88 research outputs found

    Accounting for density reduction and structural loss in standing dead trees: Implications for forest biomass and carbon stock estimates in the United States

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    <p>Abstract</p> <p>Background</p> <p>Standing dead trees are one component of forest ecosystem dead wood carbon (C) pools, whose national stock is estimated by the U.S. as required by the United Nations Framework Convention on Climate Change. Historically, standing dead tree C has been estimated as a function of live tree growing stock volume in the U.S.'s National Greenhouse Gas Inventory. Initiated in 1998, the USDA Forest Service's Forest Inventory and Analysis program (responsible for compiling the Nation's forest C estimates) began consistent nationwide sampling of standing dead trees, which may now supplant previous purely model-based approaches to standing dead biomass and C stock estimation. A substantial hurdle to estimating standing dead tree biomass and C attributes is that traditional estimation procedures are based on merchantability paradigms that may not reflect density reductions or structural loss due to decomposition common in standing dead trees. The goal of this study was to incorporate standing dead tree adjustments into the current estimation procedures and assess how biomass and C stocks change at multiple spatial scales.</p> <p>Results</p> <p>Accounting for decay and structural loss in standing dead trees significantly decreased tree- and plot-level C stock estimates (and subsequent C stocks) by decay class and tree component. At a regional scale, incorporating adjustment factors decreased standing dead quaking aspen biomass estimates by almost 50 percent in the Lake States and Douglas-fir estimates by more than 36 percent in the Pacific Northwest.</p> <p>Conclusions</p> <p>Substantial overestimates of standing dead tree biomass and C stocks occur when one does not account for density reductions or structural loss. Forest inventory estimation procedures that are descended from merchantability standards may need to be revised toward a more holistic approach to determining standing dead tree biomass and C attributes (i.e., attributes of tree biomass outside of sawlog portions). Incorporating density reductions and structural loss adjustments reduces uncertainty associated with standing dead tree biomass and C while improving consistency with field methods and documentation.</p

    Recessive mutations in the INS gene result in neonatal diabetes through reduced insulin biosynthesis

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    Heterozygous coding mutations in the INS gene that encodes preproinsulin were recently shown to be an important cause of permanent neonatal diabetes. These dominantly acting mutations prevent normal folding of proinsulin, which leads to beta-cell death through endoplasmic reticulum stress and apoptosis. We now report 10 different recessive INS mutations in 15 probands with neonatal diabetes. Functional studies showed that recessive mutations resulted in diabetes because of decreased insulin biosynthesis through distinct mechanisms, including gene deletion, lack of the translation initiation signal, and altered mRNA stability because of the disruption of a polyadenylation signal. A subset of recessive mutations caused abnormal INS transcription, including the deletion of the C1 and E1 cis regulatory elements, or three different single base-pair substitutions in a CC dinucleotide sequence located between E1 and A1 elements. In keeping with an earlier and more severe beta-cell defect, patients with recessive INS mutations had a lower birth weight (-3.2 SD score vs. -2.0 SD score) and were diagnosed earlier (median 1 week vs. 10 weeks) compared to those with dominant INS mutations. Mutations in the insulin gene can therefore result in neonatal diabetes as a result of two contrasting pathogenic mechanisms. Moreover, the recessively inherited mutations provide a genetic demonstration of the essential role of multiple sequence elements that regulate the biosynthesis of insulin in man

    IGF-I activates caspases 3/7, 8 and 9 but does not induce cell death in colorectal cancer cells

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    Background: Colorectal cancer is the third most common cancer in the western world. Chemotherapy is often ineffective to treat the advanced colorectal cancers due to the chemoresistance. A major contributor to chemo-resistance is tumour-derived inhibition or avoidance of apoptosis. Insulin-like growth factor I (IGF-I) has been known to play a prominent role in colorectal cancer development and progression. The role of IGF-I in cancer cell apoptosis is not completely understood.Methods: Using three colorectal cancer cell lines and one muscle cell line, associations between IGF-I and activities of caspase 3/7, 8 and 9 have been examined; the role of insulin-like growth factor I receptor (IGF-IR) in the caspase activation has been investigated.Results: The results show that exogenous IGF-I significantly increases activity of caspases 3/7, 8 and 9 in all cell lines used; blocking IGF-I receptor reduce IGF-I-induced caspase activation. Further studies demonstrate that IGF-I induced caspase activation does not result in cell death. This is the first report to show that while IGF-I activates caspases 3/7, 8 and 9 it does not cause colorectal cancer cell death.Conclusion: The study suggests that caspase activation is not synonymous with apoptosis and that activation of caspases may not necessarily induce cell death

    Detection and Characterization of CD133+ Cancer Stem Cells in Human Solid Tumours

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    Osteosarcoma is the most common primary tumour of bone. Solid tumours are made of heterogeneous cell populations, which display different goals and roles in tumour economy. A rather small cell subset can hold or acquire stem potentials, gaining aggressiveness and increasing expectancy of recurrence. The CD133 antigen is a pentaspan membrane glycoprotein, which has been proposed as a cancer stem cell marker, since it has been previously demonstrated to be capable of identifying a cancer initiating subpopulation in brain, colon, melanoma and other solid tumours. Therefore, our aim was to observe the possible presence of cells expressing the CD133 antigen within solid tumour cell lines of osteosarcoma and, then, understand their biological characteristics and performances.In this study, using SAOS2, MG63 and U2OS, three human sarcoma cell lines isolated from young Caucasian subjects, we were able to identify and characterize, among them, CD133+ cells showing the following features: high proliferation rate, cell cycle detection in a G2\M phase, positivity for Ki-67, and expression of ABCG2 transporters. In addition, at the FACS, we were able to observe the CD133+ cell fraction showing side population profile and forming sphere-clusters in serum-free medium with a high clonogenic efficiency.Taken together, our findings lead to the thought that we can assume that we have identified, for the first time, CD133+ cells within osteosarcoma cell lines, showing many features of cancer stem cells. This can be of rather interest in order to design new therapies against the bone cancer

    Renal malformations associated with mutations of developmental genes: messages from the clinic

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    Renal tract malformations (RTMs) account for about 40% of children with end-stage renal failure. RTMs can be caused by mutations of genes normally active in the developing kidney and lower renal tract. Moreover, some RTMs occur in the context of multi-organ malformation syndromes. For these reasons, and because genetic testing is becoming more widely available, pediatric nephrologists should work closely with clinical geneticists to make genetic diagnoses in children with RTMs, followed by appropriate family counseling. Here we highlight families with renal cysts and diabetes, renal coloboma and Fraser syndromes, and a child with microdeletion of chromosome 19q who had a rare combination of malformations. Such diagnoses provide families with often long-sought answers to the question “why was our child born with kidney disease”. Precise genetic diagnoses will also help to define cohorts of children with RTMs for long-term clinical outcome studies
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