receptors (TRs), the liver X receptors (LXRs), the vitamin D3 receptors (VDRs), and the steroid receptors (SRs), are ligand-activated transcription factors and belong to the nuclear receptor family ,12. Threectively ,14.The activation of PPARs requires heterodimerization with the nuclear receptor, RXR. PPARs/RXRs can be activated by 9-cis retinoic acid or natural or synthetic PPAR ligands . The PPAα agonists used to treat dyslipidemias [β/δ is involved in cell differentiation, lipid accumulation, and polarization [2 (PGI2) and diverse PUFAs are natural PPARβ/δ agonists [2) and iloprost are drugs that activate PPARβ/δ [γ plays a pivotal role in adipogenesis, inflammation, and glucose metabolism [γ can be activated by diverse natural ligand PUFAs, including eicosanoids, fatty acids, and oxidized low-density lipoprotein. The bioactive metabolite of prostaglandin D2, 15-Deoxy-12,14-prostaglandin J2 (15dPGJ2), is a potent natural PPARγ agonist [γ and involved in insulin-sensitizing activity, fatty acid uptake, and accumulation [Each PPAR isoform has tissue-specific expression patterns that are correlated with their distinct functions. PPARα is described as a regulator of fatty acid metabolism . Endogenpidemias . PPARβ/δrization . Prostagagonists . Carbapr PPARβ/δ . PPARγ ptabolism ,24. PPAR agonist . Additiomulation . The desα and PPARγ nuclear transport is mediated by two nuclear localization signals (NLSs) in DNA-binding domain (DBD)–hinge and activation function 1 (AF1) regions, and their respective receptors include importin α/β, importin 7, and an unidentified receptor. Furthermore, the shuttling of PPARγ from nuclear to cytoplasmic is mediated via PPAR ligands and concentration Ca2+ [γ transport from nuclear to cytoplasmic occurs via interaction with the extracellular signal-regulated kinase (ERK) cascade, a component of the mitogen-activated protein kinase (MAPK)/MEK 1/2 [PPARs predominantly localize to the nucleus. Interestingly, PPARs can shuttle between the nucleus and cytoplasm, to regulate biological functions through multiple signals. PPARion Ca2+ . PPARγ t/MEK 1/2 . The locTrophoblast comes from the Greek word “tropho” that refers to feeding the epithelial cell in the placenta. This transient organ plays a pivotal role in fetal growth and development during pregnancy . For a hIn mice, the lack of PPARγ leads to embryonic lethality due to implantation defects. Thanks to MORE-PGKO mice, we understood that PPARγ expression in trophoblasts was sufficient to rescue embryonic lethality and confirmed that PPARγ was necessary for adipogenesis and normal insulin sensitivity . PPARγ s2, a natural PPARγ ligand, hindered the process and promoted the trophoblast apoptosis with the upregulation of P53 [Surprisingly, the role of PPARγ in trophoblast differentiation is controversial, depending mainly on synthetic or natural ligand, trophoblast subpopulation, and gestational age and type. Human primary trophoblast exposure to troglitazone, a synthetic PPARγ ligand, promoted the trophoblast differentiation. However, 15deltaPGJn of P53 . PPARs an of P53 . Barak Tn of P53 . The expn of P53 . Taken tThere is also the link among hypoxia, PPARs, and trophoblast differentiation. Daoud et al. proposed that cobalt, a mimic hypoxia chemical agent, inhibited the heart and liver fatty acid-binding protein  and PPAR expression and impaired trophoblast cell differentiation by inducing Hash-2 expression . Hypoxia−/−trophoblast occurs during default differentiation and invasion [PPARγ involvement in the process of trophoblast differentiation through hCG and GCM-1 is unquestionable . The PPAinvasion . PPARβ pinvasion . It is nThe implantation of the embryo involves a complex process of trophoblast secretion, maturation, fusion, proliferation, migration, and invasion during the first trimester of the placenta.Zhang et al. discovered that the PPARγ signaling pathway is involved in the regulation of visfatin by interleukin (IL)-6 in BeWo, indicating that PPARγ might promote the energy metabolism of trophoblast cells through the secretion of inflammatory cytokines . PPARβ aFollowing blastocyst adhesion, villous CTBs undergo cell fusion, so as to form the multinuclear STB, which exchanges the nutrients, gas, and metabolites in the fetal–maternal interface . PPARγ/RAs a direct transcription target of PPARγ, ANGPTL4 mediated the survival, proliferation, migration, and invasion of HTR-8/SVneo in vitro . The PPANutrients transported from the maternal to fetal circulation cross the villous trophoblast. Among nutrients, lipid from lipoproteins, glucose, and amino acids are essential for energy supply, steroid hormone synthesis, and fetus growth. The maternal profile influences placenta FA uptake through human trophoblasts .PPARs modulate fat transport, fat storage, and fat metabolism in trophoblast. The lipid droplet that is associated with protein adipophilin existed in human trophoblast and was enhanced during trophoblast differentiation and upregulated by PPARγ/RXR . The levThe PPARγ agonists thiazolidinedione and pioglitazone induced the expression of visfatin by IL-6, implying that PPARγ promotes trophoblasts’ energy metabolism . HyperglPPARs are linked with insulin signaling and amino acid transport in trophoblast. The activation of PPARα inhibits IRS-1 and AKT phosphorylation, thus leading insulin to stimulate the expression of SNAT2 and amino acid transport in trophoblast, which is essential for fetal growth . PPARγ wThese findings pointed out that the master regulator PPARγ/RXR, which dramatically alters fat, glucose and amino acid metabolism in trophoblasts, might provide clues to cure pregnancy metabolic diseases such as gestational diabetes mellitus (GDM) and PE.In summary, our review summarizes the current bodies of evidence about the role of PPARs in trophoblast differentiation, including secretion, fusion, maturation, proliferation, migration, and invasion, which is associated with energy metabolism. The dysregulation of these human trophoblast physiology processes can cause gestational diseases, including recurrent miscarriage, GDM, PE, and IUGR. PPAR ligands, especially rosiglitazone and 15dPGJ2, should be further investigated as well as their potential as therapeutic therapy for abnormal trophoblast function in related gestational diseases.


