Urine Metabonomics Reveals Early Biomarkers in Diabetic Cognitive Dysfunction

Unveiling novel metabolic alterations in postmenopausal osteoporosis and type 2 diabetes mellitus through NMR-based metabolomics: A pioneering approach for identifying early diagnostic markers

BACKGROUND AND AIMS

Postmenopausal osteoporosis (PMO) and type 2 diabetes mellitus (T2DM) frequently coexist in postmenopausal women. The study aimed to explore metabolic variations linked to these circumstances and their simultaneous presence through proton nuclear magnetic resonance metabolomics (1H NMR).

MATERIALS AND METHODS

Serum samples from 80 postmenopausal women, including 20 PMO individuals, 20 T2DM, 20 T2DM + PMO, and 20 healthy postmenopausal women, were analyzed using 1H NMR spectroscopy.

RESULTS

Our study revealed significant metabolic profile differences among the four groups. Notably, the T2DM + PMO group showed elevated levels of alanine, pyruvate, glutamate, lactate, and aspartate, indicating their involvement in lipid metabolism, energy, and amino acids. Importantly, our multivariate statistical analysis identified a metabolite set that accurately distinguished the groups, suggesting its potential as an early diagnostic marker.

CONCLUSION

The 1H NMR metabolomics approach uncovered metabolic biomarkers intricately linked to postmenopausal osteoporosis (PMO), type 2 diabetes mellitus (T2DM), and their concurrent presence. Among these biomarkers, alanine emerged as a pivotal player, showing its significant role in the metabolic landscape associated with PMO and T2DM. These findings shed light on the pathophysiological mechanisms underlying these conditions and underscore alanine's potential as a diagnostic biomarker.

Risk factors and metabolomics of mild cognitive impairment in type 2 diabetes mellitus

Objective: This study aimed to explore the risk factors, metabolic characteristics, and potential biomarkers of mild cognitive impairment in type 2 diabetes mellitus (T2DM-MCI) and to provide potential evidence for the diagnosis, prevention, and treatment of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 103 patients with T2DM were recruited from the Endocrinology Department of The Second Affiliated Hospital of Dalian Medical University for inclusion in the study. The Montreal Cognitive Assessment (MoCA) was utilized to evaluate the cognitive functioning of all patients. Among them, 50 patients were categorized into the T2DM-MCI group (MoCA score < 26 points), while 53 subjects were classified into the T2DM without cognitive impairment (T2DM-NCI) group (MoCA score ≥ 26 points). Serum samples were collected from the subjects, and metabolomics profiling data were generated by Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). These groups were analyzed to investigate the differences in expression of small molecule metabolites, metabolic pathways, and potential specific biomarkers. Results: Comparison between the T2DM-MCI group and T2DM-NCI group revealed significant differences in years of education, history of insulin application, insulin resistance index, insulin-like growth factor-binding protein-3 (IGFBP-3), and creatinine levels. Further binary logistic regression analysis of the variables indicated that low educational level and low serum IGFBP-3 were independent risk factor for T2DM-MCI. Metabolomics analysis revealed that differential expression of 10 metabolites between the T2DM-MCI group and T2DM-NCI group (p < 0.05 and FDR<0.05, VIP>1.5). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis revealed that fatty acid degradation was the most significant pathway. Receiver operating characteristic (ROC) analysis shows that lysophosphatidylcholine (LPC) 18:0 exhibited greater diagnostic efficiency. Conclusion: This study revealed that a shorter duration of education and lower serum IGFBP-3 levels are independent risk factors for T2DM-MCI. Serum metabolites were found to be altered in both T2DM-MCI and T2DM-NCI groups. T2DM patients with or without MCI can be distinguished by LPC 18:0. Abnormal lipid metabolism plays a significant role in the development of MCI in T2DM patients.

Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma

Despite the well-established connection between systematic metabolic abnormalities and the pathophysiology of pituitary adenoma (PA), current metabolomic studies have reported an extremely limited number of metabolites associated with PA. Moreover, there was very little consistency in the identified metabolite signatures, resulting in a lack of robust metabolic biomarkers for the diagnosis and treatment of PA. Herein, we performed a global untargeted plasma metabolomic profiling on PA and identified a highly robust metabolomic signature based on a strategy. Specifically, this strategy is unique in (1) integrating repeated random sampling and a consensus evaluation-based feature selection algorithm and (2) evaluating the consistency of metabolomic signatures among different sample groups. This strategy demonstrated superior robustness and stronger discriminative ability compared with that of other feature selection methods including Student's t-test, partial least-squares-discriminant analysis, support vector machine recursive feature elimination, and random forest recursive feature elimination. More importantly, a highly robust metabolomic signature comprising 45 PA-specific differential metabolites was identified. Moreover, metabolite set enrichment analysis of these potential metabolic biomarkers revealed altered lipid metabolism in PA. In conclusion, our findings contribute to a better understanding of the metabolic changes in PA and may have implications for the development of diagnostic and therapeutic approaches targeting lipid metabolism in PA. We believe that the proposed strategy serves as a valuable tool for screening robust, discriminating metabolic features in the field of metabolomics.

Tangzhiqing decoction attenuates cognitive dysfunction of mice with type 2 diabetes by regulating AMPK/mTOR autophagy signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Tangzhiqing decoction (TZQD) is an effective prescription developed by Jiangsu Province Hospital of Chinese Medicine for the treatment of diabetes mellitus (DM) and its complications, which has a clear cerebral protective effect on mice with diabetic cognitive dysfunction, but its specific mechanism has not been well elucidated.

AIMS OF THE STUDY

This study aims to verify the protection of TZQD on cognitive function in mice with type 2 diabetes mellitus (T2DM) and explore the possible underlying mechanisms.

MATERIALS AND METHODS

Six active ingredients in TZQD were detected using high-performance liquid chromatography analysis. In vivo experiments, the protection of TZQD on cognitive function and hippocampal neurons in type 2 diabetes mice was verified to obtain the optimal intervention dose of TZQD. TZQD and 3-methyladenine (3 MA) respectively or jointly intervened in mice with T2DM for 12 weeks, followed by detecting the cognitive difference, hippocampus cornu ammonis 1 (CA1) region injury, and hippocampal neuronal apoptosis in each group. Simultaneously, the investigation of autophagosome formation and organelle impairment in hippocampal neurons, along with the examination of AMPK/mTOR pathway proteins and autophagy-related proteins, was conducted to elucidate the potential mechanisms, through which TZQD modulates autophagy and enhances cognitive function. In vitro experiments, TZQD-containing serum and AMPK inhibitor Compound C (CC) were used to intervene in mouse hippocampal neuron HT22 cells under high glucose environment, further clarifying the regulatory role of TZQD on the AMPK/mTOR pathway and its impact on HT22 cell apoptosis and autophagy.

