Search

Microscale-based separations are increasingly being applied in the field of metabolomics for the analysis of small-molecule metabolites. These methods have the potential to provide improved sensitivity, less solvent waste, and reduced sample-size requirements. Ion-pair free microflow-based global metabolomics methods, which we recently reported, were further compared to analytical flow ion-pairing reagent containing methods using a sample set from a urea cycle disorder (UCD) mouse model. Mouse urine and brain homogenate samples representing healthy, diseased, and disease-treated animals were analyzed by both methods. Data processing was performed using univariate and multivariate techniques followed by analyte trend analysis. The microflow methods performed comparably to the analytical flow ion-pairing methods with the ability to separate the three sample groups when analyzed by partial least-squares analysis. The number of detected metabolic features present after each data processing step was similar between the microflow-based methods and the ion-pairing methods in the negative ionization mode. The observed analyte trend and coverage of known UCD biomarkers were the same for both evaluated approaches. The 12.5-fold reduction in sample injection volume required for the microflow-based separations highlights the potential of this method to support studies with sample-size limitations.

Background Malignant pleural mesothelioma (MPM) is a rare and aggressive carcinoma located in pleural cavity. Due to lack of effective diagnostic biomarkers and therapeutic targets in MPM, the prognosis is extremely poor. Because of difficulties in sample extraction, and the high rate of misdiagnosis, MPM is rarely studied. Therefore, novel modeling methodology is crucially needed to facilitate MPM research. Methods A novel patient-derived xenograft (PDX) modeling strategy was designed, which included preliminary screening of patients with pleural thickening using computerized tomography (CT) scan, further reviewing history of disease and imaging by a senior sonographer as well as histopathological analysis by a senior pathologist, and PDX model construction using ultrasound-guided pleural biopsy from MPM patients. Gas chromatography-mass spectrometry-based metabolomics was further utilized for investigating circulating metabolic features of the PDX models. Univariate and multivariate analysis, and pathway analysis were performed to explore the differential metabolites, enriched metabolism pathways and potential metabolic targets. Results After screening using our strategy, 5 out of 116 patients were confirmed to be MPM, and their specimens were used for modeling. Two PDX models were established successfully. Metabolomics analysis revealed significant metabolic shifts in PDX models, such as dysregulations in amino acid metabolism, TCA cycle and glycolysis, and nucleotide metabolism. Conclusions To sum up, we suggested a novel modeling strategy that may facilitate specimen availability for MM research, and by applying metabolomics in this model, several metabolic features were identified, whereas future studies with large sample size are needed.

Background: The main components of mineral metabolism can influence non-classical target organs such as adipose tissue, pancreas, vascular wall. The «metabolic» effects of parathyroid hormone (PTH) and other participants of phosphorus-calcium metabolism in the hyperfunction of parathyroid glands remain unclear. The study of disorders of carbohydrate, fat and other types of metabolism in primary hyperparathyroidism (PHPT) will help to develop effective measures for prophylaxis and treatment of the patients in order to improve the quality and life span of the population.Aim: To study the main parameters of metabolism in young patients with an active stage of PHPT before surgical treatment.Materials and methods: A one-stage comparative study of young patients with PHPT and healthy volunteers matched by sex, age and body mass index (BMI) was carried out. The participants underwent a comprehensive biochemical and hormonal examination, a hyperinsulinemic euglycemic clamp and a bioimpedance analysis of the body composition.Results: 21 patients with PHPT and 18 healthy volunteers were included in the study. Patients with PHPT have higher level of serum triglycerides (p=0.003) without statistically differences of the main carbohydrate and purine parameters comparing with the control group. Visceral obesity were revealed in 42.9% of patients, including those with a normal BMI. Insulin resistance in the PHPT group was noted in 52.4% of cases, while the M-index was statistically lower than in the control subgroup (p=0.008), despite of the comparable body composition of the participants. The M-index showed a positive correlation with blood phosphorus level (p=0.010) only in the general group. Statistically positive correlations of PTH, albumin-corrected calcium and osteocalcin with triglyceride levels, calcium with fasting glycaemia, and PTH with uric acid levels were determined.Conclusion: PHPT is associated with insulin resistance in patients that is the main risk factor for the development of serious carbohydrate and fat disorders. The positive correlation of PTH and blood calcium levels with triglycerides, as well as the tendency to hypertriglyceridemia comparing with healthy volunteers, suggest the disease effect on the development of dyslipidemia.