Aspergillus oryzae or Bacillus subtilis on soybean substrates extracted at 4, 25, or 55 °C. As metabolic changes for both A. oryzae and B. subtilis were most pronounced for substrates extracted at 55 °C, this temperature was selected to compare the two microbial fermentation strategies, which were shown to be markedly different. Specifically, fermentation by A. oryzae increased the levels of most organic acids, γ-aminobutyric acid, and glutamine, which were ascribed to carbohydrate metabolism and conversion of glutamic acid into GABA and glutamine. In contrast, fermentation by B. subtilis increased the levels of most amino acids and isoflavones, which indicated the high activity of proteases and β-glucosidase. Overall, the obtained results were concluded to be useful for the optimization of processing steps in terms of nutritional preferences.Soybean processing, e.g., by soaking, heating, and fermentation, typically results in diverse metabolic changes. Herein, multivariate analysis-based metabolic profiling was employed to investigate the effects of fermentation by  Glycine max L. Merill) contain numerous functional components such as proteins, isoflavones, fatty acids, vitamins, and essential amino acids, their direct use is hindered by indigestion caused by the presence of anti-nutrients such as oligosaccharides and trypsin inhibitors [Although soybeans , most prior investigations probed the individual effects of inoculated microbes on fermented soybeans, with only few studies comparing the effects of soybean fermentation by A. oryzae and B. subtilis on the corresponding metabolic profiles [Metabolic profiling of fermented products can be used to monitor metabolic changes and evaluate product nutritional value and functional characteristics . Althougprofiles ,14,15. Iprofiles ,17. ThusA. oryzae and B. subtilis after water extraction at 4, 25, or 55 °C, using gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS), gas chromatography-flame ionization detection (GC-FID), gas chromatography–mass spectrometry (GC–MS), and ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to identify primary and secondary metabolites. Metabolic differences are characterized by multivariate analysis, and correlation analysis is employed to explain sample variations and relationships between metabolites. The acquired data are matched with the metabolic pathways to investigate relative compositional fluctuations in fermented soybeans.Herein, we perform a comprehensive metabolic comparison of soybeans fermented by A. oryzae strain KCTC6983 was grown on yeast/peptone/dextrose agar at 25 °C for seven days, and the mycelium was collected into phosphate-buffered saline containing 0.01% Tween 80 and adjusted to an optical density of unity at 620 nm (OD620). The B. subtilis strain 168 was pre-cultured in tryptic soy broth at 37 °C overnight, inoculated into the same to a concentration of 1 vol%, and grown at 37 °C for 3 h. Subsequently, the culture was adjusted to an OD600 of unity.The Glycine max L. Merill; 100 g) seeds were soaked in sterile water (300 mL) and hydrolyzed at 70 rpm and 4, 25, or 55 °C for 24 h using a modification of a previously reported method [7 spores/mL) of A. oryzae (AO) or the cultured cells (2 × 108 /mL) of B. subtilis (BS) was then inoculated into the soybean medium to a final concentration of 1 vol%. A. oryzae and B. subtilis were cultured at 30 °C for seven days or at 37 °C for three days in a shaking incubator, respectively. After cultivation, the medium was lyophilized. Overall, six types of fermented soybeans were obtained.Soybean (v/v/v), and ribitol  was added as an internal standard (IS). After 30-min incubation at 37 °C and 1200 rpm, the samples were centrifuged at 16,000 × g and 4 °C for 3 min. The supernatants (800 μL) were transferred into new tubes, diluted with water (400 μL), and centrifuged under identical conditions. The resulting supernatants (900 μL) were transferred to new tubes and concentrated on a rotary evaporator  over 3 h. The residues were lyophilized for at least 16 h at −80 °C , and the dried samples were methoximated with 80 μL of methoxyamine hydrochloride in pyridine  at 30 °C and 1200 rpm for 90 min. For silylation, the samples were incubated with 80 μL of N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA) at 37 °C and 1200 rpm for 30 min. Hydrophilic compounds were analyzed on an Agilent 6890N GC  instrument equipped with a Pegasus TOF-MS  spectrometer. The extracted samples (1 μL) were injected in split mode (1:25 ratio) at an inlet temperature of 230 °C. Helium was used as a carrier gas at a flow rate of 1.00 mL/min. Metabolite separations were conducted for 28 min using a CP-Sil 8CB low-bleed/MS fused-silica capillary column . The initial oven temperature of 80 °C was held for 2 min, increased by 15 °C/min to 320 °C, and held for 10 min. Ion source and transfer line temperatures were set to 230 and 250 °C, respectively. m/z values of 85–600 were scanned, and the detector voltage was set to 1700 V. The acquired mass spectral data were compared with in-house, NIST, and Wiley9 libraries using ChromaTOF software . For quantification, the analyte/IS peak area ratio was estimated for selected ions , and pentadecanoic acid in chloroform  was introduced as an IS. After mixing, samples were extracted by 20-min ultrasonication, treated with aqueous NaCl , and centrifuged at 4 °C and 13,000× g for 5 min. The bottom layers were transferred into new tubes and concentrated, and the residues were treated with methanol (0.18 mL), toluene (0.1 mL), and 5 M aqueous NaOH (0.02 mL). The resulting mixtures were incubated in a thermomixer  at 85 °C and 300 rpm for 5 min, treated with methanolic BF3 , processed as described above, and treated with water (0.4 mL) and pentane (0.8 mL). The obtained solutions were centrifuged at 4 °C and 750× g for 15 min, and supernatants were collected into new 2-mL tubes before concentration. Finally, solutions of the thus prepared fatty acid methyl esters (FAMEs) in hexane (0.1 mL) were passed through 0.5-µm syringe filters and subjected to GC-FID analysis . For each run, 1-µL samples were injected by an Agilent G4513A autosampler using a split ratio of 10:1. Nitrogen gas was flowed into a DB-Wax  column at a rate of 1.00 mL/min. Both front inlet and detector temperatures were set to 250 °C. The initial GC temperature of 130 °C was held for 3 min, increased to 230 °C at 20 °C/min, further increased to 250 °C at 3 °C/min, and held for 5 min. Data were acquired using ChemStation software (Agilent), and qualification and quantification were conducted by comparison with FAME mixture standards . The extracts were treated with 5α-cholestane  as an IS, vortexed, and placed in a water bath held at 85 °C for 5 min. Saponification with aqueous KOH  was conducted in a water bath held at 85 °C for 10 min and was followed by immediate cooling in ice for 5 min. The mixtures were treated with hexane and water (1.5 mL each), agitated, and centrifuged at 4 °C and 1200× g for 5 min. The supernatants were transferred into new tubes, and extraction was repeated with hexane (1.5 mL). The supernatants (3 mL) were blown dry with N2 gas and further concentrated on a rotary evaporator (TOMY). The