The microbiome compositional and functional differences between rectal mucosa and feces.

In recent years, most studies on the gut microbiome have primarily focused on feces samples, leaving the microbial communities in the intestinal mucosa relatively unexplored. To address this gap, our study employed shotgun metagenomics to analyze the microbial compositions in normal rectal mucosa and matched feces from 20 patients with colonic polyps. Our findings revealed a pronounced distinction of the microbial communities between these two sample sets. Compared with feces, the mucosal microbiome contains fewer genera, with Burkholderia being the most discriminating genus between feces and mucosa, highlighting its significant influence on the mucosa. Furthermore, based on the microbial classification and KEGG Orthology (KO) annotation results, we explored the association between rectal mucosal microbiota and factors such as age, gender, BMI, and polyp risk level. Notably, we identified novel biomarkers for these phenotypes, such as Clostridium ramosum and Enterobacter cloacae in age. The mucosal microbiota showed an enrichment of KO pathways related to sugar transport and short chain fatty acid metabolism. Our comprehensive approach not only bridges the knowledge gap regarding the microbial community in the rectal mucosa but also underscores the complexity and specificity of microbial interactions within the human gut, particularly in the Chinese population. IMPORTANCE: This study presents a system-level map of the differences between feces and rectal mucosal microbial communities in samples with colorectal cancer risk. It reveals the unique microecological characteristics of rectal mucosa and its potential influence on health. Additionally, it provides novel insights into the role of the gut microbiome in the pathogenesis of colorectal cancer and paves the way for the development of new prevention and treatment strategies.

Metagenomic analysis of the effects of salinity on microbial community and functional gene diversity in glacial meltwater estuary, Ny-Alesund, Arctic.

Due to the inflow of meltwater from the Midre Lovénbreen glacier upstream of Kongsfjorden, the nutrient concentration of Kongsfjorden change from the estuary to the interior of the fjord. Our objective was to explore the changes in bacterial community structure and metabolism-related genes from the estuary to fjord by metagenomic analysis. Our data indicate that glacial meltwater input has altered the physicochemical properties of the fjords, with a significant effect, in particular, on fjords salinity, thus altering the relative abundance of some specific bacterial groups. In addition, we suggest that the salinity of a fjord is an important factor affecting the abundance of genes associated with the nitrogen and sulfur cycles in the fjord. Changes in salinity may affect the relative abundance of microbial populations that carry metabolic genes, thus affecting the relative abundance of genes associated with the nitrogen and sulfur cycles.

Maternal serum amino acids and hydroxylated sphingomyelins at pregnancy are associated with anxiety symptoms during pregnancy and throughout the first year after delivery.

BACKGROUND: Studies suggest an interplay between maternal metabolome and mental health. OBJECTIVE: We investigated the association of maternal serum metabolome at pregnancy with anxiety scores during pregnancy and throughout the first year postpartum. METHODS: A prospective cohort of Brazilian women collected 119 serum metabolome at pregnancy (28-38 weeks) and anxiety scores measured by the State-Trait Anxiety Inventory (STAI) at pregnancy (n = 118), 1 (n = 83), 6 (n = 68), and 12 (n = 57) months postpartum. Targeted metabolomics quantified metabolites belonging to amino acids (AA), biogenic amines/amino acid-related compounds, acylcarnitines, lysophosphatidylcholines, diacyl phosphatidylcholines, alkyl:acyl phosphatidylcholines, non-hydroxylated and hydroxylated sphingomyelins [SM(OH)], and hexoses classes. Linear mixed-effect models were used to evaluate the association of metabolites and STAI scores. Hierarchical clustering and principal component analyses were employed to identify clusters and metabolites, which drove their main differences. Multiple comparison-adjusted p-values (q-value) ≤ 0.05 were considered significant. RESULTS: AA (ß = -1.44) and SM(OH) (ß = -1.49) classes showed an association with STAI scores trajectory (q-value = 0.047). Two clusters were identified based on these classes. Women in cluster 2 had decreased AA and SM(OH) concentrations and higher STAI scores (worse symptoms) trajectory (ß = 2.28; p-value = 0.041). Isoleucine, leucine, valine, SM(OH) 22:1, 22:2, and 24:1 drove the main differences between the clusters. LIMITATIONS: The target semiquantitative metabolome analysis and small sample size limited our conclusions. CONCLUSIONS: Our results suggest that AA and SM(OH) during pregnancy play a role in anxiety symptoms throughout the first year postpartum.