Spatial metabolomics can reveal intercellular heterogeneity and tissue organization. Here we report on the spatial single nuclear metabolomics (SEAM) method, a flexible platform combining high-spatial-resolution imaging mass spectrometry and a set of computational algorithms that can display multiscale and multicolor tissue tomography together with identification and clustering of single nuclei by their in situ metabolic fingerprints. We first applied SEAM to a range of wild-type mouse tissues, then delineated a consistent pattern of metabolic zonation in mouse liver. We further studied the spatial metabolic profile in the human fibrotic liver. We discovered subpopulations of hepatocytes with special metabolic features associated with their proximity to the fibrotic niche, and validated this finding by spatial transcriptomics with Geo-seq. These demonstrations highlighted SEAM’s ability to explore the spatial metabolic profile and tissue histology at the single-cell level, leading to a deeper understanding of tissue metabolic organization. SEAM is a platform for the analysis of high-resolution secondary ion mass spectrometry imaging that allows spatially resolved nuclear metabolomic profiling at the single-cell level.

In-source fragmentation (ISF) is a naturally occurring phenomenon during electrospray ionization (ESI) in liquid chromatography-mass spectrometry (LC-MS) analysis. ISF leads to false metabolite annotation in untargeted metabolomics, prompting misinterpretation of the underlying biological mechanisms. Conventional metabolomic data cleaning mainly focuses on the annotation of adducts and isotopes, and the recognition of ISF features is mainly based on common neutral losses and the LC coelution pattern. In this work, we recognized three increasingly important patterns of ISF features, including (1) coeluting with their precursor ions, (2) being in the tandem MS (MS2) spectra of their precursor ions, and (3) sharing similar MS2 fragmentation patterns with their precursor ions. Based on these patterns, we developed an R package, ISFrag, to comprehensively recognize all possible ISF features from LC-MS data generated from full-scan, data-dependent acquisition, and data-independent acquisition modes without the assistance of common neutral loss information or MS2 spectral library. Tested using metabolite standards, we achieved a 100% correct recognition of level 1 ISF features and over 80% correct recognition for level 2 ISF features. Further application of ISFrag on untargeted metabolomics data allows us to identify ISF features that can potentially cause false metabolite annotation at an omics-scale. With the help of ISFrag, we performed a systematic investigation of how ISF features are influenced by different MS parameters, including capillary voltage, end plate offset, ion energy, and "collision energy". Our results show that while increasing energies can increase the number of real metabolic features and ISF features, the percentage of ISF features might not necessarily increase. Finally, using ISFrag, we created an ISF pathway to visualize the relationships between multiple ISF features that belong to the same precursor ion. ISFrag is freely available on GitHub (https://github.com/HuanLab/ISFrag).

Background Segmented filamentous bacteria (SFB) are intestinal commensal microorganisms that have been demonstrated to induce the innate and adaptive immune responses in mouse and rat hosts. SFB are Gram-positive, spore-forming bacteria that fail to grow optimally under in vitro conditions due to unique metabolic requirements. Recently, SFB have been implicated in improved health and growth outcomes in commercial turkey flocks. To assess the nature and variations in SFB of turkeys and how they may differ from mammalian-associated SFB, the genome of turkey-associated SFB was compared with six representative genomes from murine hosts using an in silico approach. Results The SFB-turkey genome is 1.6 Mb with a G + C content of 26.14% and contains 1,604 coding sequences (CDS). Comparative genome analyses revealed that all the seven SFB strain possesses a common set of metabolic deficiencies and auxotrophies. Specifically, the inability of all the SFB strains to synthesize most of the amino acids, nucleotides and cofactors, emphasizing the importance of metabolite acquisition from the host intestinal environment. Among the seven SFB genomes, the SFB-turkey genome is the largest and contains the highest number of 1,604 predicted CDS. The SFB-turkey genome possesses cellular metabolism genes that are absent in the rodent SFB strains, including catabolic pathways for sucrose, stachyose, raffinose and other complex glycans. Other unique genes associated with SFB-turkey genome is loci for the biosynthesis of biotin, and degradation enzymes to recycle primary bile acids, both of which may play an important role to help turkey associated SFB survive and secure mutualism with its avian host. Conclusions Comparative genomic analysis of seven SFB genomes revealed that each strain have a core set of metabolic capabilities and deficiencies that make these bacteria challenging to culture under ex vivo conditions. When compared to the murine-associated strains, turkey-associated SFB serves as a phylogenetic outgroup and a unique member among all the sequenced strains of SFB. This turkey-associated SFB strain is the first reported non-mammalian SFB genome, and highlights the impact of host specificity and the evolution of metabolic capabilities.

