Gossypium hirsutum) and other crop plants. This study was carried out from 2019 to 2020 to determine the effects of different concentrations of MPCA-Na on physiological and metabolic activities besides growth and yield of cotton plants at seedling, budding, flowering and boll stages. Moreover, we evaluated the different combinations of 24-epibrassinolide, gibberellin (GA3), phthalanilic acid and seaweed fertilizer to ameliorate herbicide damage.2-methyl-4-chlorophenoxy acetic acid-Na (MPCA-Na) is a phenoxy carboxylic acid selective hormone herbicide that is widely used in the crop fields. However, drift of MPCA-Na during application is highly damaging to cotton  exposure caused a decrease in the chlorophyll content, and an increase in the soluble protein content, Malondialdehyde (MDA) content and protective enzyme activity. It also caused significant reductions in plant height, boll number and the single boll weight at the seedling and budding stages, but had little effects on plant height and the single boll weight at flowering and boll stage. Under the maximum recommended dose of MPCA-Na (130 g/L), the number of cotton bolls at seedling and budding stages decreased by 75.33 and 79.50%, respectively, and the single boll weight decreased by 46.42 and 36.31%, respectively. Nevertheless, the number of G. hirsutum yield. When the cotton exposed to MCPA-Na at the seedling stage, it should be treated with phthalanilic acid + seaweed fertilizer, while plants exposed at the budding stage should be treated with 24-epibrassinolide + seaweed fertilizer, and those exposed at the flowering and boll stages should be treated with GA3 + seaweed fertilizer to mitigate stress.The results of current study suggest that certain plant growth regulators could be used to alleviate MPCA-Na damage and maintain The online version contains supplementary material available at 10.1186/s12870-022-03917-x. Gossypium hirsutum) is an important economic crop in many places in the world [Cotton (he world . In the he world . Pesticihe world . In parthe world .G. hirsutum plants [2-methyl-4-chlorophenoxy acetic acid-Na (MCPA-Na) is a phenoxyacetic acid selective hormone herbicide . It expom plants . ReducinFor a long time, herbicide damage has been an important limiting factor of crop yield, especially in relation to inactivated herbicides –15. FielG. hirsutum is therefore important.Plant growth regulators play an important role in regulating crop growth and development, improving yield and quality, and enhancing stress resistance , 17. Not3, phthalanilic acid and seaweed fertilizer) were used following MCPA-Na exposure, which could promote cotton plants growth. The protective effects of different combinations of plant growth regulators on MCPA-Na phytotoxicity were then examined at each growth stage. The results of this study provide an understanding of the underlying mechanism of MCPA-Na toxicity in G. hirsutum, supporting measures aimed at the use of plant growth regulators to alleviate damage, which has important practical significance for cotton producers. And the study provides a case for the solution of herbicide damage in other crops.During this study, we examined the effects of MCPA-Na on physiometabolic activities and yield traits in cotton following herbicide exposure at the seedling, budding, flowering and boll stages. Four plant growth regulators . The soil was loam, containing 7.51 mg·kg-1 seeds). Seeding was carried out under mulch film with width of 1.5 m. Row were spaced at (30 + 50 + 30) cm, the cotton plants were spaced above 10 cm, and with a planting density of 150,000 plants/hm2.The cotton variety used was Xinluzao 12 , and the seeds were treated with imidacloprid seed coating agent 3PO4 @ 175 kg hm-2 and urea @ 260 kg hm-2 were applied as basal fertilizer. The seeds were sown on 15 April, 2019 and 25 April, 2020. Irrigation was carried out four times throughout the growing period on 2019  and 2020 , respectively. Drip irrigation was also carried out using 4125 and 4830 m3 hm-2 water on 2019 and 2020, respectively. During the cotton growth period (June–August), 525 kg hm-2 urea, and 450 kg hm-2 KH2PO4·NH4H2PO4 were also fertilization through drip irrigation. Chemical capping was carried out on 2019 (10 July and 25 July) and 2020 (3 July and 20 July) using 250–300 g hm-2 mepiquat chloride , respectively. Pest and disease control were carried out according to the standard management practices, mainly to control cotton aphids, thrips and spider mites.Before sowing, (NH3) crystal powder , seaweed fertilizer , and 20% Phthalanilic acid soluble concentrate .The following plant growth regulators were used: 13% MPCA-Na aqueous solution , 0.0075% 24-epibrassinolide aqueous solution , 75% Gibberellin (GA-1 (500 kg water hm-2) were configured for use in this study. In the preparation of MCPA-Na with different concentrations, 8.125, 16.25, 32.5, 65, and 130 g MCPA-Na were weighed with electronic balance, respectively. Then, poured into a bucket containing 1 L of water, and stirred evenly with a glass rod. The prepared of MCPA-Na was poured into a 3WBD-20 L back-loaded electric sprayer. The preparation was repeated according to the above steps until the sprayer was filled with the MCPA-Na.According to the recommended dose of 13% MCPA-Na, concentrations of 0, 8.125, 16.25, 32.5, 65, and 130 g L2 (10 m × 10 m), which contained nine rows in the plot. A 3WBD-20 L back-loaded electric sprayer was used to evenly apply MCPA-Na at the seedling (growth of the fourth true leaf), budding, flowering and boll stages. Each treatment was repeated three times. Contents of chlorophyll, soluble protein and MDA, and activities of SOD, CAT and POD in the cotton leaves were then measured on days 1, 4, and 7 after treatment. Plant height, boll number and the single boll weight were also measured on 15 October 2019 and 10 October 2020 (harvest period) to determine the effect on yield.The experiment followed a completely randomized block design, with each plot measuring an area of 100 m2. MCPA-Na at the maximum concentration of 130 g L-1 was applied using the 3WBD-20 L back-loaded electric sprayer at the seedling, budding, flowering and boll stages. Two days after spraying MCPA-Na, different combinations of plant growth regulators were then applied (see Table 3 + seaweed fertilizer), T3 (24-epibrassinolide + seaweed fertilizer) and T4 , T5 (GA3), T6 , T7 , T8 .A complete randomized block design was also used to study the effects of the plant growth regulators, with each plot measuring 100 m3), 20% phthalanilic acid and seaweed fertilizer were applied at dosages of 0.25 mL L-1, 0.01 g L-1, 0.5 g L-1, and 3.5 mL L-1 (500 kg water hm-2), all of which represent the recommended concentrations of each component. Preparation of T1: 0.25 mL 24-epibrassinolide was poured into bucket filled with 1 L water. Preparation of T2: 0.01 g GA3 and 3.5 mL seaweed fertilizer were poured into bucket filled with 1 L water. Preparation of T3: 0.25 mL 24-epibrassinolide and 3.5 mL seaweed fertilizer were pour into bucket filled with 1 L water. Preparation of T4: 0.5 g phenylamino acid and 3.5 mL seaweed fertilizer were pour into bucket filled with 1 L water. Preparation of T5: 0.01 g GA3 was poured into bucket filled with 1 L water. Preparation of T6: 0.25 mL 24-epibrassinolide, 0.01 g GA3, 0.5 g phthalanilic acid and 3.5 mL seaweed fertilizer were poured into bucket filled with 1 L water. Preparation of T7: 0.5 g phenylamino acid was poured into bucket filled with 1 L water. Preparation of T8: 0.25 mL 24-epibrassinolide, 0.01 g GA3 and 0.5 g phthalanilic acid were poured into bucket filled with 1 L water. Each treatment was repeated three times. Contents of chlorophyll, soluble protein and MDA, and activities of SOD, CAT and POD in the cotton leaves were then measured as above on days 1, 4 and 7 after treatment. Plant height, boll number and the single boll weight were also measured on 15 October 2019 and 10 October 2020 (harvest period) to determine the effect on yield.0.0075% 24-epibrassinolide, 75% gibberellin  caused decreases in the chlorophyll content of 30.72, 29.93, and 41.86% (p < 0.05) on days 1, 4 and 7 after treatment, respectively , respectively  is recommended.Plant growth regulators are often used to alleviate herbicide damage . For exa3 can promote plant flowering [3 and seaweed fertilizer can promote the boll setting of cotton and increase the yield. We suggest that when using plant growth regulators to alleviate the phytotoxicity of cotton, it should be used in a scientific combination according to the characteristics of cotton growth stage and plant growth regulators, so as to avoid antagonism and secondary phytotoxicity when using growth regulators.There are antagonistic or synergistic effects between different kinds of plant growth regulators. It is necessary to use them reasonably according to the characteristics of their effects to reduce herbicide damage. 24-epibrassinolide can effectively improve the chlorophyll content and photosynthetic efficiency of plants , 57, prolowering , increaslowering . Phthalalowering , 63. As lowering , promotilowering , 66. TheUnder a fixed planting density, cotton yield is determined by the number of bolls and the single boll weight . Herbici3 + seaweed. However, despite these findings, the effect of the plant growth regulators on cotton damaged at the flowering and boll stage was less than satisfactory, causing branches and leaves lush and boll opening difficulties at later stages. Therefore, for cotton exposed at these later stages, we suggest a low dosage of plant growth regulators to avoid shoot elongation and reduce the impact on yield.In terms of yield, the findings of this study suggest that cotton exposed to MCPA-Na at the seedling stage should be treated with phthalanilic acid + seaweed fertilizer, while plants exposed at the budding stage should be treated with 24-epibrassinolide + seaweed fertilizer, and those exposed at the flowering and boll stage should be treated with GAOverall, this study clarified the physiological and metabolic response of cotton plants to MCPA-Na exposure at different growth stages, as well as the differing effects on plant height and subsequent yield. Moreover, the mitigating effects of different combinations of plant growth regulators were also confirmed at different growth stages. Following MCPA-Na exposure, the soluble protein content and protective enzymes activity played an important role in the defense response of cotton. The single boll weight and boll number decreased significantly at the seedling and budding stages, while only the boll number decreased significantly at the flowering and boll stages, suggesting that the vegetative growth stage is more sensitive to MCPA-Na damage. Meanwhile, the application of plant growth regulators reduced the content of MDA, helping reduce MCPA-Na damage, and they also had a positive effect on the cotton yield traits. These findings suggest that in production practice, plant growth regulators could be reasonably applied to alleviate MCPA-Na damage in the field; however, more importantly, the drift of herbicides should be avoided, and the occurrence of pesticide accidents should be fundamentally reduced.Additional file 1.


