Illusory intuitions: Challenging the claim of non-exclusivity.

A person who arrives at correct solutions via false premises is right and wrong simultaneously. Similarly, a person who generates "logical intuitions" through superficial heuristics can likewise be right and wrong at the same time. However, heuristics aren't guaranteed to deliver the logical solution, so the claim that system 1 can routinely produce the alleged system 2 response is unfounded.

Nanoliposome targeting in breast cancer is influenced by the tumor microenvironment.

MM-302 is an anti-HER2 antibody-targeted pegylated liposomal doxorubicin designed to deliver doxorubicin specifically to HER2-expressing solid tumors. The delivery and activity of MM-302 were evaluated in orthotopic, transgenic, and intravenous breast cancer models expressing varying levels of HER2 that metastasize to some of the most common sites of dissemination for breast cancer, namely, lung, liver, and brain. Metastatic burden was quantified by gross evaluation, immunohistochemistry (IHC), and bioluminescent imaging. Liposome delivery was quantified by IHC and ex vivo fluorescent imaging. Unlike its non-targeted counterpart, pegylated liposomal doxorubicin (PLD), MM-302 showed activity at controlling both primary and metastatic tumor burden in all models tested. The effect of HER2-targeting was greatest in the lung where lymphatic vessel density and MM-302 delivery were highest. Our data indicate that the therapeutic advantage of actively targeting a nanoliposome with an antibody is influenced by both target expression and the tumor microenvironment.

Aliskiren and valsartan mediate left ventricular remodeling post-myocardial infarction in mice through MMP-9 effects.

We evaluated whether aliskiren, valsartan, or a combination of both was protective following myocardial infarction (MI) through effects on matrix metalloproteinase (MMP)-9. C57BL/6J wild type (WT, n=94) and MMP-9 null (null, n=85) mice were divided into 4 groups at 3h post-MI: saline (S), aliskiren (A; 50mg/kg/day), valsartan (V; 40mg/kg/day), or A+V and compared to no MI controls at 28days post-MI. All groups had similar infarct areas, and survival rates were higher in the null mice. The treatments influenced systolic function and hypertrophy index, as well as extracellular matrix (ECM) and inflammatory genes in the remote region, indicating that primary effects were on the viable myocardium. Saline treated WT mice showed increased end systolic and diastolic volumes and hypertrophy index, along with reduced ejection fraction. MMP-9 deletion improved LV function post-MI. Aliskiren attenuated the increase in end systolic volume and hypertrophy index, while valsartan improved end diastolic volumes and aliskiren+valsartan improved the hypertrophy index only when MMP-9 was absent. Extracellular matrix and inflammatory gene expression showed distinct patterns among the treatment groups, indicating a divergence in mechanisms of remodeling. This study shows that MMP-9 regulates aliskiren and valsartan effects in mice. These results in mice provide mechanistic insight to help translate these findings to post-MI patients.

Reduced BDNF attenuates inflammation and angiogenesis to improve survival and cardiac function following myocardial infarction in mice.

Brain-derived neurotrophic factor (BDNF) increases in failing hearts, but BDNF roles in cardiac remodeling following myocardial infarction (MI) are unclear. Male BDNF(+/+) [wild-type (WT)] and BDNF(+/-) heterozygous (HET) mice at 6-9 mo of age were subjected to MI and evaluated at days 1, 3, 5, 7, or 28 post-MI. At day 28 post-MI, 76% of HET versus 40% of WT survived, whereas fractional shortening improved and neovascularization levels were reduced in the HET (all, P < 0.05). At day 1, post-MI, matrix metalloproteinase-9, and myeloperoxidase (MPO) increased in WT, but not in HET. Concomitantly, monocyte chemotactic protein-1 and -5 levels increased and vascular endothelial growth factor (VEGF)-A decreased in HET. Neutrophil infiltration peaked at days 1-3 in WT mice, and this increase was blunted in HET. To determine if MPO administration could rescue the HET phenotype, MPO was injected at 3 h post-MI. MPO restored VEGF-A levels without altering matrix metalloproteinase-9 or neutrophil content. In conclusion, reduced BDNF levels modulated the early inflammatory and neovascularization responses, leading to improved survival and reduced cardiac remodeling at day 28 post-MI. Thus reduced BDNF attenuates early inflammation following MI by modulating MPO and angiogenic response through VEGF-A.

Illusory intuitive inferences: Matching heuristics explain logical intuitions.