If life exists on Mars, it would face several challenges including the presence of perchlorates, which destabilize biomacromolecules by inducing chaotropic stress. However, little is known about perchlorate toxicity for microorganisms on the cellular level. Here, we present the first proteomic investigation on the perchlorate‐specific stress responses of the halotolerant yeast Debaryomyces hansenii and compare these to generally known salt stress adaptations. We found that the responses to NaCl and NaClO4‐induced stresses share many common metabolic features, for example, signalling pathways, elevated energy metabolism, or osmolyte biosynthesis. Nevertheless, several new perchlorate‐specific stress responses could be identified, such as protein glycosylation and cell wall remodulations, presumably in order to stabilize protein structures and the cell envelope. These stress responses would also be relevant for putative life on Mars, which—given the environmental conditions—likely developed chaotropic defence strategies such as stabilized confirmations of biomacromolecules or the formation of cell clusters.

BACKGROUND AND PURPOSE To compare and characterize metabolic features of high- and low-grade glioma tumors using 68 Ga-PSMA-617 and 18 F-FDG positron emission tomography/computed tomography (PET/CT). METHODS Thirty patients who underwent both 68 Ga-PSMA-617 and 18 F-FDG PET/CT over 2 consecutive days and then underwent surgical treatment were retrospectively identified. All tumors were diagnosed histologically. This report includes 16 high-grade glioma (HGG) and 14 low-grade glioma (LGG) tumors. Standard uptake value (SUV) and target to nontarget (T/NT) were quantitatively investigated through the entire tumor region. Statistical analyses were performed using area under the curve (AUC) and comparison of two means. RESULTS SUVmax and SUVmean were the most effective (AUC, 0.96 and 0.94 for PSMA PET; AUC, 0.79 and 0.74 for FDG PET, respectively) for differentiating HGGs from LGGs. These methods distinguished between HGG and LGG effectively (PSMA PET: SUVmax , 5.766 ± 3.945 vs. 0.7364 ± 0.5295, p < 0.0001; SUVmean , 1.666 ± 1.680 and 0.1514 ± 0.1534, p < 0.0001, respectively) (FDG PET: SUVmax , 11.67 ± 3.639 and 9.118 ± 6.612; SUVmean , 5.648 ± 2.114 and 4.435 ± 2.872; p = 0.0083, 0.0262, respectively). The Youden index for SUVmax and SUVmean of 68 Ga-PSMA-617 and 18 F-FDG were 0.82 and 0.79 and 0.54 and 0.61, separately. T/NTmax was helpful for visual inspection of 68 Ga-PSMA-617-PET images (T/NTmax : 1.291 ± 0.9553 in grade II, 5.25 ± 2.435 in grade III, and 13.61 ± 13.84 in grade IV). T/NTmax differed significantly between LGG and HGG and between subtypes of LGG. CONCLUSION PET/CT with 68 Ga-PSMA-617 and 18 F-FDG may help distinguish between HGG and LGG, and 68 Ga-PSMA-617 PET/CT is superior to18 F-FDG in differentiating HGG and LGG.

Acute myeloid leukemia (AML) is a cancer derived from the myeloid lineage of blood cells, characterized by overproduction of leukemic blasts. Although therapeutic improvements have made a significant impact on the outcomes of patients with AML, survival rates remain low due to a high incidence of relapse. Similar to how wildfires can reignite from hidden embers not extinguished from an initial round of firefighting, leukemic stem cells (LSCs) are the embers remaining after completion of traditional chemotherapeutic treatments. LSCs exhibit a unique metabolic profile and contain metabolically distinct subpopulations. In this review, we detail the metabolic features of LSCs and how thetse characteristics promote resistance to traditional chemotherapy. We also discuss new therapeutic approaches that target metabolic vulnerabilities of LSC to selectively eradicate them.