RESULTS

In vivo experiment results showed that TZQD had an obvious hypoglycemic effect. Different doses of TZQD could improve cognitive function and hippocampus damage in diabetes mice, with the middle dose of TZQD showing the best effect. TZQD increased the swimming speed of diabetes mice, improved their spatial recognition and memory ability, and reduced hippocampal neuronal apoptosis, Nissl body injury, and p-tau217 protein deposition. In addition, through transmission electron microscopy (TEM), immunofluorescence, and Western blot (WB) detection, TZQD significantly improved the organelle damage of hippocampal neurons in diabetes mice, promoted the formation of autophagy lysosomes, increased the expression of autophagy-related proteins like Beclin 1, LC3II/LC3I, LAMP1, and LAMP2, reduced the level of P62 and promoted autophagy flow, which, however, were all significantly weakened by 3 MA. Meanwhile, TZQD regulated the expressions of AMPK/mTOR pathway proteins. In vitro experimental study results showed that TZQD can regulate the expression ratio of p-AMPK/AMPK alpha 1 and p-mTOR/mTOR in HT22 cells under high glucose conditions and improved the morphology and vitality of HT22 cells. By employing techniques such as monodansylcadaverine (MDC) staining, Lysosomal red fluorescent probe staining, and Annexin V-FITC/PI double staining, the investigation revealed that TZQD administration resulted in enhanced autophagosome formation, preservation of a lysosomal acidic milieu, and consequent mitigation of HT22 cell apoptosis under high glucose conditions.

CONCLUSIONS

TZQD can regulate the AMPK/mTOR pathway to activate autophagy to attenuate hippocampal neuronal apoptosis, thereby protecting cognitive function in diabetic mice.

Analysis of bone metabolic alterations linked with osteoporosis progression in type 2 diabetic db/db mice

Type 2 diabetes (T2D) is a common chronic disease, characterized by persistent hyperglycemia and insulin resistance. This disorder is associated with decreased bone quality and an elevated risk of bone fractures. However, evidence on the relationship between systemic metabolic change and the development of type 2 diabetic osteoporosis (T2DOP) remains elusive. Herein, we investigate the changes of bone metabolites with bone loss in db/db mice (an animal model of T2DOP exhibited bone loss with age progression), and explore the potential metabolic mechanism underlying type 2 diabetes and osteoporosis. C57BKS male mice were distributed in four groups, consisting six mice in each group: 8w m/m, 24w m/m, 8w db/db and 24w db/db. Bone morphometric and biomechanical parameters of db/db mice were analyzed by micro-CT and materials tester, it was found that 24w db/db mice showed severe bone loss and decreased bone tissue hardness compared with misty/misty littermates. The tibia of misty/misty mice (8 weeks, 24 weeks) and db/db mice (8 weeks, 24 weeks) were screened for differential metabolites by UPLC-Orbitrap MS. Ninety-eight metabolites were identified (35 and 63 metabolites are associated with early staged and late staged, respectively), consisting of amino acids, fatty acyls, and nucleotides. Notably, fatty acyls (such as 18-HEPE, 16(17)-EpDPE, arachidonic acid) and glycerophospholipids (such as phosphocholines (PC) (O-10:1(9E)/0:0), PC (O-16:1(9E)/0:0) [U] and phosphatidylethanolamines (PE) (P-16:0/0:0)) were significantly increased, and metabolites of amino acid pathway (such as l-glutamine, proline, phenylalanine) showed a downregulation trend. Dysregulation of lipid and glutathione pathways is the major contributor to progression of T2DOP in C57BKS mice.

Neuroprotective effect of salidroside on hippocampal neurons in diabetic mice via PI3K/Akt/GSK-3β signaling pathway

BACKGROUND

Diabetic encephalopathy is manifested by cognitive dysfunction. Salidroside, a nature compound isolated from Rhodiola rosea L, has the effects of anti-inflammatory and antioxidant, hypoglycemic and lipid-lowering, improving insulin resistance, inhibiting cell apoptosis, and protecting neurons. However, the mechanism by which salidroside alleviates neuronal degeneration and improves learning and memory impairment in diabetic mice remains unclear.

OBJECTIVE

To investigate the effects and mechanisms of salidroside on hippocampal neurons in streptozotocin-induced diabetic mice.

MATERIALS AND METHODS

C57BL/6 mice were randomly divided into 4 groups to receive either sham (control group (CON)), diabetes mellitus (diabetes group (DM)), diabetes mellitus + salidroside (salidroside group (DM + SAL)), and diabetes mellitus + salidroside + phosphatidylinositol 3-kinase (PI3K) inhibitor LY294002 (diabetes mellitus + salidroside + LY294002 group (DM + SAL + LY294002)). After 12 weeks of diabetes onset, the cognitive behaviors were tested using Morris water maze. The number of hippocampal neurons was detected by Nissl staining. The expressions of PI3K, p-PI3K, Akt, p-Akt, GSK-3β, p-GSK-3β, cleaved caspase-3, caspase-3, Bax, Bcl-2, MAP2, and SYN in the hippocampus were detected by Western blot. Moreover, the expression of MAP2 and SYN in the hippocampus was further confirmed by immunofluorescence staining.

RESULTS

Salidroside increased the time of diabetic mice in the platform quadrant and reduced the escape latency of diabetic mice. Salidroside also increased the expression of p-PI3K, p-Akt, p-GSK-3β, MAP2, SYN, Bcl-2, while suppressed the expression of cleaved caspase-3, caspase3, and Bax in the DM + SAL group compared with the DM group (P < 0.05). The Nissl staining showed that the number of hippocampus neurons in the DM + SAL group was increased with the intact, compact, and regular arrangement, compared with the DM groups (P < 0.05). Interestingly, the protective effects of salidroside on diabetic cognitive dysfunction, hippocampal morphological alterations, and protein expressions were abolished by inhibition of PI3K with LY294002.

CONCLUSIONS

Salidroside exerts neuroprotective properties in diabetic cognitive dysfunction partly via activating the PI3K/Akt/GSK-3β signaling pathway.

