Our previous research has demonstrated that mice lacking functional growth hormone‐releasing hormone (GHRH) exhibit distinct physiological characteristics, including an extended lifespan, a ...preference for lipid utilization during rest, mild hypoglycemia, and heightened insulin sensitivity. They also show a further increase in lifespan when subjected to caloric restriction. These findings suggest a unique response to fasting, which motivated our current study on the response to glucagon, a key hormone released from the pancreas during fasting that regulates glucose levels, energy expenditure, and metabolism. Our study investigated the effects of an acute glucagon challenge on female GHRH knockout mice and revealed that they exhibit reduced glucose production, likely due to suppressed gluconeogenesis. However, these mice showed an increase in energy expenditure. We also observed alterations in pancreatic islet architecture, with smaller islets and a reduction of insulin‐producing beta cells but no changes in glucagon‐producing alpha cells. Additionally, the analysis of hepatic glucagon signaling showed a decrease in glucagon receptor expression and phosphorylated CREB. In conclusion, our findings suggest that the unique metabolic phenotype observed in these long‐lived mice may be partly explained by changes in glucagon signaling. Further exploration of this pathway may lead to new insights into the regulation of longevity in mammals.
Our past research showed that mice without functional growth hormone‐releasing hormone (GHRH) have distinct traits like a longer lifespan and lipid‐based energy use. Our new study on these mice's response to glucagon, a fasting‐related hormone, revealed reduced glucose production, increased energy expenditure, and changes in pancreatic architecture. These findings suggest altered glucagon signaling may contribute to their unique metabolism and extended lifespan.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
2.
Type 2 diabetes Tate, A Rosemary
The Lancet (British edition),
03/2018, Volume:
391, Issue:
10127
Journal Article
Peer reviewed
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
New hybrid species might be expected to show patterns of gene expression intermediate to those shown by parental species 1, 2. “Transcriptomic shock” may also occur, in which gene expression is ...disrupted; this may be further modified by whole genome duplication (causing allopolyploidy) 3–16. “Shock” can include instantaneous partitioning of gene expression between parental copies of genes among tissues 16–19. These effects have not previously been studied at a population level in a natural allopolyploid plant species. Here, we survey tissue-specific expression of 144 duplicated gene pairs derived from different parental species (homeologs) in two natural populations of 40-generation-old allotetraploid Tragopogon miscellus (Asteraceae) plants. We compare these results with patterns of allelic expression in both in vitro “hybrids” and hand-crossed F1 hybrids between the parental diploids T. dubius and T. pratensis, and with patterns of homeolog expression in synthetic (S1) allotetraploids. Partitioning of expression was frequent in natural allopolyploids, but F1 hybrids and S1 allopolyploids showed less partitioning of expression than the natural allopolyploids and the in vitro “hybrids” of diploid parents. Our results suggest that regulation of gene expression is relaxed in a concerted manner upon hybridization, and new patterns of partitioned expression subsequently emerge over the generations following allopolyploidization.
► Allotetraploid T. miscellus plants show tissue-specific homeologous gene expression ► Diploid parents T. dubius and T. pratensis show tissue-specific gene expression ► Genes are globally activated by hybridization and little affected by polyploidization ► Tissue-specific expression emerges in 40 generations of natural allopolyploidy
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Electronic health records are invaluable for medical research, but much of the information is recorded as unstructured free text which is time-consuming to review manually.
To develop an algorithm to ...identify relevant free texts automatically based on labelled examples.
We developed a novel machine learning algorithm, the 'Semi-supervised Set Covering Machine' (S3CM), and tested its ability to detect the presence of coronary angiogram results and ovarian cancer diagnoses in free text in the General Practice Research Database. For training the algorithm, we used texts classified as positive and negative according to their associated Read diagnostic codes, rather than by manual annotation. We evaluated the precision (positive predictive value) and recall (sensitivity) of S3CM in classifying unlabelled texts against the gold standard of manual review. We compared the performance of S3CM with the Transductive Vector Support Machine (TVSM), the original fully-supervised Set Covering Machine (SCM) and our 'Freetext Matching Algorithm' natural language processor.
