Compositional Signatures Research Articles

An exploratory study on the use of different composite magnetic and colour fingerprints in aeolian sediment provenance fingerprinting

There is an urgent need for reliable and cost-effective sediment source tracing techniques for apportioning aeolian sediment (sand dune) sources for guiding the selection of best management practices for wind erosion control. Accordingly, the main aim of this study was to quantify the contributions of aeolian sources to sand dune target sediment samples collected in a case study in central Iran using a source fingerprinting procedure based on low-cost fingerprints comprising colour and magnetic tracers. Colour (RGB), magnetic susceptibility (χlf and χhf) and 13 colour and magnetic indices were measured on 54 aeolian sediment source samples and ten aeolian target sediment samples. Three different composite fingerprints for discriminating and apportioning the aeolian sediment sources were selected based on a combination of statistical tests comprising the Kruskal–Wallis H test (KW-H), discriminant function analysis (DFA), principal component & classification analysis (PCCA), and a general classification & regression tree (GC&RT) model. The Modified MixSIR Bayesian un-mixing model was used to apportion aeolian source contributions using the final composite fingerprints. The composite signatures all suggested that the salt flat plain was the dominant (average 63%, and standard deviation, SD, 5.9%) source of the aeolian target sediment samples, whilst agricultural land was second (average 63%, SD 5.6%,) most important. The root mean square difference between the apportionment results based on the three composite fingerprints ranged from 0.2% to 8.3%. Pairwise comparisons of the posterior distributions for the predicted source proportions generated using the three composite signatures showed that eight of 12 pairwise comparisons were not significantly different. Virtual mixture accuracy tests of the fingerprinting models using the three composite signatures suggested errors ranging between 2.2%−20.6% (with a mean of 9.9%), 1.4%−17.0% (mean value 8.3%), and 0.03%−1.0% (mean value 0.8%). The results support the use of low-cost colour and magnetic tracers by investigations into aeolian sediment provenance.

Using different size fractions to source fingerprint fine-grained channel bed sediment in a large drainage basin in Iran

Sediment fingerprinting in data sparse regions, such as the mountainous areas of Iran, is more suited to a confluence-based sample design wherein tributary sub-basins are characterised by sediment samples using different size fractions. Our objective was therefore to fingerprint spatial source contributions to the < 37 and 37–63 µm fractions of fine-grained channel bed sediment samples collected in a large erodible mountainous river basin in Iran based on a number of statistical and machine learning approaches. Geochemical elements were measured in channel bed surface drape sediments from seven sub-basins and in delivered sediments from the basin outlet. A Bayesian mass balance model (modified MixSIR) was applied to apportion sub-basin spatial sources with four composite signatures selected using the different statistical approaches. For the < 37 and 37–63 µm fractions, the signatures all indicated that sub-basins 3 (Andajroud; 46.7%) and 7 (Ninehroud; 36.8%) were the dominant spatial sources of the fine-grained bed drape sediment samples, respectively, identifying the most active erosional zones spatially. The statistical error between known and predicted spatial source contributions using virtual mixture tests for both size fractions demonstrated the importance of using multiple different composite fingerprints to decrease the model prediction uncertainties. Despite the difficult terrain in such data sparse areas, the source fingerprinting approach provides a basis for assembling new evidence which, in turn, is of interest to scientists and managers alike.

Integrated Fecal Microbiome and Serum Metabolomics Analysis Reveals Abnormal Changes in Rats with Immunoglobulin A Nephropathy and the Intervention Effect of Zhen Wu Tang

