Impaired Increase of Plasma Abscisic Acid in Response to Oral Glucose Load in Type 2 Diabetes and in Gestational Diabetes

The plant hormone abscisic acid (ABA) is present and active in humans, regulating glucose homeostasis. In normal glucose tolerant (NGT) human subjects, plasma ABA (ABAp) increases 5-fold after an oral glucose load. The aim of this study was to assess the effect of an oral glucose load on ABAp in type 2 diabetes (T2D) subjects. We chose two sub-groups of patients who underwent an oral glucose load for diagnostic purposes: i) 9 treatment-naive T2D subjects, and ii) 9 pregnant women with gestational diabetes (GDM), who underwent the glucose load before and 8–12 weeks after childbirth. Each group was compared with matched NGT controls. The increase of ABAp in response to glucose was found to be abrogated in T2D patients compared to NGT controls. A similar result was observed in the women with GDM compared to pregnant NGT controls; 8–12 weeks after childbirth, however, fasting ABAp and ABAp response to glucose were restored to normal in the GDM subjects, along with glucose tolerance. We also retrospectively compared fasting ABAp before and after bilio-pancreatic diversion (BPD) in obese, but not diabetic subjects, and in obese T2D patients, in which BPD resulted in the resolution of diabetes. Compared to pre-BPD values, basal ABAp significantly increased 1 month after BPD in T2D as well as in NGT subjects, in parallel with a reduction of fasting plasma glucose. These results indicate an impaired hyperglycemia-induced ABAp increase in T2D and in GDM and suggest a beneficial effect of elevated ABAp on glycemic control.     

Treatment of Solitary Painful Osseous Metastases with Radiotherapy,Cryoablation or Combined Therapy: Propensity Matching Analysis in 175 Patients

Purpose

aim of this study was to identify outcomes in pain relief and quality of life in patients with a solitary painful osseous metastasis treated by radiotherapy, cryoablation or the combination using a propensity score matching study design.

Materials and Methods

175 patients with painful bone metastases were included in the study. Twenty-five of them underwent a radiation course (20 Gy in five daily fractions) 15 days after the cryoablation. These subjects were retrospectively matched by propensity analysis with a group of subjects treated by radiotherapy (125 subjects) and with a group treated byCryoablation (25 subjects). The pain relief in terms of complete response, rate of subjects requiring analgesics after treatments and the changes in self-rated quality of life were measured. Informed consent was obtained from the subject and the study was approved by the local Ethical Committee.

Results

An higher proportion of subjects treated by cryoablation (32%) or cryoablation followed by RT (72%;) experienced a complete response compared with patients treated by radiotherapy alone (11.2%). After Bonferroni correction strategy, the addition of radiotherapy to cryoablation significantly improved the rate of complete response compared with cryoablation alone (p = 0.011) and this paralleled with an improved self-rated quality of life. Seventeen subjects (13.6%) of patients in the radiotherapy group, 9 (36%) in the cryoablation group, and 19 (76)% in the cryoablation- radiotherapy group did not require narcotic medications.

Conclusions

The addition of radiotherapy to cryoablation favorably impacts on perceived pain, with a favorable toxicity profile. However, our data should be interpreted with caution and could serve as a framework around which to design future trials.     

Multi-Target Analysis and Design of Mitochondrial Metabolism

Analyzing and optimizing biological models is often identified as a research priority in biomedical engineering. An important feature of a model should be the ability to find the best condition in which an organism has to be grown in order to reach specific optimal output values chosen by the researcher. In this work, we take into account a mitochondrial model analyzed with flux-balance analysis. The optimal design and assessment of these models is achieved through single- and/or multi-objective optimization techniques driven by epsilon-dominance and identifiability analysis. Our optimization algorithm searches for the values of the flux rates that optimize multiple cellular functions simultaneously. The optimization of the fluxes of the metabolic network includes not only input fluxes, but also internal fluxes. A faster convergence process with robust candidate solutions is permitted by a relaxed Pareto dominance, regulating the granularity of the approximation of the desired Pareto front. We find that the maximum ATP production is linked to a total consumption of NADH, and reaching the maximum amount of NADH leads to an increasing request of NADH from the external environment. Furthermore, the identifiability analysis characterizes the type and the stage of three monogenic diseases. Finally, we propose a new methodology to extend any constraint-based model using protein abundances.     

