Skin morphogenesis, maintenance, and healing after wounding require complex epithelial–mesenchymal interactions. In this study, we show that for skin homeostasis, interleukin-1 (IL-1) produced by keratinocytes activates peroxisome proliferator–activated receptor β/δ (PPARβ/δ) expression in underlying fibroblasts, which in turn inhibits the mitotic activity of keratinocytes via inhibition of the IL-1 signaling pathway. In fact, PPARβ/δ stimulates production of the secreted IL-1 receptor antagonist, which leads to an autocrine decrease in IL-1 signaling pathways and consequently decreases production of secreted mitogenic factors by the fibroblasts. This fibroblast PPARβ/δ regulation of the IL-1 signaling is required for proper wound healing and can regulate tumor as well as normal human keratinocyte cell proliferation. Together, these findings provide evidence for a novel homeostatic control of keratinocyte proliferation and differentiation mediated via PPARβ/δ regulation in dermal fibroblasts of IL-1 signaling. Given the ubiquitous expression of PPARβ/δ, other epithelial–mesenchymal interactions may also be regulated in a similar manner.
Successful translation of laboratory-based surface-enhanced Raman scattering (SERS) platforms to clinical applications requires multiplex and ultratrace detection of small metabolites from a complex biofluid. However, these metabolites exhibit low Raman scattering cross-sections and do not possess specific affinity to plasmonic nanoparticle surfaces, significantly increasing the challenge of detecting them at low concentrations. Herein, a 'confine-and-capture' approach is demonstrated for multiplex detection of two families of urine metabolites correlated with miscarriage risks, 5β-pregnane-3α,20α-diol-3α-glucuronide and tetrahydrocortisone. To enhance SERS signals by 10 12 -fold, specific nanoscale surface chemistry is used for targeted metabolite capture from a complex urine matrix prior to confining them on a superhydrophobic SERS platform. Applying chemometrics, including principal component analysis and partial least square regression, enables conversion of molecular fingerprint information into quantifiable readouts. The whole screening procedure requires only 30 minutes, including urine pretreatment, sample drying on the SPHB-mirror platform, SERS measurements and chemometric analyses. These readouts correlate well with the pregnancy outcomes in a case-control study of 40 patients presenting threatened miscarriage symptoms.Keywords. surface-enhanced Raman spectroscopy (SERS), superhydrophobic SERS platform, chemometrics, metabolomics, urine-based diagnostic test 3 Achieving ultratrace detection of small molecules with low Raman scattering cross-sections and without specific affinity to plasmonic nanoparticle surfaces remains challenging in surfaceenhanced Raman scattering (SERS) spectroscopy. [1][2][3] This difficulty is further compounded by the need to perform multiplex and quantitative molecular detection from a complex matrix.Successfully addressing these issues is instrumental towards the translating laboratory-based SERS platforms into practical sensing devices. 4 SERS offers multiple advantages over conventional analytical platforms such as fluorescence-based techniques. 5 SERS platforms can be tailored to generate intense electromagnetic field enhancements and dense plasmonic hotspots, in turn enhancing molecule-specific Raman vibrational fingerprint intensities by >10 9 -fold. 6,7 These fingerprints exhibit substantially narrower peak widths as compared to the broad fluorescence emission bands (full-width half-maximum of ~ 2 nm versus 30 nm respectively), further enabling SERS to achieve label-free multiplex analysis with ease. 8 SERS measurements also require significantly shorter time as compared to conventional chromatography-or mass spectrometrybased analytical approaches, whereby SERS analyses can be completed within an hour. 9 More importantly, the fingerprint specificity of SERS readouts enables differentiation of isomeric structures which cannot be easily achieved using other techniques. [10][11][12] However, majority of current SERS research focus predominantly on platform design, using s...