Only 60% of texts with Read codes for angiogram actually contained angiogram results. However, the S3CM algorithm achieved 87% recall with 64% precision on detecting coronary angiogram results, outperforming the fully-supervised SCM (recall 78%, precision 60%) and TSVM (recall 2%, precision 3%). For ovarian cancer diagnoses, S3CM had higher recall than the other algorithms tested (86%). The Freetext Matching Algorithm had better precision than S3CM (85% versus 74%) but lower recall (62%).
Our novel S3CM machine learning algorithm effectively detected free texts in primary care records associated with angiogram results and ovarian cancer diagnoses, after training on pre-classified test sets. It should be easy to adapt to other disease areas as it does not rely on linguistic rules, but needs further testing in other electronic health record datasets.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The predictability of evolution is debatable, with recent evidence suggesting that outcomes may be constrained by gene interaction networks 1. Whole-genome duplication (WGD; ...polyploidization—ubiquitous in plant evolution 2) provides the opportunity to evaluate the predictability of genome reduction, a pervasive feature of evolution 3, 4. Repeated patterns of genome reduction appear to have occurred via duplicated gene (homeolog) loss in divergent species following ancient WGD 5–9, with evidence for preferential retention of duplicates in certain gene classes 8–10. The speed at which these patterns arise is unknown. We examined presence/absence of 70 homeologous loci in 59 Tragopogon miscellus plants from five natural populations of independent origin; this allotetraploid arose ∼80 years ago via hybridization between diploid parents and WGD 11. Genes were repeatedly retained or lost in clusters, and the gene ontology categories of the missing genes correspond to those lost after ancient WGD in the same family (Asteraceae; sunflower family) 6 and with gene dosage sensitivity 8. These results provide evidence that the outcomes of WGD are predictable, even in 40 generations, perhaps due to the connectivity of gene products 8, 10, 12. The high frequency of single-allele losses detected and low frequency of changes fixed within populations provide evidence for ongoing evolution.
► Duplicate genes are rapidly lost in young allotetraploid T. miscellus populations ► Clusters of genes tend to be lost together repeatedly in independent populations ► Patterns of loss are similar to those in ancient polyploids of the same plant family ► The connectivity of gene products in networks may determine which genes are lost
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Hematopoietic stem cell transplantation (HSCT) is a curative therapy for blood and immune diseases with potential for many settings beyond current standard-of-care. Broad HSCT application is ...currently precluded largely due to morbidity and mortality associated with genotoxic irradiation or chemotherapy conditioning. Here we show that a single dose of a CD117-antibody-drug-conjugate (CD117-ADC) to saporin leads to > 99% depletion of host HSCs, enabling rapid and efficient donor hematopoietic cell engraftment. Importantly, CD117-ADC selectively targets hematopoietic stem cells yet does not cause clinically significant side-effects. Blood counts and immune cell function are preserved following CD117-ADC treatment, with effective responses by recipients to both viral and fungal challenges. These results suggest that CD117-ADC-mediated HSCT pre-treatment could serve as a non-myeloablative conditioning strategy for the treatment of a wide range of non-malignant and malignant diseases, and might be especially suited to gene therapy and gene editing settings in which preservation of immunity is desired.
Hematopoietic stem cell transplantation is a potential curative therapy for malignant and nonmalignant diseases. Improving the efficiency of stem cell collection and the quality of the cells acquired ...can broaden the donor pool and improve patient outcomes. We developed a rapid stem cell mobilization regimen utilizing a unique CXCR2 agonist, GROβ, and the CXCR4 antagonist AMD3100. A single injection of both agents resulted in stem cell mobilization peaking within 15 min that was equivalent in magnitude to a standard multi-day regimen of granulocyte colony-stimulating factor (G-CSF). Mechanistic studies determined that rapid mobilization results from synergistic signaling on neutrophils, resulting in enhanced MMP-9 release, and unexpectedly revealed genetic polymorphisms in MMP-9 that alter activity. This mobilization regimen results in preferential trafficking of stem cells that demonstrate a higher engraftment efficiency than those mobilized by G-CSF. Our studies suggest a potential new strategy for the rapid collection of an improved hematopoietic graft.