Selective Cytotoxicity of 1,3,4-Thiadiazolium Mesoionic Derivatives on Hepatocarcinoma Cells (HepG2)

In this work, we evaluated the cytotoxicity of mesoionic 4-phenyl-5-(2-Y, 4-X or 4-X-cinnamoyl)-1,3,4-thiadiazolium-2-phenylamine chloride derivatives (MI-J: X=OH, Y=H; MI-D: X=NO₂, Y=H; MI-4F: X=F, Y=H; MI-2,4diF: X=Y=F) on human hepatocellular carcinoma (HepG2), and non-tumor cells (rat hepatocytes) for comparison. MI-J, M-4F and MI-2,4diF reduced HepG2 viability by ~ 50% at 25 μM after 24-h treatment, whereas MI-D required a 50 μM concentration, as shown by 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyltetrazolium bromide assays. The cytotoxicity was confirmed with lactate dehydrogenase assay, of which activity was increased by 55, 24 and 16% for MI-J, MI-4F and MI-2,4diF respectively (at 25 μM after 24 h). To identify the death pathway related to cytotoxicity, the HepG2 cells treated by mesoionic compounds were labeled with both annexin V and PI, and analyzed by flow cytometry. All compounds increased the number of doubly-stained cells at 25 μM after 24 h: by 76% for MI-J, 25% for MI-4F and MI-2,4diF, and 11% for MI-D. It was also verified that increased DNA fragmentation occurred upon MI-J, MI-4F and MI-2,4diF treatments (by 12%, 9% and 8%, respectively, at 25 μM after 24 h). These compounds were only weakly, or not at all, transported by the main multidrug transporters, P-glycoprotein, ABCG2 and MRP1, and were able to slightly inhibit their drug-transport activity. It may be concluded that 1,3,4-thiadiazolium compounds, especially the hydroxy derivative MI-J, constitute promising candidates for future investigations on in-vivo treatment of hepatocellular carcinoma.     

Quantitation of Malaria Parasite-Erythrocyte Cell-Cell Interactions Using Optical Tweezers

Erythrocyte invasion by Plasmodium falciparum merozoites is an essential step for parasite survival and hence the pathogenesis of malaria. Invasion has been studied intensively, but our cellular understanding has been limited by the fact that it occurs very rapidly: invasion is generally complete within 1 min, and shortly thereafter the merozoites, at least in in vitro culture, lose their invasive capacity. The rapid nature of the process, and hence the narrow time window in which measurements can be taken, have limited the tools available to quantitate invasion. Here we employ optical tweezers to study individual invasion events for what we believe is the first time, showing that newly released P. falciparum merozoites, delivered via optical tweezers to a target erythrocyte, retain their ability to invade. Even spent merozoites, which had lost the ability to invade, retain the ability to adhere to erythrocytes, and furthermore can still induce transient local membrane deformations in the erythrocyte membrane. We use this technology to measure the strength of the adhesive force between merozoites and erythrocytes, and to probe the cellular mode of action of known invasion inhibitory treatments. These data add to our understanding of the erythrocyte-merozoite interactions that occur during invasion, and demonstrate the power of optical tweezers technologies in unraveling the blood-stage biology of malaria.     

SAR study and conformational analysis of a series of novel peptide G protein‐coupled receptor kinase 2 inhibitors

G protein‐coupled receptor kinase 2 (GRK2) plays a central role in the cellular transduction network. In particular, during chronic heart failure GRK2 is upregulated and believed to contribute to disease progression. Thereby, its inhibition offers a potential therapeutic solution to several pathological conditions. In the present study, we performed a SAR study and a NMR conformational analysis of peptides derived from HJ loop of GRK2 and able to selectively inhibit GRK2. From Ala‐scan and d ‐Ala point replacement, we found that Arg residues don't affect the inhibitory properties, while a d ‐amino acid at position 5 is key to the activity. Conformational analysis identified two β‐turns that involve N‐terminal residues, followed by a short extended region. These information can help the design of peptides and peptido‐mimetics with enhanced GRK2 inhibition properties. © 2013 Wiley Periodicals, Inc. Biopolymers 101: 121–128, 2014.     

Estrogen down-regulates uncoupling proteins and increases oxidative stress in breast cancer

Oxidative stress has been postulated as one of the mechanisms underlying the estrogen carcinogenic effect in breast cancer. Estrogens are known to increase mitochondrial-derived reactive oxygen species (ROS) by an unknown mechanism. Given that uncoupling proteins (UCPs) are key regulators of mitochondrial energy efficiency and ROS production, our aim was to check the presence and activity of UCPs in estrogen receptor (ER)-positive and ER-negative breast cancer cells and tumors, as well as their relation to oxidative stress. Estrogen (1 nM) induced higher oxidative stress in the ER-positive MCF-7 cell line, showing increased mitochondrial membrane potential, H₂O₂ levels, and DNA and protein damage compared to ER-negative MDA-MB-231 cells. All isoforms of uncoupling proteins were highly expressed in ER-positive breast cancer cells and tumors compared to negative ones. ROS production in mitochondria isolated from MCF-7 was increased by inhibition of UCPs with GDP, but not in mitochondria from MDA-MB-231. Estrogen treatment decreased uncoupling protein and catalase levels in MCF-7 and decreased GDP-dependent ROS production in isolated mitochondria. On the whole, these results suggest that estrogens, through an ER-dependent mechanism, may increase mitochondrial ROS production by repressing uncoupling proteins, which offers a new perspective on the understanding of why estrogens are a risk factor for breast cancer.     