Complexation of histone deacetylase inhibitor belinostat to Cu(II) prevents premature metabolic inactivation in vitro and demonstrates potent anti-cancer activity in vitro and ex vivo in colon cancer.

PURPOSE: The histone deacetylase inhibitor (HDACi), belinostat, has had limited therapeutic impact in solid tumors, such as colon cancer, due to its poor metabolic stability. Here we evaluated a novel belinostat prodrug, copper-bis-belinostat (Cubisbel), in vitro and ex vivo, designed to overcome the pharmacokinetic challenges of belinostat. METHODS: The in vitro metabolism of each HDACi was evaluated in human liver microsomes (HLMs) using mass spectrometry. Next, the effect of belinostat and Cubisbel on cell growth, HDAC activity, apoptosis and cell cycle was assessed in three colon cancer cell lines. Gene expression alterations induced by both HDACis were determined using RNA-Seq, followed by in silico analysis to identify master regulators (MRs) of differentially expressed genes (DEGs). The effect of both HDACis on the viability of colon cancer patient-derived tumor organoids (PDTOs) was also examined. RESULTS: Belinostat and Cubisbel significantly reduced colon cancer cell growth mediated through HDAC inhibition and apoptosis induction. Interestingly, the in vitro half-life of Cubisbel was significantly longer than belinostat. Belinostat and its Cu derivative commonly dysregulated numerous signalling and metabolic pathways while genes downregulated by Cubisbel were potentially controlled by VEGFA, ERBB2 and DUSP2 MRs. Treatment of colon cancer PDTOs with the HDACis resulted in a significant reduction in cell viability and downregulation of stem cell and proliferation markers. CONCLUSIONS: Complexation of belinostat to Cu(II) does not alter the HDAC activity of belinostat, but instead significantly enhances its metabolic stability in vitro and targets anti-cancer pathways by perturbing key MRs in colon cancer. Complexation of HDACis to a metal ion might improve the efficacy of clinically used HDACis in patients with colon cancer.

Magnetocardiography-based coronary artery disease severity assessment and localization using spatiotemporal features.

Objective.This study aimed to develop an automatic and accurate method for severity assessment and localization of coronary artery disease (CAD) based on an optically pumped magnetometer magnetocardiography (MCG) system.Approach.We proposed spatiotemporal features based on the MCG one-dimensional signals, including amplitude, correlation, local binary pattern, and shape features. To estimate the severity of CAD, we classified the stenosis as absence or mild, moderate, or severe cases and extracted a subset of features suitable for assessment. To localize CAD, we classified CAD groups according to the location of the stenosis, including the left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA), and separately extracted a subset of features suitable for determining the three CAD locations.Main results.For CAD severity assessment, a support vector machine (SVM) achieved the best result, with an accuracy of 75.1%, precision of 73.9%, sensitivity of 67.0%, specificity of 88.8%, F1-score of 69.8%, and area under the curve of 0.876. The highest accuracy and corresponding model for determining locations LAD, LCX, and RCA were 94.3% for the SVM, 84.4% for a discriminant analysis model, and 84.9% for the discriminant analysis model.Significance. The developed method enables the implementation of an automated system for severity assessment and localization of CAD. The amplitude and correlation features were key factors for severity assessment and localization. The proposed machine learning method can provide clinicians with an automatic and accurate diagnostic tool for interpreting MCG data related to CAD, possibly promoting clinical acceptance.

Impact of Lactation Stage on the Metabolite Composition of Bovine Milk.