It is shown that their emission on the nanosecond timescale is largely dominated by high-energy components peaking at a wavelength shorter than 305 nm. Because of their anisotropy (0.02) and their sensitivity to base stacking, modulated by the duplex size and the ionic strength of the solution, these components are attributed to mixed ππ*/charge transfer excitons. As high-energy long-lived excited states may be responsible for photochemical reactions, their identification via theoretical studies is an important challenge.The publication deals with polymeric pA●pT and oligomeric A Compared to transient absorption spectroscopy, probing strongly populated excited states [A series of articles published since the beginning of this century ,2,3,4,5 d states ,7,8,9, fr determined for DNA multimers at these wavelengths  was discovered [n●(GC)n, whose steady-state fluorescence spectrum is largely dominated by an emission band peaking at around 305 nm [n●(AT)n and also in genomic DNA [High-energy Emitting Long-lived Mixed excitons, or more simply HELM excitons. Quantum chemistry studies proposed their assignment to mixed ππ*/CT exciton states, extended over both strands and characterized by a weak intrastrand purine-to-pyrimidine charge transfer [As highlighted recently , the loneference ). More rscovered ,23,24,25d 305 nm ,23,24. SIn the beginning of this year, Ma, Kwok et al. reported dual long-lived fluorescence for RNA duplexes composed by homopolymeric adenine-uracil sequences . A “high20●T20. The structure of such duplexes has been extensively characterized by X-ray and CD measurements, which revealed that they adopt a B-type of double helix with some particularities  [−1 Na2HPO4, 0.03 mol●L−1 NaH2PO4, 0.48 mol●L−1 NaCl), to which we refer as “standard buffer”. We report time-resolved fluorescence spectra, fluorescence decays and fluorescence anisotropies obtained by time-correlated single photon counting (TCSPC) with an excitation wavelength of either 267 nm or 285 nm. The results presented and discussed hereafter clearly show the existence of fluorescence components stemming from HELM excitons, despite the fact that their fingerprint is not observable in the steady-state emission spectra  ,32,33. F spectra .Time-resolved spectra determined for the polymeric duplex at selected time-windows are shown in −4 and the buffer concentration is much higher than the DNA concentration (~10−4 mol●L−1 per base). Therefore, we replaced our standard buffer by a KCl aqueous solution with the same ionic strength and recorded the fluorescence decay at 305 nm. The latter is compared in At this stage, it is important to check if the high-energy long-lived fluorescence band, presented in The time-resolved spectra and the decays presented so far  were obtThe decays presented in R of the long-lived fluorescence at 305 nm, in respect to that at 420 nm, which for a long time have been considered as the only source of ns emission, we proceeded as follows. First, we determined for each decay the percentage of photons emitted on the ns timescale. Then, we multiplied this ratio by the relative intensities of the steady-state fluorescence spectrum at these wavelengths (R from Equation (1):In order to quantify the relative importance R values corresponding to both excitation wavelengths , is 3.7, a value similar to that found for pA●pT , while that of pA●pT in the diluted buffer is reduced to 60%. Inversely, the hypochromism of the polymer is higher than that of the oligomer and it increases for the polymer when it is dissolved in a buffer with higher ionic strength.The increase in the amplitude of the long-lived components occurring upon decreasing the duplex size a or redur at 305 nm has a value of ~0.15 at 0.1 ns and drops rapidly on a sub-ns timescale. Subsequently, r acquires a constant value of ~0.02 for the polymer and twice as high (~0.04) for the oligomer. In contrast, at 420 nm, the two systems have practically identical r values on the ns timescale (~0.02). However, on the shorter timescale, where r has lower values than at 305 nm for both systems, we remark a significant difference: the r determined for the oligomer between 0.2 and 0.8 ns is slightly negative (−0.01), while for the polymer r remains slightly positive (0.01).Finally, we examine the behavior of the fluorescence anisotropy at 305 and 420 nm for the polymeric and the oligomeric duplexes . For bot20●T20 contain components emitting in the blue part of the fluorescence spectrum (20 and T20 (solid state synthesis), used to form the oligomeric duplex by annealing, differs from the biochemical synthesis of the double-stranded structure pA●pT. Yet, both systems exhibit high-energy long-lived emission.The results presented in spectrum  and decaspectrum . This hispectrum  nor in tn●Tn duplexes (n ≤ 10) and showed the existence of Frenkel excitons delocalized over a few bases [Before further discussing the high-energy long-lived excited states of the examined duplexes, we briefly recall the main findings regarding their excited states, reported in the literature. Several theoretical studies have rationalized the Franck–Condon excited states of small Aew bases ,39,40,41ew bases . The mosew bases ). This eew bases ,45,46,47ew bases ,24.n●Tn duplexes described the trapping of the Frenkel excitons by CT states [Various theoretical studies of the excited state relaxation in AT states ,48,49. AT states ,8,50. DeT states . A minorT states , had been●Tn have not detected any species decaying on the ns timescale [−4 [−4 for dAMP and 1.5 × 10−4 for TMP) [The fact that transient absorption measurements on Aimescale ,8,17,50 cale [−4 . Consequfor TMP) .n●(AT)n [n●(GC)n [20●T20 n  and (GC)[n●(GC)n ,23. As m [20●T20 b. It als [20●T20 b. A corr20●T20 (average lifetime: 1.3 ps) than for pA●pT (average lifetime: 2.1 ps) [An X-ray diffraction study in solution demonstrated that the amplitude of conformational motions in adenine-thymine double-stranded structures is reduced when their size increases . This is 2.1 ps) .r, we note that the initial values found for the mononucleotides dAMP and TMP are 0.23 at 0.36, respectively [r, observed in r = 0.02, r = 0.04; Coming to the fluorescence anisotropy ectively . Howeverectively ,30. The r is equal to −0.2. With this in mind, it is worth-noticing that the A20●T20 anisotropy at 420 nm attains slightly negative values on the sub-ns timescale  than that for the polymer (5400 cm−1). We explain these observations by the fact that the more efficient base stacking in the polymeric duplex induces a faster mixing between ππ* and CT states, while imposing constraints for the geometrical rearrangement required for excited states with strong CT character. It is worth stressing that, despite these differences, the overall ϕ of the two systems is the same within 15%.We remark that the gap between the  A20●T20 . A simil A20●T20 , whose w20 and T20, purified by reversed phase HPLC and tested by MALDI-TOF, were purchased from Eurogentec. For the formation of A20●T20, a thermal treatment in a dry bath (Eppendorf-ThermoStatplus) was applied to an equimolar mother solution of the constitutive single strands : the solution, after being heated at 96 °C, was cooled to the melting point of the system (cooling time: 1 h), where the temperature was maintained for 10 min; subsequently, the solution was cooled to 4 °C (cooling time: 2 h), where it was incubated overnight. Ultrapure water was delivered by a MILLIPORE  system. Melting curves were obtained with a Perkin-Elmer Lambda 900 spectrophotometer. The temperature of the solution was controlled by a Huber CC3 apparatus with a precision of ±0.1 °C.pA●pT was obtained as a duplex by Amersham Biosciences. DNA single strands AThe laser source was a commercial mode-locked Ti:Sapphire , pumped by a cw solid state laser , delivering ~120 fs pulses at 795 nm with about 2 W average power at 76 MHz repetition rate. The infrared laser beam was used to pump an optical parametric oscillator , delivering visible ~120 fs pulses with an average power of ~0.5 W. The 267 and 285 nm excitation beams were generated by focusing the visible laser beam into a 5 mm BBO type I crystal. The repetition rate was reduced at 4.75 MHz by using a pulse picker . The fluorescence from the sample cell, filtered by a Schott WG 295 filter, was collected and imaged by two parabolic mirrors on the input slit of a small monochromator (Jobin-Yvon HR25). The detector was a microchannel plate  providing an instrumental response function of ~80 ps (FWHM), as given by the Raman line of water. The TCSPC setup used a SPC630 card (Becker & Hickl).r = (parI − perpI)/(parI + perp)2I, parallel (parI) and perpendicular (perpI) components of the fluorescence decay were recorded by controlling the polarization of the exciting beam with a half-wave plate. The excitation energies under parallel and perpendicular conditions were identical, giving a G factor of 1.Fluorescence decays were recorded at the magic angle (54.7°). For the determination of fluorescence anisotropy 2 quartz cell, were continuously stirred. The exciting beam was defocused on the surface decreasing its intensity to 3 kW●cm−2. Moreover, fresh samples were used to record signals at each emission wavelength. We systematically checked that the successive measurements provided identical decays; the data sets were finally merged to increase the signal-to-noise ratio.To avoid photodegradation, mainly due to thymine dimerization  and phot20●T20 unveiled the existence of high-energy long-lived fluorescence stemming from mixed ππ*/CT states, which is not detectable in their steady-state emission spectra. Associated to previous studies performed for the same systems on a shorter timescale [Our present time-resolved fluorescence study on the DNA duplexes pA●pT and Aimescale ,27,29,30In 20●T20, in terms of fluorescence lifetime and anisotropy, as well as their dependence on the duplex size and the ionic strength, strongly resembles that reported for the HELM excitons of (GC)n●(GC)n and (AT)n●(pAT)n duplexes. As mentioned in the introduction, quantum chemistry calculations on such alternating duplexes assigned the high-energy long-lived excited states to mixed excitons. They were found to extend over at least four bases and be characterized by a weak (q < 0.2 au) intrastrand transfer (G+δ → C−δ or A+δ → T−δ) [The behavior of the high-energy long-lived excited states of pA●pT and Aδ → T−δ) ,25. Thes