Feature-Based Molecular Networking Facilitates the Comprehensive Identification of Differential Metabolites in Diabetic Cognitive Dysfunction Rats

Cognitive dysfunction is a frequent complication of type 2 diabetes mellitus (T2DM), usually accompanied by metabolic disorders. However, the metabolic changes in diabetic cognitive dysfunction (DCD) patients, especially compared to T2DM groups, are not fully understood. Due to the subtle differences in metabolic alterations between DCD groups and T2DM groups, the comprehensive detection of the untargeted metabolic profiles of hippocampus and urine samples of rats was conducted by LC-MS, considering the different ionization modes and polarities of the examined compounds, and feature-based molecular networking (FBMN) was performed to help identify differential metabolites from a comprehensive perspective in this study. In addition, an association analysis of the differential metabolites in hippocampus and urine was conducted by the O2PLS model. Finally, a total of 71 hippocampal tissue differential metabolites and 179 urine differential metabolites were identified. The pathway enrichment results showed that glutamine and glutamate metabolism, alanine, aspartate, and glutamate metabolism, glycerol phospholipid metabolism, TCA cycle, and arginine biosynthesis in the hippocampus of DCD animals were changed. Seven metabolites (AUC > 0.9) in urine appeared as key differential metabolites that might reflect metabolic changes in the target tissue of DCD rats. This study showed that FBMN facilitated the comprehensive identification of differential metabolites in DCD rats. The differential metabolites may suggest an underlying DCD and be considered as potential biomarkers for DCD. Large samples and clinical experiments are needed for the subsequent elucidation of the possible mechanisms leading to these alterations and the verification of potential biomarkers.

Characterization of Gut Microbiota Compositions along the Intestinal Tract in CD163/pAPN Double Knockout Piglets and Their Potential Roles in Iron Absorption

The gut microbiota is known to play a role in regulating host metabolism, yet the mechanisms underlying this regulation are not well elucidated. Our study aimed to characterize the differences in gut microbiota compositions and their roles in iron absorption between wild-type (WT) and CD163/pAPN double-gene-knockout (DKO) weaned piglets. A total of 58 samples along the entire digestive tract were analyzed for microbial community using 16S rRNA gene sequencing. The colonic microbiota and their metabolites were determined by metagenomic sequencing and untargeted liquid chromatography-mass spectrometry (LC-MS), respectively. Our results showed that no alterations in microbial community structure and composition were observed between DKO and WT weaned piglets, with the exception of colonic microbiota. Interestingly, the DKO piglets had selectively increased the relative abundance of the Leeia genus belonging to the Neisseriaceae family and decreased the Ruminococcaceae_UCG_014 genus abundance. Functional capacity analysis showed that organic acid metabolism was enriched in the colon in DKO piglets. In addition, the DKO piglets showed increased iron levels in important tissues compared with WT piglets without any pathological changes. Pearson's correlation coefficient indicated that the specific bacteria such as Leeia and Ruminococcaceae_UCG_014 genus played a key role in host iron absorption. Moreover, the iron levels had significantly (P < 0.05) positive correlation with microbial metabolites, particularly carboxylic acids and their derivatives, which might increase iron absorption by preventing iron precipitation. Overall, this study reveals an interaction between colonic microbiota and host metabolism and has potential significance for alleviating piglet iron deficiency. IMPORTANCE Iron deficiency is a major risk factor for iron deficiency anemia, which is among the most common nutritional disorders in piglets. However, it remains unclear how the gut microbiota interacts with host iron absorption. The current report provides the first insight into iron absorption-microbiome connection in CD163/pAPN double knockout piglets. The present results showed that carboxylic acids and their derivatives contributed to the absorption of nonheme iron by preventing ferric iron precipitation.

Precision Medicine Approaches with Metabolomics and Artificial Intelligence

Recent technological innovations in the field of mass spectrometry have supported the use of metabolomics analysis for precision medicine. This growth has been allowed also by the application of algorithms to data analysis, including multivariate and machine learning methods, which are fundamental to managing large number of variables and samples. In the present review, we reported and discussed the application of artificial intelligence (AI) strategies for metabolomics data analysis. Particularly, we focused on widely used non-linear machine learning classifiers, such as ANN, random forest, and support vector machine (SVM) algorithms. A discussion of recent studies and research focused on disease classification, biomarker identification and early diagnosis is presented. Challenges in the implementation of metabolomics–AI systems, limitations thereof and recent tools were also discussed.

Zi Shen Wan Fang Attenuates Neuroinflammation and Cognitive Function Via Remodeling the Gut Microbiota in Diabetes-Induced Cognitive Impairment Mice

Background: Cognitive dysfunction is a critical complication of diabetes mellitus, and there are still no clinically approved drugs. Zi Shen Wan Fang (ZSWF) is an optimized prescription composed of Anemarrhenae Rhizoma, Phellodendri Chinensis Cortex, and Cistanches Herba. The purpose of this study is to investigate the effect of ZSWF on DCI and explore its mechanism from the perspective of maintaining intestinal microbial homeostasis in order to find an effective prescription for treating DCI.

Methods: The diabetes model was established by a high-fat diet combined with intraperitoneal injections of streptozotocin (STZ, 120 mg/kg) and the DCI model was screened by Morris water maze (MWM) after 8 weeks of continuous hyperglycemic stimulation. The DCI mice were randomly divided into the model group (DCI), the low- and high-ZSWF–dose groups (9.63 g/kg, 18.72 g/kg), the mixed antibiotic group (ABs), and the ZSWF combined with mixed antibiotic group (ZSWF + ABs). ZSWF was administered orally once a day for 8 weeks. Then, cognitive function was assessed using MWM, neuroinflammation and systemic inflammation were analyzed by enzyme-linked immunosorbent assay kits, intestinal barrier integrity was assessed by hematoxylin-eosin (HE) staining and Western blot and high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Furthermore, the alteration to intestinal flora was monitored by 16S rDNA sequencing.

Results: ZSWF restored cognitive function in DCI mice and reduced levels of proinflammatory cytokines such as IL-1β, IL-6, and TNF-α. Moreover, ZSWF protected the integrity of the intestinal barrier by increasing intestinal ZO-1 and occludin protein expression and decreasing urinary lactulose to mannitol ratio. In addition, ZSWF reshaped the imbalanced gut microbiota in DCI mice by reversing the abundance changes of a wide range of intestinal bacteria at the phyla and genus levels. In contrast, removing gut microbiota with antibiotics partially eliminated the effects of ZSWF on improving cognitive function and reducing inflammation, confirming the essential role of gut microbiota in the improvement of DCI by ZSWF.

Conclusion: ZSWF can reverse cognitive impairment in DCI mice by remolding the structure of destructed gut microbiota community, which is a potential Chinese medicine prescription for DCI treatment.

Zi Shen Wan Fang regulates kynurenine metabolism to alleviate diabetes-associated cognitive impairment via activating the skeletal muscle PGC1α-PPARα signaling

BACKGROUND

Cognitive dysfunction is commonly observed in diabetic patients, yet, the underlying mechanisms are obscure and there are no approved drugs. Skeletal muscle is a key pathological organ in diabetes. Evidence is accumulating that skeletal muscle and brain communication are important for cognitive, and kynurenine (KYN) metabolism is one of the mediators.