Bovine milk is a nutrient-dense food and a major component of the human diet. Therefore, understanding the factors that impact its composition is of great importance. Applications of metabolomics provide in-depth analysis of the metabolite composition of milk. The objective of this research was to examine the impact of lactation stage on bovine milk metabolite levels. Metabolomic analysis of bovine milk powder samples across lactation (N = 18) was performed using nuclear magnetic resonance (1H-NMR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Forty-one metabolites were identified and quantified in the 1H-NMR spectra. Statistical analysis revealed that 17 metabolites were significantly different across lactation stages (FDR < 0.05), of which the majority had higher levels in early lactation. In total, 491 metabolites were measured using LC-MS/MS, of which 269 had significantly different levels across lactation (FDR < 0.05). Compound classes significantly affected by lactation stage included phosphatidylcholines (59%) and triglycerides (64%), of which 100% of phosphatidylcholines and 61% of triglycerides increased from early lactation onwards. Our study demonstrates significant differences in metabolites across the stages of lactation, with early-lactation milk having a distinct metabolomic profile. More research is warranted to further explore these compositional differences to inform animal feeding practice.

Metabolomic based approach to identify biomarkers of broccoli intake.

It is well-established that consumption of cruciferous and brassica vegetables has a correlation with reduced rates of many negative health outcomes. There is an increased interest in identifying food intake biomarkers to address limitations related to self-reported dietary assessment. The study aims to identify biomarkers of broccoli intake using metabolomic approaches, examine the dose-response relationship, and predict the intake by multimarker panel. Eighteen volunteers consumed cooked broccoli in A-Diet Discovery study and fasting and postprandial urine samples were collected at 2, 4 and 24 hours. Subsequently the A-Diet Dose-response study was performed where volunteers consumed different portions of broccoli (49, 101 or 153 g) and urine samples were collected at the end of each intervention week. Urine samples were analysed by 1H-NMR and LC-MS. Multivariate data analysis and one-way ANOVA were performed to identify discriminating biomarkers. A panel of putative biomarkers was examined for its ability to predict intake through a multiMarker model. Multivariate analysis revealed discriminatory spectral regions between fasting and fed metabolic profiles. Subsequent time-series plots revealed multiple features increased in concentration following the consumption. Urinary S-methyl cysteine sulfoxide (SMCSO) increased as broccoli intake increased (0.17-0.24 µM per mOSM per kg, p < 0.001). Similarly from LC-MS data genipin, dihydro-ß-tubaic acid and sinapic acid increased with increasing portions of intake. A panel of 8 features displayed good ability to predict intake from biomarker data only. In conclusion, urinary SMCSO and several LC-MS features appeared as potentially promising biomarkers of broccoli consumption and demonstrated dose-response relationship. Future work should focus on validating these compounds as food intake biomarkers.

Glomerular filtration rate in patients with type 2 diabetes mellitus: is serum isthmin-1 level a possible link?

INTRODUCTION: Isthmin-1 (Ism-1) is a novel adipokine. However, little is known regarding the association between Ism-1 and type 2 diabetes mellitus (T2DM). This study aimed to investigate the relationship between serum Ism-1 levels and glomerular filtration rate (GFR) in patients with T2DM. RESEARCH DESIGN AND METHODS: A total of 209 patients with T2DM were recruited into this retrospective study. Clinical data were collected. Fasting blood samples were collected for serum Ism-1 testing using ELISA kits. Based on the estimated glomerular filtration rate (eGFR), participants were divided into the normal eGFR group (n=167) and the decreased eGFR group (n=42). The relationship between Ism-1 and eGFR was assessed using linear and binary logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was employed to examine the predictive efficacy of Ism-1 for distinguishing patients with eGFR <60 mL/min/1.73 m2. RESULTS: Compared with patients with normal eGFR, serum Ism-1 levels were increased in patients with decreased eGFR (p<0.001). Serum Ism-1 levels were negatively correlated with eGFR in patients with T2DM even after multiple adjustments (p<0.001). For each 0.1 ng/mL increment of Ism-1, the odds of having an eGFR <60 mL/min/1.73 m2 increased by 54.5% (OR=1.545; p<0.001) in patients with T2DM. ROC analysis showed that higher serum Ism-1 levels (>1.297 ng/mL) had predictive efficacy in patients with eGFR <60 mL/min/1.73 m2, with an area under the curve of 0.908. CONCLUSIONS: Serum Ism-1 levels were inversely associated with eGFR, and high Ism-1 levels may be used as a potential biomarker for predicting kidney function impairment in patients with T2DM.