The application of microbial strains as axenic cultures has frequently been employed in a diverse range of sectors. In the natural environment, microbes exist as multispecies and perform better than monocultures. Cell signaling and communication pathways play a key role in engineering microbial consortia, because in a consortium, the microorganisms communicate via diffusible signal molecules. Mixed microbial cultures have gained little attention due to the lack of proper knowledge about their interactions with each other. Some ideas have been proposed to deal with and study various microbes when they live together as a community, for biotechnological application purposes. In natural environments, microbes can possess unique metabolic features. Therefore, microbial consortia divide the metabolic burden among strains in the group and robustly perform pesticide degradation. Synthetic microbial consortia can perform the desired functions at naturally contaminated sites. Therefore, in this article, special attention is paid to the microbial consortia and their function in the natural environment. This review comprehensively discusses the recent applications of microbial consortia in pesticide degradation and environmental bioremediation. Moreover, the future directions of synthetic consortia have been explored. The review also explores the future perspectives and new platforms for these approaches, besides highlighting the practical understanding of the scientific information behind consortia.

The potential to convert renewable plant biomasses into fuels and chemicals by microbial processes presents an attractive, less environmentally intense alternative to conventional routes based on fossil fuels. This would best be done with microbes that natively deconstruct lignocellulose and concomitantly form industrially relevant products, but these two physiological and metabolic features are rarely and simultaneously observed in nature. Genetic modification of both plant feedstocks and microbes can be used to increase lignocellulose deconstruction capability and generate industrially relevant products. Separate efforts on plants and microbes are ongoing, but these studies lack a focus on optimal, complementary combinations of these disparate biological systems to obtain a convergent technology. Improving genetic tools for plants have given rise to the generation of low-lignin lines that are more readily solubilized by microorganisms. Most focus on the microbiological front has involved thermophilic bacteria from the genera Caldicellulosiruptor and Clostridium, given their capacity to degrade lignocellulose and to form bio-products through metabolic engineering strategies enabled by ever-improving molecular genetics tools. Bioengineering plant properties to better fit the deconstruction capabilities of candidate consolidated bioprocessing microorganisms has potential to achieve the efficient lignocellulose deconstruction needed for industrial relevance. This article is protected by copyright. All rights reserved.

Purpose The aim of our work is to evaluate the correlation of two-dimensional (2D) and three-dimensional (3D) radiomics and metabolic features of hepatocellular carcinoma (HCC) with tumour diameter, staging, and metabolic tumour volume (MTV). Material and methods Thirty-three patients with HCC were studied using 18F-fluorodeoxyglucose positron-emission tomography with computed tomography (18F [FDG] PET/CT). The tumours were segmented from the PET images after CT correction. Metabolic parameters and 35 radiomics features were compared using 2D and 3D modes. The metabolic parameters and tumour morphology were compared using 2 different types of software. Tumour heterogeneity was studied in both metabolic parameters and radiomics features. Finally, the correlation between the metabolic and radiomics features in 3D mode, as well as tumour morphology and staging according to the American Joint Committee on Cancer (AJCC) staging were studied. Results Most of the metabolic parameters and radiomics features are statically stable through the 2D and 3D modes. Most of the 3D mode features show a correlation with metabolic parameters; the total lesion glycolysis (TLG) shows the highest correlation, with a Spearman correlation coefficient (rs) of 0.9776. Also, the grey level run length matrix/run length non-uniformity (GLRLM_RLNU) from radiomics features exhibits a correlation with a Spearman correlation coefficient of 0.9733. Maximum tumour diameter is correlated with TLG and GLRLM_RLNU, with rs equal to 0.7461 and 0.7143, respectively. Regarding AJCC staging, some features show a medium but prognostic correlation. In the case of 2D-mode features, all metabolic and radiomics features show no significant correlation with MTV, AJCC staging, and tumour maximum diameter. Conclusions Most of the normal metabolic parameters and radiomics features are statistically stable through the 3D and 2D modes. 3D radiomics features are significantly correlated with tumour volume, maximum diameter, and staging. Conversely, 2D features have negligible correlation with the same parameters. Therefore, 3D mode features are preferable and can accurately evaluate tumour heterogeneity.