In cultured human mast cells, exogenous NO is able to inhibit mast cell degranulation via NO-cGMP signaling. However, under inflammatory oxidative or nitrosative stress, sGC becomes insensitive to NO. The occurrence of mast cells in healthy and inflamed human tissues and the in vivo expression of the α1 and β1 subunits of sGC in human mast cells during inflammation remain largely unresolved and were investigated here. Using peroxidase and double immunohistochemical incubations, no mast cells were found in healthy dental pulp, whereas the inflammation of dental pulp initiated the occurrence of several mast cells expressing the α1 and β1 subunits of sGC. Since inflammation-induced oxidative and nitrosative stress oxidizes Fe2+ to Fe3+ in the β1 subunit of sGC, leading to the desensitization of sGC to NO, we hypothesize that the NO- and heme-independent pharmacological activation of sGC in mast cells may be considered as a regulatory strategy for mast cell functions in inflamed human dental pulp.The binding of nitric oxide (NO) to heme in the β In the heterodimeric α1β1 and α2β1 isoforms, sGC induces the production of cGMP, resulting in cell-specific functions such as vasodilation [The inter- and intracellular molecule nitric oxide (NO)-sensitive soluble guanylyl cyclase (sGC) is a heterodimeric enzyme with an α and β subunit ,2. The rrodimers ,4. Heme  state Fe+ causes oduction ,6. Under state Fe+ causes dilation , the inhdilation ,9, leukodilation , and thedilation ,12.Mast cells originate from the yolk sac during embryogenesis and after birth from CD34+ hematopoietic stem cells in the bone marrow via definitive hematopoiesis ,14. Imma2−) and peroxynitrite (ONOO−) oxidizes sGC, leading to the insensitivity of sGC to NO [NO is produced in mast cells through the activity of eNOS, nNOS, and iNOS ,26,27. IGC to NO ,5. ThereGC to NO ,32,33,341 and β1 subunits of sGC in these cells in healthy and inflamed dental pulp.Inflammation in the dental pulp occurs as a consequence of bacterial infection caused by dentin caries ,36,37,381 . In the inflamed human dental pulp (n = 6), MCT was detected in mast cells. When compared, the inflamed dental pulp showed different numbers of mast cells , which can be explained by the different mixed inflammation states in the dental pulp.MCT was not detectable in any cells of the healthy human dental pulp .The immunofluorescence staining intensities for the α results . No sign1 and β subunits of sGC in mast cells, indicating the existence of the α1β1 heterodimers of sGC at the protein level in mast cells during inflammation. In inflammation, O2− and ONOO− oxidize sGC (Fe2+ to Fe3+ in the β1 subunit of sGC), leading to the insensitivity of sGC to NO [2− and ONOO− have been detected at higher concentrations in inflamed dental pulp [1β1 isoform in mast cells at the protein level and could be insensitive to NO in the oxidized state in these cells during the inflammation of human dental pulp.Histopathological studies of mast cells in inflamed tissues are required to elucidate their pathophysiological role in organ-specific inflammation . AlthougGC to NO ,5,6. Bectal pulp ,50, we sIn the present study, the inflammatory regions in human dental pulp showed the histopathological features of mixed inflammation, ranging from a necrotic region to regions with chronic, subacute, and acute inflammatory features. In necrotically altered inflammatory regions, where blood vessels were degraded, no mast cells were found. In inflamed dental pulps, mast cells were observed around blood vessels in chronic, subacute, and/or acute inflammatory regions. In chronically inflamed regions, numerous neutrophil granulocytes left the blood vessel walls and formed acute inflammatory areas in the pulp . Due to The mechanism controlling the inflammatory response  in denta1 and β1 subunits of sGC in the mast cells of inflamed dental pulp with different staining intensities. In some mast cells, the α1 and β1 subunits of sGC were detected with a stronger staining intensity, whereas in other mast cells the intensity was lower. The difference in the intensities of the α1 and β1 subunits of sGC suggests that mast cells exist in different functional states under inflammatory conditions and that the expression of the α1 and β1 subunits of sGC depends on the chronic, subacute, or acute inflammation region-associated mast cell behavioral status.We detected the α1β1 and α2β1 heterodimers. It is possible that sGC may also be activated as α2β1 heterodimers in subpopulations of mast cells negative for α1 subunit of sGC. Therefore, future studies should clarify whether the α2 subunit of sGC is present in mast cells at the protein level under in vivo conditions. We detected the α1 subunit of sGC only in mast cells and in blood vessels, whereas the β1 subunit of sGC was detected in mast cells, blood vessels, and also in a subpopulation of other inflammatory cells that were negative for MCT. Therefore, it should be clarified whether the α2 subunit of sGC is also present in other immune cells that are negative for the α1 subunit and MCT but positive for the β1 subunit.In smooth muscle cells and in neurons, sGC is active as both α2) by NADPH oxidase is increased in macrophages, neutrophil granulocytes, and dendritic cells that accumulate in the area of inflammation because NADPH oxidase transfers electrons from intracellular NADPH to O2 to generate superoxide (O2−) [2− generated by uncoupled endothelial nitric oxide synthase (eNOS) [2O2), which can lead to the formation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) under inflammatory conditions [2+ state in the β1 subunit of sGC under physiological conditions and the oxidized Fe3+ state in the β1 subunit of sGC under inflammatory conditions are essential for determining the activity of sGC in a cell [2+ to Fe3+) by higher concentrations of O2− and ONOO−, leading to the insensitivity of sGC to NO [In inflammation, the consumption of molecular oxygen (Ode (O2−) . The O2−e (eNOS) ,69 or innditions ,70. The n a cell ,5,6. NO n a cell ,27 and in a cell ,29. NO dn a cell . In cultn a cell , suggestGC to NO ,5,6. InfGC to NO ,72; thisGC to NO ,50. In aGC to NO ,33,34,731 and β1 subunits. Therefore, the NO- and heme-independent pharmacological activation of sGC in mast cells may be considered as a regulatory strategy for mast cell functions in inflamed human dental pulp. For example, indirect and direct pulp capping materials used in the treatment of deep dentin caries containing sGC activators could represent an immunomodulatory treatment option in the future.Our results showed that mast cells were present in inflamed but not in healthy human dental pulp. In these mast cells, sGC was detectable at the protein level with both its αThe Human Ethics Committee of the Heinrich-Heine University Düsseldorf approved the collection of human third molars extracted during orthodontic treatment (No. 2980).The healthy molars were unrestored and clinically asymptomatic and showed no pain upon stimuli-induced testing and percussion. The carious molars showed clinically stimuli-induced, spontaneous, or percussion-induced pain and/or radiographic carious dentin and inflamed periodontal lesions.n = 6) and inflamed third molars with deep dentin caries (n = 6) were extracted from patients who had undergone orthodontic extraction treatment. The molars were immersion-fixed in a fixative containing 4% paraformaldehyde and 0.2% picric acid in 0.1 M phosphate-buffered saline (PBS), pH 7.4, for 48 h. The molars were demineralized in 4 M formic acid for 21 days. The non-carious and carious molars were cryoprotected with 30% sucrose solution in 0.1 M PBS, pH 7.4, for 48 h. The molars were frozen-embedded, stored at −82 °C, and frozen-sectioned on a cryostat at 30 µm.The healthy   and the 1 subunit of sGC in mast cells, we developed a specific polyclonal rabbit antibody against the human α1 subunit of sGC  that was characterized by immunohistochemistry and immunoblotting [1 subunit antibody was verified with immunohistochemistry and immunoblotting using lung protein extracts from sGCβ1+/+ and sGCβ1−/− mice [To detect the αblotting . The spe−/− mice .2O2 in 0.05 M Tris-buffered saline (TBS) for 20 min to inhibit endogenous peroxidase. Nonspecific immunoglobulin binding sites were blocked by the incubation of sections in blocking solution containing 5% normal goat serum  and 2% bovine serum albumin (BSA) . The sections of subgroups of healthy and carious molars were incubated with mouse monoclonal anti-human MCT (1:2000) , mouse monoclonal anti-human HLA-DR (1:2000) , and mouse monoclonal anti-human CD68 (1:2000) (eBioscience). To detect the α1 and β1 subunits in cells from the healthy and inflamed dental pulps, sections were incubated overnight with rabbit anti-human polyclonal sGC α1 (1:1000) and β1 subunit (1:1000) antibodies at 4 °C. Then, sections were incubated for 1 h with biotinylated goat anti-mouse IgG (1:1000) (Vector) or goat anti-rabbit IgG (1:500) (Vector). The sections were incubated for 1 h with avidin–biotin–peroxidase complex (1:100) (Vector). The immunohistochemical reaction was developed in all incubations for 15 min with 0.05% 3,3′-diaminobenzidine tetrahydrochloride  in 0.05 M Tris-HCl buffer, pH 7.6, containing 0.01% H2O2 and 0.01% nickel sulfate [Free-floating sections were incubated with 0.3% H sulfate ,50.To control for secondary antibodies and avidin–biotin–peroxidase complex reagents , the omission of primary antibodies was performed as control staining.TM 488-conjugated goat anti-mouse IgG  for 1 h. In separate incubations, the sections were incubated with rabbit polyclonal anti-human α1 subunit (1:1000) and rabbit polyclonal β1 subunit (1:1000) antibodies overnight at 4 °C. Then, in separate incubations, the sections were incubated for 1 h with DyLightTM 550-conjugated goat anti-rabbit IgG (Thermo Fischer Scientific). To show the cell nuclei, sections were stained with DRAQ5  for 15 min. The sections were coverslipped with Aqua Poly/Mount  and analyzed with an LSM510 confocal microscope  [Free-floating sections were incubated with 5% normal goat serum and 2% BSA to block the nonspecific immunoglobulin binding sites of the secondary antibodies. The sections were incubated first with mouse anti-human MCT antibodies (Santa Cruz Biotechnology) at 4 °C. Then, the sections were incubated with DyLightGermany) ,74.To control for the immunohistochemical reagents , sections were incubated in the absence of the first and secondary primary antibodies.n = 6 molars of 6 different patients) and inflamed (n = 6 molars of 6 different patients) dental pulp, MCT-positive cells were visualized using conventional light microscopy. Sections stained with the avidin-biotin-peroxide method were imaged at 5× magnification using an Olympus microscope  connected to the Cell F Imaging software . Then, an examiner (B.P.) counted the MCT-positive cells using the counting tool in QuPath (version 0.3.2) [https://qupath.github.io. The results were verified by a second examiner (Y.K.).In healthy (n 0.3.2) . The sou1 subunit and β1 subunit of sGC in mast cells were annotated by one investigator (B.P.) and reviewed by a second investigator (Y.K.). The mean intensity of the red fluorescence  was then exported to R.Three colour fluorescence images were taken with an LSM 510 META confocal microscope  and exported to QuPath (version 0.3.2) . The celp values using an unpaired t-test. A p value < 0.05 was considered significant. For cell counting, the mean and SEM (standard error of the mean) were calculated.Statistical analyses were performed in R (version 4.1.1). Data were tested for normal distribution using a Shapiro–Wilk test. Parametric values were tested for significant