Serum Isthmin-1 is negatively correlated with HDL-C in type 2 diabetes mellitus.

BACKGROUND: Isthmin-1 (Ism-1) is a newly identified insulin-like adipokine that increases glucose uptake by adipocytes and inhibits hepatic lipid synthesis. Recent studies have shown that Ism-1 can improve the metabolic disorders associated with type 2 diabetes mellitus (T2DM) and improve lipid metabolism. The classic function of high-density lipoprotein cholesterol (HDL-C) is to transport cholesterol from extra-hepatic tissues to the liver for metabolism. In contrast, disorders of lipid metabolism and inflammation are the leading causes of atherosclerosis (As). Atherosclerosis often manifests as loss of elasticity, lipid accumulation, fibrous tissue proliferation and calcium deposits in the affected arteries, eventually forming plaques. AIM: To illustrate the correlation between HDL-C and Ism-1 in T2DM, and the relationship between lipoprotein cholesterol and carotid plaque. METHODS: A total of 128 patients with T2DM were enrolled in the study and basic information was collected. HDL-C levels were measured chemically. Serum Ism-1 levels were measured using an enzyme-linked immunosorbent assay (ELISA). Linear regression analysis was used to assess the correlation between serum Ism-1 levels and HDL-C in patients with T2DM. Basic information was again collected from 226 patients with T2DM. Independent sample t-tests were performed to explore the relationship between carotid plaque formation and lipids. RESULTS: HDL-C was divided into four groups according to quartiles and there was a between-group difference in Ism-1 (p = 0.040). Multivariable linear regression showed a negative association between Ism-1 and HDL-C in T2DM (ß = -0.235, p < 0.001), even after adjusting for related factors (ß = -0.165, p = 0.009). Low-density lipoprotein cholesterol (LDL-C) and HDL-C showed significant differences between the carotid plaque group and the non-carotid plaque group (pLDL-C = 0.007, pHDL-C = 0.003). CONCLUSION: Serum Ism-1 and HDL-C are negatively correlated in T2DM. LDL-C is significantly higher in carotid plaque group than non-carotid plaque group, while HDL-C is significantly lower than in the non-carotid plaque group.

Study of Archaeal Diversity in the Arctic Meltwater Lake Region.

Two typical lakes formed from meltwater in the Ny-Ålesund area were taken as the study subjects in 2018. To investigate the archaeal community compositions of the two lakes, 16S rRNA genes from soil samples from the intertidal and subtidal zones of the two lakes were sequenced with high throughput. At the phylum level, the intertidal zone was dominated by Crenarchaeota and the subtidal zone was dominated by Halobacter; at the genus level, the intertidal zone was dominated by Nitrososphaeraceae_unclassified and Candidatus_Nitrocosmicus, while the subtidal zone was dominated by Methanoregula. The soil physicochemical factors pH, moisture content (MC), total organic carbon (TOC), total organic nitrogen (TON), nitrite nitrogen (NO2--N), and nitrate nitrogen (NO3--N) were significantly different in the intertidal and subtidal zones of the lake. By redundancy analysis, the results indicated that NH4+-N, SiO32--Si, MC, NO3--N, and NO2--N have had highly significant effects on the archaeal diversity and distribution. A weighted gene co-expression network analysis (WGCNA) was used to search for hub archaea associated with physicochemical factors. The results suggested that these physicochemical factors play important roles in the diversity and structure of the archaeal community at different sites by altering the abundance of certain hub archaea. In addition, Woesearchaeales was found to be the hub archaea genus at every site.