Immunoglobulin A nephropathy (IgAN), an autoimmune renal disease with complicated pathogenesis, is one of the principal reasons for end-stage renal disease in the clinic. Evidence has linked apparent alterations in the components of the microbiome and metabolome to renal disease in rats. However, thus far, there is insufficient evidence that supports the potential relationship between gut microbiome, circulating metabolites, and IgAN. This study was designed to probe the effects of IgAN on intestinal microecology and metabolic phenotypes and to understand the possible underlying mechanisms. Fecal and serum samples were collected from IgAN rats. Composition of the gut microbiota and biochemical changes in the metabolites was analyzed using 16S rDNA sequencing and untargeted metabolomics. The IgAN rats exhibited renal insufficiency and increased concentration of 24-h urine protein, in addition to deposition of IgA and IgG immune complexes in the kidney tissues. There was a disturbance in the balance of gut microbiota in IgAN rats, which was remarkably associated with renal damage. Marked changes in microbial structure and function were accompanied by apparent alterations in 1,403 serum metabolites, associated with the disorder of energy, carbohydrate, and nucleotide metabolisms. Administration of Zhen Wu Tang ameliorated microbial dysbiosis and attenuated the renal damage. Besides, treatment with Zhen Wu Tang modulated the metabolic phenotype perturbation in case of gut microbiota dysbiosis in IgAN rats. In conclusion, these findings provided a comprehensive understanding of the potential relationship between the intestinal microbiota and metabolic phenotypes in rats with IgAN. Elucidation of the intestinal microbiota composition and metabolic signature alterations could identify predictive biomarkers for disease diagnosis and progression, which might contribute to providing therapeutic strategies for IgAN.

Validation of a noninvasive prognostic signature for allograft failure following BK virus associated nephropathy.

Identifying kidney transplant recipients at risk for graft failure following BK virus nephropathy (BKVN) may allow personalization of therapy. We have reported that a noninvasive composite signature of urinary cell level of plasminogen activator inhibitor-1(PAI-1) mRNA and serum creatinine level, measured at the time of BKVN diagnosis, is prognostic of graft failure. In this investigation, we determined whether the composite signature is prognostic of graft failure in an independent cohort of 25 patients with BKVN. Of the 25 patients, 8 developed graft failure and 17 did not. We measured urinary cell levels of PAI-1 mRNA, 18S rRNA, and BKV VP1 mRNA at the time of BKVN diagnosis and evaluated clinical parameters including Banff pathology scores, acute rejection, and graft function. The area under the receiver operating characteristic curve for the noninvasive composite signature was 0.95 (P<.001) for prognosticating graft failure. The previously reported threshold of -0.858 predicted graft failure with a sensitivity of 75% and a specificity of 94%. Our current study validates the use of composite signature and the threshold of -0.858 to identify those at risk for graft failure following BKVN diagnosis, and supports future studies utilizing the composite signature score to personalize treatment of BKVN.

Radiomic signatures to predict survival in patients with advanced hepatocellular carcinoma (HCC) treated with sorafenib +/- doxorubicin: Correlative science from CALGB 80802 (Alliance).