PURPOSE

This study aims to elucidate the mechanism of diabetes-induced cognitive impairment (DCI) from the perspective of skeletal muscle and brain communication, and to explore the therapeutic effect of Zi Shen Wan Fang (ZSWF, a optimized prescription consists of Anemarrhenae Rhizoma (Anemarrhena asphodeloides Bge.), Phellodendri Chinensis Cortex (Phellodendron chinense Schneid.) and Cistanches Herba (Cistanche deserticola Y.C.Ma)), in order to provide new strategies for the prevention and treatment of DCI and preliminarily explore valuable drugs.

METHODS

DCI was induced by intraperitoneal injection of streptozotocin (STZ) combined with a high-fat diet and treated with different dosage ZSWF extract by oral gavage for 8 weeks, once a day. Cognitive and skeletal muscle function was assessed, synaptic plasticity and L-type amino acid transporter (LAT1) was measured. KYN and its metabolites as well as metabolic enzymes in the hippocampus, peripheral blood and skeletal muscle were measured. Peroxisome proliferator-activated receptor-γ co-activator-1α (PGC-1α) and peroxisome proliferator-activated receptor α (PPARα) were measured in skeletal muscle.

RESULTS

Compared with healthy mice, DCI mice not only showed decreased cognitive function and abnormal skeletal muscle function, but also showed imbalance of KYN metabolism in brain, circulating blood and skeletal muscle. Fortunately, ZSWF administration for 8 weeks notably attenuated the cognitive function, synaptic plasticity and skeletal muscle function in DCI mice. Besides, ZSWF significantly attenuated KYN metabolism in brain, circulation and skeletal muscle of DCI mice. Furthermore, ZSWF activated PGC1α-PPARα in skeletal muscle of DCI mice.

CONCLUSIONS

These results indicate that abnormal PGC1α-PPARα signaling in skeletal muscle mediating KYN metabolism disorder is one of the pathological mechanisms of DCI, and ZSWF can reverse diabetes-induced cognitive impairment via activating skeletal muscle PGC1α-PPARα signaling to maintain KYN metabolism homeostasis.

Effect of Dietary Exposure to Acrylamide on Diabetes-Associated Cognitive Dysfunction from the Perspectives of Oxidative Damage, Neuroinflammation, and Metabolic Disorders

Acrylamide is a toxic compound that is produced widely during food processing, but whether the daily dietary consumption of acrylamide can impair the cognitive dysfunction in diabetic individuals and the potential underlying mechanisms are unknown. The aim of the present study was to observe the changes in cognitive and memory performance caused by chronic acrylamide exposure and to evaluate its influence on the brain morphology, oxidative damage, neuroinflammation, and brain metabolic disturbance. Goto-Kakizaki (GK) rats, a rat model of diabetes, were orally administered acrylamide at 1 mg/kg body weight for 8 weeks. The results of the novel object recognition and Y-maze tests showed that the consumption of acrylamide significantly aggravated diabetes-associated cognitive dysfunction in GK rats. Acrylamide increased reactive oxygen species and malondialdehyde formation and reduced glutathione levels, catalase, and total antioxidant capacity activity, which caused a succession of events associated with oxidative damage, including glial cell activation. After the activation of astrocytes and microglia, related cytokines, including interleukin-1β, interleukin-6, tumor necrosis factor-α, and lipopolysaccharide, were released, amyloid β-protein was accumulated, brain-derived neurotrophic factor was decreased, and the expression of caspase-3 and caspase-9 was increased, which aggravated neuroinflammation. Furthermore, there was perturbation of some important metabolites, including glutamic acid, citric acid, pyruvic acid, lactate, and sphinganine, and their related glucose, amino acid, and energy metabolism pathways in the brain. This work helps to demonstrate the effect of consumption of acrylamide in the daily diet on diabetes-associated cognitive dysfunction and its underlying mechanisms.

Cerebrospinal Fluid Amino Acid Metabolite Signatures of Diabetic Cognitive Dysfunction Based on Targeted Mass Spectrometry

BACKGROUND

Diabetic cognitive dysfunction (DCD) is one of severe diabetic complications and might develop to irreversible dementia. Early diagnosis and detection of DCD is significant for prevention and treatment.

OBJECTIVE

The main objective of this study was to investigate the amino acid profiles of rat with DCD in the cerebrospinal fluid (CSF) to distinguish the early specific biomarkers.

METHODS

In total, rats were assigned into control and model groups. Model was induced by intraperitoneal injection of streptozotocin. The Morris water maze (MWM) method was used to evaluate learning and memory in rats on the 13th week after the model established. CSF samples were collected via cisterna magna puncture at the 0th, 5th, 9th, and 13th week, and amino acids profiling of CSF samples were performed via ultra performance liquid chromatography multiple reaction monitoring mass spectrometry (UPLC-MRM-MS). The amino acid profile was processed through multivariate analysis to identify potential biomarkers, and the related metabolic pathways were analyzed by MetaboAnalyst 5.0.

RESULTS

Compared to the control group, the escape latency of the MWM was significantly prolonged in model group rats (p <  0.05). Different amino acid profiles were obtained between two groups. L-Alanine, L-Glutamine, L-Lysine, L-Serine, and L-Threonine were identified as potential biomarkers for DCD. These biomarkers are principally involved in glycine, serine, and threonine metabolism, aminoacyl-tRNA biosynthesis, alanine, aspartate, and glutamate metabolism, and glyoxylate and dicarboxylate metabolism.

CONCLUSION

There are amino acid biomarkers in the CSF of rat with DCD. The mechanism of DCD is related to those pathways, which provide help for the early diagnosis and treatment and mechanism research.

MS-IDF: A Software Tool for Nontargeted Identification of Endogenous Metabolites after Chemical Isotope Labeling Based on a Narrow Mass Defect Filter

Chemical isotope labeling liquid chromatography mass spectrometry (LC-MS) is an emerging metabolomic strategy for the quantification and characterization of small molecular compounds in biological samples. However, its subsequent data analysis is not straightforward due to a large amount of data produced and interference of biological matrices. In order to improve the efficiency of searching and identification of target endogenous metabolites, a new software tool for nontargeted metabolomics data processing called MS-IDF was developed based on the principle of a narrow mass defect filter. The developed tool provided two function modules, including IsoFinder and MDFinder. The IsoFinder function module applied a conventional peak extraction method by using a fixed mass differences between the heavy and light labels and by the alignment of chromatographic retention time (RT). On the other hand, MDFinder was designed to incorporate the accurate mass defect differences between or among stable isotopes in the peak extraction process. By setting an appropriate filter interval, the target metabolites can be efficiently screened out while eliminating interference. Notably, the present results showed that the efficiency in compound identification using the new MDFinder module was nearly doubled as compared to the conventional IsoFinder method (an increase from 259 to 423 compounds). The Matlab codes of the developed MS-IDF software are available from github at https://github.com/jydong2018/MS_IDF. Based on the MS-IDF software tool, a novel and effective approach from nontargeted to targeted metabolomics research was developed and applied to the exploration of potential primary amine biomarkers in patients with schizophrenia. With this approach, potential biomarkers, including N,N-dimethylglycine, S-adenosine-l-methionine, dl-homocysteine, and spermidine, were discovered.