Biological light-weight materials: The endoskeletons of cephalopod mollusks.

Structural biological hard tissues fulfill diverse tasks: protection, defence, locomotion, structural support, reinforcement, buoyancy. The cephalopod mollusk Spirula spirula has a planspiral, endogastrically coiled, chambered, endoskeleton consisting of the main elements: shell-wall, septum, adapical-ridge, siphuncular-tube. The cephalopod mollusk Sepia officinalis has an oval, flattened, layered-cellular endoskeleton, formed of the main elements: dorsal-shield, wall/pillar, septum, siphuncular-zone. Both endoskeletons are light-weight buoyancy devices that enable transit through marine environments: vertical (S. spirula), horizontal (S. officinalis). Each skeletal element of the phragmocones has a specific morphology, component structure and organization. The conjunction of the different structural and compositional characteristics renders the evolved nature of the endoskeletons and facilitates for Spirula frequent migration from deep to shallow water and for Sepia coverage over large horizontal distances, without damage of the buoyancy device. Based on Electron-Backscatter-Diffraction (EBSD) measurements and TEM, FE-SEM, laser-confocal-microscopy imaging we highlight for each skeletal element of the endoskeleton its specific mineral/biopolymer hybrid nature and constituent arrangement. We demonstrate that a variety of crystal morphologies and biopolymer assemblies are needed for enabling the endoskeleton to act as a buoyancy device. We show that all organic components of the endoskeletons have the structure of cholesteric-liquid-crystals and indicate which feature of the skeletal element yields the necessary mechanical property to enable the endoskeleton to fulfill its function. We juxtapose structural, microstructural, texture characteristics and benefits of coiled and planar endoskeletons and discuss how morphometry tunes structural biomaterial function. Both mollusks use their endoskeleton for buoyancy regulation, live and move, however, in distinct marine environments.

Using a Metabotype Framework to Deliver Personalized Nutrition Improves Dietary Quality and Metabolic Health Parameters: A 12-Week Randomized Controlled Trial.

SCOPE: Effective strategies for tailoring dietary advice to individuals are urgently needed. The effectiveness of personalized nutrition advice delivered using a metabotype framework in improving dietary quality and metabolic health biomarkers compared to population-level advice is investigated. MATERIALS AND RESULTS: A 12-week parallel randomized controlled trial is performed with 107 healthy adults. Individuals in the personalized group are classified into metabotypes using four markers (triacylglycerol, high-density lipoprotein [HDL]-cholesterol, total cholesterol [TC], and glucose) and received dietary advice from decision tree algorithms containing metabotypes characteristics and individual traits. Individuals in the control group received generic dietary advice based on national guidelines. The personalized approach results in higher dietary quality assessed by the Alternate Mediterranean Diet Score (effect size [95% confidence interval, CI], 0.77 [0.07, 1.48], 12% versus 3% increase) and significantly lower concentrations of triacylglycerol (-0.17 [-0.28, -0.06] log10 mmol L-1 ), TC (-0.42 [-0.74, -0.10] mmol L-1 ), low-density lipoprotein (LDL)-cholesterol (-0.34, [-0.60, -0.09] mmol L-1 ), and lower triacylglycerol-glucose index (-0.40, [-0.67, -0.13]). Sixteen phosphatidylcholines and six lysophosphatidylcholines, predominately with chain lengths of 30-36 carbons, are lower in the personalized group. CONCLUSIONS: Personalized nutrition advice delivered using the metabotype framework is effective to improve dietary quality, which could result in reduced CVD risk, and metabolic heath biomarkers.

Energy Metabolism Is Altered in Radioresistant Rectal Cancer.