BackgroundOur recent paper, based on a pilot cohort of 119 women, showed that serum progesterone <35 nmol/L was prognostic of spontaneous miscarriage by 16 weeks in women with threatened miscarriage in early pregnancy. Using a larger cohort of women from the same setting (validation cohort), we aim to assess the validity of serum progesterone <35 nmol/L with the outcome of spontaneous miscarriage by 16 weeks.MethodsIn a prospective cohort study, 360 pregnant women presenting with threatened miscarriage between gestation weeks 6–10 at a tertiary hospital emergency unit for women in Singapore were recruited for this study. The main outcome measure measured is spontaneous miscarriage prior to week 16 of gestation. Area under the ROC curve (AUC) and test characteristics (sensitivity, specificity, positive and negative predictive value) at a serum progesterone cutpoint of <35 nmol/L for predicting high and low risk of spontaneous miscarriage by 16 weeks were compared between the Pilot and Validation cohorts.ResultsTest characteristics and AUC values using serum progesterone <35 nmol/L in the validation cohort were not significantly different from those in the Pilot cohort, demonstrating excellent accuracy and reproducibility of the proposed serum progesterone cut-off level.ConclusionsThe cut-off value for serum progesterone (35 nmol/L) demonstrated clinical relevance and allow clinicians to stratify patients into high and low risk groups for spontaneous miscarriage.
BackgroundProgesterone is a critical hormone in early pregnancy. A low level of serum progesterone is associated with threatened miscarriage. We aim to establish the distribution of maternal serum progesterone in normal pregnancies compared to pregnancies complicated by threatened miscarriage from 5 to 13 weeks gestation.MethodsThis is a single centre, prospective cohort study of 929 patients. Women from the Normal Pregnancy [NP] cohort were recruited from antenatal clinics, and those in the Threatened Miscarriage [TM] cohort were recruited from emergency walk-in clinics. Women with multiple gestations, missed, incomplete or inevitable miscarriage were excluded from the study. Quantile regression was used to characterize serum progesterone levels in the NP and TM cohorts by estimating the 10th, 50th and 90th percentiles from 5 to 13 weeks gestation. Pregnancy outcome was determined at 16 weeks of gestation. Subgroup analysis within the TM group compared progesterone levels of women who subsequently miscarried with those who had ongoing pregnancies at 16 weeks of gestation.ResultsMedian serum progesterone concentration demonstrated a linearly increasing trend from 57.5 nmol/L to 80.8 nmol/L from 5 to 13 weeks gestation in the NP cohort. In the TM cohort, median serum progesterone concentration increased from 41.7 nmol/L to 78.1 nmol/L. However, median progesterone levels were uniformly lower in the TM cohort by approximately 10 nmol/L at every gestation week. In the subgroup analysis, median serum progesterone concentration in women with ongoing pregnancy at 16 weeks gestation demonstrated a linearly increasing trend from 5 to 13 weeks gestation. There was a marginal and non-significant increase in serum progesterone from 19.0 to 30.3 nmol/L from 5 to 13 weeks gestation in women who eventually had a spontaneous miscarriage.ConclusionsSerum progesterone concentration increased linearly with gestational age from 5 to 13 weeks in women with normal pregnancies. Women with spontaneous miscarriage showed a marginal and non-significant increase in serum progesterone. This study highlights the pivotal role of progesterone in supporting an early pregnancy, with lower serum progesterone associated with threatened miscarriage and a subsequent complete miscarriage at 16 weeks gestation.Electronic supplementary materialThe online version of this article (10.1186/s12884-018-2002-z) contains supplementary material, which is available to authorized users.
Endometriosis is a common inflammatory gynecological disorder which causes pelvic scarring, pain, and infertility, characterized by the implantation of endometrial-like lesions outside the uterus. The peritoneum, ovaries, and deep soft tissues are the commonly involved sites, and endometriotic lesions can be classified into three subphenotypes: superficial peritoneal endometriosis (PE), ovarian endometrioma (OE), and deep infiltrating endometriosis (DIE). In 132 women diagnosed laparoscopically with and without endometriosis (n = 73, 59 respectively), and stratified into PE, OE, and DIE, peritoneal fluids (PF) were characterized for 48 cytokines by using multiplex immunoassays. Partial-least-squares-regression analysis revealed distinct subphenotype cytokine signatures—a six-cytokine signature distinguishing PE from OE, a seven-cytokine signature distinguishing OE from DIE, and a six-cytokine-signature distinguishing PE from DIE—each associated with different patterns of biological processes, signaling events, and immunology. These signatures describe endometriosis better than disease stages (p < 0.0001). Pathway analysis revealed the association of ERK1 and 2, AKT, MAPK, and STAT4 linked to angiogenesis, cell proliferation, migration, and inflammation in the subphenotypes. These data shed new insights on the pathophysiology of endometriosis subphenotypes, with the potential to exploit the cytokine signatures to stratify endometriosis patients for targeted therapies and biomarker discovery.
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