Fatty liver, characterized by excessive lipid droplet (LD) accumulation in hepatocytes, is a common physiological condition in humans and aquaculture species. Lipid mobilization is an important strategy for modulating the number and size of cellular LDs. Cyclooxygenase (COX)-mediated arachidonic acid derivatives are known to improve lipid catabolism in fish; however, the specific derivatives remain unknown. In the present study, we showed that serum starvation induced LD degradation via autophagy, lipolysis, and mitochondrial energy production in zebrafish hepatocytes, accompanied by activation of the COX pathway. The cellular concentration of PGF2α, but not other prostaglandins, was significantly increased. Administration of a COX inhibitor or interference with PGF2α synthase abolished serum deprivation-induced LD suppression, LD–lysosome colocalization, and expression of autophagic genes. Additionally, exogenous PGF2α suppressed the accumulation of LDs, promoted the accumulation of lysosomes with LD and the autophagy marker protein LC3A/B, and augmented the expression of autophagic genes. Moreover, PGF2α enhanced mitochondrial accumulation and ATP production, and increased the transcript levels of β-oxidation- and mitochondrial respiratory chain-related genes. Collectively, these findings demonstrate that the COX pathway is implicated in lipid degradation induced by energy deprivation, and that PGF2α is a key molecule triggering autophagy, lipolysis, and mitochondrial development in zebrafish hepatocytes. With rapid industrialization, obesity and fatty liver disease have become non-communicable diseases that threaten modern societies worldwide . CoincidArachidonic acid  is a major n-6 long-chain polyunsaturated fatty acid that is primarily esterized at the sn-2 position of phospholipids in the cell membrane . ARA is 12,14-PGJ2 is an endogenous ligand of the adipogenic protein PPARγ [ARA and its metabolites may play pivotal roles in fish lipid catabolism. Previously, we showed that dietary ARA increases ATGL transcription and serum non-esterified fatty acid levels in freshwater grass carp. Moreover, acetylsalicylic acid, a COX inhibitor, abolishes the lipolysis-promoting function of ARA, suggesting that increased cellular ARA levels facilitate lipolysis and that COX-mediated metabolites are involved in the regulation of this process ,26,27. Hin PPARγ . Meanwhiin PPARγ ,30,31. Hin PPARγ . Notablyin PPARγ ,34.In the present study, we used a zebrafish liver cell line, an academically accepted model for studying LD regulation, to preliminarily explore the dynamics of ARA-derived COX metabolites in response to autophagy and lipolysis activation and to elucidate the key molecules regulating lipid catabolism and oxidation in fish hepatocytes.The zebrafish liver (ZFL) cell line was purchased from American Type Culture Collection . Cells were cultured in a mixed medium  supplemented with 0.15 g/L sodium bicarbonate , 15 mM HEPES (Sigma-Aldrich), 0.01 mg/mL bovine insulin (Sigma-Aldrich), 50 ng/mL epidermal growth factor (Sigma-Aldrich), 5% fetal bovine serum (Gibco), and 0.5% trout serum . The cells were incubated at 28 °C in a 100% air atmosphere. The medium was replaced every 2 days.LD-containing cells were prepared by adding 400 μM lipid mixture  for 24 h. LD-containing cells were directly incubated with PGF2α and PGE2 . Before treatment, cytotoxicity of the molecules was assessed using a 3--2,5-diphenyl-2H-tetrazolium bromide assay.The cells were not transfected with siRNA or treated with the inhibitor until they reached 75% confluency. For RNA interference, the cells were transfected with specific siRNA sequences against ATG7 , ATGL , and PTGFS , or nontargeting siRNA , for 24 h with a transfection reagent . The siRNAs were designed and synthesized by GenePharma . The gene knockdown efficiency was 74.12% for ATG7, 54.38% for ATGL, and 45.89% for PTGFS . For inh6/well in six-well plates for 24 h, with three replicates per assay. After treatment, the cells were washed twice with phosphate-buffered saline (PBS) and fixed in 10% formalin for 30 min. After rinsing twice with PBS, the cells were stained with BODIPY solution  for 30 min. After washing the cells three times with PBS to remove the BODIPY solution, the nuclei were stained with DAPI solution  for 10 min. Finally, after removing the DAPI solution and washing with PBS, the cells were observed under an inverted fluorescence microscope with a ×40 objective . Three nonoverlapping images were obtained for each treatment group. Eighteen cells (six cells per image) in each treatment were randomly selected, and the particle number was quantified using ImageJ software . In addition, the relative puncta of BODIPY fluorescence values and cell numbers (in each image) were quantified using ImageJ software .ZFL cells were seeded at 1.2 × 106/well for 24 h prior to treatment, with three replicates per assay. The cells were fixed in 4% paraformaldehyde for 30 min and then washed three times with PBS. The cells were then incubated with Triton X-100 (0.5%) for 10 min and washed with PBS. After blocking with 5% bovine serum albumin for 30 min, the cells were incubated with the primary antibody  overnight (4 °C). After washing with PBS, the cells were incubated with a secondary antibody conjugated to Alexa Fluor 488  for 2 h. The cell LDs and nuclei were then stained. The cells were observed and imaged under an inverted fluorescence microscope with a ×40 objective (Nikon TS2). The relative puncta of fluorescence values and cell numbers (in each image) were quantified using ImageJ software.For immunofluorescence microscopy, ZFL cells were seeded in six-well plates at 1.2 × 106/well in 25 cm plastic bottles for 24 h prior to treatment. Six replicates were used for each treatment. At harvest, the cells were digested with 0.25% trypsin–EDTA, washed twice with PBS, and suspended in 100 μL PBS, and the cell medium was collected. The cells were then subjected to three freeze–thaw cycles (−80 °C) and centrifuged for 10 min at 5000× g at 4 °C. The supernatant was then transferred to a fresh Eppendorf tube for further analysis. Major PGs, including 15d-PGJ2, PGE2, PGF2α, and PGI2, were quantified using an enzyme-linked immunosorbent assay kit  according to the manufacturer’s protocol, using a microtiter plate spectrophotometer  at an absorbance of 450 nm. All metabolite assays were performed in duplicates. The results are expressed as nanograms of PGs per microgram of protein (for cells) or milliliter (for medium).For the PG test, cells were seeded at a density of 1.0 × 106/well for 24 h prior to treatment, with three replicates per assay. For lysosomal staining, growing cells were incubated with 20 nM LysoTracker Red DND-99  for 30 min at 28 °C before fixation. For mitochondrial staining, growing cells were incubated with 100 nM MitoTracker Red FM  for 30 min at 28 °C before fixation. The cell LDs and nuclei were stained and captured under an inverted fluorescence microscope with a ×40 objective (Nikon TS2). The relative puncta of fluorescence values and cell numbers (in each image) were quantified using ImageJ software. The Mander’s overlap coefficient of LDs and lysosome puncta was measured using the Coloc 2 plug-in.ZFL cells were seeded in six-well plates at 1.2 × 106/well for 24 h prior to treatment, with four replicates per assay, lysed, and collected. TG assays were performed using an enzymatic kit . The cell medium was collected after treatment and measured using free fatty acid and glycerol assay kits .For TG assays, ZFL cells were seeded in six-well plates at 1.2 × 106/well for 24 h prior to treatment, with six replicates per treatment. A commercial kit  was used to normalize the total protein concentration, according to the manufacturer’s instructions.To measure ATP generation, ZFL cells were seeded in six-well plates at 1.2 × 106/well. Each treatment was replicated three times. After treatment, the cells were washed twice with PBS, and 1 mL TRIzol reagent  was added to extract total RNA, according to the manufacturer’s instructions. RNA integrity was assessed using agarose gel electrophoresis and an Implen NanoPhotometer . After removing DNA from the total RNA, cDNA was synthesized using the PrimeScript® RT Reagent Kit . qRT-PCR assays were performed in triplicate using the LightCycler® 96 real-time PCR machine  in a 20 μL reaction system containing 2.0 μL primers (2.5 μM), 2.0 μL diluted first-strand cDNA, 10 μL 2× Power SYBR™ Green PCR Master Mix (Thermo Fisher Scientific), and 6.0 μL sterilized double-distilled water. The cycling conditions were as follows: 95 °C for 5 min, followed by 40 cycles of 95 °C for 15 s, and finally, 60 °C for 1 min. After PCR, melting curves were analyzed over a range of 72–95 °C (at 1 °C/20 s steps) to confirm product singularity. Relative gene expression levels were determined using the comparative CT method (2−ΔΔCt), as described previously [For qRT-PCR, ZFL cells were seeded in six-well plates at 1.2 × 10eviously ,36.6/well. Each treatment was replicated four times. To measure mtDNA, total DNA was extracted using a DNA extraction kit , following the manufacturer’s instructions. In the present study, the copy number of mitochondrial cytochrome b (mt-cyb) was considered the copy number of mtDNA. β-actin was used as the internal reference. qRT-PCR was performed as described previously .All data are expressed as the mean ± standard deviation. One-way analysis of variance followed by Bonferroni’s post hoc test was used to compare the differences between experimental treatments. Differences between the non-starved and starved cells were determined using an independent sample p < 0.05; p < 0.05; atg12, ef1α, lamp2, and lc3b was increased in serum-starved cells, with the expression of ef1α and lc3b being significantly different from that of the control  in serum starvation-treated ZFL cells was clearly decreased compared with that in control cells . Moreover, ptges, ptgfs, and ptgds expression was increased in cells treated with serum-free medium, with ptges and ptgfs expression being significantly different compared to the control (p < 0.05). However, ptgis transcript expression was downregulated in the starved cells (p < 0.05). Accordingly, ARA-derived COX metabolites in the cells and medium were measured (p < 0.05), whereas no obvious differences were noted in the concentrations of other PGs, including 15-dPGJ2, PGE2, and PGI2 (p > 0.05). Interestingly, although the concentrations of these four metabolites were not significantly different in the medium, 15-dPGJ2, PGE2, and PGI2 concentrations markedly increased