residues were derivatizated with MSTFA (30 μL) and pyridine (30 μL) at 60 °C and 1200 rpm for 30 min, and the thus obtained lipophilic compounds were analyzed on a GC–MS QP2010 Ultra system equipped with an AOC-20i autosampler . For separation, 1-μL sample aliquots were injected into an Rtx-5MS column  at a split ratio of 1:10. Helium was flowed at a constant rate of 1.00 mL/min, and the inlet temperature equaled 290 °C. The initial oven temperature of 150 °C was maintained for 2 min, ramped to 320 °C at 15 °C/min, and held for 10 min. The ion source and interface temperatures equaled 230 and 250 °C, respectively. Spectra were acquired for m/z 85–600, and ions were detected in selected ion monitoring (SIM) mode for peak analysis. For absolute quantification, accurate calibration curves were determined for each lipophilic standard at loadings of 0.025–5.00 μg and fixed to an IS weight of 0.50 μg , and calibration curves for absolute quantification were plotted in the range of 0.10–50.00 μg.Raffinose was extracted using the protocol employed for hydrophilic compounds, and the extracts were injected into the GC–MS instrument (Shimadzu). The operating conditions were as follows: carrier gas = helium (1.00 mL/min); injection volume = 1 μL; split mode ratio = 25:1; injection temperature = 290 °C; column = Rtx-5MS ; temperature program = start at 150 °C, hold for 2 min, increase at 15 °C/min to 320 °C, hold for 25 min; ion source and interface temperatures = 230 and 280 °C, respectively. Ions with m/z 100–1500 under the following conditions: capillary voltage = 2300 V; cone voltage = 50 V; ion source temperature = 110 °C; desolvation temperature = 450 °C; desolvation nitrogen gas flow rate = 800 L/h; and mass scan time = 0.25 s. Leucine enkephalin (m/z 556.2771) was used as a reference.Isoflavone analysis was performed using a modification of a previously reported method . Typicalt-test were presented as box-and-whisker plots created in MetaboAnalyst . Correlations among metabolites and between samples and metabolites were established by hierarchical cluster analysis (HCA) and heatmap visualization, respectively. Pearson’s correlation analysis was conducted using the statistical analysis system (SAS) software package . In the case of heatmaps, the result was obtained from UV-scaled data. Both HCA and heatmap visualizations were performed using MultiExperiment Viewer (MeV) software . For identified metabolite mappings, fold changes (FCs) were calculated for the average level of each metabolite as the BS fermented soybean/AO fermented soybean ratio. The outcome was transformed to log2 values (log2FC). PathVisio software  was employed to match log2FC values with the drawn metabolic pathways based on the Arabidopsis thaliana pathway in WikiPathways, Glycine max pathway in the KEGG database, and the published literature [Two differently fermented samples (AO or BS) were prepared for substrates extracted at three different temperatures . For metabolite analysis, three biological repetitions were used per sample. Relationships among or within group variations were probed by principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) after unit variance (UV) scaling using soft independent modeling of class analogy (SIMCA) software . To represent significantly different metabolites between two groups, the results of the Student’s terature ,23.In general, primary metabolites such as amino acids, organic acids, sugars, and fatty acids are variously assembled as end-products of fermentations and interrelated with secondary metabolites as precursors . SecondaAmong the multivariate descriptions, PCA is well known as an unsupervised technique and the initial step of multivariate analysis used to outline overall data with dimension reduction . Thus, dUltimately, PCA results demonstrated that soybean metabolic changes were mainly attributable to fermentation by AO and BS. For the same microbe species, soybeans extracted at 55 °C were notably different from those extracted at 4 or 25 °C, which suggested that the metabolic strategies of both AO and BS at 55 °C were different from those at 4 or 25 °C.Correlation analysis relates the results of quantitative metabolite profiling with clustering coefficients . As metaAll metabolites were largely grouped into two correlations, and some metabolites  produced by closely related pathways were clustered together. In addition, HCA patterns resembled those of PCA in R2). The quality parameter of X variables (RX2 = 0.629) was measured as 32.6% and 30.3% of the total variance for the first and second principal components, respectively. The prediction accuracy of the OPLS-DA model was represented by prediction goodness (Q2), which was estimated as 0.975 and thus indicated excellent prediction power (Q2 > 0.9) [Although unsupervised analyses such as PCA and HCA are useful for investigating overall sample patterns, they do not allow one to easily identify common properties for each variation. On the other hand, OPLS-DA is a suitable tool for reducing non-correlated variation and model complexity with improved interpretational ability, and its appropriate application can yield beneficial insights into common and predictive features in each sample group . As meta2 > 0.9) . Thus, tRX2 and Q2 were obtained as 0.595 and 0.963, respectively. In addition to the cross-validated Q2 value, the prediction strength was estimated based on the root mean square error of prediction (RMSEP), the low values of which indicate good prediction ability [p < 0.0001, 17 variables were considered as metabolites distinguishing between AO- and BS-fermented soybeans  and increased levels of lactic acid. Although fatty acid release commonly takes place under the action of microbial lipases, the preference of lipase activity depends on the initial substrates . As regaFor the BS-fermented group, extraction at 55 °C resulted in increased levels of amino acids  and tocopherols . The observed differences of amino acid contents were attributed to the intensified combination effects of heat treatment and BS fermentation. Soybean heat treatment has been demonstrated to induce the breakdown of protein peptide bonds and the release of amino acids . MoreoveRX2 and Q2 values were obtained as 0.897 and 0.996, respectively, and were indicative of excellent predictive power. OPLS 1 and OPLS 2 accounted for 83.4% and 6.4% of the total variance, respectively. VIP scores were used to determine metabolites mainly contributing to variation  refer to higher levels in AO-fermented soybeans, while shades of red (0 < log2FC < 5.5) imply higher levels in BS-fermented soybeans. In addition, metabolites significantly different  between the two experimental conditions in OPLS-DA results are indicated by asterisks (*).Pathway analysis is a powerful way of gaining insights into the metabolic change patterns associated with two different distributers. Based on all of the metabolites of soybean substrates, inoculated microbes produced or decomposed metabolites in some parts of the metabolic pathway of soybeans during fermentation . HoweverathVisio . For eacDue to carbohydrate metabolism, most sugars, sugar alcohols, and organic acids  were more abundant in AO-fermented