Effects of Subcortical Atrophy and Alzheimer’s Pathology on Cognition in Elderly Type 2 Diabetes: The Alzheimer’s Disease Neuroimaging Initiative Study

Background

Subcortical atrophy and increased cerebral β-amyloid and tau deposition are linked to cognitive decline in type 2 diabetes. However, whether and how subcortical atrophy is related to Alzheimer’s pathology in diabetes remains unclear. This study therefore aimed to investigate subcortical structural alterations induced by diabetes and the relationship between subcortical alteration, Alzheimer’s pathology and cognition.

Methods

Participants were 150 patients with type 2 diabetes and 598 propensity score-matched controls without diabetes from the Alzheimer’s Disease Neuroimaging Initiative. All subjects underwent cognitive assessments, magnetic resonance imaging (MRI), and apolipoprotein E (ApoE) genotyping, with a subset that underwent amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) assays to determine cerebral β-amyloid deposition (n = 337) and CSF p-tau (n = 433). Subcortical structures were clustered into five modules based on Pearson’s correlation coefficients of volumes across all subjects: the ventricular system, the corpus callosum, the limbic system, the diencephalon, and the striatum. Using structural equation modeling (SEM), we investigated the relationships among type 2 diabetes, subcortical structural alterations, and AD pathology.

Results

Compared with the controls, the diabetic patients had significant reductions in the diencephalon and limbic system volumes; moreover, patients with longer disease duration (>6 years) had more severe volume deficit in the diencephalon. SEM suggested that type 2 diabetes, age, and the ApoE ε4 allele (ApoE-ε4) can affect cognition via reduced subcortical structure volumes (total effect: age > ApoE-ε4 > type 2 diabetes). Among them, age and ApoE-ε4 strongly contributed to AD pathology, while type 2 diabetes neither directly nor indirectly affected AD biomarkers.

Conclusion

Our study suggested the subcortical atrophy mediated the association of type 2 diabetes and cognitive decline. Although both type 2 diabetes and AD are correlated with subcortical neurodegeneration, type 2 diabetes have no direct or indirect effect on the cerebral amyloid deposition and CSF p-tau.

Multimodal brain imaging effect of "Adjust Zang-fu and Arouse Spirit" electroacupuncture on diabetic cognitive impairment: study protocol of a randomized, sham-controlled pilot trial

BACKGROUND

Diabetic cognitive impairment (DCI) is a serious chronic complication caused by diabetes. The pathogenesis of DCI is complex, but brain nerve injury and brain nerve cell apoptosis are important pathological changes. Multimodal brain imaging is one of the most important techniques to study the neural mechanism of the brain. For the clinical treatment of DCI, there is no effective targeted Western medicine and a lack of clear drug intervention methods. Therefore, there is an urgent need to find effective complementary and alternative methods and clarify their mechanism. This research seeks to explore the multimodal brain imaging effect of "Adjust Zang-fu and Arouse Spirit" electroacupuncture for DCI.

METHODS

This clinical research will be a randomized, sham-controlled pilot trial. Eligible participants will be randomly assigned to the intervention group (n = 60) and the control group (n = 30). The intervention group will be divided into the "Adjust Zang-fu and Arouse Spirit" electroacupuncture group (n = 30) and sham electroacupuncture group (n = 30). All participants will continue to receive routine hypoglycemic therapy. The treatment period is the same in both groups. The primary outcomes include functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), Montreal Cognitive Assessment Scale (MoCA), and Clinical Dementia Rating (CDR). The secondary outcomes include blood glucose and blood lipid tests, Instrumental Activities of Daily Living Scale (IADL), Hachinski Ischemic Scale (HIS), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS). Outcomes will be assessed at baseline and before and after treatment, and adverse events will be examined. Inter- and intragroup analyses will be performed.

DISCUSSION

This randomized controlled study, combined with multimodal brain imaging techniques and a clinical evaluation scale, was designed to explore the mechanism of "Adjust Zang-fu and Arouse Spirit" electroacupuncture in improving the central nervous system in DCI.

TRIAL REGISTRATION

Chinese Clinical Trial Registration ChiCTR2000040268 . Registered on 26 November 2020.

Acupuncture therapy and cognitive dysfunction in patients with type 2 diabetes: A protocol for systematic review

BACKGROUND

With the aging of society, the incidence of type 2 diabetes (T2DM) is increasing every year, and there is a clear correlation between T2DM and cognitive dysfunction. Acupuncture therapy has been widely used in the treatment of T2DM, but there is no systematic review on the treatment of T2DM associated with cognitive impairment. Therefore, this study aimed to conduct a meta-analysis of acupuncture in the treatment of T2DM with cognitive impairment to clarify its efficacy.

METHODS

A structured and systematic literature search will be conducted in the following databases up to April 26, 2021: PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science (WOS), China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), Chinese Scientific and Journal Database (VIP), and Wan Fang database (Wanfang). We will use the Review Manager 5.4 software provided by the Cochrane Collaborative Network for statistical analysis. We then assessed the quality and risk of the included studies and observed the outcome measures.

RESULTS

This meta-analysis further determined the beneficial effects of acupuncture on T2DM with cognitive impairment.

CONCLUSION

The purpose of this meta-analysis was to explore the effect of acupuncture on patients T2DM with and cognitive impairment patients, and provide more options for clinicians and patients to treat T2DM with cognitive impairment.

ETHICS AND DISSEMINATION

This systematics review will evaluate the efficacy and safety of acupuncture in the treatment of T2DM with cognitive impairment. Since all the data included were published, the systematic review did not require ethical approval.

REGISTRATION NUMBER

CRD42021245681.