Background: Hypothalamic obesity often develops after surgical treatment of craniopharyngioma and is characterized by rapid weight gain, high frequency of metabolic disorders, body composition specificity and resistance to standard lifestyle modification approaches and medication therapy of obesity. Recent studies show that one of the mechanisms, explaining weight gain in these children is decrease in resting energy expenditure (REE).Aims: To compare REE, body composition parameters, and the frequency of metabolic disorders in children with hypothalamic and simple obesity.Materials and methods: The study included 60 obese children aged 7 to 17 years, divided into two groups. The study group included 20 children with hypothalamic obesity, developed after craniopharyngioma treatment. The control group consisted of 40 children with simple obesity. Body composition, REE, and metabolic disorders were associated in all children.Results: Children with hypothalamic obesity showed a significant decrease of resting energy expenditure. The average decrease in REE was 13.1%, but in single patients it reached 33.4%. The percentage of fat mass in hypothalamic and simple obesity does not differ significantly (39.7% [36.2; 42.6] vs 38.8 % [35.9; 43.2]; p=0.69). Screening for metabolic disorders revealed a high prevalence of metabolic disorders in hypothalamic obesity: impaired glucose tolerance - in 10%; dyslipidemia - 55%, insulin resistance-50%, non-alcoholic fatty liver disease - 60 %.Conclusions: Children with hypothalamic obesity showed a significant decrease of resting energy expenditure. When planning a diet in this group of patients it is preferable to use indirect calorimetry. Hypothalamic obesity even at an early age is associated with a high frequency of metabolic disturbance. Hypothalamic obesity in children is not associated with more pronounced hyperinsulinemia and insulin resistance compared to the simple obesity.

In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (1H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL-SVM). We retrospectively analysed 23 confirmed patients and 16 healthy controls, who underwent a 3.0 T magnetic resonance imaging (MRI) sequence with multivoxel 1H-MRS in our hospitals. One hundred and seventeen metabolic features were extracted from the multivoxel 1H-MRS image. Thirty-three metabolic features selected by the Mann-Whitney U test were considered to have a statistically significant difference ( p < 0.05 ). However, the best accuracy achieved by conventional statistical methods using these 33 metabolic features was only 77%. We turned to develop a support vector machine broad learning system (BL-SVM) to quantitatively analyse the metabolic features from 1H-MRS. Although not all the individual features manifested statistics significantly, the BL-SVM could still learn to distinguish the NPSLE from the healthy controls. The area under the receiver operating characteristic curve (AUC), the sensitivity, and the specificity of our BL-SVM in predicting NPSLE were 95%, 95.8%, and 93%, respectively, by 3-fold cross-validation. We consequently conclude that the proposed system effectively and efficiently working on limited and noisy samples may brighten a noinvasive in vivo instrument for early diagnosis of NPSLE.

Long-term exposure to particular matter (PM), especially fine PM (< 2.5 μm in the aerodynamic diameter, PM2.5), is associated with increased risk of cardiovascular disorders. This study aimed to evaluate the association between long-term exposure to PM2.5/PM10 and the metabolic change in the plasma. Specifically, using metabolomics, we sought to identify the biomarkers for the vulnerable subgroup to PM2.5 exposure. A total of 78 college student volunteers were recruited into this prospective cohort study. All participants received 8 rounds of physical examinations at twice quarterly. Air purifiers were placed in 40 of 78 participants' dormitories for 14 days. Before and after intervention, physical examinations were performed and the peripheral blood was collected. Plasma metabolomics was determined by ultra-performance liquid chromatography-mass spectrometry. During the follow-up, the average concentrations of PM2.5 and PM10 were 53 μg/m3 and 93 μg/m3, respectively. Totally, 42 and 120 differential metabolic features were detected for PM10 and PM2.5 exposure, respectively. In total, 25 differential metabolites were identified for PM2.5 exposure, most of which were phospholipids. No distinctive metabolites were found for PM10 exposure. A total of 6 differential metabolites (lysoPC (P-20:0), lysoPC (P-18:1(9z)), lysoPC (20:1), lysoPC (O-16:0), choline, and found 1,3-diphenylprop-2-en-1-one) were characterized and confirmed for sensitive individuals. Importantly, we found LysoPC (P-20:0) and LysoPC (P-18:1(9z)) changed significantly before and after air purifier intervention. Our results indicated that the phospholipid catabolism was involved in long-term PM2.5 exposure. LysoPC (P-20:0) and LysoPC (P-18:1(9z)) may be the biomarkers of PM2.5 exposure.