soybeans. Three sugars  and two sugar alcohols (glycerol and mannitol) were only observed in AO-fermented soybeans. The abundances of sugars, sugar alcohols, and organic acids in AO-fermented samples were similar to those found in previous studies ,40. ConsBacillus than in Aspergillus [Bacillus [Regarding amino acid metabolism, the levels of most amino acids  were maintained at much higher values in the case of BS fermentation. Amino acids are nitrogen sources for both starting fermentation and growing microorganisms in general . In a prergillus ,40. Thusergillus . PreviouBacillus ,45. ThusBacillus .AO-fermented soybeans featured elevated levels of GABA, glutamine, and asparagine, which were ascribed to the high levels of glutamate decarboxylase  ,47 and gKoji rice fermented by Bacillus than in that fermented by Aspergillus [As regards secondary metabolism, we observed that two isoflavones (daidzein and genistein) were relatively abundant in BS groups. Isoflavones, known as phytoestrogens, exist in soybeans in two chemical forms, namely as aglycones and glucosides. Although the latter form is predominant, food processing methods such as heating and fermentation convert isoflavone glucosides into their aglycone forms by activating β-glucosidase . In partergillus . Therefoergillus ,53. Hencergillus .This study evaluated the metabolic differences between AO- and BS-fermented soybeans extracted at 4, 25, or 55 °C. Overall, soybean samples were grouped on the basis of fermenter type, which suggested that this type was the main factor responsible for the above differences. Interestingly, substrate extraction temperature also influenced the metabolic changes of fermented soybeans within the two fermenter groups, that is, soybeans extracted at 55 °C were different from those extracted at 4 or 25 °C. Within the AO group, soybeans extracted at 55 °C showed comparatively high amounts of lactic acid and reduced levels of fatty acids. In the BS group, elevated levels of amino acids were observed in soybeans extracted at 55 °C. These results implied that soybean extraction at 55 °C contributed to the activated metabolic changes of fermented products. For further investigation of differences between AO and BS, soybeans extracted at 55 °C were selected as a uniform substrate. Contrasting metabolic changes for AO and BS were explained by considering metabolic pathways. AO-fermented soybeans featured higher levels of sugar alcohols and organic acids, which was indicative of energy metabolism, and were also rich in GABA and glutamine because of the increased GAD and GS activities. On the other hand, the levels of most essential and nonessential amino acids were higher in BS-fermented soybeans, which were ascribed to elevated protease activities and the usage of organic acids as precursors. BS fermentation also resulted in comparatively high amounts of isoflavone aglycones. Hence, our results showed that different metabolic strategies of AO and BS as well as substrate conditions were largely responsible for the metabolic profile differences of fermented soybeans. The obtained insights are expected to deepen our understanding of variously fermented foods and help to optimize the processing steps for selectively enhancing the contents of the desired nutrients.


Streptococcus pneumoniae and non-typeable Haemophilus influenzae (NTHi) are the primary pathogens. We compared otitis media outcomes in infants randomised to either a combination of Synflorix™  and Prevenar13™ , with recommended schedules for each vaccine alone. We previously reported superior broader overall immunogenicity of the combination schedule at 7 months, and early superiority of PHiD-CV10 compared to PCV13 at 4 months.Aboriginal children living in Australian remote communities are at high risk of early and persistent otitis media, hearing loss, and social disadvantage. SSSP). Ears were assessed using tympanometry at 1 and 2 months, combined with otoscopy at 4, 6, and 7 months. A worst ear diagnosis was made for each child visit according to a severity hierarchy of normal, otitis media with effusion (OME), acute otitis media without perforation (AOMwoP), AOM with perforation (AOMwiP), and chronic suppurative otitis media (CSOM).In an open-label superiority trial, we randomised (1:1:1) Aboriginal infants at 28 to 38 days of age, to either Prevenar13™ (P) at 2–4-6 months (_PPP), Synflorix™ (S) at 2–4-6 months (_SSS), or Synflorix™ at 1–2-4 months plus Prevenar13™ at 6 months (SSSP(141). Ear assessments were successful in 96% scheduled visits. At 7 months prevalence of any OM was 91, 86, and 90% in the _PPP, _SSS, and SSSP groups, respectively. There were no significant differences in prevalence of any form of otitis media between vaccine groups at any age. Combined group prevalence of any OM was 43, 57, 82, 87, and 89% at 1, 2, 4, 6, and 7 months of age, respectively. Of 388 infants with ear assessments at 4, 6 and 7 months, 277 (71.4%) had OM that met criteria for specialist referral; rAOM, pOME, or CSOM.Between September 2011 and September 2017, 425 infants were allocated to _PPP(143), _SSS(141) or Despite superior broader overall immunogenicity of the combination schedule at 7 months, and early superiority of PHiD-CV10 compared to PCV13 at 4 months, there were no significant differences in prevalence of otitis media nor healthy ears throughout the first months of life.ACTRN12610000544077 registered 06/07/2010 and ClinicalTrials.govNCT01174849 registered 04/08/2010.The online version contains supplementary material available at 10.1186/s12887-021-02552-z. A 2008 analysis of the global burden of acute and chronic suppurative otitis media (AOM and CSOM) estimated an overall CSOM incidence rate of 4.76 per thousand people, 22.6% cases in under five-year-old children. In the first year of life, the lowest CSOM incidence rate was 1.59 per thousand in High Income Asia Pacific, the highest was in Oceania (36 per thousand) .Haemophilus influenzae (NTHi) in 58% cases and PCV7-type pneumococci in 5%, compared to 55 and 17%, respectively in non-PCV historic controls [During surveillance studies in the NT, culture of ear discharge from 83 cases of acute otitis media with perforation (AOMwiP) or CSOM in PCV7-vaccinees detected non-typeable controls .Few early-intervention trials for prevention or treatment of OM have been conducted in this population. One randomised controlled trial reported that long term antibiotics compared to placebo increase the resolution of OME and prevented progression to tympanic membrane perforation (TMP), with no increase in bacterial resistance . Whilst Haemophilus influenzae protein D conjugated vaccine, PHiD-CV10 (2009 to 2011), and 13-valent PCV13 (from 2011)  in low-risk infants, and a lack of effect in a small RCT in high-risk infants . The RRRSSSP group) with standard 2–4-6-month schedules of each vaccine (_PPP and _SSS groups). To date we have reported primary and secondary immunogenicity and safety outcomes; the SSSP schedule was safe, and from 2 months of age immunogenicity was superior overall [We proposed that infants at high risk of early mixed infections would benefit from both PHiD-CV10  and PCV13  given in the primary course schedule. We designed a 