343 Background: Alliance/CALGB 80802, a randomized phase III trial, evaluated sorafenib plus doxorubicin vs. doxorubicin in pts with HCC and showed no improvement in median overall survival (OS) (HR[95CI] 1.05[0.83-1.31]) or PFS (HR[95CI] 0.93[0.75-1.16]). In HCC surrogacy of tumor response with OS remains controversial, in part due to varying criteria used for response evaluation (e.g., RECIST1.1 and mRECIST). We evaluated the performance of several models to predict OS using pretreatment clinical and radiomic variables. Methods: In CALBG 80802, we segmented all measurable tumor lesions on sequential CT scans. A lesion’s imaging phenotype was deciphered with 23 uncorrelated quantitative imaging features measured at baseline and week (wk) 10 (first follow-up). An OS landmark survival analysis was conducted at wk 10. Patients were randomly assigned (3:1) to training (n = 92) and validation (n = 37) sets. In a training set, 6 random forest predictive models (6 signatures) used features that best predicted OS using 3 sets of variables: radiomics only (n = 23), clinical only (n = 9), radiomics and clinical (n = 32). Two time points (baseline only or baseline + wk 10) were assessed. Each signature's output was an individualized prediction and a continuous value ranging from 0 to 1 (from most to least favorable predicted OS). The primary endpoint was to compare these models' performance to predict OS using error rate (Harrell's concordance-index) in the validation set. Results: Of the 6 training signatures evaluated, the one achieving the highest performance in the validation set was an 8-feature signature combining radiomics and clinical variables measured at two time points (baseline + wk 10) with an error rate of 35.6%. The variables [rank of importance] (table) selected by the signature included baseline clinical features (albumin[1], AFP[2], Child-Pugh[4]), baseline radiomics features (component 17[3], component 1[5], component 9[7], tumor volume[8]) and wk 10 radiomics features (delta tumor volume[6]). Variable delta tumor volume [6] used a more enhanced estimation of tumor burden at baseline and a delta tumor volumetric measurement; compared to RECIST1.1 measurement of percentage change in unidimensional measurement of a subset of target lesions. The four quartiles of the signature were significantly associated with OS (Log-Rank, P &lt; 0.0001). Conclusions: The selected combined radiomic and clinical composite signature provided the best prediction for OS in the 80802 study patients’ population. It is a suggested way forward to go beyond single anatomic measurement techniques such as RECIST or mRECIST. [Table: see text]

Integrated gut virome and bacteriome dynamics in COVID-19 patients

ABSTRACT SARS-CoV-2 is the cause of the current global pandemic of COVID-19; this virus infects multiple organs, such as the lungs and gastrointestinal tract. The microbiome in these organs, including the bacteriome and virome, responds to infection and might also influence disease progression and treatment outcome. In a cohort of 13 COVID-19 patients in Beijing, China, we observed that the gut virome and bacteriome in the COVID-19 patients were notably different from those of five healthy controls. We identified a bacterial dysbiosis signature by observing reduced diversity and viral shifts in patients, and among the patients, the bacterial/viral compositions were different between patients of different severities, although these differences are not entirely distinguishable from the effect of antibiotics. Severe cases of COVID-19 exhibited a greater abundance of opportunistic pathogens but were depleted for butyrate-producing groups of bacteria compared with mild to moderate cases. We replicated our findings in a mouse COVID-19 model, confirmed virome differences and bacteriome dysbiosis due to SARS-CoV-2 infection, and observed that immune/infection-related genes were differentially expressed in gut epithelial cells during infection, possibly explaining the virome and bacteriome dynamics. Our results suggest that the components of the microbiome, including the bacteriome and virome, are affected by SARS-CoV-2 infections, while their compositional signatures could reflect or even contribute to disease severity and recovery processes.

The effect of probiotics supplementation in postoperative cancer patients: a prospective pilot study.

PurposeMicrobiota manipulation through selected probiotics may be a promising tool to prevent cancer development as well as onset, to improve clinical efficacy for cancer treatments. The purpose of this study was to evaluate change in microbiota composition after-probiotics supplementation and assessed the efficacy of probiotics in improving quality of life (QOL) in postoperative cancer patients.MethodsStool samples were collected from 30 cancer patients from February to October 2020 before (group I) and after (group II) 8 weeks of probiotics supplementation. We performed 16S ribosomal RNA gene sequencing to evaluate differences in gut microbiota between groups by comparing gut microbiota diversity, overall composition, and taxonomic signature abundance. The health-related QOL was evaluated through the EORTC Quality of life Questionnaire Core 30 questionnaire.ResultsStatistically significant differences were noted in group II; increase of Shannon and Simpson index (P = 0.004 and P = 0.001), decrease of Bacteroidetes and Fusobacteria at the phylum level (P = 0.032 and P = 0.014, retrospectively), increased of beneficial bacteria such as Weissella (0.096% vs. 0.361%, P < 0.004), Lactococcus (0.023% vs. 0.16%, P < 0.001), and Catenibacterium (0.0% vs. 0.005%, P < 0.042) at the genus level. There was a significant improvement in sleep disturbance (P = 0.039) in group II.ConclusionGut microbiota in cancer patients can be manipulated by specific probiotic strains, result in an altered microbiota. Microbiota modulation by probiotics can be considered as part of a supplement that helps to increase gut microbiota diversity and improve QOL in cancer patients after surgery.