Introduction and Aim: PCOS is a complicated endocrinopathy of women in reproductive age with unknown etiology causing ovulatory dysfunction and metabolic disturbances. The present study investigated the effects of ethanolic seed extract of Caesalpinia bonducella (ESECB) in a mifepristone model of polycystic ovarian syndrome, which has the same clinical and metabolic features as in PCOS women. Materials and Methods: A daily administration of mifepristone (4mg/kg b.w.) to female rats for 8 days induces PCOS by indicating persistent estrous cycle. PCOS induced rats were treated with ESECB 200mg and 400mg/kg b. w. per oral for 28 days and at the end, the weight of the body and reproductive organs were determined. Biochemical parameters were also estimated. Metformin was used as a standard drug. Results: A significant increase (p

BACKGROUND Prematurity is a severe pathophysiological condition, however, little is known about the gestational age-dependent development of the neonatal metabolome. METHODS Using an untargeted liquid chromatography-tandem mass spectrometry metabolomics protocol, we measured over 9000 metabolites in 298 neonatal residual heel prick dried blood spots retrieved from the Danish Neonatal Screening Biobank. By combining multiple state-of-the-art metabolome mining tools, we retrieved chemical structural information at a broad level for over 5000 (60%) metabolites and assessed their relation to gestational age. RESULTS A total of 1459 (~16%) metabolites were significantly correlated with gestational age (false discovery rate-adjusted P

The possibility of selectively delivering metal complexes to a defined cohort of cells on the basis of their metabolic features is a highly challenging goal, which may be extremely useful for a series of purposes, including diagnosis and therapy of pathological states, such as cancer. Tumor cells display augmented requests for carbohydrates and, in particular, for glucose in order to sustain their high proliferation rate, which causes an increased glycolytic process (Warburg effect). Since several metal complexes display diagnostic and/or therapeutic properties, their conjugation to carbohydrate portions often induce their preferential accumulation in cancer cells, similarly to what is observed with fluorodeoxyglucose (FDG). In this review we have considered the latest developments of glycoconjugates containing metal complexes in their structures. These compounds are classified as diagnostic or therapeutic agents and are further systematically discussed on the basis of the metal atom they contain. Several diagnostic techniques are possible with these probes, since, depending on the metal species included in their structures, they may be employed in nuclear medicine (PET, SPECT), magnetic resonance imaging, luminescence and phosphorescence. At the same time, the lack of selective cytotoxicity displayed by several metal-based chemotherapeutic agents, may also be solved by the conjugation of these agents to carbohydrate portions. Overall, data so far available reveal the great potential of this chemical class in the early detection and in the cure of severe neoplastic diseases, which still needs to be fully explored in the clinic.

Disturbances during intrauterine life have been implicated in the origin of polycystic ovary syndrome (PCOS) and may modify the endocrine and metabolic function of a child born to a mother with PCOS independently of genetic inheritance and sex. Daughters of women with PCOS show 4 components of the syndrome (ovarian dysfunction, neuroendocrine dysfunction, hyperandrogenism, and hyperinsulinemia) that appear in a sequential pattern during infancy, childhood, and puberty increasing the chance for developing PCOS during adulthood. Sons born to mothers with PCOS show few reproductive but important metabolic disturbances. These metabolic features, both in girls and boys, have early cardiovascular effects that may put these children at risk for later cardiovascular disease. Recent combined animal/human models have been able to identify common markers that will help us elucidate the precise mechanisms involved in the transgenerational transmission of this syndrome and provide possible therapies to prevent it.