in numerical value (p > 0.05). To investigate whether PGF2α is derived from LD degradation induced by serum starvation, we knocked down ATG7 and ATGL using RNA interference. The expression of ATG7 and ATGL (a key gene for lipolysis) was significantly decreased . Second, knockdown of PTGFS by RNA interference decreased the expression of PTGFS by 45.89% and reduced the production of PGF2α (p < 0.05). Furthermore, PTGFS knockdown significantly attenuated the starvation-induced expression of the autophagy-related genes atg12, ef1α, lamp2, and lc3b (p < 0.05). Overall, these results indicate that COX and PTGFS inhibition can restore serum starvation-induced lipid degradation and autophagy.of PGF2α , which ap < 0.05, ef1α, lamp2, lc3b, and atg12  was upregulated in response to starvation and PGF2α treatment. Thus, the role of CMA in lipid degradation must be further evaluated.The present study had some limitations. First, the interaction of LDs and autophagosomes/lysosomes, as well as autophagy flux, were not comprehensively explored; thus, the role of PGF2α in lipophagy warrants further discussion. Second, chaperone-mediated autophagy (CMA) also plays an essential role in lipid metabolism in fish , and we The present study provides novel insights into the dynamics of ARA-derived COX metabolites in response to nutritional deprivation in fish hepatocytes. We demonstrated that PGF2α expression was increased and was accompanied by autophagy and lipolysis. Exogenous treatment with PGF2α, but not PGE2, accelerated lipid degradation through enhanced autophagy and lipolysis and improved mitochondrial β-oxidation and energy production . Further


Together, these results reveal that MitoQ reduces oxidative stress in ovarian follicles via its antioxidative action, thereby protecting oocytes and granulosa cells and providing an efficient way to improve the quality of in vitro-generated oocytes.Ovarian organoids, based on mouse female germline stem cells (FGSCs), have great value in basic research and are a vast prospect in pre-clinical drug screening due to their properties, but the competency of these in vitro-generated oocytes was generally low, especially, in vitro maturation (IVM) rate. Recently, it has been demonstrated that the 3D microenvironment triggers mitochondrial dysfunction during follicle growth in vitro. Therefore, therapies that protect mitochondria and enhance their function in oocytes warrant investigation. Here, we reported that exposure to 100 nM MitoQ promoted follicle growth and maturation in vitro, accompanied by scavenging ROS, reduced oxidative injury, and restored mitochondrial membrane potential in oocytes. Mechanistically, using mice granulosa cells (GCs) as a cellular model, it was shown that MitoQ protects GCs against H Gametes are tasked with faithfully transmitting genetic and epigenetic information from one generation to the next. Oocytes, as female germ cells, provide the necessary maternally derived organelles support for the development of embryos, especially mitochondria. Generally, ovarian reserve is established early in life with a finite number of oocytes. Currently, there is no direct evidence that adult oogenesis ever occurs under physiological conditions . TherefoTakashima et al.  indicateMitoQ (MitoQuinone), as a derivative of ubiquinone conjugated to triphenylphosphonium, bearing a lipophilic cation, can enter and accumulate within the mitochondria as a result of the electrochemical gradient ,9,10. As2O2-induced apoptosis in GCs have been revealed. Our work provides an effective strategy for treating reproductive defects caused by 3D environmental stress.In the present study, the antioxidant effect of MitoQ is investigated during oogenesis in vitro culture. The treatment performance of MitoQ to mouse ovarian organoids is demonstrated by follicles size, maturation rate, ROS production, mitochondrial content, and ΔѰm in in vitro-generated oocytes. Meanwhile, the mechanisms of MitoQ against Hp > 0.05; vs. MitoQ 150 nM: 10.65% ± 2.12, p > 0.05, p < 0.01, To establish FGSC lines, FGSCs were isolated and cultured as in the previous study . After sp < 0.05, p > 0.05, Then, individual follicles were subjected to in vitro growth. After 11 days of culture, in vitro-generated (IVG) oocytes grew into GV oocytes among the experimental groups. When transferring them under the in vitro maturation (IVM) culture conditions, 40.75% of the GV oocytes extruded a first polar body in the control group. As the MitoQ concentration rose, the maturation rate of IVG oocytes began to rise gradually. The highest maturation rate was obtained when the concentration of MitoQ reached 100 nM, compared to the control side  and INHIBIN-α (GCs) were examined by immunohistochemical staining A. Compar2O2-treated GCs oxidative stress model and used the CCK8 array to assess the effects of MitoQ on GCs. The untreated control (no H2O2 and no MitoQ) was set as 100%. CCK8 results indicated that various H2O2 exposure  showed concentration-dependent inhibition of GCs survival. When cells were treated with 100 μM H2O2 for 24 h, the cell survival rate was 59.17% ± 6.20, which was closest to the IC50 . When even higher MitoQ concentrations (100 nM) were achieved, the viability defect in GCs was significantly relieved (p < 0.01) compared with the H2O2 group.Follicular GCs are closely related to ovarian function. Here, we constructed an Hthe IC50 A. Theref2O2-treated GCs was higher than those in the control group , while MitoQ produced a significant mitigating effect on mitochondrial depolarization during oxidative stress  via the preservation of mitochondrial function. Therefore, we have reason to believe that the beneficial effect of MitoQ on oocyte potential may be largely attributable to the GCs proliferation.The mammalian oocyte growth and maturation in a mutually dependent relationship with adjacent somatic cells. Due to the naive mitochondrial state of immature oocytes, the growth and maturation of immature oocytes are mostly supported by the surrounding GCs . AccordiAging is known to be associated with sub-optimal reproductive performance in females. However, the exact mechanisms by which it affects fertility are complex . State-oThe outbred ICR mouse was purchased from SPF Biotechnology . Mice were bred in the mouse house of Inner Mongolia University in the standard temperature/humidity constant environment.MitoQuinone  was obtained from Selleck .max , 1 mM Sodium Pyruvate , 1 mM MEM non-essential amino acids , 100 IU/mL Penicillin-streptomycin , 10 ng/mL recombinant Human FGF-basic , 10 ng/mL Human GDNF Recombinant Protein , 20 ng/mL mouse epidermal growth factor , 10 ng/mL mouse leukemia inhibitory factor , and β-mercaptoethanol  at 37 °C with 5% CO2. The culture medium was changed every second day.In this study, protocols for FGSCs isolation and sorting were identical to previous studies ,58,59. I3 FGSCs co-culture with 3 × 104 female gonadal somatic cells (from 1–3 dpp ovaries) in a U-bottomed 96-well plate for 2 d with GK15+RA medium  supplemented with 15% Knockout serum replacement , 1.5 μM retinoic acid , 2 mM Glutamax, 1 mM MEM non-essential amino acids, 1 mM Sodium Pyruvate, 100 mM β-mercaptoethanol, 20 ng/mL EGF, 10 ng/mL bFGF, 10 ng/mL GDNF, 10 ng/mL LIF, and 100 IU/mL Penicillin-streptomycin). To extensively remove endogenous germ cells, gonadal somatic cells have been sorted by DDX4  antibodies conjugated with magnetic beads. Next, ovarian organoids were transferred onto Transwell-COL membranes  soaked in GK15+RA medium for 2 d and the medium was changed 24 h. Afterward, ovarian organoids cultured with α-MEM-based medium , 20 ng/mL EGF, 50 mM β-mercaptoethanol and 100 IU/mL penicillin-streptomycin) and StemPro-34-based medium  supplemented with 10% FBS, 2 mM Glutamax, 100 μM ascorbic acid, 20 ng/mL EGF, 50 mM β-mercaptoethanol, 800 nM ICI182780, 100 IU/mL penicillin-streptomycin) for 21 d. The ovarian organoids were incubated at 37 °C with 5% CO2 and half the medium volume (0.6 mL) was changed every second day.The ovarian organoid was formed using a modified method described elsewhere ,3. A brimax, 200 μM ascorbic acid, 50 mM β-mercaptoethanol, 100 IU/mL Penicillin-streptomycin, 20 ng/mL EGF, 1 mM Sodium Pyruvate, 0.2 IU/mL follicle-stimulating hormone , 20 ng/mL BMP15 , and 20 ng/mL GDF9  at 37 °C with 5% CO2. After 2 days of follicle 3D culture, follicles were treated with 0.1% type IV collagenase for 5 min, and further cultured in follicle 3D culture medium continued for 9 d, while changing the medium every other day. Following this, in vitro-grown follicles were subjected to IVM.Under a stereomicroscope, the individual follicles were isolated from ovarian organoids using 27-gauge needles and cultured with follicle 3D culture medium ,2 mM Gluta6 /mL to a drop of human tubal fluid medium containing the MII oocyte. After inoculation for 6 h at 37 °C, the oocytes were transferred to KSOM medium and further cultured for 18 h.For in vitro maturation, cumulus oocyte complexes were maturated in vitro in a α-MEM based maturation media containing 5% FBS, 30 mg/mL sodium pyruvate, 0.1 IU/mL follicle-stimulating hormone, 4 ng/mL EGF, 1.2 IU/mL human chorionic gonadotrophin , 4 ng/mL bFGF, 30 mg/ ml penicillin, 75 mg/mL streptomycin. After 16–18 h of maturation, MII oocytes were transferred into 90-µL human tubal fluid droplets (each containing 20–25 oocytes) covered with paraffin liquid in a 35-mm dish. Spermatozoa were collected from the cauda epididymis of adult ICR male mice and added at a final concentration of 2 × 10The ROS production, distribution of mitochondria, and ΔѰm in oocytes were detected by ROS Assay Kit , MitoTracker Red CMXRos , Enhanced mitochondrial membrane potential assay kit with JC-1 , respectively. Briefly, GV/MII oocytes were cultured in DCFH-DA (10 μM), MitoTracker (200nM) and JC-1 (10 μM) solution for 30 min at 37 °C, respectively. After being washed three times in preheated culture medium, oocytes were transferred to the glass-bottom culture dish supplemented with PBS droplet and the signals from each group were detected with the same scanning settings immediately.4 /well, after treatment with H2O2 or MitoQ according to the experimental design, cells were incubated with DCFH-DA (10 μM), MitoTracker (200 nM) and JC-1 (10 μM) solution for 30 min at 37 °C, respectively. After washing 3 times with PBS, 5 visual fields were randomly selected under the fluorescence microscope  for observation. The fluorescence intensity of each sample was analyzed by Image J  software. ROS production and distribution of mitochondria were evaluated as the intensity of signals, respectively. ΔѰm was evaluated as the ratio of the red to green fluorescence intensity. Three samples from each group were assayed and performed in triplicate.The level of ROS, mitochondria content and ΔѰm in GCs were detected as above. In brief, GCs were seeded on 6-well plates with a density of 8 × 102O2 in PBS to inactivate endogenous peroxidase activity and incubated with blocking buffer, 10% serum in PBS, for 1 h at 37 °C. After that, the sections were incubated with the first antibody  overnight at 4 °C. The slides were washed three times in PBS, each time for 10 min, after which the slides were incubated with horseradish peroxidase (HRP) conjugated anti-rabbit IgG  and the integrated optical density (IOD). The staining intensity (SI) for each image was calculated as SI = IOD/IA. The follicles were classified according to their developmental stages based on the GCs morphology. All staining were repeated more than three times.Ovarian organoids were fixed in 4% paraformaldehyde, embedded in paraffin and sectioned. For immunohistochemical analyses, the sections were dewaxed and rehydrated by xylol and alcohol, respectively. The section (3–5 μm) was furtherly immersed into 10 mM sodium citrate buffer, pH 6.0 and heated for 10 min. Then, the slides were treated with 1% H6 cells in DMEM/F12 medium  containing 5% FBS, 6 mg/mL Penicillin-streptomycin in 24-well culture dishes. After overnight culture, cells were washed and cultured in serum-free medium before any further treatment.Primary GCs were isolated from PMSG-primed (24 h) PD23 female mice ovary according to described previously ,61. GCs 3 cells per well were plated in 96-well plates. After 48 h of culture under DMEM/F12-based medium, GCs reached ~70% confluency. CCK8 reagent  was added to the 96-well plate (10 μL/well) and incubated accordingly. Finally, the absorption value was measured with a microplate reader  at 450 nm wavelength. Three samples from each group were assayed, and each reaction was performed in triplicate.GCs with 5 × 10Proteins of GCs were obtained by RIPA lysis buffer RIPA  supplemented with a protease inhibitor cocktail in centrifuged tubes in ice for 20 min. The concentration of the protein was measured by using the BCA protein assay . 30 μg of proteins from each sample were loaded to SDS-PAGE before transferring to nitrocellulose membranes , and probed with the indicated antibodies . Next day, the peroxidase-conjugated secondary antibody  was added to incubate the mem-brane. Bands were visualized with the Clarity™ Western ECL Substrate  and quantified with Image J. All samples were performed in triplicate.t-test when only a single variable was manipulated or one-way ANOVA with Tukey–Kramer post hoc when multiple variables were manipulated. p < 0.05 was considered as a statistical significance.Experimental data were expressed as the means ± SD with each experiment. Analyses were conducted with SPSS (Version 24) and consisted of independent-samples In summary, our results demonstrated that MitoQ supplementation during ovarian organoids culture could reverse the 3D culture environment-induced oxidative stress by directly scavenging ROS and promoting the proliferation activity of GCs. The ameliorative influence of MitoQ was reflected by the improvement of mitochondrial function, follicle size, and ultimately by enhancement of oocyte maturation. To thoroughly explore the underlying mechanisms of MitoQ protection, further studies indicated that MitoQ alleviates oxidative stress and attenuates oxidative stress-associated damage in GCs. This study is warranted to validate that MitoQ may serve as a potential therapeutic drug for anti-ovarian aging.


Escherichia coli isolate of sequence type (ST) 38 spiked into a synthetic microbial community at varying abundances. Approximately 300,000 reads or 15× genome coverage was sufficient to detect ARGs in E. coli ST38, with comparable sensitivity and PPV to ~100× genome coverage. Using metagenome assembly of mixed microbial communities, ARG detection at E. coli relative abundances of 1% would require assembly of approximately 30 million reads to achieve 15× target coverage. The minimum sequencing depths were validated using public data sets of 948 E. coli genomes and 10 metagenomic rectal swab samples. A read-based approach using k-mer alignment (KMA) for ARG prediction did not substantially improve minimum sequencing depths for ARG detection compared to assembly of the E. coli ST38 genome or the combined metagenomic samples. Analysis of sequencing depths from recent studies assessing ARG content in metagenomic samples demonstrated that sequencing depths had a median estimated detection frequency of 84% (interquartile range: 30%–92%) for a relative abundance of 1%.Short-read sequencing can provide detection of multiple genomic determinants of antimicrobial resistance from single bacterial genomes and metagenomic samples. Despite its increasing application in human, animal, and environmental microbiology, including human clinical trials, the performance of short-read Illumina sequencing for antimicrobial resistance gene (ARG) detection, including resistance-conferring single nucleotide polymorphisms (SNPs), has not been systematically characterized. Using paired-end 2 × 150 bp (base pair) Illumina sequencing and an assembly-based method for ARG prediction, we determined sensitivity, positive predictive value (PPV), and sequencing depths required for ARG detection in an IMPORTANCE Systematically determining Illumina sequencing performance characteristics for detection of ARGs in metagenomic samples is essential to inform study design and appraisal of human, animal, and environmental metagenomic antimicrobial resistance studies. In this study, we quantified the performance characteristics of ARG detection in E. coli genomes and metagenomes and established a benchmark of ~15× coverage for ARG detection for E. coli in metagenomes. We demonstrate that for low relative abundances, sequencing depths of ~30 million reads or more may be required for adequate sensitivity for many applications. Increasing throughput and decreasing costs of DNA sequencing have made whole genome and metagenomic sequencing accessible for antimicrobial resistance detection on a broad scale. This technology is a useful epidemiological tool capable of tracking multiple antimicrobial resistance genes (ARGs) in a single strain , 2, and 6–13–de novo assembly (assembly without a reference) of the raw sequencing reads into contiguous sequences (contigs) and aligning the contigs to an ARG reference database. In contrast, a read-based approach directly aligns the raw genomic or metagenomic sequences to an ARG reference database for ARG prediction  and the Comprehensive Antibiotic Resistance Gene Database (CARD)  with an E. coli ST38 genome. As our goal was to determine minimum sequencing depths needed to detect ARGs, subsamples were examined at 5,000,000 (~250×), 1,000,000 (~50×), 500,000 (~25×), 300,000 (~15×), 250,000 (~12.5×), 200,000 (~10×), 150,000 (~7.5×), 100,000 (~5×), 50,000 (~2.5×), and 10,000 (~0.5×) read pairs to simulate sequencing at lower depths. Reads were then assembled into contigs and ARGs predicted using RGI main , with the ARGs and associated detection frequencies across subsamples in To ensure sequencing depth was not a limiting factor in ARG detection, approximately 136 million 2 × 150 bp (base pair) reads  were generated for the 10.1128/msystems.00022-22.4DATA SET S1E. coli ST38 across subsamples using DIAMOND or BLAST as an alignment tool. Download Data Set S1, XLSX file, 0.04 MB.Antimicrobial resistance gene detection frequencies from contig assemblies in Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the blaCTX-M-15, and parC and gyrA variants as well as 69 other ARGs with a mean detection frequency of 99.9% ± 0.5% (standard deviation), where additional sequencing depth did not increase the total number of ARGs detected even by 5,000,000 reads , 5 unique aminoglycoside transferases, and 46 distinct efflux-associated genes of which 41.3% (19/46) are regulatory  performed similarly to 1 million reads for sensitivity  or DIAMOND (b) as a local aligner. Individual dots represent a single ARG and are connected by lines to demonstrate trends in detection across subsamples. CTX-M-15bla, gyrA, and parC variants conferring resistance to fluoroquinolones are highlighted as previously identified resistance determinants for this strain. The horizontal dotted line marks 90% detection frequency. The red vertical dashed line marks the subsample at 300,000 reads. The total number of unique genes present in 1 or more bootstraps (c), as well as the number of unique ARGs predicted with ≥90% detection frequency (d), and with ≤50% detection frequency (e) using BLAST or DIAMOND as an aligner across subsamples, are plotted. (f) Venn diagrams of the number of ARGs that were uniquely predicted by BLAST or DIAMOND or similarly predicted by BLAST and DIAMOND with ≥90% detection frequency or ≤50% detection frequency. Download FIG S1, PDF file, 1.1 MB.Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the E. coligyrA and parC variants conferring resistance to fluoroquinolones as well as E. coli EF-Tu mutants conferring resistance to pulvomycin, E. colicyaA with a mutation conferring resistance to fosfomycin, E. coliglpT with a mutation conferring resistance to fosfomycin, and a PBP3 conferring resistance to beta-lactam antibiotics. Of the 6 ARG variants and associated SNPs evaluated, 200,000 assembled reads were sufficient to detect 6/6 with high confidence  detection frequencies (%) predicted in Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the E. coli isolates  threshold for ARG detection was validated across 948 isolates . The isoE. coli isolate set, a total of 322 unique ARGs were observed. n = 84), 65 isolates had 1 false positive, 12 isolates had 2 false positives, 3 isolates had 3 false positives, and the remaining 4 isolates had 5, 7, 16, and 70 false positives, respectively. For the isolates with a sensitivity of <1, the median number of false negatives was 1 (range 1–15).Across the 10.1128/msystems.00022-22.7TABLE S1E. coli (n = 948) isolates at 300,000 reads. Download Table S1, XLSX file, 0.02 MB.Performance characteristics of each antimicrobial resistance gene detected across Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the APH(6)-ld (n = 25), sul2 (n = 23), and mphA (n = 23), with a sensitivity of approximately 93% for all three genes respectively, while the top three genes that contributed the most false positives were OXA-320bla (n = 13), aadA (n = 6), and OXA-140bla (n = 6)  were classified as true positive for all 948 isolates, of which 90.5% (19/21) were efflux-associated genes. The top three ARGs that contributed the most false negatives were  (n = 6) .ofE. coli ST38 relative abundance on ARG detection in a multispecies metagenome, the DNA of E. coli ST38 and a 34-species cultivated microbial consortium, where each isolate was subject to antibiotic susceptibility testing and included in the consortium if phenotypically susceptible to a range of antibiotics , we estimated that at 90%, 50%, 10%, and 1% relative abundance, 333,333, 600,000, 3,000,000, and 30,000,000 