Angkorian Khmer Stoneware: Production and Provenance

From ~900 to 1450 CE the Angkorian Khmer state extended control over much of inland Southeast Asia. This economically complex polity supported a large number and a diverse range of specialist producers across its territory. Given the limited types of textual data, our understanding of the Angkorian Khmer economy is heavily reliant on appropriate archaeological data to address key issues such as the relationship between specialist producers and the Angkorian elite. Here we address the production side of this question through elemental characterization (Neutron Activation Analysis) of a large sample of high temperature ceramics - stonewares - (~1000) from 15 Angkorian Khmer complexes in Cambodia and Thailand. In the majority of cases we can identify kiln-specific compositional signatures as the groundwork for the next stage of analysis: studying the consumption-side dynamics of Angkorian stoneware distribution. The study also highlights the spatial resolution of stoneware NAA possible in this context. Together, defining patterns of stoneware production, distribution and consumption will allow a new bottom-up perspective on the operation of the Angkorian Khmer political and ritual economy.

Three Years of High Time-resolution Air Pollution Monitoring in the Complex Multi-source Harbor of New York and New Jersey.

In densely developed port areas with numerous emissions sources, relating measured air quality changes to emissions is challenging given the geographic density of sources without unique pollutant composition signatures. To better understand air quality during increasing emission controls at the Port of New York and New Jersey (“Port”), an air monitoring station was sited to minimize collinearity of sources along ordinal directions. The study area includes an international airport, interstate highway, port terminals and shipping lanes, and industrial sources, as well as typical urban emissions of a megacity. Because air flow travel time from sources to the monitor were usually much less than one hour, minute-by-minute, high-precision data were collected for three years (2013–2015) for sulfur dioxide (SO2), carbon monoxide (CO), oxides of nitrogen (NO, NO2), black carbon (BC), fine particulate matter (PM2.5), and meteorology (wind speed, wind direction, temperature, humidity). From summer 2014 to spring 2015, hourly metals data were also collected. A high degree of temporal variability was observed for pollutants associated with direct emissions, with highest hourly average coefficient of variation observed for NO (2.65), SO2 (1.45) and BC (1.21). Nonparametric trajectory analysis (NTA) was utilized to separate the source areas influencing the monitoring data and observe how they changed over time, with over 1.6 million trajectories computed in total. Comparing the last 5 quarters of the study to the first 5 quarters, concentrations at the monitoring site associated with three port-related geographic areas decreased by 34–41%, 11–17%, and 28–41% for SO2, NOx, and BC, respectively. Over the same period, indicators of shipping and cargo activity at the port remained relatively constant; therefore, a shift in emission factors is likely the cause of the change. This study demonstrates the value of high-time resolution, accurate monitoring data along with careful siting to understand source area influences.

A model of algal organic carbon distributions in the Pearl River estuary using the amino acid carbon isotope values

To better understand the sources and behavior of estuarine labile organic matter, we measured stable carbon isotope patterns of individual amino acids in suspended particles and surface sediments from the Pearl River Estuary in China; samples were taken along a salinity transect in December, 2016. Here we demonstrate that carbon isotope values (δ13C) of individual amino acids in these samples gradually increase with salinity downstream, reflecting the increase in δ13C values of algal-derived organic carbon along the salinity gradient. The isotopic difference between amino acids and bulk organic carbon varies, most likely due to changes in the relative contributions of algal-derived organic matter and refractory terrestrial input. In addition, algal-derived organic matter can consist of labile and semi-labile organic matter in varied proportions depending on degradation state. This isotopic difference between amino acids and bulk organic carbon is much larger in surface sediments than in suspended particles, suggesting that labile organic carbon contributed more to suspended particles than to sediments. Using the relative abundances and δ13C ratios of amino acids and total organic carbon, a Lability Model was constructed to evaluate the relative contributions of three forms of estuarine organic carbon: labile algal material as amino acids, semi-labile algal material as lipids and acid-insoluble material, and refractory terrestrial organic material. The model suggests highly dynamic contributions of semi-labile algal-derived organic carbon and terrestrial organic carbon to estuarine particulate organic carbon. This evaluation of organic carbon sources illustrates the importance of decomposition in shaping the molecular composition and isotopic signature of particulate organic carbon in the estuary.