Identification of Key Biomarkers and Immune Infiltration in Sciatic Nerve of Diabetic Neuropathy BKS-db/db Mice by Bioinformatics Analysis

Diabetic neuropathy (DN) is one of the chronic complications of diabetes which can cause severe harm to patients. In order to determine the key genes and pathways related to the pathogenesis of DN, we downloaded the microarray data set GSE27382 from Gene Expression Omnibus (GEO) and adopted bioinformatics methods for comprehensive analysis, including functional enrichment, construction of PPI networks, central genes screening, TFs-target interaction analysis, and evaluation of immune infiltration characteristics. Finally, we examined quantitative real- time PCR (qPCR) to validate the expression of hub genes. A total of 318 differentially expressed genes (DEGs) were identified, among which 125 upregulated DEGs were enriched in the mitotic nuclear division, extracellular region, immunoglobulin receptor binding, and p53 signaling pathway, while 193 downregulated DEGs were enriched in ion transport, membrane, synapse, sodium channel activity, and retrograde endocannabinoid signaling. GSEA plots showed that condensed nuclear chromosome kinetochore were the most significant enriched gene set positively correlated with the DN group. Importantly, we identified five central genes (Birc5, Bub1, Cdk1, Ccnb2, and Ccnb1), and KEGG pathway analysis showed that the five hub genes were focused on progesterone-mediated oocyte maturation, cell cycle, and p53 signaling pathway. The proportion of immune cells from DN tissue and normal group showed significant individual differences. In DN samples, T cells CD4 memory resting and dendritic cells resting accounted for a higher proportion, and macrophage M2 accounted for a lower proportion. In addition, all five central genes showed consistent correlation with immune cell infiltration levels. qPCR showed the same expression trend of five central genes as in our analysis. Our research identified key genes related to differential genes and immune infiltration related to the pathogenesis of DN and provided new diagnostic and potential therapeutic targets for DN.

The Role of Intestinal Dysbacteriosis Induced Arachidonic Acid Metabolism Disorder in Inflammaging in Atherosclerosis

Background

Aging induced chronic systemic inflammatory response is an important risk factor for atherosclerosis (AS) development; however, the detailed mechanism is yet to be elucidated.

Objective

To explore the underlying mechanism of how aging aggravates AS advancement.

Methods

A young (five-week-old, YM) and aged group (32-week-old, OM) male apoE^-/- mice with a high fat diet were used as models, and age-matched male wild-type C57BL/6J (WT) mice were used as controls. AS lesion size, serum lipid profile, cytokines, and gut microbiota-derived LPS were analyzed after 32 weeks of diet intervention. A correlation analysis between the 16S rRNA sequencing of the feces and serum metabolomics profiles was applied to examine the effect of their interactions on AS.

Results

ApoE^-/- mice developed severe atherosclerosis and inflammation in the aorta compared to the WT groups, and aged apoE^-/- mice suffered from a more severe AS lesion than their younger counterparts and had low-grade systemic inflammation. Furthermore, increased levels of serum LPS, decreased levels of SCFAs production, as well as dysfunction of the ileal mucosal barrier were detected in aged mice compared with their younger counterparts. There were significant differences in the intestinal flora composition among the four groups, and harmful bacteria such as Lachnospiraceae_FCS020, Ruminococcaceae_UCG-009, Acetatifactor, Lachnoclostridium and Lactobacillus_gasseri were significantly increased in the aged apoE^-/- mice compared with the other groups. Concurrently, metabolomics profiling revealed that components involved in the arachidonic acid (AA) metabolic pathway such as 20-HETE, PGF2α, arachidonic acid, and LTB4 were significantly higher in the aged AS group than in the other groups. This suggested that metabolic abnormalities and disorders of intestinal flora occurred in AS mice.

Conclusions

Aging not only altered the gut microbiome community but also substantially disturbed metabolic conditions. Our results confirm that AA metabolism is associated with the imbalance of the intestinal flora in the AS lesions of aged mice. These findings may offer new insights regarding the role of gut flora disorders and its consequent metabolite changed in inflammaging during AS development.

LC-MS-Based Untargeted Metabolomics Reveals Early Biomarkers in STZ-Induced Diabetic Rats With Cognitive Impairment

Diabetes in the elderly increases cognitive impairment, but the underlying mechanisms are still far from fully understood. A non-targeted metabolomics approach based on liquid chromatography-mass spectrometry (LC-MS) was performed to screen out the serum biomarkers of diabetic mild cognitive impairment (DMMCI) in rats. Total 48 SD rats were divided into three groups, Normal control (NC) group, high-fat diet (HFD) fed group and type 2 diabetes mellitus (T2DM) group. The T2DM rat model was induced by intraperitoneal administration of streptozotocin (STZ, 35 mg/kg) after 6 weeks of high-fat diet (HFD) feeding. Then each group was further divided into 4-week and 8-week subgroups, which were calculated from the time point of T2DM rat model establishment. The novel object recognition test (NORT) and the Morris water maze (MWM) method were used to evaluate the cognitive deficits in all groups. Compared to the NC-8w and HFD-8w groups, both NOR and MWM tests indicated significant cognitive dysfunction in the T2DM-8w group, which could be used as an animal model of DMMCI. Serum was ultimately collected from the inferior vena cava after laparotomy. Metabolic profiling analysis was conducted using ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) technology. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to verify the stability of the model. According to variable importance in the project (VIP > 1) and the p-value of t-test (P < 0.05) obtained by the OPLS-DA model, the metabolites with significant differences were screened out as potential biomarkers. In total, we identified 94 differentially expressed (44 up-regulated and 50 down-regulated) endogenous metabolites. The 10 top up-regulated and 10 top down-regulated potential biomarkers were screened according to the FDR significance. These biomarkers by pathway topology analysis were primarily involved in the metabolism of sphingolipid (SP) metabolism, tryptophan (Trp) metabolism, Glycerophospholipid (GP) metabolism, etc. Besides, SP metabolism, Trp metabolism and GP metabolism mainly belonging to the lipid metabolism showed marked perturbations over DMMCI and may contribute to the development of disease. Taken collectively, our results revealed that T2DM could cause cognitive impairment by affecting a variety of metabolic pathways especially lipid metabolism. Besides, serum PE, PC, L-Trp, and S1P may be used as the most critical biomarkers for the early diagnosis of DMMCI.

Testosterone deficiency accelerates early stage atherosclerosis in miniature pigs fed a high-fat and high-cholesterol diet: urine 1H NMR metabolomics targeted analysis

To gain insights into the role of testosterone in the development of atherosclerosis and its related metabolic pathways, we applied a proton nuclear magnetic resonance (¹H NMR)-based metabolomics approach to investigate urine metabolic profiles in miniature pigs fed a high-fat and high-cholesterol (HFC) diet among intact male pigs (IM), castrated male pigs (CM) and castrated male pigs with testosterone replacement (CMT). Our results showed that testosterone deficiency significantly increased atherosclerotic lesion areas, intima-media thickness, as well as serum lipid levels in the CM pigs. Moreover, seventeen significantly changed metabolites were identified in both IM vs. CM and CMT vs. CM groups. Among these, seven were shared between the two comparative groups and were all significantly reduced in the urine of the CM group but rescued in the CMT group. In addition, the correlation analysis demonstrated that several metabolites, including niacinamide, myo-inositol, choline and 3-hydroxyisovalerate, were negatively correlated with atherosclerotic lesion areas. Our study demonstrated that testosterone deficiency accelerated early AS formation in HFC diet-fed pigs, which involved several metabolites predominantly related to lipid metabolism, inflammation, oxidative stress and endothelial disorders. Our results reveal potential pathways in the pathogenesis of atherosclerosis caused by testosterone deficiency and HFC diet.