Cancer immunotherapy has received extensive attention due to its ability to activate the innate or adaptive immune systems of patients to combat tumors. Despite a few clinical successes, further endeavors are still needed to tackle unresolved issues, including limited response rates, development of resistance, and immune-related toxicities. Accumulating evidence has pinpointed the tumor microenvironment (TME) as one of the major obstacles in cancer immunotherapy due to its detrimental impacts on tumor-infiltrating immune cells. Nanomedicine has been battling with the TME in the past several decades, and the experience obtained could be exploited to improve current paradigms of immunotherapy. Here, we discuss the metabolic features of the TME and its influence on different types of immune cells. The recent progress in nanoenabled cancer immunotherapy has been summarized with a highlight on the modulation of immune cells, tumor stroma, cytokines and enzymes to reverse the immunosuppressive TME.

ObjectivesTo investigate metabolic features that may predispose to GCA in a nested case–control study.MethodsIndividuals who developed GCA after inclusion in a population-based health survey (the Malmö Preventive Medicine Project; N = 33 346) were identified and validated through a structured review of medical records. Four controls for every validated case were selected from the database.ResultsA total of 76 cases with a confirmed incident diagnosis of GCA (61% female, 65% biopsy positive, mean age at diagnosis 70 years) were identified. The median time from screening to diagnosis was 20.7 years (range 3.0–32.1). Cases had significantly lower fasting blood glucose (FBG) at baseline screening compared with controls [mean 4.7 vs 5.1 mmol/l (S.d. overall 1.5), odds ratio (OR) 0.35 per mmol/l (95% CI 0.17, 0.71)] and the association remained significant when adjusted for smoking [OR 0.33 per mmol/l (95% CI 0.16, 0.68)]. Current smokers had a reduced risk of GCA [OR 0.35 (95% CI 0.18, 0.70)]. Both cholesterol [mean 5.6 vs 6.0 mmol/l (S.d. overall 1.0)] and triglyceride levels [median 1.0 vs 1.2 mmol/l (S.d. overall 0.8)] were lower among the cases at baseline screening, with significant negative associations with subsequent GCA in crude and smoking-adjusted models [OR 0.62 per mmol/l (95% CI 0.43, 0.90) for cholesterol; 0.46 per mmol/l (95% CI 0.27, 0.81) for triglycerides].ConclusionDevelopment of GCA was associated with lower FBG and lower cholesterol and triglyceride levels at baseline, all adjusted for current smoking, suggesting that metabolic features predispose to GCA.

The effect of metabolic characteristics on the prognosis of patients with metastatic renal cell carcinoma remains controversial. We investigated the associations between metabolic features of each individual and disease prognosis in patients with metastatic renal cell carcinoma. Data of 1,584 patients with metastatic renal cell carcinoma from a multi-institutional database were retrospectively analyzed. The entire cohort was stratified into three subgroups according to how many patients had abnormal metabolic features (hypertension, diabetes mellitus, and low body mass index). The Kaplan-Meier and Cox proportional analyses were performed to investigate the associations between abnormal metabolic features and disease prognosis. mThere were 465 subjects without any metabolic features, 995 with one or two, and 124 with three. When the survival outcomes were compared according to the number of metabolic features, patients with higher numbers of metabolic features had significantly shorter overall and cancer-specific survival than those with fewer metabolic features (all p values

Background Liver involvement in Gaucher disease (GD) is a result of glucosylceramide (GL1) and its deacylated lysolipid, glucosylsphingosine (lyso-GL1) infiltration of macrophages. The long-term liver-related complications of GD could include liver fibrosis and cirrhosis. The aim of the study was to evaluate clinical utility and relevance of TE by FibroScan in GD patients by assessing two parameters: controlled attenuation parameter (CAP) and liver stiffness (LS), in regard of GD-related variables, type of GD, age of patients, enzymatic replacement therapy (ERT), and metabolic features. Methods 59 Polish patients (55 adults, 4 children) with GD (43 patients with type 1 and 16 patients with type 3) aged 7–86 years, underwent TE by FibroScan; elevated CAP was defined as >250 dB/m and elevated LS as >7 kPa. All patients, except five patients with type 1 GD (patients' refusal), were treated by ERT. Results Elevated CAP was present in 23% of GD1 patients and 19% of GD3 patients. Elevated LS was present in 21% of GD1 patients and 13% of GD3 patients. CAP was fairly, positively (ρ = 0.356) correlated with BMI. LS was fairly, positively (ρ = 0.4) correlated with patient's age, as well as the age at start of ERT (ρ = 0.326). CAP was strongly, negatively (ρ = −0.52) correlated with the age at start of ERT. LS and CAP were correlated (strongly, positively) only in GD3. Conclusions TE by FibroScan could be considered as an additional method for evaluating GD patients for non-invasive assessment of CAP and LS. The investigation of serial TE measurements in untreated as well as treated GD patients is needed to better determine whether this technology should be added to recommendations for monitoring GD patients. TE by FibroScan could be performed in GD patients with increased BMI and especially those with metabolic syndrome as they have other important risks for liver disease. After our analysis we think these risks factors are independent of GD but still very important for their overall health.