Identification of a Synthetic Lethal Relationship between Nucleotide Excision Repair Deficiency and Irofulven Sensitivity in Urothelial Cancer

Cisplatin-based chemotherapy is a first-line treatment for muscle-invasive and metastatic urothelial cancer. Approximately 10% of bladder urothelial tumors have a somatic missense mutation in the nucleotide excision repair (NER) gene, ERCC2, which confers increased sensitivity to cisplatin-based chemotherapy. However, a significant subset of patients is ineligible to receive cisplatin-based therapy due to medical contraindications, and no NER-targeted approaches are available for platinum-ineligible or platinum-refractory ERCC2-mutant cases. We used a series of NER-proficient and NER-deficient preclinical tumor models to test sensitivity to irofulven, an abandoned anticancer agent. In addition, we used available clinical and sequencing data from multiple urothelial tumor cohorts to develop and validate a composite mutational signature of ERCC2 deficiency and cisplatin sensitivity. We identified a novel synthetic lethal relationship between tumor NER deficiency and sensitivity to irofulven. Irofulven specifically targets cells with inactivation of the transcription-coupled NER (TC-NER) pathway and leads to robust responses in vitro and in vivo, including in models with acquired cisplatin resistance, while having minimal effect on cells with intact NER. We also found that a composite mutational signature of ERCC2 deficiency was strongly associated with cisplatin response in patients and was also associated with cisplatin and irofulven sensitivity in preclinical models. Tumor NER deficiency confers sensitivity to irofulven, a previously abandoned anticancer agent, with minimal activity in NER-proficient cells. A composite mutational signature of NER deficiency may be useful in identifying patients likely to respond to NER-targeting agents, including cisplatin and irofulven.See related commentary by Jiang and Greenberg, p. 1833.

Nitrogen-Doped Titanium Dioxide Nanoparticles Modified by An Electron Beam for Improving Human Breast Cancer Detection by Raman Spectroscopy: A Preliminary Study.

Titanium dioxide (TiO2) is commonly used as a pigment in paints, paper products, polymer compositions, and cosmetic products, and even as a food additive or drug coating material. In recent times, it has also been used in photovoltaic cells, semiconductors, biomedical devices, and air purification. In this paper, the potential application of nitrogen-doped TiO2 nanoparticles modified by an electron beam for improving human breast cancer detection by Raman spectroscopy is presented. Raman spectroscopy (RS) is a promising noninvasive analytical technique in cancer detection that enables us to retrieve a molecular signature of the biochemical composition of cancerous tissue. However, RS still has some challenges in signal detection, mainly related to strong concurrent background fluorescence from the analyzed tissue. The Raman signal scattering is several orders of magnitude smaller than the fluorescence intensity, and strong fluorescence masks a much weaker Raman signal. The Raman results demonstrate that the N-doped TiO2 electron beam-irradiated nanoparticles amplify the Raman scattering. The intrinsic properties of the adsorbed molecules from human breast tissue and the surface properties of the N-doped TiO2 electron beam-irradiated nanoparticles (the excited electron–hole pair at the surface) have a significant effect on the enhanced Raman signal intensity.