The capacity to evaluate logical arguments intuitively is a fundamental assumption of recent dual-process theories. One observation supporting this effect is the standard conflict effect on incongruent arguments under belief instruction. Conflict arguments are evaluated less accurately than non-conflict arguments, arguably because logic is intuitive and automatic enough to interfere with belief judgments. However, recent studies have challenged this interpretation by finding the same conflict effects when a matching heuristic cues the same response as logic, even on arguments with no logically valid structures. In this study, we test the matching heuristic hypothesis across 4 experiments (total N = 409) by manipulating the arguments propositions so that matching cues a response that is either (1) aligned or (2) misaligned with logic, or (3) cues no response at all. Consistent with the predictions of the matching heuristic, standard, reversed, and no conflict effects were found in those conditions, respectively. These results indicate that intuitively correct inferences which are assumed as evidence of logical intuitions are actually driven by a matching heuristic that cues responses aligned with logic. Alleged intuitive logic effects are reversed when the matching heuristic cues an opposing logical response or disappears when there are no matching cues. Therefore, it appears as though the operation of a matching heuristic, rather than an intuitive access to logic, drives logical intuitions.

The bright homunculus in our head: Individual differences in intuitive sensitivity to logical validity.

Classic dual process theories of human reasoning attribute explicit reasoning to effortful, deliberative thinking. According to these models, intuitive processes lack any access to the formal rules of logic and probability and hence rely exclusively on superficial problem features to determine a response. However, in recent years, researchers have demonstrated that reasoners are able to solve simple logical or probabilistic problems relatively automatically, a capability which has been called "logical intuition." In four experiments, we instructed participants to judge the validity (Experiments 1 and 4), likeability (Experiments 1, 2, and 3), and physical brightness (Experiments 2, 3, and 4) of the conclusion to several reasoning problems. Brightness judgements were made by evaluating the font shade brightness of the argument's conclusion. Participants were also asked to complete a range of individual differences measures, drawing on cognitive ability and cognitive style, to evaluate the extent to which "logical intuitions" were linked to measures of deliberative reasoning. The results showed that participants judged the conclusion of logically valid statements to be more valid, more likable, and more physically bright than invalid statements. Participants with higher cognitive ability and unlimited processing time showed greater effects of logical validity in their liking judgements (varied across experiments). However, these effects were absent in the brightness tasks, suggesting that logic effects observed under instructions to judge conclusion brightness are a purer measure of "logical intuition." We discuss the implications of our findings for recent dual process theories of human reasoning.

Logical intuition is not really about logic.

Recent research suggests that reasoners are able to draw simple logical or probabilistic inferences relatively intuitively and automatically, a capacity that has been termed "logical intuition" (see, e.g., De Neys & Pennycook, 2019). A key finding in support of this interpretation is that conclusion validity consistently interferes with judgments of conclusion believability, suggesting that information about logical validity is available quickly enough to interfere with belief judgments. In this study, we examined whether logical intuitions arise because reasoners are sensitive to the logical features of a problem or another structural feature that just happens to align with logical validity. In three experiments (N = 113, 137, and 254), we presented participants with logical (determinate) and pseudological (indeterminate) arguments and asked them to judge the validity or believability of the conclusion. Logical arguments had determinately valid or invalid conclusions, whereas pseudological arguments were all logically indeterminate, but some were pseudovalid (possible strong arguments) and others pseudoinvalid (possible weak arguments). Experiments 1 and 2 used simple modus ponens and affirming the consequent structures; Experiment 3 used more complex denying the antecedent and modus tollens structures. In all three experiments, we found that pseudovalidity interfered with belief judgments to the same extent as real validity. Altogether, these findings suggest that while people are able to draw inferences intuitively, and these inferences impact belief judgments, they are not logical intuitions. Rather, the intuitive inferences are driven by the processing of more superficial structural features that happen to align with logical validity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

TAK-676: A Novel Stimulator of Interferon Genes (STING) Agonist Promoting Durable IFN-dependent Antitumor Immunity in Preclinical Studies.