2 × 150 bp reads, respectively, would be required to detect reference-based ARGs (n = 20) and protein variant-associated SNPs (n = 6) contributed by the E. coli ST38 isolate with ≥90% detection frequency. Reads were assembled into metagenomic contigs and ARGs predicted using RGI main with its low_quality flag . The reference-based ARGs and SNPs detected in each of the four metagenomic samples across subsamples are summarized in To assess the effect ibiotics , were coE. coli ST38 relative abundance decreased, the number of reads necessary to detect the reference-based ARGs  of the reference-based ARGs and 67% (4/6) of the SNPs had a detection frequency of ≥90% with ≤30,000,000 reads (ugd had a detection frequency 50% (cyaA SNP (S352T) had a detection frequency of 40%, and the gyrA SNPs  were not detected at 30,000,000 reads , respectively, required the most sequencing information to detect them at each of the detection frequency cutoffs compared to the other ARGs and SNPs.Enterococcus positive by culture and vanA positive in 9/10 swabs by Illumina sequencing (Enterococcus genome coverage for the detection of vanA. The study authors performed 2 × 75 bp sequencing and achieved a mean 9.1 million reads (range: 5.7–15 million reads), post quality filtering and removal of human reads. The rectal swab samples had a range of Enterococcus relative abundances  and genome coverages  , had the largest estimated target genome coverage of ~375×. Rectal swab number 4 had the lowest Enterococcus relative abundance (0.02%) and 9.1 million sequences, which resulted in a target genome coverage of ~0.07× for this sample  . Rectal s sample .vanA in the rectal swab metagenomes, reads were sampled 10 times at each subsampling depth to achieve a range of target genome coverages from 0.5× to 15× to determine vanA detection frequency. As above, reads were assembled into metagenomic contigs and ARGs predicted using RGI main with its -low_quality flag. The results of this analysis are displayed in vanA gene across rectal swab samples, 5 rectal swab samples required Enterococcus genome coverage of less than 5× , while 2 required at least 15× coverage . At 15× Enterococcus genome coverage, vanA was detected in 10/10 bootstraps for all samples that had adequate sequencing depth for subsampling. Rectal swab number 4 did not have enough reads to achieve 0.5× Enterococcus genome coverage, and vanA was not detected when we analyzed all reads available, which is consistent with the authors’ published findings that describe their inability to detect vanA using paired-end Illumina sequencing  to the assembly-based approach to determine if it would improve ARG prediction at lower sequencing depths. Reads (2 × 150 bp) were aligned to CARD reference sequences using KMA within RGI’s bwt branch . All KMA-predicted ARGs across subsamples in E. coli ST38 are outlined in E. coli ST38 genome  and parC (S80I) genes did not achieve a detection frequency ≥50% even at maximum subsample depths in most metagenomic samples   with as little as 50,000 reads compared to assembly at the same depth (2.6 ± 2.1). With increasing read depth, the number of nonreference ARGs predicted by KMA increased to 87.0 ± 5.1 at 5,000,000 reads. The increase in nonreference ARGs with increasing read depth was not observed with an assembly-based method at 5,000,000 reads (3.2 ± 3.1) . Thus, tWe hypothesized that filtering potentially erroneous ARGs would improve the precision of KMA. Four ARG filtering strategies at a range of cutoff values were evaluated for their effect on the performance of KMA . The ARG10.1128/msystems.00022-22.2FIG S2n = 72) in Escherichia coli ST38. Precision-recall curves are plotted where precision is a measure of positive predictive value and recall is a measure of sensitivity for a range of cutoff values shown in the table for each filtration method. Performance was evaluated at a subsampling depth of 200,000 reads. The horizontal dotted line denotes an unfiltered precision of 66%. The vertical dotted line denotes an unfiltered recall of 93%. Download FIG S2, PDF file, 1.3 MB.Effects of four filtering strategies on KMA-based classification of reference-based ARGs  for the detection of known determinants of resistance in metagenomic samples to inform the use of these approaches in human, animal, and environmental studies. It is axiomatic that sequencing depth affects ARG assay sensitivity in single isolates , 18 and de novo contig-assembly approach, approximately 15× coverage  provides similar sensitivity to higher sequencing depths for the detection of ARGs in E. coli isolates and is sufficient for detecting SNPs and other resistance genes. Although sequencing depths as low as 0.5 million reads have been proposed to capture the total compositional information of metagenomes  that had a high detection frequency with assembly, had a low detection frequency with KMA. Although KMA was designed to overcome the problem of mapping sequences to highly redundant gene databases  was modeled. These selections were made to reflect dominant modes of metagenome analysis in a clinically relevant organism to define the “order of magnitude” of depth required for ARG detection from metagenomes, which may not be generalizable to all organisms, community types, or modes of resistance. The microbial consortia of 34 bacterial species used in this study to represent a metagenomic sample, is not comparable to highly diverse sample types such as soil  in the presence of more abundant wild-type alleles.Our approach has the following limitations. A single approach utilizing a widely used sequencing strategy, two bioinformatic pipelines, and one ARG detection platform (CARD) for a single organism  from metagenomic samples, with paired-end Illumina sequencing data. The culture confirmation of vancomycin resistance and target organism is critical as it provided ground truth to base the sequencing depth recommendations on.We chose to spike the ibiotics . The metE. coli  and fluoroquinolone resistance-conferring SNPs in parC (S80I) and gyrA  was selected. Briefly, E. coli ST38 was cultured from a glycerol stock on LB agar, and a single colony was inoculated into 25 mL of LB broth, which was placed on a shaker incubator (130 rpm) at 37°C for 4 h until media was turbid. Turbid media (25 mL) was transferred to a 50 mL conical tube, subject to centrifugation at 2,500 g, the supernatant removed, and the pellet resuspended in 500 μL of LB broth. A description of the microbial consortia preparation was described previously  using the DNeasy PowerSoil kit (Qiagen) and DNA concentration was measured using a Qubit Fluorometer (Thermo Fisher), following the manufacturer’s instructions, respectively. E. coli and microbial consortia DNA were combined to a final concentration of 20.1 ng/μL, while varying the concentration of E. coli so that it approximately represented 90%, 50%, 10%, 1%, 0.1%, 0.01%, 0.001%, and 0.0001% relative to the microbial consortia. Sequencing libraries were prepared using the Nextera DNA Flex kit (Illumina) following the manufacturer’s instructions and stored at −20°C. All 10 samples  were subject to paired-end sequencing at 2 × 150 bp on the NovaSeq 6000 at the Princess Margaret Genomics Centre. Since the minimum sequencing depths needed to detect ARGs in the combined samples where E. coli ST38 represented 0.1%, 0.01%, 0.0001%, and 0.0001% were not achieved, these samples were not analyzed.DNA was extracted from thawed microbial consortia (250 μL), and the n number of reads, specifying the –sample flag with 100 bootstraps performed (sampling with replacement) for all samples and subsamples, except the combined sample with an E. coli ST38 relative abundance of 1% where at the 30 million read subsample 10 bootstraps were performed. In seqtk, the seed parameter, -s, had a unique number to ensure every bootstrap was a random sampling of reads. Paired-end fastq files (read 1 and read 2) were assessed for quality using FastQC  assembled with SPAdes and for the combined samples with spiked E. coli ST38 relative abundances from 90%–1% assembled with metaSPAdes. (a) N50, (b) total number of contigs, and (c) total length of the assembly in base pairs (bp). The mean and standard deviation at each subsample is plotted. Download FIG S3, PDF file, 0.3 MB.Assembly quality metrics across subsample for the Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/msystems.00022-22.8TABLE S2E. coli ST38 across subsamples. Download Table S2, XLSX file, 0.01 MB.The percent of sequences with quality score greater than Q20 or Q30 and sequence length (base pairs) of less than 20 or 35 for the combined samples and the Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the main v.5.1.0 of the CARD v.3.1.0 (perfect and strict hits identified only) was used  or “ARO_Term” (raw reads) column of each sample RGI output file, to create a new “unique AMR genes” file for each sample. ARG or SNP presence in a bootstrap sample was indicated by 1 and absence indicated by 0. Then, using Metaphlan2 v.2.9.14, the E. coli ST38 genome (100% relative abundance), reference #1 was used and consisted of all ARGs (n = 72) predicted from a single bootstrap of 5,000,000 E. coli ST38 contig-assembled reads (~250× coverage). For analyses in the combined metagenomic samples, reference #2 was used and consisted of ARGs unique to reference #1 (n = 20) and not predicted in contigs assembled from 82.5 million (2 × 150 bp) microbial consortia reads. For SNP analyses, reference #3 was used and consisted of protein variants and associated SNPs predicted with CARD’s protein variant model (n = 6), which were detected in a single bootstrap of 5,000,000 E. coli ST38 contig-assembled reads. To quantify additional ARGs in the combined metagenomic samples not found in the E. coli ST38 genome or the microbial consortia, reference #4 was used and consisted of all ARGs in reference #1 (n = 72) as well as microbial consortia specific ARGs (n = 19) predicted from 82.5 million reads assembled into contigs. The total ARGs in reference #4 is 90. Reference-based ARG and SNPs were plotted across subsamples, and minimum subsampling depths for individual ARGs and SNPs were summarized by three detection frequency cutoffs of greater than or equal to 50%, 90%, and 99% and visualized using R version 4.1.2 with the ggplot2 package.ARG and SNP reference sets are listed in 10.1128/msystems.00022-22.9TABLE S3Table S3, XLSX file, 0.01 MB.Antimicrobial resistance gene and single nucleotide polymorphism reference sets. Download Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the E. coli ST38 isolate, the ARGs predicted in each bootstrap of a subsample using a contig assembly approach with SPAdes or a read-based approach with KMA were compared to reference set #1 for ARGs  and rounding to 6 Mbp, which represents the larger size of E. coli genomes found in NCBI’s microbial genome database. To estimate the number of reads