Free Kleene algebras with domain

First we identify the free algebras of the class of algebras of binary relations equipped with the composition and domain operations. Elements of the free algebras are pointed labelled finite rooted trees. Then we extend to the analogous case when the signature includes all the Kleene algebra with domain operations; that is, we add union and reflexive transitive closure to the signature. In this second case, elements of the free algebras are ‘regular’ sets of the trees of the first case. As a corollary, the axioms of domain semirings provide a finite quasiequational axiomatisation of the equational theory of algebras of binary relations for the intermediate signature of composition, union, and domain. Next we note that our regular sets of trees are not closed under complement, but prove that they are closed under intersection. Finally, we prove that under relational semantics the equational validities of Kleene algebras with domain form a decidable set.

A predictable conserved DNA base composition signature defines human core DNA replication origins

DNA replication initiates from multiple genomic locations called replication origins. In metazoa, DNA sequence elements involved in origin specification remain elusive. Here, we examine pluripotent, primary, differentiating, and immortalized human cells, and demonstrate that a class of origins, termed core origins, is shared by different cell types and host ~80% of all DNA replication initiation events in any cell population. We detect a shared G-rich DNA sequence signature that coincides with most core origins in both human and mouse genomes. Transcription and G-rich elements can independently associate with replication origin activity. Computational algorithms show that core origins can be predicted, based solely on DNA sequence patterns but not on consensus motifs. Our results demonstrate that, despite an attributed stochasticity, core origins are chosen from a limited pool of genomic regions. Immortalization through oncogenic gene expression, but not normal cellular differentiation, results in increased stochastic firing from heterochromatin and decreased origin density at TAD borders.

Collisional history of Ryugu’s parent body from bright surface boulders

The asteroid (162173) Ryugu and other rubble-pile asteroids are likely re-accumulated fragments of much larger parent bodies that were disrupted by impacts. However, the collisional and orbital pathways from the original parent bodies to subkilometre rubble-pile asteroids are not yet well understood1–3. Here we use Hayabusa2 observations to show that some of the bright boulders on the dark, carbonaceous (C-type) asteroid Ryugu4 are remnants of an impactor with a different composition as well as an anomalous portion of its parent body. The bright boulders on Ryugu can be classified into two spectral groups: most are featureless and similar to Ryugu’s average spectrum4,5, while others show distinct compositional signatures consistent with ordinary chondrites—a class of meteorites that originate from anhydrous silicate-rich asteroids6. The observed anhydrous silicate-like material is likely the result of collisional mixing between Ryugu’s parent body and one or multiple anhydrous silicate-rich asteroid(s) before and during Ryugu’s formation. In addition, the bright boulders with featureless spectra and less ultraviolet upturn are consistent with thermal metamorphism of carbonaceous meteorites7,8. They might sample different thermal-metamorphosed regions, which the returned sample will allow us to verify. Hence, the bright boulders on Ryugu provide new insights into the collisional evolution and accumulation of subkilometre rubble-pile asteroids. The Hayabusa2 team has discovered two types of bright boulder on the dark, carbonaceous asteroid Ryugu. One type has a spectrum consistent with material from an anhydrous silicate-rich asteroid, likely introduced by one or more collisions in Ryugu’s past.

Kidney Tertiary Lymphoid Structures in Lupus Nephritis Develop into Large Interconnected Networks and Resemble Lymph Nodes in Gene Signature

