The design and synthesis of indazole and pyrazolopyridine based glucokinase activators for the treatment of Type 2 diabetes mellitus

Glucokinase activators represent a promising potential treatment for patients with Type 2 diabetes. Herein, we report the identification and optimization of a series of novel indazole and pyrazolopyridine based activators leading to the identification of 4-(6-(azetidine-1-carbonyl)-5-fluoropyridin-3-yloxy)-2-ethyl-N-(5-methylpyrazin-2-yl)-2H-indazole-6-carboxamide (42) as a potent activator with favorable preclinical pharmacokinetic properties and in vivo efficacy.     

Synthesis and evaluation of cytotoxic effects of novel α-methylenelactone tetracyclic diterpenoids

A series of tetracyclic diterpenoids bearing the α-methylenelactone group have been synthesized and screened for their in vitro anti-tumor activities against six human cancer cell lines. The results showed that compounds 1c, 2a and 2b exhibited significant cytotoxicity superior to the positive control doxorubicin hydrochloride against MDA-MB-231, K562 and HepG2 cell lines. In particular, compound 2b was identified as the most promising anticancer agent against HepG2 cells with IC(50) value of 0.09μM.     

Facile synthesis of a dimeric dipyrrole-polyamide and synergetic DNA-cleaving activity of its Cu(II) complex

Inspired by the potent DNA-cleaving activity of the Cu(II) complex of monopyrrole-polyamide dimer 1 (i.e., 1@Cu(2+)), we designed a new dimeric dipyrrole-polyamide analog 2 with the aim to optimize the catalytic activities of the metal complexes of this type of polypyrrole-polyamides. Compound 2 was prepared in 50% yield from the reaction of 1-methyl-4-[(1-methyl-4-nitro-1H-pyrrole-2-carbonyl)-amino]-1H-pyrrole-2-carboxylic acid with 2,2'-(ethane-1,2-diylbis(oxy))diethanamine, and fully characterized on the basis of NMR ((1)H and (13)C), MS (ESI and HR) and IR. Spectrophotometric titration, ESI-MS and conductivity measurements indicated that compound 2 formed a 1:1 complex with Cu(2+) ion (i.e., 2@Cu(2+)). Agarose gel electrophoresis studies indicated that 2@Cu(2+) was capable of efficiently converting pBR322 DNA into open circular and linear forms under physiological conditions, most probably via an oxidative mechanism. Its overall catalytic activity was estimated to be at least 30-fold higher than that of 1@Cu(2+). The fact that the cleaving activities of these Cu(II) complexes parallel, exactly, their binding affinities, raises the possibility that the cleaving activities of polypyrrole-polyamide derivatives of the type can be regulated by the binding affinities.     

The sex determination gene shows no founder effect in the giant honey bee, Apis dorsata

Background

All honey bee species (Apis spp) share the same sex determination mechanism using the complementary sex determination (csd) gene. Only individuals heterogeneous at the csd allele develop into females, and the homozygous develop into diploid males, which do not survive. The honeybees are therefore under selection pressure to generate new csd alleles. Previous studies have shown that the csd gene is under balancing selection. We hypothesize that due to the long separation from the mainland of Hainan Island, China, that the giant honey bees (Apis dorsata) should show a founder effect for the csd gene, with many different alleles clustered together, and these would be absent on the mainland.

Methodology/Principal Findings

We sampled A. dorsata workers from both Hainan and Guangxi Provinces and then cloned and sequenced region 3 of the csd gene and constructed phylogenetic trees. We failed to find any clustering of the csd alleles according to their geographical origin, i.e. the Hainan and Guangxi samples did not form separate clades. Further analysis by including previously published csd sequences also failed to show any clade-forming in both the Philippines and Malaysia.

Conclusions/Significance

Results from this study and those from previous studies did not support the expectations of a founder effect. We conclude that because of the extremely high mating frequency of A. dorsata queens, a founder effect does not apply in this species.     