Resistance to neoadjuvant chemoradiation therapy is a significant clinical challenge in the management of rectal cancer. There is an unmet need to identify the underlying mechanisms of treatment resistance to enable the development of biomarkers predictive of response and novel treatment strategies to improve therapeutic response. In this study, an in vitro model of inherently radioresistant rectal cancer was identified and characterized to identify mechanisms underlying radioresistance in rectal cancer. Transcriptomic and functional analysis demonstrated significant alterations in multiple molecular pathways, including the cell cycle, DNA repair efficiency and upregulation of oxidative phosphorylation-related genes in radioresistant SW837 rectal cancer cells. Real-time metabolic profiling demonstrated decreased reliance on glycolysis and enhanced mitochondrial spare respiratory capacity in radioresistant SW837 cells when compared to radiosensitive HCT116 cells. Metabolomic profiling of pre-treatment serum samples from rectal cancer patients (n = 52) identified 16 metabolites significantly associated with subsequent pathological response to neoadjuvant chemoradiation therapy. Thirteen of these metabolites were also significantly associated with overall survival. This study demonstrates, for the first time, a role for metabolic reprograming in the radioresistance of rectal cancer in vitro and highlights a potential role for altered metabolites as novel circulating predictive markers of treatment response in rectal cancer patients.

Energy Metabolism, Metabolite, and Inflammatory Profiles in Human Ex Vivo Adipose Tissue Are Influenced by Obesity Status, Metabolic Dysfunction, and Treatment Regimes in Patients with Oesophageal Adenocarcinoma.

Oesophageal adenocarcinoma (OAC) is a poor prognosis cancer with limited response rates to current treatment modalities and has a strong link to obesity. To better elucidate the role of visceral adiposity in this disease state, a full metabolic profile combined with analysis of secreted pro-inflammatory cytokines, metabolites, and lipid profiles were assessed in human ex vivo adipose tissue explants from obese and non-obese OAC patients. These data were then related to extensive clinical data including obesity status, metabolic dysfunction, previous treatment exposure, and tumour regression grades. Real-time energy metabolism profiles were assessed using the seahorse technology. Adipose explant conditioned media was screened using multiplex ELISA to assess secreted levels of 54 pro-inflammatory mediators. Targeted secreted metabolite and lipid profiles were analysed using Ultra-High-Performance Liquid Chromatography coupled with Mass Spectrometry. Adipose tissue explants and matched clinical data were collected from OAC patients (n = 32). Compared to visceral fat from non-obese patients (n = 16), visceral fat explants from obese OAC patients (n = 16) had significantly elevated oxidative phosphorylation metabolism profiles and an increase in Eotaxin-3, IL-17A, IL-17D, IL-3, MCP-1, and MDC and altered secretions of glutamine associated metabolites. Adipose explants from patients with metabolic dysfunction correlated with increased oxidative phosphorylation metabolism, and increases in IL-5, IL-7, SAA, VEGF-C, triacylglycerides, and metabolites compared with metabolically healthy patients. Adipose explants generated from patients who had previously received neo-adjuvant chemotherapy (n = 14) showed elevated secretions of pro-inflammatory mediators, IL-12p40, IL-1α, IL-22, and TNF-ß and a decreased expression of triacylglycerides. Furthermore, decreased secreted levels of triacylglycerides were also observed in the adipose secretome of patients who received the chemotherapy-only regimen FLOT compared with patients who received no neo-adjuvant treatment or chemo-radiotherapy regimen CROSS. For those patients who showed the poorest response to currently available treatments, their adipose tissue was associated with higher glycolytic metabolism compared to patients who had good treatment responses. This study demonstrates that the adipose secretome in OAC patients is enriched with mediators that could prime the tumour microenvironment to aid tumour progression and attenuate responses to conventional cancer treatments, an effect which appears to be augmented by obesity and metabolic dysfunction and exposure to different treatment regimes.

Hypercapnia alters mitochondrial gene expression and acylcarnitine production in monocytes.