required to detect E. coli ST38 at a range of relative abundances, the minimum read requirement  was divided by the target relative abundance. For example, if the target relative abundance was 10%, 300,000/0.10 would equal 3,000,000 reads.Sequencing coverage was estimated using the Lander-Waterman equation . We overE. coli isolates , we subsampled each metagenomic sample and bootstrapped each subsample 10 times. Each subsample depth was calculated using the Lander-Waterman equation, as described above, while accounting for the Enterococcus relative abundance in the sample, as determined using Metaphlan2. Similarly to the E. coli genome estimation described above, we overestimated the Enterococcus genome size at 4 Mbp.To validate 15× target genome coverage in metagenomic samples  and to dE. coli ST38 represented 100%, 90%, 50%, 10%, and 1% relative abundance, assuming a genome length of 6 Mbp, then these values were log-transformed. Using GraphPad Prism version 9.1.2, sigmoidal curves were fit to detection frequency data for the blaCTX-M-15 for each sample, where E. coli ST38 represented 100%, 90%, 50%, 10%, and 1% relative abundance. The equations were constrained at 0 and 100, and detection frequency was interpolated for relative abundances 100%, 90%, 50%, 10%, and 1% based on coverage estimation.Post-quality filtered sequence depths were extracted that were provided in each study’s supplementary material for Studies 1 (9), 2 (6), and 3 (10). For Study 3, the sequences reported under the heading “After human contamination removal” under the subheading “read-pairs” were used. Sequencing read lengths were reported in Study 2 (2 × 150 bp) and 3 (2 × 100 bp), but for Study 1 we extracted the read lengths from the individual studies referenced within the paper. For each sample, coverage was estimated from the published data sets and for each subsample performed on the samples where Comparisons between paired ARG detection frequencies using KMA or SPAdes/metaSPAdes assemblies for ARG prediction were made using the Wilcoxon matched-pairs signed-rank test at each subsample in GraphPad Prism v.9.3.0.PRJNA649958. Metadata for the generated samples can be found in Escherichia coli genome set analyzed in this study can be found at NCBI under BioProject PRJNA521038, and through Zenodo.org under the DOIs 10.5281/zenodo.3706855 and 10.5281/zenodo.3701595. Sequencing data from a public data set of 10 rectal swab samples analyzed in this study can be found in the NCBI sequence read archive under BioProject PRJNA655185.The data set generated during the current study is available in the NCBI sequence read archive under BioProject 10.1128/msystems.00022-22.10TABLE S4Table S4, XLSX file, 0.01 MB.Metadata for samples sequenced on the NovaSeq 6000 at 2 × 150 bp. Download Copyright © 2022 Rooney et al.2022Rooney et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the


Background. Salivary metabolomics is garnering increasing attention in the health field because of easy, minimally invasive saliva sampling. Dihydrouracil (DHU) is a metabolite of pyrimidine metabolism present in urine, plasma, and saliva and of fluoropyrimidines-based chemotherapeutics. Its fast quantification would help in the identification of patients with higher risk of fluoropyrimidine-induced toxicity and inborn errors of pyrimidine metabolism. Few studies consider DHU as the main salivary metabolite, but reports of its concentration levels in saliva are scarce. We propose the direct determination of DHU in saliva by reversed-phase high-performance liquid chromatography (RP-HPLC-UV detector) as a simple, rapid procedure for non-invasive screening. Methods. The method used was validated and applied to 176 saliva samples collected from 21 nominally healthy volunteers and 4 saliva samples from metastatic colorectal cancer patients before and after receiving 5-fluorouracil chemotherapy. Results. DHU levels in all samples analyzed were in the μmol L−1 range or below proving that DHU is not the main metabolite in saliva and confirming the results found in the literature with LC-MS/MS instrumentation. Any increase of DHU due to metabolism dysfunctions can be suggestive of disease and easily monitored in saliva using common, low-cost instrumentation available also for population screening. Its incrimidine ,8. Thus,−1. Pan et al. recently reported an improved method for the detection of uracil and dihydrouracil in human plasma using reversed-phase high-performance liquid chromatography. Tsuchiya et al. determined DHU in urine by GC-MS and LC-MS reporting reference values in Fujita Health University Hospital in the range of 0–16 μmol mmol−1 creatine  [−1 in healthy subjects determined by LC–MS/MS [−1 (0.673–1.798 μmol L−1 range) [−1 (range 0.537–1.023 μmol L−1); in saliva, DHU had a median of 2.168 μmol L−1 (range 1.139–5.013 μmol L−1) [−1 in saliva of 10 healthy adults and 8.6 μmol L−1 in 10 neonates [−1. In contrast with these values found in saliva, other fundamental papers on salivary metabolomics [−1, i.e., a concentration 1000 higher than that found in saliva, plasma, and urine by the previously mentioned works. DHU concentration has been reported to be 2168 ± 128 μmol L−1 by Dame et al. [−1 by Sugimoto et al. [Many analytical techniques have been developed for the determination of DHU in plasma based on UV ,11,12,13atinine) , findingLC–MS/MS . Analogo1 range) ,18. Gala1 range) . They fomol L−1) . Al-Shehneonates . Only afbolomics ,22 reporWe recently approached the study of salivary metabolites with the aim of using saliva analysis as a minimally invasive, safe, and painless tool for the monitoring of the health status ,24,25,26Dihydrouracil  was purchased from Sigma Aldrich . Methanol HPLC grade was purchased from Merck . Purified water was obtained from an Elga Purelab Ultra system from Veolia Labwater . Additionally, 0.20 μm RC Mini-Uniprep filter units were obtained from . Saliva samples were collected using a Salivette device .−1. Working solutions (concentrations 1–2500 μmol L−1) were prepared by dilution of the stock solutions with the eluent phase (5 mM sulfuric acid).DHU stock solution was prepared in water at the concentration of 10 mmol L® roll-shaped polyester swabs  were used for the collection of non-stimulated saliva samples collected in different days from 21 nominally healthy volunteers and from 4 metastatic colorectal cancer patients receiving 5-fluorouracil at the University Hospital of Pisa  within 1 h from the beginning of the 5-fluorouracil infusion and at the end of the infusion. 5-fluorouracil was administered as a continuous 48 h intravenous infusion at a dose of 2400 mg/mq (maintenance therapy). In total, N = 176 saliva samples were collected from healthy volunteers sampling in different days. This study was conducted in accordance with the principles set in the Helsinki Declaration. Ethical review and approval are not applicable because all subjects were volunteers. All subjects provided their written informed consent before any procedure. The healthy participant population included 11 men and 10 women, ranging in age from 26 to 62 y ; patients included 1 man and 3 women, ranging in age from 52 to 78 y (64 ± 14 y). For all participants, saliva samples were collected at the same time of the day (6:00 a.m. to 7:00 a.m.), to avoid fluctuation in the results due to the circadian saliva cycle, after at least 8 h of fasting or tooth brushing. Salivette® swabs  were kept in the mouth for 5 min and, after collection were immediately stored at −20 °C. Prior to analysis, swabs were thawed at room temperature and then centrifuged at 4500× g for 10 min at 4 °C (Eppendorf™ 5804R Centrifuge) . Saliva samples were diluted 5 times in 5 mM sulfuric acid, filtered using a 0.20 μm RC Mini-Uniprep filter, and then injected (Vinj = 5 μL) in the HPLC system.SalivetteAn Agilent 1260 Infinity HPLC system (G1311B quaternary pump) equipped with 1260 Infinity High-Performance Degasser, a TCC G1316A thermostat, 1260ALS autosampler (G1329B), and UV/vis diode array (1260 DAD G4212B)  was employed. The identification of metabolites was based on the comparison of the retention time and UV spectra of standard compounds. The chromatographic separation was carried out by Zorbax Phenyl-Hexyl RP  250 × 4.6 mm (silica particle size 5 μm) at 45 °C using an isocratic elution with 100% 5 mM sulfuric acid (pH 2.2) for 6 min. The column was rinsed with 100% methanol for 15 min, and then, a re-equilibration step was performed. All the solutions were filtered using a 0.22 μm regenerate cellulose filter .−1 DHU eluting in our operating conditions at tR = 5.151. The method was validated in saliva by evaluating linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, and precision. LOD and LOQ were determined by the analysis of samples with known concentrations of the standard analyte and by establishing the minimum level at which the analyte can be reliably detected and quantified with acceptable accuracy and precision, respectively. Linearity was calculated in the range 1–2500 μmol L−1 for the chemical standard DHU. Precision was recorded in standard solutions at three concentration levels in  in three replicates to calculate the percentage of relative standard deviation (RSD), resulting as 3.4, 2.1, and 1.1%, respectively. In saliva at QCLow = 10 μmol L−1, QCMedium = 500 μmol L−1, and QCHigh = 2000 μmol L−1 RSD resulted as 6.1, 2.3, and 2.5%, respectively. DHU concentration was calculated based on the area of the peak at tR = 5.151 min and the corresponding calibration curve obtained in the matrix.inj = 5 μL) in the HPLC system (N = 3 replicates). −1 DHU. The spike of DHU to saliva sample showed a peak eluting at tR = 5.151 min, which was not detected in unspiked saliva. −1 DHU. −1 DHU standard solution before and after adsorption/centrifugation of Salivette®. −1, in saliva, LOQ spans from 0.103 to 3 μmol L−1 depending on the concentration level of α-ketoglutaric acid , 0.66 ± 0.67 , and 0.19 ± 0.14 μmol L−1 . In all saliva samples of 18 out of 21 nominally healthy volunteers , DHU was below the LOQ of this method. In three subjects, DHU concentration was found 4.01 ± 1.15  [Despite the limited number of cases examined, the finding of a slightly higher concentration of DHU in 3 out of 21 nominally healthy volunteers arouses interest in the role of DHU in metabolism. DHU monitoring is indeed commonly related to DPD dysfunctions during chemotherapy treatments. However, DHU is an oxidation product of the nucleotide uracil and may provide a stable marker of altered nucleotide metabolism in several diseases ,30,31,32= 0.006) . Wikoff = 0.006) . DHU was= 0.006) . Thus, tThe direct RP-HPLC-DAD method proposed allows the analyst to determine DHU in saliva in less than 6 min after an easy, fast dilution and filtration of the saliva sample. The DHU concentration levels found in saliva in this work as well as the values found by other authors ,18,19,20