3-arm randomised controlled trial comparing a novel 4-dose primary course schedule of PHiD-CV10 at 1, 2, and 4 months plus PCV13 at 6 months  trial.The trial took place in five remote Aboriginal and Torres Strait Islander communities in the Northern Territory and Western Australia . The PRENomenclature used in this manuscript are: italics P and S indicate vaccine (Prevenar13™ or Synflorix™) received at the time point of interest, and to indicate the comparison of interest .Inclusion criteria: Infants 28 to 38 days of age with gestational age > 32 weeks, eligible for routine immunisations, first born if twins, and whose families intended to remain in one of the five participating communities until infant age 7 months [Parents and families were provided with information about the studies from pregnancy and provided written informed consent and assent (from mothers younger than 16 years of age) at infant age 28 to 38 days of age. 7 months .SSSP. Details of vaccine formulations are given elsewhere [Haemophilus influenzae conjugated vaccine, PHiD-CV10 (Synflorix™) contains ten pneumococcal serotypes, most of which are conjugated to protein D of H. influenzae. 13-valent pneumococcal conjugate vaccine, PCV13 (Prevenar™) has three additional serotypes, 3, 6A, and 19A, and all are conjugated to CRM197.Research nurses were trained in giving vaccines and in standardised ear and general health checks. See Table lsewhere . BrieflyR at 2–4 months, InfanrixR Hexa, and (for non-study participants) Prevenar13 at 2–4-6 months. Study staff provided treatment or referral for all concomitant conditions according to local guidelines.Throughout this study, the Australian Indigenous infant vaccination schedule was EngerixB™ at birth, RotarixEar assessments were made at scheduled study visits at 1, 2, 4, 6, and 7 months by research nurses trained in paediatric video otoscopy and tympanometry. Diagnostic categories (see Table SSSP group (20%) compared to either _SSS or _PPP groups (10%), and 70% power when compared to _PPP and _SSS groups combined (10%). Vaccine group comparisons were tested with Fisher’s exact test for the proportion of infants with each diagnosis of otitis media at each timepoint; 95% confidence intervals (95%CI) were calculated. An intention to treat approach was used, including all available data. Longitudinal patterns of ear disease from 4 months of age are described from available data. We also conducted post-hoc logistic regression analyses of risk factors for any OM, suppurative OM, tympanic membrane perforation, or bilateral OM at 7 months of age. We included vaccine schedule, gender, community, mothers report of infant chest or ear infections, or runny nose, number of recent clinic visits for ear problems, family (mother and sibling) history of ‘runny ears’, number of other children the mother had, number of children under the age of 5 years in the household, breast and bottle feeding, maternal smoking during pregnancy, mother current smoker, smoker in the household, exposure to fire smoke. Risk factors with univariate p < 0.10 were included in multivariable logistic regression model for each OM outcome. All data were analysed using Stata/IC 15.1 [The study sample size was estimated for analysis of immunogenicity. With this sample size we estimate 55% power to detect a doubling in the proportion of children free from OM at 7 months in the /IC 15.1 .The study was overseen by an independent Data Safety and Monitoring Board (iDSMB).The funders had no role in design, collection, analysis, interpretation of data, writing the report or decision to submit for publication. As corresponding author, AJL had full access to all the data in the study and had final responsibility for the decision to submit for publication. AJL was not paid by any agency to write this article.SSSP (141). 396 (93%) infants were randomised within the study window of 28 to 38 days of age , _SSS (141) or There were no substantial vaccine group differences in key risk factors for OM Table .SSSP groups, respectively. At 2 months, following a single dose of PHiD-CV10 in the SSSP group the prevalence of normal ears was 40, 48, and 40%, respectively. At 4 months, following a single dose of vaccine in the _PPP and _SSS groups and following two doses in the SSSP group, these figures were 20, 20, and 16%, respectively. At 6 months, following 2 doses in the _PPP and _SSS groups and three doses in the SSSP group, bilateral normal ears were detected in 10, 14 and 14%, and at 7 months 9, 14, and 10%. There were no statistically significant differences in the prevalence of bilaterally normal ears between vaccine groups at any age  was: i) OME in 38, 48, and 44% infants at 4 months, 34, 38, and 40% at 6 months, and 30, 34, and 34% at 7 months; ii) AOMwoP in 39, 32 and 37% infants at 4 months. 43, 40, and 39% at 6 months, and 49, 42, and 49% at 7 months; iii) AOMwiP in 3, 0, and 2% infants at 4 months, 10, 4, and 5% at 6 months, and 7, 6, and 5% at 7 months; iv) CSOM in 0, 1, and 1% infants at 4 months, 3, 5, and 2% at 6 months, and 6, 3, and 2% at 7 months. Any suppurative OM  was the worst ear diagnosis in 42, 33, and 40% infants at 4 months, 56, 48, and 46% at 6 months, and 61, 52, and 57% at 7 months. Any tympanic membrane perforation  was the worst ear diagnosis in 3, 1, and 3% infants at 4 months, 13, 8, and 7% at 6 months, and 12, 9, and 7% at 7 months. There were no statistically significant differences in any OM diagnosis between vaccine groups at any age  defined as three episodes in 6 months or four in 12 months, persistent OME (pOME) for at least 3 months, or any CSOM . RecurreTransitions from OM to no OM were very rare; 60 of 172 (35%) infants with OM at one month; 30 of 221 (14%) infants with OM at 2 months; 26 of 308 (8%) infants with OME or AOMwoP at 4 months; 27 of 307 (9%) infants with OME or AOMwoP at 6 months. Of 34 infants with AOMwiP at 4 or 6 months, two (6%) returned to normal at 7 months, and of 15 infants with CSOM at 4 or 6 months, none returned to normal ears at 7 months (Supplementary Table p = 0.03) compared to reference community. Statistically significant risk factors for suppurative OM and tympanic membrane perforations at 7 months were presence of prior ear discharge reported by the mother , number of recent visits to the clinic for ear problems , recent chest infections (OR 2.44 p = 0.01 for TMP only), recent runny nose (OR 2.29 p = 0.01 for TMP only), and mother having other children (OR up to 4.68 p < 0.01 for suppurative OM only). A multivariable analysis using a univariable approach  identified ear discharge (OR 4.98 p = 0.001) and number of children the mother had (OR up to 5.87 p = 0.006) as significant risk factors for suppurative OM. Ear discharge (OR 52.04 p < 0.0001) and number of visits to the clinic for ear problems (OR up to 5.45 p = 0.003) were significant risk factors for any TMP  of 0.37 .Additional file 2 Supplementary Table 2. Proportion  of infants with transitions in OM status from 1 to 2, 2 to 4, 4 to 6, and 6 to 7 months of age, for infants with ear assessments at both timepoints .Additional file 3. Supplementary Table 3. Univariable regression: odds ratios for suppurative OM, any OM, or bilateral OM at 7 months of age.