CO2 is produced during aerobic respiration. Normally, levels of CO2 in the blood are tightly regulated but pCO2 can rise (hypercapnia, pCO2 > 45 mmHg) in patients with lung diseases, for example, chronic obstructive pulmonary disease (COPD). Hypercapnia is a risk factor in COPD but may be of benefit in the context of destructive inflammation. The effects of CO2 per se, on transcription, independent of pH change are poorly understood and warrant further investigation. Here we elucidate the influence of hypercapnia on monocytes and macrophages through integration of state-of-the-art RNA-sequencing, metabolic and metabolomic approaches. THP-1 monocytes and interleukin 4-polarized primary murine macrophages were exposed to 5% CO2 versus 10% CO2 for up to 24 h in pH-buffered conditions. In hypercapnia, we identified around 370 differentially expressed genes (DEGs) under basal and about 1889 DEGs under lipopolysaccharide-stimulated conditions in monocytes. Transcripts relating to both mitochondrial and nuclear-encoded gene expression were enhanced in hypercapnia in basal and lipopolysaccharide-stimulated cells. Mitochondrial DNA content was not enhanced, but acylcarnitine species and genes associated with fatty acid metabolism were increased in hypercapnia. Primary macrophages exposed to hypercapnia also increased activation of genes associated with fatty acid metabolism and reduced activation of genes associated with glycolysis. Thus, hypercapnia elicits metabolic shifts in lipid metabolism in monocytes and macrophages under pH-buffered conditions. These data indicate that CO2 is an important modulator of monocyte transcription that can influence immunometabolic signaling in immune cells in hypercapnia. These immunometabolic insights may be of benefit in the treatment of patients experiencing hypercapnia.

Prepregnancy Body Mass Index and Lipoprotein Fractions are Associated with Changes in Women's Serum Metabolome from Late Pregnancy to the First Months of Postpartum.

BACKGROUND: Pregnancy and postpartum are periods of intense changes in women's metabolism. The knowledge of the metabolites and maternal factors underlying these changes is limited. OBJECTIVES: We aimed to investigate the maternal factors that could influence serum metabolome changes from late pregnancy to the first months of postpartum. METHODS: Sixty-eight healthy women from a Brazilian prospective cohort were included. Maternal blood and general characteristics were collected during pregnancy (28-35 wk) and postpartum (27-45 d). A targeted metabolomics approach was applied to quantify 132 serum metabolites, including amino acids, biogenic amines, acylcarnitines, lysophosphatidylcholines (LPC), diacyl phosphatidylcholines (PC), alkyl:acyl phosphatidylcholines (PC-O), sphingomyelins with (SM) and without hydroxylation [SM(OH)], and hexoses. Metabolome changes from pregnancy to postpartum were measured as log2 fold change (log2FC), and simple linear regressions were employed to evaluate associations between maternal variables and metabolite log2FC. Multiple comparison-adjusted P values of < 0.05 were considered significant. RESULTS: Of 132 metabolites quantified in serum, 90 changed from pregnancy to postpartum. Most metabolites belonging to PC and PC-O classes decreased, whereas most LPC, acylcarnitines, biogenic amines, and a few amino acids increased in postpartum. Maternal prepregnancy body mass index (ppBMI) showed positive associations with leucine and proline. A clear opposite change pattern was observed for most metabolites across ppBMI categories. Few phosphatidylcholines were decreased in women with normal ppBMI, while an increase was observed in women with obesity. Similarly, women with high postpartum levels of total cholesterol, LDL cholesterol, and non-HDL cholesterol showed increased sphingomyelins, whereas a decrease was observed for women with lower levels of those lipoproteins. CONCLUSIONS: The results revealed several maternal serum metabolomic changes from pregnancy to postpartum, and the maternal ppBMI and plasma lipoproteins were associated with these changes. We highlight the importance of the nutritional care of women prepregnancy to improve their metabolic risk profile.

Serum isthmin-1 levels are positively and independently correlated with albuminuria in patients with type 2 diabetes mellitus.

