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Background During biological aging, significant metabolic dysregulation in the central nervous system may lead to cognitive decline and neurodegeneration. However, the metabolomics of the aging process in cerebrospinal fluid (CSF) has not been thoroughly explored. Methods In this cohort study of CSF metabolomics using liquid chromatography-mass spectrometry (LC–MS), fasting CSF samples collected from 92 cognitively unimpaired adults aged 20–87 years without obesity or diabetes were analyzed. Results We identified 37 metabolites in these CSF samples with significant positive correlations with aging, including cysteine, pantothenic acid, 5-hydroxyindoleacetic acid (5-HIAA), aspartic acid, and glutamate; and two metabolites with negative correlations, asparagine and glycerophosphocholine. The combined alterations of asparagine, cysteine, glycerophosphocholine, pantothenic acid, sucrose, and 5-HIAA showed a superior correlation with aging (AUC = 0.982). These age-correlated changes in CSF metabolites might reflect blood–brain barrier breakdown, neuroinflammation, and mitochondrial dysfunction in the aging brain. We also found sex differences in CSF metabolites with higher levels of taurine and 5-HIAA in women using propensity-matched comparison. Conclusions Our LC–MS metabolomics of the aging process in a Taiwanese population revealed several significantly altered CSF metabolites during aging and between the sexes. These metabolic alterations in CSF might provide clues for healthy brain aging and deserve further exploration.

Diabetic kidney disease is the leading cause of end-stage kidney disease worldwide; however, the integration of high-dimensional trans-omics data to predict this diabetic complication is rare. We develop artificial intelligence (AI)-assisted models using machine learning algorithms to identify a biomarker signature that predisposes high risk patients with diabetes mellitus (DM) to diabetic kidney disease based on clinical information, untargeted metabolomics, targeted lipidomics and genome-wide single nucleotide polymorphism (SNP) datasets. This involves 618 individuals who are split into training and testing cohorts of 557 and 61 subjects, respectively. Three models are developed. In model 1, the top 20 features selected by AI give an accuracy rate of 0.83 and an area under curve (AUC) of 0.89 when differentiating DM and non-DM individuals. In model 2, among DM patients, a biomarker signature of 10 AI-selected features gives an accuracy rate of 0.70 and an AUC of 0.76 when identifying subjects at high risk of renal impairment. In model 3, among non-DM patients, a biomarker signature of 25 AI-selected features gives an accuracy rate of 0.82 and an AUC of 0.76 when pinpointing subjects at high risk of chronic kidney disease. In addition, the performance of the three models is rigorously verified using an independent validation cohort. Intriguingly, analysis of the protein–protein interaction network of the genes containing the identified SNPs (RPTOR, CLPTM1L, ALDH1L1, LY6D, PCDH9, B3GNTL1, CDS1, ADCYAP and FAM53A) reveals that, at the molecular level, there seems to be interconnected factors that have an effect on the progression of renal impairment among DM patients. In conclusion, our findings reveal the potential of employing machine learning algorithms to augment traditional methods and our findings suggest what molecular mechanisms may underlie the complex interaction between DM and chronic kidney disease. Moreover, the development of our AI-assisted models will improve precision when diagnosing renal impairment in predisposed patients, both DM and non-DM. Finally, a large prospective cohort study is needed to validate the clinical utility and mechanistic implications of these biomarker signatures.

Three coordination complexes, [Cu(L1)(2,2–bipy)]2n·3nH2O (1), [Cu(L1)(2,2–bipy)2]·xH2O (2: x = 3.5 and 3: x = 5), were synthesized by reactions of the flexible ligand 1,1´-methylenebis(5-methyl-pyrazole-4-carboxylic acid) (H2L1) and coligands 2,2'–bipyridyl (2,2-bipy) with Cu(OAc)2·H2O in different reaction condition, respectively. The structures of these complexes were established by elemental analysis, IR and single-crystal X-ray diffraction analysis. Complex 1 possessed a one-dimensional (1D) chainlike structure, (L1)2− group exhibited trans-configuration and coordinated to Cu(II) ions by carboxylate O atoms in µ2–k:O,O′; k:O′′′,O′′′ mode. In the similar subjectival structure of 2 and 3, (L1)2− anions also presented trans-configuration, but only one carboxylate group chelated to a Cu(II) ion, and the other carboxylate group remains free in a deprotonated form. The 1D chains in 1 were further assembled to a 3D supramolecular architecture via intermolecular C–H···O hydrogen bond. The mononuclear zwitterionic complexes 2 and 3 are further assembled into a 2D/3D supramolecular architecture by intermolecular hydrogen bonds and π···π interaction. The thermal and photoluminescent properties of 1–3 in the solid state have also been investigated.