Pseudallescheria boydii ZM01, was isolated and characterized. Strain ZM01 can tolerate a maximum THF concentration of 260 mM and can completely degrade 5 mM THF in 48 h, with a maximum THF degradation rate of 133.40 mg THF h−1 g−1 dry weight. Growth inhibition was not observed when the initial THF concentration was below 150 mM, and the maximum THF degradation rate was still maintained at 118.21 mg THF h−1 g−1 dry weight at 50 mM THF, indicating the great potential of this strain to degrade THF at high concentrations. The initial key metabolic intermediate 2-hydroxytetrahydrofuran was detected and identified by gas chromatography (GC) analyses for the first time during the THF degradation process. Analyses of the effects of initial pH, incubation temperature, and heavy metal ions on THF degradation revealed that strain ZM01 can degrade THF under a relatively wide range of conditions and has good degradation ability under low pH and Cu2+ stress, suggesting its adaptability and applicability for industrial wastewater treatment.Tetrahydrofuran (THF) is widely used as a precursor for polymer syntheses and a versatile solvent in industries. THF is an environmental hazard and carcinogenic to humans. In the present study, a new THF-degrading filamentous fungus,  Strain YYL can completely degrade 6 mM THF within 32 h without a lag phase, whereas the lag phase increased to more than 96 h when the initial concentration of THF was increased to 100 mM [R. aetherivorans M8 exhibits an obvious lag phase of 5 days in the presence of 15 mM THF, which was prolonged to more than 15 d when the THF concentration was increased up to 30 mM [Pseudomonas oleovorans DT4, which has a superior maximum THF degradation rate compared to the other reported THF-degrading strains, cannot mineralize THF completely in the presence of THF concentrations higher than 30 mM, with the degradation ratio decreasing to 45% with 40 mM THF [Tetrahydrofuran (THF) is a colorless, highly soluble, and volatile heterocyclic compound that is widely used as an important basic feedstock for chemical syntheses and is an excellent solvent for lacquers and printing inks ,2. With −1) . A numbew on THF ,13,14,15o 100 mM . R. aethto 30 mM . PseudomAureobasidium pullulans, Cordyceps sinensis [Graphium sp. ATCC 58400 [Filamentous fungi are involved in multiple pathways associated with wastewater treatment, such as organic compound biodegradation, the formation of sludge flocs, settleability of the treated sludge, and sludge detoxification . Filamensinensis , and GraCC 58400  have beeGraphium sp. ATCC 58400, Mycobacterium vaccae JOB-5, and Rhodococcus sp. DTB after incubation with THF [R. aetherivorans M8, which was initiated by the addition of 5 mM THF [Two different microbial THF degradation pathways have been proposed in previous studies, but some metabolites remain speculative, such as 2-hydroxytetrahydrofuran. In the oxidation pathway, THF is inferred to be initially oxidized to 2-hydroxytetrahydrofuran, and 2-hydroxytetrahydrofuran is then oxidized to γ-butyrolactone before being transformed to 4-hydroxybutyrate. 2-hydroxytetrahydrofuran is a cyclic hemiacetal that can also autonomously form its tautomer 4-hydroxybutyraldehyde, which can be directly converted to 4-hydroxybutyrate. The metabolite 4-hydroxybutyrate, which is common to both metabolic pathways, is further oxidized to succinate and then thoroughly mineralized in the tricarboxylic acid cycle ,28,29. Swith THF ,29,30. I5 mM THF . However5 mM THF ,32.Pseudallescheria boydii ZM01 in THF degradation under different culture conditions and to further evaluate the range of substrates that strain ZM01 can degrade. The metabolic intermediates during THF degradation were also identified, and the metabolic pathway of THF in strain ZM01 was proposed.In the present study, a new filamentous fungus capable of sustained growth on THF as the sole carbon source was isolated and identified. We aimed to characterize the potential of THF (>99% in purity), γ-butyrolactone (>99% in purity), 1,4-dioxane (>99% in purity), and 1,4-butanediol (>98% in purity) were purchased from Aladdin Industrial Corporation  while 2-hydroxytetrahydrofuran (>95% in purity) was purchased from Macklin Biochemical Co., Ltd. . All other chemicals used as degradation substrates were of reagent or analytical grade.2HPO4∙12H2O, 1.0 g KH2PO4, 1.5 g NH4Cl, 0.2 g MgSO4∙7H2O, 0.03 g CaCl2∙2H2O, and 1 mL trace element medium stock solution . Mycelia of filamentous fungi were inoculated onto potato dextrose agar (PDA) plates at 30 °C for 10 days to produce conidia. Conidia were harvested by washing the cultured PDA plates with 5 mL of distilled water and were counted with a hemocytometer as previously described [6 conidia mL−1) for THF degradation characterizations and metabolic intermediates analyses. All liquid culture experiments were performed in 250-mL narrow-mouthed shake flasks, and the bottle mouth was sealed to reduce the evaporation of THF during the cultivation process.Minimal salt medium (MSM) supplemented with THF was initially used to isolate and culture THF-degrading microorganisms. MSM was prepared with the following components (per liter): 4.5 g Naescribed . Then, thttps://blast.ncbi.nlm.gov). All the reference sequences were aligned using Clustal X, and a phylogenetic tree was generated with MEGA6 using the neighbor-joining method [The THF-degrading strain was enriched and isolated from activated sludge collected from Jiaxing Chemical Factory, Zhejiang Province, China. The collected samples were acclimatized in 100 mL of MSM supplemented with different concentrations of THF from 20 mM to 50 mM at 30 °C with continuous shaking at 200 rpm. After 28 days of continuous passage cultivation, the stable degradation