Novel induced <Emphasis Type="Italic">mlo</Emphasis> mutant alleles in combination with site-directed mutagenesis reveal functionally important domains in the heptahelical barley Mlo protein

Background  

Recessively inherited natural and induced mutations in the barley Mlo gene confer durable broad-spectrum resistance against the powdery mildew pathogen, Blumeria graminis f.sp. hordei. Mlo codes for a member of a plant-specific family of polytopic integral membrane proteins with unknown biochemical activity. Resistant barley mlo mutant alleles identify amino acid residues that are critical for Mlo function in the context of powdery mildew susceptibility.     

Identification of Targeted Analyte Clusters for Studies of Schizophrenia

The search for biomarkers to diagnose psychiatric disorders such as schizophrenia has been underway for decades. Many molecular profiling studies in this field have focused on identifying individual marker signals that show significant differences in expression between patients and the normal population. However, signals for multiple analyte combinations that exhibit patterned behaviors have been less exploited. Here, we present a novel approach for identifying biomarkers of schizophrenia using expression of serum analytes from first onset, drug-naïve patients and normal controls. The strength of patterned signals was amplified by analyzing data in reproducing kernel spaces. This resulted in the identification of small sets of analytes referred to as targeted clusters that have discriminative power specifically for schizophrenia in both human and rat models. These clusters were associated with specific molecular signaling pathways and less strongly related to other neuropsychiatric disorders such as major depressive disorder and bipolar disorder. These results shed new light concerning how complex neuropsychiatric diseases behave at the pathway level and demonstrate the power of this approach in identification of disease-specific biomarkers and potential novel therapeutic strategies.Schizophrenia is a debilitating neuropsychiatric disorder that affects more than 1% of the world population and costs hundreds of billions of United States dollars in healthcare provision and lost earnings (1). The diagnosis of this disease has not changed substantially over several decades and currently relies on subjective psychopathological ratings such as the Diagnostic and Statistical Manual of Mental Disorders (DSM)1-IV. Thus, diagnosis can be complicated by the presence of overlapping symptoms frequently occurring in other psychiatric illnesses such as bipolar disorder (BD) and major depressive disorder (MDD) and by the presence of confounding factors such as drug abuse and co-morbidities. This often results in diagnosis being delayed for several months to years. A delay in establishing an accurate diagnosis can have serious deleterious implications because a late or imprecise diagnosis can contribute to unsatisfactory outcomes to currently used drug therapies and to higher rates of relapse (2). Most importantly, more than half of schizophrenia subjects develop a progressive course of the disease associated with deficit symptoms (3).In contrast, early therapeutic intervention holds promise in preventing or diminishing such effects (4–6). An empirical assay for early and accurate diagnosis of schizophrenia would deliver improved patient outcomes and reduce the costs of the disease for healthcare services and society (7–9). Such an assay could also provide a means of stratifying patients and monitoring drug responses and may also lead to the development of translational medicine tools that are critical for discovery of novel therapeutic strategies. Molecular profiling methods that afford the simultaneous measurement of multiple analytes in clinical and preclinical samples have considerable promise in this endeavor. These methods have been aimed predominantly at identifying individual molecules that show differences in expression between the disease and control conditions. However, such studies have often been fraught with small fold-changes in analyte levels, a common obstacle when investigating complex neuropsychiatric disorders (10–12). Thus, standard statistical techniques such as t tests will not be able to explore patterned behaviors involving proteins that have subtle expression changes but still contribute to the development of schizophrenia.The main objective of this study was to determine whether unique patterns of biomarkers can be identified for subjects with first onset antipsychotic-naïve schizophrenia. Analyte expression lists were generated using the Multi-Analyte Profiling (MAP®) fluorescent bead-based technology for profiling serum samples from 77 male schizophrenia patients and 66 matched male controls. For comparison with other psychiatric disorders, we also analyzed the serum samples of 13 male BD and 17 male MDD patients. In parallel, serum samples from four relevant animal models were also profiled for comparison with the human disease state. Analysis of the respective expression lists was carried out using non-linear statistical analysis, which identifies small sets of analytes called targeted analyte clusters (TACs) that have the power to discriminate the patients from normal controls. We present here the performance of these clusters for diagnosis of schizophrenia. In addition, we show how this method can also contribute to increasing our understanding of the etiology of the disorder by determining its ability to classify various preclinical models of psychiatric disorders. The biological pathways associated with these clusters are discussed with their relevance to schizophrenia.