Glucose-6-phosphate dehydrogenase (G6PD) is the first and rate-limiting enzyme in pentose phosphate pathway (PPP), excessive activation of which has been considered to be involved in tumorigenesis. Here, we show that tyrosine kinase c-Src interacts with and phosphorylates G6PD at Tyr 112. This phosphorylation enhances catalytic activity of G6PD by dramatically decreasing its Km value and increasing its Kcat value for substrate glucose-6-phosphate. Activated G6PD therefore augments the PPP flux for NADPH and ribose-5-phosphate production which is required for detoxification of intracellular reactive oxygen species (ROS) and biosynthesis of cancer cells, and eventually contributes to tumorigenesis. Consistently, c-Src activation is closely correlated with tyrosine phosphorylation and activity of G6PD in clinical colorectal cancer samples. We thus uncover another aspect of c-Src in promoting cell proliferation and tumorigenesis, deepening our understanding of c-Src as a proto-oncogene.

Elevated phenylalanine has been observed in patients with advanced heart failure (HF) and in community cohorts at risk of HF, and has been shown to have prognostic value. This study aimed to explore the factors associated with elevated phenylalanine in HF patients. Mass spectrometry was performed on blood from 669 participants, including 75 normal controls and 594 HF patients (stages A, B, and C). We measured phenylalanine and associated degradation products on the catecholamine pathway, C-reactive protein, valerylcarnitine, methionine sulfoxide, estimated glomerular filtration rate (eGFR), and B-type natriuretic peptide. Longitudinal analysis was conducted on 61 stage C HF patients who had recovered systolic function after 1 year. Phenylalanine and tyrosine levels increased from normal through stages A, B and C. Cross-sectional analysis in patients at stage C showed that phenylalanine levels were related to total bilirubin, eGFR, valerylcarnitine, methionine sulfoxide, C-reactive protein, and male gender. Longitudinal analysis in the patients at stage C with recovered systolic function after 1 year revealed that phenylalanine, tyrosine, methionine sulfoxide, total bilirubin, and C-reactive protein levels significantly decreased from baseline to 12 months. Based on a generalized estimating equations analysis model with time interaction considered, the only significant factor associated with changes in phenylalanine was changes in C-reactive protein concentrations from baseline to 12 months [B (coefficient) = 0.81, P

Aberrant metabolisms have been hypothesized to precede the occurrence of hepatocellular carcinoma (HCC), therefore, we investigated biomarkers associated with subsequent HCC in peripheral bloods using metabolomic technologies. A cohort of 475 HCC-naïve liver cirrhotic patients were recruited and prospectively followed. A total of 39 patients developed HCC in the follow-up period. Baseline plasma metabolites were explored using untargeted nuclear magnetic resonance. Candidates were then quantified by ultra-performance liquid chromatography. A series of univairiate and multivariate analysis showed that Phenylalanine (Phe) and Glutamine (Gln) levels are associated with time to HCC, independent of viological etiologies and age. A HCC risk score R was then constructed using the polynomial combination of age, Phe and Gln in the units of micromolar (μM):$$\begin{aligned} {\text{R }} & = {\text{ Age }}* \, \left( {0.0694} \right) + {\text{ Phe }}* \, \left( {0.3399} \right) + {\text{ Phe }^{2}}* \, \left( { - 0.00188154} \right) \hfill \\ & \quad + {\text{ Gln }}* \, \left( { - 0.0133} \right) + {\text{ Gln }^{2}}* \, \left( { \, 0.00002244} \right) \hfill \\ \end{aligned}$$ R = Age ∗ 0.0694 + Phe ∗ 0.3399 + Phe 2 ∗ - 0.00188154 + Gln ∗ - 0.0133 + Gln 2 ∗ 0.00002244 R correlates with the time to HCC significantly (Hazard ratio [HR] = 2.368, 95% confidence interval [CI] 1.760–3.187, P