consortium was serially diluted and plated on MSM agar plates containing 20 mM THF at 30 °C for 7 days. The colonies were continuously selected, and pure cultures were finally isolated after continuous passage cultivation for more than five generations. Fungal genomic DNA was extracted from mycelia using an Omega Fungal DNA kit . The internal transcribed spacer (ITS) region of strain ZM01 was amplified using the universal primers and sequenced by TsingKe Biotech . The obtained ITS region was aligned to sequences of other related species using the program BLAST . Samples collected at designated intervals were analyzed by GC to assess the residual THF concentration. The mycelia were filtered from fermentation liquid with gauze and vacuum freeze-dried to measure dry weight. The effects of THF volatilization have been considered and evaluated in our previous studies ,35, and maxμ is the maximum specific growth rate (h−1), S is the substrate concentration (mg/L), sK is the half-saturation constant (mg/L), and iK is the inhibition constant (mg/L). Thus, the specific degradation rate (v) can be calculated using the specific growth rate (μ) and growth yield (x/sY) as below [The Monod equation was unsatisfactory to determine the kinetic parameters due to substrate inhibition, while Haldane’s growth model was well-fitted even at inhibitory levels of the substrate. Thus, Equation (1) was adopted and is shown below :(1)μ=μmaas below :(2)v=dsdoC is the initial concentration of THF and tC is the residual THF concentration in fermentation liquid.The THF degradation ratio was calculated as follows: THF degradation ratio (%) = 5, 106, 2 × 106, 3 × 106, and 4 × 106 conidia mL−1); Cd2+ ; Pb2+ ; Mn2+ , and Cu2+ . The mother conidial suspensions with an initial concentration of 108 conidia mL−1 were prepared to analyze the effect of inoculum size on THF degradation. The effects of different culture conditions were finally evaluated based on the specific THF degradation ratio.In single factor experiments, conidial suspensions of strain ZM01 were incubated in 100 mL MSM containing 50 mM THF with shaking at 200 rpm. Various environmental factors were assayed to investigate their effects on THF degradation characteristics, including pH ; temperature ; inoculum size  after passing through a GC-MS interface maintained at 250 °C. Ions with masses ranging from 10 to 400 atomic mass units were scanned at 1-s intervals. Compounds were identified by comparing their fragmentation patterns with those of the authentic standards and the mass spectra library .To identify the intermediate metabolites of THF produced by strain ZM01, the intermediate metabolites were concentrated by organic solvent extraction. To this end, 20 mL of ethyl acetate was added directly to 70 mL of fermentation liquid, and the mixture was vigorously shaken for 20 min to completely extract the metabolites. The extraction phase was then evaporated to dryness and dissolved in 1 mL of ethyl acetate for GC-MS analysis. The final concentrated metabolic intermediates were identified using a GC-MS instrument  equipped with an HP-5ms capillary column (30 m × 0.25 mm × 0.25 μm). The column oven temperature was maintained at 40 °C for 3 min and then increased to 120 °C for 2 min at a rate of 10 °C minPseudallescheria sp. Based on phylogenetic analysis of the ITS region sequences (GenBank Accession No. MT754398) (P. boydii (GenBank Accession No. AY213683) with a high degree of similarity (99%). Thus, on the basis of morphological characteristics and phylogenetic relationships analysis, we identified the isolated THF-degrading fungus as Pseudallescheria boydii strain ZM01. To the best of our knowledge, this is the first report showing that THF can be metabolized by a Pseudallescheria sp. strain.A filamentous fungus capable of growing in MSM supplemented with THF as the sole carbon source was successfully isolated from activated sludge by enrichment cultivation and designated strain ZM01. Strain ZM01 could grow as white thread-like hyphae and could develop conidia growing directly on vegetative hyphae after cultivation for 7 d at 30 °C. Most conidia were usually brown, thick-walled, globose to subglobose. The shape of conidiogenous cells was cylindrical, and no yellow diffusible pigment was produced during the cultivation of strain ZM01 on PDA at 30 °C . The micT754398) , strain R. ruber YYL (200 mM), P. oleovorans DT4 (100 mM), R. aetherivorans M8 (35 mM), and Pseudonocardia sp. K1 (60 mM) [maxμ) of 0.23 h−1. The maximum THF degradation rate of strain ZM01 at 5 mM THF was 133.40 mg THF h−1 g−1 dry weight at a yield (X/CY) of up to 0.058 (dry weight substrate carbon−1) (R. ruber YYL (137.60 mg THF h−1 g−1 dry weight) [P. oleovorans DT4 (203.9 mg THF h−1 g−1 dry weight) [Graphium sp. strain ATCC 58400 (11.22 mg THF h−1 g−1 dry weight) [P. oleovorans DT4 significantly decreased to only 22.64 mg THF h−1 g−1 dry weight when the substrate concentration was increased to 20 mM, while it was 118.21 mg THF h−1 g−1 dry weight at 50 mM THF in strain ZM01, indicating that the degradation ability of strain ZM01 is superior to that of P. oleovorans DT4 at high THF concentrations.The substrate tolerance of strain ZM01 was studied at various THF concentrations. As shown in  (60 mM) ,17,30. Aarbon−1) , which w weight)  but lowe weight) . NotablyR. ruber YYL and P. oleovorans DT4, which were unable to completely mineralize THF higher than 30 mM and experienced a prolonged lag phase (more than 70 h) at THF concentrations below 50 mM, strain ZM01 exhibits superior THF degradation and growth characteristics under substrate stress [Incomplete degradation and a prolonged lag phase at higher substrate concentrations are frequently encountered problems for most THF-degrading