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•GROβ is well tolerated and induces mobilization in a first in-human study•Combination treatment with GROβ+AMD3100 results in rapid stem cell mobilization•Mouse strain nucleotide polymorphisms in MMP-9 alter biologic activity•Rapid mobilization releases a highly engraftable hematopoietic stem cell
A new strategy for stem cell mobilization enables rapid collection of an improved hematopoietic graft in humans.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Hematopoietic stem cell transplantation (HSCT) offers curative therapy for patients with hemoglobinopathies, congenital immunodeficiencies, and other conditions, possibly including AIDS. Autologous ...HSCT using genetically corrected cells would avoid the risk of graft-versus-host disease (GVHD), but the genotoxicity of conditioning remains a substantial barrier to the development of this approach. Here we report an internalizing immunotoxin targeting the hematopoietic-cell-restricted CD45 receptor that effectively conditions immunocompetent mice. A single dose of the immunotoxin, CD45-saporin (SAP), enabled efficient (>90%) engraftment of donor cells and full correction of a sickle-cell anemia model. In contrast to irradiation, CD45-SAP completely avoided neutropenia and anemia, spared bone marrow and thymic niches, enabling rapid recovery of T and B cells, preserved anti-fungal immunity, and had minimal overall toxicity. This non-genotoxic conditioning method may provide an attractive alternative to current conditioning regimens for HSCT in the treatment of non-malignant blood diseases.
Signaling pathways are commonly organized through inducible protein-protein interactions, mediated by adaptor proteins that link activated receptors to cytoplasmic effectors. However, we have little ...quantitative data regarding the kinetics with which such networks assemble and dissolve to generate specific cellular responses. To address this deficiency, we designed a mass spectrometry method, affinity purification-selected reaction monitoring (AP-SRM), which we used to comprehensively and quantitatively investigate changes in protein interactions with GRB2, an adaptor protein that participates in a remarkably diverse set of protein complexes involved in multiple aspects of cellular function. Our data reliably define context-specific and time-dependent networks that form around GRB2 after stimulation, and reveal core and growth factor-selective complexes comprising 90 proteins identified as interacting with GRB2 in HEK293T cells. Capturing a key hub protein and dissecting its interactions by SRM should be equally applicable to quantifying signaling dynamics for a range of hubs in protein interaction networks.
Predicting which children will go on to develop mental health symptoms as adolescents is critical for early intervention and preventing future, severe negative outcomes. Although many aspects of a ...child's life, personality, and symptoms have been flagged as indicators, there is currently no model created to screen the general population for the risk of developing mental health problems. Additionally, the advent of machine learning techniques represents an exciting way to potentially improve upon the standard prediction modelling technique, logistic regression. Therefore, we aimed to I.) develop a model that can predict mental health problems in mid-adolescence II.) investigate if machine learning techniques (random forest, support vector machines, neural network, and XGBoost) will outperform logistic regression.
In 7,638 twins from the Child and Adolescent Twin Study in Sweden we used 474 predictors derived from parental report and register data. The outcome, mental health problems, was determined by the Strengths and Difficulties Questionnaire. Model performance was determined by the area under the receiver operating characteristic curve (AUC).
Although model performance varied somewhat, the confidence interval overlapped for each model indicating non-significant superiority for the random forest model (AUC = 0.739, 95% CI 0.708-0.769), followed closely by support vector machines (AUC = 0.735, 95% CI 0.707-0.764).
Ultimately, our top performing model would not be suitable for clinical use, however it lays important groundwork for future models seeking to predict general mental health outcomes. Future studies should make use of parent-rated assessments when possible. Additionally, it may not be necessary for similar studies to forgo logistic regression in favor of other more complex methods.
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