Endometrial cancer (EC) is one of the most common gynecologic neoplasms in developed countries but lacks screening biomarkers. We aim to identify and validate metabolomic biomarkers in cervicovaginal fluid (CVF) for detecting EC through nuclear magnetic resonance (NMR) spectroscopy. We screened 100 women with suspicion of EC and benign gynecological conditions, and randomized them into the training and independent testing datasets using a 5:1 study design. CVF samples were analyzed using a 600-MHz NMR spectrometer equipped with a cryoprobe. Four machine learning algorithms—support vector machine (SVM), partial least squares discriminant analysis (PLS-DA), random forest (RF), and logistic regression (LR), were applied to develop the model for identifying metabolomic biomarkers in cervicovaginal fluid for EC detection. A total of 54 women were eligible for the final analysis, with 21 EC and 33 non-EC. From 29 identified metabolites in cervicovaginal fluid samples, the top-ranking metabolites chosen through SVM, RF and PLS-DA which existed in independent metabolic pathways, i.e. phosphocholine, malate, and asparagine, were selected to build the prediction model. The SVM, PLS-DA, RF, and LR methods all yielded area under the curve values between 0.88 and 0.92 in the training dataset. In the testing dataset, the SVM and RF methods yielded the highest accuracy of 0.78 and the specificity of 0.75 and 0.80, respectively. Phosphocholine, asparagine, and malate from cervicovaginal fluid, which were identified and independently validated through models built using machine learning algorithms, are promising metabolomic biomarkers for the detection of EC using NMR spectroscopy.

Amino acid-derived metabolites, including protein-bound uremic toxins, may have prognostic value for patients with heart failure (HF). The aim of this study was to investigate whether p-cresyl sulfate (PCS), indoxyl sulfate (IS), and arginine metabolites provided prognostic values in addition to the traditional biomarker, B-type natriuretic peptide (BNP), in patients with HF. Chromatography mass spectrometry was performed to measure tyrosine, tryptophan, arginine, PCS, IS, and asymmetric (ADMA) and symmetric dimethylarginine (SDMA) in the plasma from 51 normal controls and 136 HF patients. Compared to the normal controls, PCS levels significantly increased in HF patients (p = 0.003). During the follow-up (2.3 ± 1.1 years), 35 (25.7 %) patients experienced a composite event of death or HF-related re-hospitalization. In univariable analysis, PCS, estimated glomerular filtration rate (eGFR), BNP, DMA/arginine ratio, and ADMA/arginine ratio were associated with a higher rate of composite events. In the multivariable analysis, PCS was the only independent predictor of composite events [hazard ratio (HR) 1.06 (per 10 μM), 95 % confidence interval (CI) 1.01–1.11, p = 0.02]. Kaplan–Meier curves showed that a PCS level of ≥50 μM was significantly associated with a higher composite event rate than those with a PCS level of

No effective drug is currently available for treatment of enterovirus 71 (EV71) infection. Schizonepeta tenuifolia Briq. (ST) has been used as a herbal constituent of traditional Chinese medicine. We studied whether the aqueous extract of Schizonepeta tenuifolia Briq (STE) has antiviral activity. STE inhibited replication of EV71, as evident by its ability to diminish plaque formation and cytopathic effect induced by EV71, and to inhibit the synthesis of viral RNA and protein. Moreover, daily single-dose STE treatment significantly improved the survival of EV71-infected mice, and ameliorated the symptoms. Mechanistically, STE exerts multiple effects on enteroviral infection. Treatment with STE reduced viral attachment and entry; the cleavage of eukaryotic translation initiation factor 4 G (eIF4G) by EV71 protease, 2Apro; virus-induced reactive oxygen species (ROS) formation; and relocation of heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) from the nucleus to the cytoplasm. It was accompanied by a decline in EV71-associated hyperphosphorylation of p38 kinase and EPS15. It is plausible that STE may inhibit ROS-induced p38 kinase activation, and subsequent hnRNP A1 relocation and EPS15-mediated membrane trafficking in infected cells. These findings suggest that STE possesses anti-EV71 activities, and may serve as health food or candidate antiviral drug for protection against EV71.