Summary. Generalized periodontitis is one of the most common and complex problems of modern dentistry. According to the WHO, its incidence corrects with age: in the group of individuals from 35 to 44 years, the prevalence of this pathology reaches more than 50 %, in people older than 65–78%, which leads to tooth loss in 40 % of cases. The complexity of the problem lies in the fact that generalized periodontitis is a multifactorial disease, which is characterized by a chronic course with a periodic exacerbation of the inflammatory process in periodontal disease. The progression of destructive phenomena in periodontal tissues depends on many reasons, the role of which from the moment of description and to this day remains the subject of debate and debate. The aim of this study is to assess the pathogenetic significance of disorders of the local components of the immune system, cytokine profile, processes of radical and antioxidant status, and features of bone remodeling in patients with aggressive generalized periodontitis. The work is based on the results of comprehensive clinical and laboratory studies of 123 patients with different course of generalized periodontitis. The study used generally accepted clinical, paraclinical and laboratory research methods, supplemented by dental volumetric tomography. The subjects were divided into 2 groups: I – with an aggravated course (62 people), II – with an aggressive (rapidly progressing) course of the disease (61 people), the control group consisted of 20 healthy volunteers. Studies have shown that exacerbated and rapidly progressing chronic generalized periodontitis is manifested by the same type of clinical symptoms and the same state of gingival and periodontal indices. In individuals with a high rate of destruction of periodontal bone structures, the activity of the inflammatory-destructive process and the rate of loss of periodontal bone tissue are caused by functional disorders of varying strengths: the state of local secretory immunity, the processes of free radical oxidation and the antioxidant defense system, changes in the cytokine profile, and is also found bone remodeling dysfunction due to increased processes of bone resorption and decreased bone formation. The need is substantiated, along with anamnestic data, to take into account the degree of increase in the levels of proinflammatory cytokines IL-1β and TNF-α, as well as features of bone metabolism and osteoparotic processes detected using dental volumetric tomography.

Rewiring cellular metabolism is a key hallmark of cancer. Multiple evidences show that alterations in various metabolic circuits directly contribute to the tumorigenic process at different levels (e.g. cancer initiation, metastasis, resistance). However, the characterization of the metabolic profile of Neurofibromatosis type 1 (NF1)-related neoplastic cells has been only partially elucidated both in benign neurofibromas and in malignant peripheral nerve sheath tumors (MPNSTs). Here, we illustrate the state of the art on the knowledge of the metabolic features of tumors related to NF1 and discuss their potential implications for the development of novel therapeutic perspectives.

Summary Untargeted liquid chromatography–mass spectrometry (LC–MS) profiling assays are capable of measuring thousands of chemical compounds in a single sample, but unreliable feature extraction and metabolite identification remain considerable barriers to their interpretation and usefulness. peakPantheR (Peak Picking and ANnoTation of High-resolution Experiments in R) is an R package for the targeted extraction and integration of annotated features from LC–MS profiling experiments. It takes advantage of chromatographic and spectral databases and prior information of sample matrix composition to generate annotated and interpretable metabolic phenotypic datasets and power workflows for real-time data quality assessment. Availability and implementation peakPantheR is available via Bioconductor (https://bioconductor.org/packages/peakPantheR/). Documentation and worked examples are available at https://phenomecentre.github.io/peakPantheR.github.io/ and https://github.com/phenomecentre/metabotyping-dementia-urine. Supplementary information Supplementary data are available at Bioinformatics online.