"Protective effect of Placenta Growth Factor (PIGF) against hypoxia-reoxgyenation and serum-deprivation induced apoptosis in neonatal rat cardiomyocytes"

Kyle Bohman, Marin Schweizer and Bob Berendt are all Drake University students. Ronald J. Torry is Associate Professor of Pharmacology at Drake University. Donald S. Torry is a faculty member at the Southern Illinois University School of Medicine.Placenta growth factor (PlGF) is known to induce angiogenesis and protect placental trophoblast from apoptosis. We have shown that PlGF mRNA expression is increased in hypoxic human myocardium and in rat neonatal cardiomyocytes. However, little is known regarding the function of PlGF in heart tissue. Others have shown that PlGF or PlGF/VEGF significantly inhibited apoptosis in endothelial cells from PlGF knockout mice and we have shown that PlGF rescues cultured trophoblast from apoptosis induced by serum deprivation. Accordingly, our hypothesis is that PlGF protects cardiomyocytes from ischemia-induced or serum deprivation-induced apoptosis. The role of PlGF will be investigated during cardiomyocyte apoptosis induced by serum-deprivation and hypoxia-reoxygenation (H/R)--physiological conditions relevant to ischemic cardiomyopathy. Hypoxic conditions were established by culturing the cells at 1-2% O2. Caspase-3,7 luminescence assay (Promega) was used to determine the level of activated Caspases 3 and 7. The caspase family of cysteine proteases, especially caspase-3, is central in amplifying the cascade of proteolysis that culminates in cell death. Serum-deprivation and H/R have been found to be consistent methods of creating ischemic stresses and inducing apoptosis in rat cardiomyocytes. Serum-deprivation produced a 1.55 fold increase of apoptosis over normoxic values (n=10). H/R lead to a 1.98 fold increase of apoptosis (n=1). Our preliminary data suggest that a PlGF (25ng/ml) or PlGF/VEGF (25ng/ml each) does not reduce apoptosis induced by serum-deprivation. However, an 8 hour pretreatment of PlGF (25ng/ml) by itself reduced caspase 3 activity by 25.5% (n=1) and 30.7% (n=3) during hypoxia or serum deprivation, respectively. The preliminary data show an 8 hour pretreatment with PlGF/VEGF (25ng/ml each) decreased caspase activity more than PlGF (25ng/ml) alone. Thus, early evidence indicates that pretreatment with PlGF or PlGF/VEGF may protect cardiomyocytes from hypoxia-reoxygenation and/or serum deprivation-induced apoptosis.Drake University, College of Pharmacy and Health Sciences. Department of Pharmaceutical Sciences

"Detection of PIGF protein in neonatal rat cardiomyocytes"

Marin Schweizer, Kyle Bohman, Carrie Mittelstedter and Ben Colton are all Drake University students. Ronald J. Torry is Associate Professor of Pharmacology at Drake University. Donald S. Torry is on the faculty at Southern Illinois University School of Medicine.Angiogenesis, the formation of blood vessels, can provide blood to the heart when its normal arteries are compromised. Angiogenesis is highly dependent on the Vascular Endothelial Growth Factor (VEGF) family. Placental Growth Factor (PlGF) is a member of this family and is crucial for pathological angiogenesis in the adult. PlGF coupled with the more common VEGF could greatly increase angiogenesis in the heart tissue, thus providing oxygen to ischemic heart tissue. Previous research has shown that PlGF mRNA increases with six hours of hypoxia which models ischemia. However, not much is known about PlGF expression on the protein level. We intend to establish that PlGF protein expression will increase in rat cardiomyocytes which have undergone 6, 12 and 24 hours of hypoxia compared to normoxic rat cardiomyocytes. This information will later be used in studies of potential protective treatments using PlGF.Drake University, College of Pharmacy and Health Sciences, Department of Pharmaceutical Sciences

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty.

This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings

How Many Replicators Does It Take to Achieve Reliability? Investigating Researcher Variability in a Crowdsourced Replication

The paper reports findings from a crowdsourced replication. Eighty-four replicator teams attempted to verify results reported in an original study by running the same models with the same data. The replication involved an experimental condition. A “transparent” group received the original study and code, and an “opaque” group received the same underlying study but with only a methods section and description of the regression coefficients without size or significance, and no code. The transparent group mostly verified the original study (95.5%), while the opaque group had less success (89.4%). Qualitative investigation of the replicators’ workflows reveals many causes of non-verification. Two categories of these causes are hypothesized, routine and non-routine. After correcting non-routine errors in the research process to ensure that the results reflect a level of quality that should be present in ‘real-world’ research, the rate of verification was 96.1 in the transparent group and 92.4 in the opaque group. Two conclusions follow: (1) Although high, the verification rate suggests that it would take a minimum of three replicators per study to achieve replication reliability of at least 95 confidence assuming ecological validity in this controlled setting, and (2) like any type of scientific research, replication is prone to errors that derive from routine and undeliberate actions in the research process. The latter suggests that idiosyncratic researcher variability might provide a key to understanding part of the “reliability crisis” in social and behavioral science and is a reminder of the importance of transparent and well documented workflows