The total flavonoids from Selaginella tamariscina (beauv.) Spring improve glucose and lipid metabolism in db/db mice

Objectives

This study aimed to investigate the glucose and lipid metabolism improving effect of the total flavonoids from Selaginella tamariscina (Beauv.) Spring (TFST) on db/db mice, and to study its mechanism of action.

Materials and Methods

The db/db mice were divided into 5 groups: the normal group (NC), the diabetic group (DM), the gliclazide group (GZ), the DM+TFST (110 mg/kg), and the DM+TFST (220 mg/kg). The body weight, blood glucose, INS, GC, TC, TG, LDL, and HDL were detected. HE staining was used to observe the liver and pancreas. Urine was tested by UPLC-QTOF-MS to study the metabolic differences of each group, coupled with SIMCA-P13.0 for PCA and OPLS-DA analysis, to identify potential biomarkers, find the metabolic pathway. Western blot was used to examine liver tissue of mice for studying effect of TFST on the PPAR-γ/PI3K/GLU4 pathway.

Results

TFST can reduce the weight and levels of TC, TG, and LDL-C, increase the level of GC in blood, and reduce the fat accumulation and inflammation in the liver, and repair the islet cell. 13 biomarkers were identified, they are mainly involved in amino acid metabolism, and purine and pyrimidine metabolism. The results of Western blot show TFST can improve the utilization rate of GLU4 by regulating PPAR-γ and PI3K expression in the liver of db/db mice.

Conclusion

TFST can improve glucose and lipid metabolism of DM, which relates to regulation of the PPAR-γ/PI3K/GLU4 signaling pathway, and affect the amino acid metabolism, purine, and pyrimidine metabolism.

Non-invasive urinary metabolomics reveals metabolic profiling of polycystic ovary syndrome and its subtypes

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder, which affects 4-10 % women of reproductive age. Though accumulating scientific evidence, its pathogenesis remains unclear. In the current study, metabolic profiling as well as diagnostic biomarkers for different phenotypes of PCOS was investigated using non-invasive urinary GCMS based metabolomics. A total of 371 subjects were recruited for the study. They constituted the following groups: healthy women, those with hyperandrogenism (HA), women with insulin-resistance (IR) in PCOS. Two cross-comparisons with PCOS were performed to characterize metabolic disturbances. A total of 23 differential metabolites were found. The altered metabolic pathways included glyoxylate and dicarboxylate metabolism, pentose and glucuronate interconversions, and citrate cycle and butanoate metabolism. For differential diagnosis, a panel consisting of 9 biomarkers was found from the comparison of PCOS from healthy subjects. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.8461 in the discovery phase. Predictive value of 89.17 % was found in the validation set. Besides, a panel of 8 biomarkers was discovered from PCOS with HA vs IR. The AUC for 8-biomarker panel was 0.8363, and a panel of clinical markers (homeostasis model assessment-insulin resistance and free androgen index) had 0.8327 in AUC. While these metabolites combined with clinical markers reached 0.9065 in AUC from the discovery phase, and 93.18 % in predictive value from the validation set. The result showed that differences of small-molecule metabolites in urine may reflect underlying pathogenesis of PCOS and serve as biomarkers for complementary diagnosis of the different phenotypes of PCOS.

A susceptibility biomarker identification strategy based on significantly differentially expressed ceRNA triplets for ischemic cardiomyopathy

Ischemic cardiomyopathy (ICM) is a common human heart disease that causes death. No effective biomarkers for ICM could be found in existing databases, which is detrimental to the in-depth study of this disease. In the present study, ICM susceptibility biomarkers were identified using a proposed strategy based on RNA-Seq and miRNA-Seq data of ICM and normal samples. Significantly differentially expressed competing endogenous RNA (ceRNA) triplets were constructed using permutation tests and differentially expressed mRNAs, miRNAs and lncRNAs. Candidate ICM susceptible genes were screened out as differentially expressed genes in significantly differentially expressed ceRNA triplets enriched in ICM-related functional classes. Finally, eight ICM susceptibility genes and their significantly correlated lncRNAs with high classification accuracy were identified as ICM susceptibility biomarkers. These biomarkers would contribute to the diagnosis and treatment of ICM. The proposed strategy could be extended to other complex diseases without disease biomarkers in public databases.

Assessment of human plasma and urine sample preparation for reproducible and high-throughput UHPLC-MS clinical metabolic phenotyping

In this study we assess multiple sample preparation methods for UHPLC-MS metabolic phenotyping analysis of human urine and plasma. All methods are discussed in terms of metabolite and lipid coverage and reproducibility.

Assessing the Effectiveness of Direct Data Merging Strategy in Long-Term and Large-Scale Pharmacometabonomics

Because of the extended period of clinic data collection and huge size of analyzed samples, the long-term and large-scale pharmacometabonomics profiling is frequently encountered in the discovery of drug/target and the guidance of personalized medicine. So far, integration of the results (ReIn) from multiple experiments in a large-scale metabolomic profiling has become a widely used strategy for enhancing the reliability and robustness of analytical results, and the strategy of direct data merging (DiMe) among experiments is also proposed to increase statistical power, reduce experimental bias, enhance reproducibility and improve overall biological understanding. However, compared with the ReIn, the DiMe has not yet been widely adopted in current metabolomics studies, due to the difficulty in removing unwanted variations and the inexistence of prior knowledges on the performance of the available merging methods. It is therefore urgently needed to clarify whether DiMe can enhance the performance of metabolic profiling or not. Herein, the performance of DiMe on 4 pairs of benchmark datasets was comprehensively assessed by multiple criteria (classification capacity, robustness and false discovery rate). As a result, integration/merging-based strategies (ReIn and DiMe) were found to perform better under all criteria than those strategies based on single experiment. Moreover, DiMe was discovered to outperform ReIn in classification capacity and robustness, while the ReIn showed superior capacity in controlling false discovery rate. In conclusion, these findings provided valuable guidance to the selection of suitable analytical strategy for current metabolomics.