bacteria. The results of our investigation showed that strain ZM01 could completely utilize 20 mM THF in 120 h and 50 mM THF in 240 h at 30 °C, with no lag phase observed when the initial THF concentration was below 150 mM . Comparee stress . The hige stress ,39,40.Afipia sp. D1, Mycobacterium sp. D6, Pseudonocardia sp. D17, and Rhodococcus sp. M8 and JCM 14343 have been reported to grow at initial pH below 6.0 when using THF or 1,4-dioxane as the substrate [Afipia sp. D1 and Rhodococcus sp. JCM14343, which maintained 50 and 56% of the highest 1,4-dioxane degradation ratio at pH 4.0, respectively, strain ZM01 has a higher tolerance to acidic environments [R. ruber YYL was inhibited at pH values lower than 7.0, and the degradation ratio was reduced by 40% when the initial pH value decreased from 8.26 to 7.0 [The effects of pH, temperature, and inoculum size were tested over a wide range and evaluated based on the THF degradation ratio . The pH ubstrate ,17,41. Wronments ,41. THF 6 to 7.0 ,38. NotaR. aetherivorans strain M8, which cannot grow at 22 °C [5 to 2 × 106 conidia mL−1, the THF degradation ratio increased from 48.54% to 85.71%. However, the degradation ratio was no longer significantly improved when the inoculum size was more than 2 × 106 conidia mL−1 due to the limited availability of some factors, such as trace elements and THF degradation-related monooxygenases [6 conidia mL−1 was used in subsequent experiments.The influence of the temperature used to cultivate strain ZM01 on the degradation ratio of THF is shown in at 22 °C , strain ygenases ,42. Base2+ > Cu2+ > Pb2+ > Mn2+. This trend was similar to that observed in a previous study on the effects of metal ions on 1,4-dioxane degradation by P. dioxanivorans CB1190 [2+, and the THF degradation ratio decreased from 63.9% to 30.7% when the Cd2+ concentration increased from 0.05 to 1 mM. The slightly stimulating effect of a small amount of Mn2+ (less than 2 mM) on THF degradation was evaluated, and the THF degradation ratio decreased by 24.6% with the addition of 4 mM Mn2+. A THF degradation ratio of more than 50% was observed when the cultures contained 1 mM Pb2+ and Cu2+, and further increasing the concentrations of these metal ions resulted in a reduction in THF biodegradation.Considering the toxic effects of heavy metals, many studies have investigated the influence of heavy metals on the biodegradation of pollutants by pure cultures or microbial consortia ,44. We ds CB1190 . Among t2+ was shown to have a strong inhibitory effect on THF degradation and was the most toxic trace element among Co2+, Cu2+, Ca2+, Zn2+, Mg2+, and Fe2+ [2+ showed that the addition of more than 10 mg/L Cu2+ caused a prolonged initial lag phase and decreased the 1,4-dioxane degradation rate [P. dioxanivorans CB1190 was shown to degrade 120 mg/L 1,4-dioxane with a degradation rate of 30.23 ± 2.86 mg L−1 d−1, which decreased by nearly 90% with the addition of 0.15 and 0.3 mM Cu2+ [2+ was also observed to sharply inhibit the THF degradation by consortium H1, with a THF degradation ratio of less than 10% observed after 108 h when the Cu2+ concentration was increased to 1 mM [2+, indicating that it has better THF degradation potential under Cu2+ stress.In previous studies, Cuand Fe2+ . A studyion rate ,46. Addi mM Cu2+ . In addi to 1 mM . Howevern-hexane, γ-butyrolactone, and 1,4-butanediol. In addition to THF, higher biomass was also observed in the presence of the candidate metabolites 2-hydroxytetrahydrofuran (58.9 ± 2.1 mg), γ-butyrolactone (53.7 ± 1.5 mg), and 1,4-butanediol (71.7 ± 1.5 mg), which is consistent with the results reported for THF-degrading bacteria [P. dioxanivorans CB1190, Afipia sp. D1, and Pseudonocardia sp. strain ENV478, strain ZM01 could also utilize 1,4-dioxane as the sole carbon and energy source in pure culture [Strain ZM01 was capable of utilizing a variety of substrates , includibacteria ,30. The  culture ,49. 1,4- culture ,37, whic culture .Although various methods have been used in an attempt to elucidate the pathway involved in THF metabolism in previous investigations, such as resting cell reaction, the metabolite 2-hydroxytetrahydrofuran still has not been detected and identified yet. In the present study, the metabolic intermediates of THF were measured and identified at different cultivation periods of strain ZM01 when utilizing 20 and 50 mM THF as substrates. As shown in Graphium sp. strain ATCC 58400 [P. boydii ZM01 (With the consumption of THF, the concentration of γ-butyrolactone increased proportionally over 84 h and then decreased gradually during THF degradation c. The maCC 58400 . The ferdii ZM01 b.P. boydii ZM01, was evaluated in this study. Strain ZM01 could tolerate THF at concentrations of up to 260 mM, which is superior to that of other reported THF-degrading strains. The maximum THF degradation rate for strain ZM01 was 133.40 mg THF h−1 g−1 dry weight at 5 mM THF and remained at 118.21 mg THF h−1 g−1 dry weight when using 50 mM THF as a substrate, indicating the great potential of strain ZM01 for the treatment of industrial wastewater contaminated with high concentrations of THF. The effects of initial pH, culture temperature, and heavy metal ions on THF degradation by strain ZM01 revealed that it has a wide range of growth and good degradation ability under low pH and Cu2+ stress. In addition to THF, strain ZM01 can also utilize 1,4-dioxane, dimethylfuran, benzene, n-hexane, and ethyl acetate as growth substrates. The results also showed that strain ZM01 degrades THF through the oxidation pathway, and notably, the THF-derived metabolite, 2-hydroxytetrahydrofuran, was detected and confirmed during THF degradation for the first time.The THF-degradation potential of a new filamentous fungus,