A new ligand 1-carboxymethyl-5-methyl-1H-pyrazole-4-carboxylic acid (H2L1) and its isomer 1-carboxymethyl-3-methyl-1H-pyrazole-4-carboxylic acid (H2L2) have been synthesized and characterized by IR and 1H NMR. Three complexes of these ligands, [M(HL1)2(H2O)2] (1: M = Zn; 2: M = Cu) and [Cd(HL2)2(H2O)2] (3) were synthesized by the reactions of H2L1 or H2L2 with the corresponding M(NO3)2·6H2O. The complexes were characterized by physico-chemical and spectroscopic methods, single-crystal X-ray diffraction, and thermogravimetric analysis. Complexes 1 and 2 are isostructural, while complex 3 crystallizes in the triclinic system. The M(II) atom in each of the complexes has a distorted octahedral geometry involving two oxygen and two nitrogen atoms from two anionic (HL1)− or (HL2)− ligands and two oxygen atoms from water ligands. Adjacent monomeric components are connected by hydrogen bonds to form a 3D supramolecular network. The free ligands and complexes 1 and 3 show dual-emissive luminescence in the solid state at room temperature. The luminescence intensity of solid complex 1 is weakened in the presence of NH3. Two new isomers, H2L1 and H2L2, and three complexes, [Zn(HL1)2(H2O)2], [Cu(HL1)2(H2O)2], and [Cd(HL2)2(H2O)2] have been synthesized, which display dual-emissive luminescence in the solid state.

Autophagy and endoplasmic reticulum (ER) stress response is important for cancer cells to maintain malignancy and resistance to therapy. trans-Resveratrol (RSV), a non-flavonoid agent, has been shown to induce apoptosis in human nasopharyngeal carcinoma (NPC) cells. In this study, the involvements of tumor-specific ER stress and autophagy in the RSV-mediated apoptosis were investigated. In addition to traditional autophagosomes, the images of transmission electron microscopy (TEM) indicated that RSV markedly induced larger, crescent-shaped vacuoles with single-layered membranes whose the expanded cisternae contains multi-lamellar membrane structures. Prolonged exposure to RSV induced a massive accumulation of ER expansion. Using an EGFP-LC3B transfection and confocal laser microscopy approach, we found RSV-induced EGFP-LC3 puncta co-localized with ER-tracker red dye, implicating the involvement of LC3II in ER expansion. The proapoptotic effect of RSV was enhanced after suppression of autophagy by ATG7 siRNA or blocking the autophagic flux by bafilomycin A1, but that was not changed after targeted silence of IRE1 or CHOP by siRNA. Using caspase inhibitors, we demonstrated the upregulation of caspase-12 (casp12) and the activation of casp4 were associated with the proapoptotic induction of RSV through the caspase-9/caspase-3 pathway. Intriguingly, siRNA knockdown of casp12, but not caspase-4, decreased the susceptibility of the NPC cells to RSV-mediated apoptosis. Further, we showed that RSV dose-dependently increased the ceramide accumulation as assessed by LC-MS/MS system. Using serine palmitoyltransferase (SPT, a key enzyme of de novo ceramide biosynthesis) inhibitors (L-cycloserine and myriocin), we found the increased ceramide accumulation was strongly correlated with the proapoptotic potential of RSV. This study revealed the ER expansion and upregulation of ER casp12 together may indicate profound biological effects of RSV and contributed to NPC cell death. Targeting the different status of ER stress may provide a possible strategy for cancer treatments.

Two cobalt(II) coordination polymers, {[Co(Hmt)2(tfbdc)(H2O)2]·(H2tfbdc)·(EtOH)2}n (1) and {[Co(Hmt)(tfbdc)(H2O)2]·(H2O)2}n (2) (H2tfbdc = 2,3,5,6-tetrafluoroterephthalic acid; Hmt = hexamethylenetetramine) have been synthesized and characterized by physicochemical and spectroscopic methods, thermogravimetric analysis, and single-crystal X-ray diffraction. In both complexes, the coordination environment around cobalt is distorted octahedral. In 1, each Co(II) atom is linked by tfbdc2− anionic ligands to form a 1D zigzag chain, which is further connected into a 3D network via hydrogen bond interactions. In 2, each Co(II) atom is bridged by anionic tfbdc2− and Hmt ligands along two directions, respectively, forming an infinite 2D structure with a parallelogram-type grid; the 2D networks are further assembled to a 3D framework via intermolecular hydrogen bond interactions. Both complexes show blue fluorescence in the solid state at room temperature. Two new coordination polymers, {[Co(Hmt)2(tfbdc)(H2O)2]·(H2tfbdc)·(EtOH)2}n (1) and {[Co(Hmt)(tfbdc)(H2O)2]·(H2O)2}n (2) have been obtained via the reactions of H2tfbdc, Hmt, and cobalt chloride hexahydrate in different molar ratios and solvents.