Mitochondrial C4375T mutation might be a molecular risk factor in a maternal Chinese hypertensive family under haplotype C.

Here, we reported a Han Chinese essential hypertensive pedigree based on clinical hereditary and molecular data. To know the molecular basis on this family, mitochondrial genome of one proband from the family was identified through direct sequencing analysis. The age of onset year and affected degree of patients are different in this family. And matrilineal family members carrying C4375T mutation and belong to Eastern Asian halopgroup C. Phylogenetic analysis shows 4375C is highly conservative in 17 species. It is suggested that these mutations might participate in the development of hypertension in this family. And halopgroup C might play a modifying role on the phenotype in this Chinese hypertensive family.

[Expression and significance of c-FLIP protein in sepsis mice with acute kidney injury].

OBJECTIVE: To observe the expression of cellular Fas-associated death domain-like interleukin-1ß converting enzyme inhibit protein (c-FLIP) in sepsis mice with acute kidney injury (SAKI) and explore its significance. METHODS: Thirty male ICR mice were divided into the normal control group (Normal group), sham operation group (Sham group) and SAKI group by random number table method, with 10 mice in each group. The SAKI model of mice was established by cecal ligation and puncture (CLP); the Sham group was not ligated and the cecum was not punctured, and other surgical procedures were the same as the SAKI group; the Normal group did not experience any treatment. The serum and renal tissues of mice in each group were harvested 24 hours after CLP model establishment. The levels of serum creatinine (SCr) and blood urea nitrogen (BUN) were detected by enzyme linked immunosorbent assay (ELISA). The renal tissues were stained with hematoxylin-eosin (HE), and the pathological changes of renal tissues were observed under light microscope and the severity of injury was determined. The expression of c-FLIP in renal tissues was detected by immunohistochemistry. The expression of c-FLIP, Bax and caspase-3 protein in renal tissue was detected by Western Blot. The correlation between c-FLIP expression and Bax, caspase-3 protein expressions in renal tissues were analyzed by Pearson test. RESULTS: In the Normal group and the Sham group, the renal tubular epithelial cells were regular and intact, and no interstitial inflammatory cell infiltration was observed; the renal injury score was both 1.30±0.48; immunohistochemistry showed a large amount of c-FLIP positive expression in renal tubular epithelial cells (IA: 120.20±3.87, 116.70±3.46); Western Blot showed high expression of c-FLIP in renal tissues (c-FLIP/GAPDH: 0.99±0.01, 0.98±0.02), and low expressions of Bax and caspase-3 (Bax/GAPDH: 0.16±0.04, 0.19±0.03, caspase-3/GAPDH: 0.24±0.04, 0.23±0.05). Compared with the Sham group, in the SAKI group, renal tubular epithelial cells were degenerated and necrosis, and a large number of interstitial inflammatory cells infiltrated, the renal injury score was significantly increased (4.60±0.52 vs. 1.30±0.48, P < 0.01); the levels of SCr and BUN were significantly increased [SCr (µmol/L): 193.90±13.54 vs. 24.50±3.78, BUN (mmol/L): 81.60±7.26 vs. 5.20±0.92, both P < 0.01]; the c-FLIP positive cells in renal tissues was significantly reduced (IA: 17.11±0.82 vs. 116.70±3.46, P < 0.01); the expression of c-FLIP protein in renal tissues was significantly decreased (c-FLIP/GAPDH: 0.29±0.03 vs. 0.98±0.02, P < 0.01), while the expressions of Bax and caspase-3 protein were significantly increased (Bax/GAPDH: 0.87±0.06 vs. 0.19±0.03, caspase-3/GAPDH: 0.88±0.07 vs. 0.23±0.05, both P < 0.01]. The correlation analysis showed that the c-FLIP protein was significantly negatively correlated with Bax (r = -0.468, P = 0.029) and caspase-3 protein expressions (r = -0.663, P = 0.004). CONCLUSIONS: The expression level of c-FLIP protein was significantly down-regulated in renal tissue of SAKI, and its down-regulation mechanism was associated with increased apoptosis of renal tubular epithelial cells, which could be an effective target for the treatment of SAKI.

Efficient algorithms for segmenting globally optimal and smooth multi-surfaces.

Despite extensive studies in the past, the problem of segmenting globally optimal single and multiple surfaces in 3D volumetric images remains challenging in medical imaging. The problem becomes even harder in highly noisy and edge-weak images. In this paper we present a novel and highly efficient graph-theoretical iterative method with bi-criteria of global optimality and smoothness for both single and multiple surfaces. Our approach is based on a volumetric graph representation of the 3D image that incorporates curvature information. To evaluate the convergence and performance of our method, we test it on a set of 14 3D OCT images. Our experiments suggest that the proposed method yields optimal (or almost optimal) solutions in 3 to 5 iterations. To the best of our knowledge, this is the first algorithm that utilizes curvature in objective function to ensure the smoothness of the generated surfaces while striving for achieving global optimality. Comparing to the best existing approaches, our method has a much improved running time, yields almost the same global optimality but with much better smoothness, which makes it especially suitable for segmenting highly noisy images.

Computing maximum association graph in microscopic nucleus images.

In this paper, we study the problem of finding organization patterns of chromosomes inside the cell nucleus from microscopic nucleus images. Emerging evidence from cell biology research suggests that global chromosome organization has a vital role in fundamental cell processes related to gene expression and regulation. To understand how chromosome territories are neighboring (or associated) to each other, in this paper we present a novel technique for computing a common association pattern, represented as a Maximum Association Graph (MAG), from the nucleus images of a population of cells. Our approach is based on an interesting integer linear programming formulation of the problem and utilizes inherent observations of the problem to yield optimal solutions. A two-stage technique is also introduced for producing near optimal approximations for large data sets.