Soil respiration in Tibetan alpine grasslands: belowground biomass and soil moisture, but not soil temperature, best explain the large-scale patterns

The Tibetan Plateau is an essential area to study the potential feedback effects of soils to climate change due to the rapid rise in its air temperature in the past several decades and the large amounts of soil organic carbon (SOC) stocks, particularly in the permafrost. Yet it is one of the most under-investigated regions in soil respiration (Rs) studies. Here, Rs rates were measured at 42 sites in alpine grasslands (including alpine steppes and meadows) along a transect across the Tibetan Plateau during the peak growing season of 2006 and 2007 in order to test whether: (1) belowground biomass (BGB) is most closely related to spatial variation in Rs due to high root biomass density, and (2) soil temperature significantly influences spatial pattern of Rs owing to metabolic limitation from the low temperature in cold, high-altitude ecosystems. The average daily mean Rs of the alpine grasslands at peak growing season was 3.92 μmol CO(2) m(-2) s(-1), ranging from 0.39 to 12.88 μmol CO(2) m(-2) s(-1), with average daily mean Rs of 2.01 and 5.49 μmol CO(2) m(-2) s(-1) for steppes and meadows, respectively. By regression tree analysis, BGB, aboveground biomass (AGB), SOC, soil moisture (SM), and vegetation type were selected out of 15 variables examined, as the factors influencing large-scale variation in Rs. With a structural equation modelling approach, we found only BGB and SM had direct effects on Rs, while other factors indirectly affecting Rs through BGB or SM. Most (80%) of the variation in Rs could be attributed to the difference in BGB among sites. BGB and SM together accounted for the majority (82%) of spatial patterns of Rs. Our results only support the first hypothesis, suggesting that models incorporating BGB and SM can improve Rs estimation at regional scale.     

Protective effect of apelin on cultured rat bone marrow mesenchymal stem cells against apoptosis

Bone marrow-derived mesenchymal stem cells (BMSCs) have shown great promise for ischemic tissue repair. However, poor viability of transplanted BMSCs within ischemic tissues has limited their therapeutic potential. Apelin, an endogenous peptide, whose level is elevated following ischemia, has been shown to enhance survival of cardiomyocytes and neuronal cells during ischemia. We hypothesized that apelin-13 protects BMSCs from apoptotic death. In this paper we determined the potential mechanism of apelin-13 effects using cultured BMSCs from adult rats. Apoptosis was induced by the specific apoptotic insult serum deprivation (SD) for up to 36 h. Apoptotic cell death was measured using immunostaining and Western blotting in the presence and absence of apelin-13 (0.1 to 5.0 nM) co-applied during SD exposure. SD-induced apoptosis was significantly reduced by apelin-13 in a concentration-dependent manner. SD-induced mitochondrial depolarization, cytochrome c release, and caspase-3 activation were largely prevented by apelin-13. The apelin-13 anti-apoptotic effects were blocked by inhibiting the MAPK/ERK1/2 and PI3K/Akt signaling pathways. Taken together, our findings indicate that apelin-13 is a survival factor for BMSCs and its anti-apoptotic property may prove to be of therapeutic significance in terms of exploiting BMSC-based transplantation therapy.     

Joint Models of Longitudinal Data and Recurrent Events with Informative Terminal Event

This article presents semiparametric joint models to analyze longitudinal data with recurrent events (e.g. multiple tumors, repeated hospital admissions) and a terminal event such as death. A broad class of transformation models for the cumulative intensity of the recurrent events and the cumulative hazard of the terminal event is considered, which includes the proportional hazards model and the proportional odds model as special cases. We propose to estimate all the parameters using the nonparametric maximum likelihood estimators (NPMLE). We provide the simple and efficient EM algorithms to implement the proposed inference procedure. Asymptotic properties of the estimators are shown to be asymptotically normal and semiparametrically efficient. Finally, we evaluate the performance of the method through extensive simulation studies and a real-data application.