Immune aggregates organized as tertiary lymphoid structures (TLS) are observed within the kidneys of patients with systemic lupus erythematosus and lupus nephritis (LN). Renal TLS was characterized in lupus-prone New Zealand black × New Zealand white F1 mice analyzing cell composition and vessel formation. RNA sequencing was performed on transcriptomes isolated from lymph nodes, macrodissected TLS from kidneys, and total kidneys of mice at different disease stages by using a personal genome machine and RNA sequencing. Formation of TLS was found in anti-double-stranded DNA antibody-positive mice, and the structures were organized as interconnected large networks with distinct T/B cell zones with adjacent dendritic cells, macrophages, plasma cells, high endothelial venules, supporting follicular dendritic cells network, and functional germinal centers. Comparison of gene profiles of whole kidney, renal TLS, and lymph nodes revealed a similar gene signature of TLS and lymph nodes. The up-regulated genes within the kidneys of lupus-prone mice during LN development reflected TLS formation, whereas the down-regulated genes were involved in metabolic processes of the kidney cells. A comparison with human LN gene expression revealed similar up-regulated genes asobserved during the development of murine LN and TLS. In conclusion, kidney TLS have a similar cell composition, structure, and gene signature as lymph nodes and therefore may function as a kidney-specific type of lymph node.

When should we order a next generation sequencing test in a patient with cancer?

Technical advances in genome sequencing and the implementation of next-generation sequencing (NGS) in clinical oncology have paved the way for individualizing cancer patient therapy based on molecular profiles. When and how to use NGS testing in the clinic is at present an unsolved issue, although new research results provide evidence favoring this approach in some types of advanced cancer. Clinical research is evolving rapidly, from basket and umbrella trials to adaptative design precision oncology clinical studies, and genomic and molecular data often displace the classical clinical validation procedures of biomarkers. In this context, physicians must be aware of the clinical evidence behind these new biomarkers and NGS tests available, in order to use them in the right moment, and with a critical point of view. This review will present the status of currently available targeted drugs that can be effective based on actionable molecular alterations, and the NGS tests that are currently available, offering a practical guide for the application of Clinical Precision Oncology in the real world routine practice.

Plasma circulating miR-23~27~24 clusters correlate with the immunometabolic derangement and predict C-peptide loss in children with type 1 diabetes.

We aimed to analyse the association between plasma circulating microRNAs (miRNAs) and the immunometabolic profile in children with type 1 diabetes and to identify a composite signature of miRNAs/immunometabolic factors able to predict type 1 diabetes progression. Plasma samples were obtained from children at diagnosis of type 1 diabetes (n = 88) and at 12 (n = 32) and 24 (n = 30) months after disease onset and from healthy control children with similar sex and age distribution (n = 47). We quantified 60 robustly expressed plasma circulating miRNAs by quantitative RT-PCR and nine plasma immunometabolic factors with a recognised role at the interface of metabolic and immune alterations in type 1 diabetes. Based on fasting C-peptide loss over time, children with type 1 diabetes were stratified into the following groups: those who had lost >90% of C-peptide compared with diagnosis level; those who had lost <10% of C-peptide; those showing an intermediate C-peptide loss. To evaluate the modulation of plasma circulating miRNAs during the course of type 1 diabetes, logistic regression models were implemented and the correlation between miRNAs and immunometabolic factors was also assessed. Results were then validated in an independent cohort of children with recent-onset type 1 diabetes (n = 18). The prognostic value of the identified plasma signature was tested by a neural network-based model. Plasma circulating miR-23~27~24 clusters (miR-23a-3p, miR-23b-3p, miR-24-3p, miR-27a-3p and miR-27b-3p) were upmodulated upon type 1 diabetes progression, showed positive correlation with osteoprotegerin (OPG) and were negatively correlated with soluble CD40 ligand, resistin, myeloperoxidase and soluble TNF receptor in children with type 1 diabetes but not in healthy children. The combination of plasma circulating miR-23a-3p, miR-23b-3p, miR-24-3p, miR-27b-3p and OPG, quantified at disease onset, showed a significant capability to predict the decline in insulin secretion 12months after disease diagnosis in two independent cohorts of children with type 1 diabetes. We have pinpointed a novel miR-23a-3p/miR-23b-3p/miR-24-3p/miR-27b-3p/OPG plasma signature that may be developed into a novel blood-based method to better stratify patients with type 1 diabetes and predict C-peptide loss.