INTRODUCTION: Isthmin-1 (Ism-1), as a novel adipokine, plays a role in glucose homeostasis and lipid metabolism. However, the relationship between Ism-1 and type 2 diabetes mellitus (T2DM) remains unclear. This study aims to investigate the association of serum Ism-1 levels with albuminuria and insulin resistance in patients with T2DM and preserved renal function. RESEARCH DESIGN AND METHODS: A total of 150 patients with T2DM were recruited. The presence of albuminuria was evaluated by urinary albumin:creatinine ratio (UACR) in first morning urine sample. Serum Ism-1 levels were tested by ELISA. Homeostasis model assessments were used to evaluate insulin resistance. Binary logistic regression and multivariable linear regression analyses were used to assess the association of serum Ism-1 levels with albuminuria. Multivariable linear regression analyses were performed to explore the correlation of serum Ism-1 levels with insulin resistance. RESULTS: Compared with the normal-albuminuria and microalbuminuria groups, serum Ism-1 levels were significantly higher in the macroalbuminuria group (p<0.01). Binary logistic regression analyses showed that serum Ism-1 was positively associated with odds of albuminuria even after multiple adjustments (OR=4.766, p=0.013). Serum Ism-1 was positively associated with log10-transformed UACR (ß=0.625, p<0.001). However, the associations between serum Ism-1 levels and insulin resistance were not observed in patients with T2DM. CONCLUSIONS: Serum Ism-1 levels were positively and independently correlated with the severity of albuminuria in patients with T2DM but not with insulin resistance.

Circulating free triiodothyronine concentration is positively associated with ß-cell function in euthyroid patients with obesity and type 2 diabetes.

OBJECTIVE: To investigate the relationship between thyroid hormone concentrations and ß-cell function in euthyroid patients with obesity and type 2 diabetes. METHODS: We performed a single-center cross-sectional study of 254 patients with type 2 diabetes mellitus aged ≥40 years. The participants were allocated to an obesity group or non-obesity group on the basis of their body mass index (BMI). Their ß-cell function was assessed by measuring C-peptide concentration during a 75-g oral glucose tolerance test (OGTT); and their serum free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone concentrations were measured. RESULTS: The serum FT3 concentration and the C-peptide concentrations at five time points of the OGTT were significantly higher in the obesity group than in the non-obesity group. FT3 was positively associated with the ß-cell function of the obesity group, but not that of the non-obesity group, in multiple linear regression analysis, after adjustment for potential confounding factors. Serum FT3 concentration was also significantly associated with indices of obesity (BMI, waist circumference, body fat percentage, fat mass, fat mass/height2 and visceral fat area). CONCLUSIONS: Obesity-associated high serum FT3 concentrations might affect ß-cell function in euthyroid patients with obesity and type 2 diabetes.

Whole-genome survey and phylogenetic analysis of Gadus macrocephalus.

Gadus macrocephalus (Pacific cod) is an economically important species on the northern coast of the Pacific. Although numerous studies on G. macrocephalus exist, there are few reports on its genomic data. Here, we used whole-genome sequencing data to elucidate the genomic characteristics and phylogenetic relationship of G. macrocephalus. From the 19-mer frequency distribution, the genome size was estimated to be 658.22 Mb. The heterozygosity, repetitive sequence content and GC content were approximately 0.62%, 27.50% and 44.73%, respectively. The draft genome sequences were initially assembled, yielding a total of 500,760 scaffolds (N50 = 3565 bp). A total of 789,860 microsatellite motifs were identified from the genomic data, and dinucleotide repeat was the most dominant simple sequence repeat motif. As a byproduct of whole-genome sequencing, the mitochondrial genome was assembled to investigate the evolutionary relationships between G. macrocephalus and its relatives. On the basis of 13 protein-coding gene sequences of the mitochondrial genome of Gadidae species, the maximum likelihood phylogenetic tree showed that complicated relationships and divergence times among Gadidae species. Demographic history analysis revealed changes in the G. macrocephalus population during the Pleistocene by using the pairwise sequentially Markovian coalescent model. These findings supplement the genomic data of G. macrocephalus, and make a valuable contribution to the whole-genome studies on G. macrocephalus.