Biomarker Discovery for Immunotherapy of Pituitary Adenomas: Enhanced Robustness and Prediction Ability by Modern Computational Tools

Pituitary adenoma (PA) is prevalent in the general population. Due to its severe complications and aggressive infiltration into the surrounding brain structure, the effective management of PA is required. Till now, no drug has been approved for treating non-functional PA, and the removal of cancerous cells from the pituitary is still under experimental investigation. Due to its superior specificity and safety profile, immunotherapy stands as one of the most promising strategies for dealing with PA refractory to the standard treatment, and various studies have been carried out to discover immune-related gene markers as target candidates. However, the lists of gene markers identified among different studies are reported to be highly inconsistent because of the greatly limited number of samples analyzed in each study. It is thus essential to substantially enlarge the sample size and comprehensively assess the robustness of the identified immune-related gene markers. Herein, a novel strategy of direct data integration (DDI) was proposed to combine available PA microarray datasets, which significantly enlarged the sample size. First, the robustness of the gene markers identified by DDI strategy was found to be substantially enhanced compared with that of previous studies. Then, the DDI of all reported PA-related microarray datasets were conducted to achieve a comprehensive identification of PA gene markers, and 66 immune-related genes were discovered as target candidates for PA immunotherapy. Finally, based on the analysis of human protein⁻protein interaction network, some promising target candidates (GAL, LMO4, STAT3, PD-L1, TGFB and TGFBR3) were proposed for PA immunotherapy. The strategy proposed together with the immune-related markers identified in this study provided a useful guidance for the development of novel immunotherapy for PA.

Metabonomics of d-glucaro-1,4-lactone in preventing diethylnitrosamine-induced liver cancer in rats

CONTEXT

d-Glucaro-1,4-lactone (1,4-GL) exists in many vegetables and fruits. Metabonomics has not been used to investigate the role of 1,4-GL in preventing liver cancer.

OBJECTIVE

The pharmacological effects and metabolite alterations of 1,4-GL on the prevention of diethylnitrosamine (DEN)-induced liver cancer were investigated.

MATERIALS AND METHODS

Ten healthy Sprague-Dawley rats served as control and 46 were used to establish rat liver cancer model. ¹HNMR-based metabonomics was used to compare the effects of oral 1,4-GL (50 mg/kg) in liver cancer rats (n = 26) after 10 consecutive weeks of intervention. The amino acids in rat serum were quantified by HPLC-UV, and the changes in Fischer's ratio were calculated.

RESULTS

The 20-week survival rate of DEN-induced liver cancer rats administered with oral 1,4-GL was increased from 45.0 to 70.0% with reduced carcinogenesis of the liver and significantly lowered serum α-fetoprotein level (14.28 ± 2.89 ng/mL vs. 18.56 ± 4.65 ng/mL, p = 0.012). The serum levels of leucine, valine, 3-hydroxybutyrate, lactate, acetate and glutamine in the DEN + 1,4-GL group returned to normal levels compared with those of the DEN group on week 20. Fischer's ratio in the rat serum of DEN group was 1.62 ± 0.21, which was significantly lower than that in healthy rats (2.3 ± 0.12). However, Fischer's ratio increased to 1.89 ± 0.22 in the DEN + 1,4-GL group.

DISCUSSION AND CONCLUSIONS

1,4-GL exerted positive effects on liver carcinogenesis in rats by pathological examination and metabonomic analysis. Its mechanism may be related to the restoration of amino acid and energy metabolism.

Meloxicam Improves Cognitive Impairment of Diabetic Rats through COX2-PGE2-EPs-cAMP/pPKA Pathway

Diabetics often face greater risk of cognitive impairment than nondiabetics. However, how to prevent this disease is still unconfirmed. In this study, we investigated the potential protection and mechanism of meloxicam on cognitive impairment in diabetic rats. The diabetic rat model was established with a high-fat diet and a small dose of streptozotocin (40 mg/kg). The changes of spatial learning and memory, histopathology, and the protein expressions of amyloid protein precursor (APP) and β-amyloid (Aβ) indicated that diabetic rats had neuronal injury and cognitive impairment. Tumor necrosis factor α (TNFα), interleukin 6 (IL-6), C reactive protein (CRP) and prostaglandin E2 (PGE2) levels, and microglial cell number were significantly increased in the diabetic rat brain. Meanwhile, the protein expressions of APP, Aβ, cyclooxygenases2 (COX2), E-type prostanoid recptors 1 (EP1) and EP2, and the level of cyclic adenosine monophosphate (cAMP) were significantly increased, while the protein expressions of EP3 and phosphorylated protein kinase A (pPKA) were significantly decreased in the diabetic rat hippocampus and cortex. However, the EP4 protein expression had no significant changes. Meloxicam significantly improved neuronal injury and cognitive impairment, and significantly decreased inflammatory cytokines levels. Meloxicam also significantly decreased the protein expressions of APP, Aβ, COX2, EP1 and EP2, and the level of cAMP and significantly increased the EP3 and pPKA protein expressions in rat hippocampus and cortex. However, meloxicam did not significantly influence the levels of blood glucose, lipids, and insulin of rats. Our results suggest that meloxicam could significantly protect diabetic rats from cognitive impairment via a mechanism that may be associated with rebalancing the COX2-PGE2-EPs-cAMP/PKA pathway.

High-pressure photon ionization time-of-flight mass spectrometry combined with dynamic purge-injection for rapid analysis of volatile metabolites in urine

Small molecule metabolites are widely used as biomarkers in the research field of metabolomics for disease diagnosis and exposure assessment. As a readily available biofluid containing plenty of volatile organic metabolites (VOMs), urine is ideal for non-invasive metabolomic analysis; however, there is still lack of rapid analysis method for VOMs in urine. Here we report a kind of rapid method for urine analysis by employing high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) combined with dynamic purge-injection. Various types of metabolites, such as ketones, alcohols, acids, sulfides, pyrroles and amines were detected directly by simple acidification or alkalization of urines. It is noteworthy that nitrogen-containing compounds, especially polar amines, could be ultrasensitively measured without any derivatization. The analytical capability of the direct HPPI-MS technique was demonstrated by analyzing five valuable metabolites, i.e., toluene, 2,5-dimethylpyrrole, trimethlyamine, styrene, and p-xylene, which exhibited relatively low limits of detection, wide linear range and satisfactory repeatability. Being highly sensitive and humidity-friendly, the whole analytical procedure is easily operated in less than 6 min. Interestingly, a new biomarker 2,5-dimethylpyrrole was exclusively found in the smoker's urine sample besides toluene. The work presents a novel tool for rapid nontarget disease biomarkers screening or target monitoring of specific compounds through the investigation of volatile metabolites in urine.