Caloric Restriction Alters Bone Marrow Adiposity And Energy Metabolism

BACKGROUND: Bone marrow adipose tissue (bMAT) refers to mesenchymal stem cell-derived adipocytes located within the bone marrow cavity. In adult humans, bMAT comprises ~15% of total body adiposity and is primarily located throughout the appendicular skeleton. bMAT is an extremely ‘plastic’ depot that rapidly responds to fluctuations in nutrient sensing and energetic homeostasis. Paradoxically, bMAT levels increase during both obesity and caloric restriction (CR); however, it is unclear whether the qualitative phenotype of bMAT differs under these conditions. PURPOSE: To identify obesity- and CR-induced alterations in bMAT lipid composition, transcriptional profile, and metabolic signature. METHODS: Male 6-week-old genetically obese ob/ob mice (leptin deficient) were housed at 32°C (thermoneutral) for 10 weeks. One group of mice was fed ad libitum (AL; N=9) for the study duration, while a second group was calorically restricted (CR; N=9) to ~50% of the AL group to prevent excess weight gain. Femora and tibiae were collected for lipid composition (gas chromatography), gene expression analysis (qRT-PCR), and in situ metabolic phenotyping (MPLSM-FLIM). Blood was collected for assessment of circulating analytes. RESULTS: CR mice had lower body mass and blood glucose, and higher blood corticosterone compared to AL mice. CR increased femur adipocyte density and adipocyte size compared to AL. Tibia lipid composition differed between AL and CR mice (AL>CR C16:0, C:18:1n-9, C:18:1n-7, C20:4n-6; CR >AL C14:0, C16:1n-7, and C18:2n-6). CR upregulated the expression of adipokines (e.g., Adipoq, CFD), which occurred co-incidentally with elevated levels of serum adiponectin and adipsin. Transcriptional profiling revealed differential expression of genes involved in adipogenesis, lipid metabolism, mitochondrial activity, and antioxidant response (e.g., CR>AL SCD1, FASN, LIPE, LPL, KLF15, PPARGC1a, PPARa, and SOD1). MPLSM-FLIM revealed highly heterogenic metabolic phenotypes among cells within the bone marrow cavity. CONCLUSION: CR induces functional changes in bMAT that occur independent of leptin. bMAT lies at the interface of metabolic and inflammatory signaling mechanisms, and is a potential mediator of systemic metabolic and inflammatory homeostasis during health and disease.

Thoracic Imaging at Exacerbation of Chronic Obstructive Pulmonary Disease: A Systematic Review.

Exacerbations of chronic obstructive pulmonary disease (COPD) are currently diagnosed based on changes in respiratory symptoms. Characterizing the imaging manifestation of exacerbations could be useful for objective diagnosis of exacerbations in the clinic and clinical trials, as well as provide a mechanism for monitoring exacerbation treatment and recovery. In this systematic review, we employed a comprehensive search across three databases (Medline, EMBASE, Web of Science) to identify studies that performed imaging of the thorax at COPD exacerbation. We included 51 from a total of 5,047 articles which met all our inclusion criteria. We used an adapted version of the Modified Newcastle-Ottawa Quality Assessment Scale for cohort studies to assess the quality of the included studies. Conclusions were weighted towards higher-quality articles. We identified a total of 36 thoracic imaging features studied at exacerbation of COPD. Studies were generally heterogeneous in their measurements and focus. Nevertheless, considering studies which performed consecutive imaging at stable state and exacerbation, which scored highest for quality, we identified salient imaging biomarkers of exacerbations. An exacerbation is characterized by airway wall and airway calibre changes, hyperinflation, pulmonary vasoconstriction and imaging features suggestive of pulmonary arterial hypertension. Most information was gained from CT studies. We present the first ever composite imaging signature of COPD exacerbations. While imaging during an exacerbation is comparatively new and not comprehensively studied, it may uncover important insights into the acute pathophysiologic changes in the cardiorespiratory system during exacerbations of COPD, providing objective confirmation of events and a biomarker of recovery and treatment response.