Oncology therapies targeting the immune system have improved patient outcomes across a wide range of tumor types, but resistance due to an inadequate T-cell response in a suppressive tumor microenvironment (TME) remains a significant problem. New therapies that activate an innate immune response and relieve this suppression may be beneficial to overcome this hurdle. TAK-676 is a synthetic novel stimulator of interferon genes (STING) agonist designed for intravenous administration. Here we demonstrate that TAK-676 dose-dependently triggers activation of the STING signaling pathway and activation of type I interferons. Furthermore, we show that TAK-676 is a highly potent modulator of both the innate and adaptive immune system and that it promotes the activation of dendritic cells, natural killer cells, and T cells in preclinical models. In syngeneic murine tumor models in vivo, TAK-676 induces dose-dependent cytokine responses and increases the activation and proliferation of immune cells within the TME and tumor-associated lymphoid tissue. We also demonstrate that TAK-676 dosing results in significant STING-dependent antitumor activity, including complete regressions and durable memory T-cell immunity. We show that TAK-676 is well tolerated, exhibits dose-proportional pharmacokinetics in plasma, and exhibits higher exposure in tumor. The intravenous administration of TAK-676 provides potential treatment benefit in a broad range of tumor types. Further study of TAK-676 in first-in-human phase I trials is ongoing. Significance: TAK-676 is a novel systemic STING agonist demonstrating robust activation of innate and adaptive immune activity resulting in durable antitumor responses within multiple syngeneic tumor models. Clinical investigation of TAK-676 is ongoing.

A high precision method for length-based separation of carbon nanotubes using bio-conjugation, SDS-PAGE and silver staining.

Parametric separation of carbon nanotubes, especially based on their length is a challenge for a number of nano-tech researchers. We demonstrate a method to combine bio-conjugation, SDS-PAGE, and silver staining in order to separate carbon nanotubes on the basis of length. Egg-white lysozyme, conjugated covalently onto the single-walled carbon nanotubes surfaces using carbodiimide method. The proposed conjugation of a biomolecule onto the carbon nanotubes surfaces is a novel idea and a significant step forward for creating an indicator for length-based carbon nanotubes separation. The conjugation step was followed by SDS-PAGE and the nanotube fragments were precisely visualized using silver staining. This high precision, inexpensive, rapid and simple separation method obviates the need for centrifugation, additional chemical analyses, and expensive spectroscopic techniques such as Raman spectroscopy to visualize carbon nanotube bands. In this method, we measured the length of nanotubes using different image analysis techniques which is based on a simplified hydrodynamic model. The method has high precision and resolution and is effective in separating the nanotubes by length which would be a valuable quality control tool for the manufacture of carbon nanotubes of specific lengths in bulk quantities. To this end, we were also able to measure the carbon nanotubes of different length, produced from different sonication time intervals.

Deriving a cardiac ageing signature to reveal MMP-9-dependent inflammatory signalling in senescence.

AIMS: Cardiac ageing involves the progressive development of cardiac fibrosis and diastolic dysfunction coordinated by MMP-9. Here, we report a cardiac ageing signature that encompasses macrophage pro-inflammatory signalling in the left ventricle (LV) and distinguishes biological from chronological ageing. METHODS AND RESULTS: Young (6-9 months), middle-aged (12-15 months), old (18-24 months), and senescent (26-34 months) mice of both C57BL/6J wild type (WT) and MMP-9 null were evaluated. Using an identified inflammatory pattern, we were able to define individual mice based on their biological, rather than chronological, age. Bcl6, Ccl24, and Il4 were the strongest inflammatory markers of the cardiac ageing signature. The decline in early-to-late LV filling ratio was most strongly predicted by Bcl6, Il1r1, Ccl24, Crp, and Cxcl13 patterns, whereas LV wall thickness was most predicted by Abcf1, Tollip, Scye1, and Mif patterns. With age, there was a linear increase in cardiac M1 macrophages and a decrease in cardiac M2 macrophages in WT mice; of which, both were prevented by MMP-9 deletion. In vitro, MMP-9 directly activated young macrophage polarization to an M1/M2 mid-transition state. CONCLUSION: Our results define the cardiac ageing inflammatory signature and assign MMP-9 roles in mediating the inflammaging profile by indirectly and directly modifying macrophage polarization. Our results explain early mechanisms that stimulate ageing-induced cardiac fibrosis and diastolic dysfunction.

Using systems biology approaches to understand cardiac inflammation and extracellular matrix remodeling in the setting of myocardial infarction.

Inflammation and extracellular matrix (ECM) remodeling are important components regulating the response of the left ventricle to myocardial infarction (MI). Significant cellular- and molecular-level contributors can be identified by analyzing data acquired through high-throughput genomic and proteomic technologies that provide expression levels for thousands of genes and proteins. Large-scale data provide both temporal and spatial information that need to be analyzed and interpreted using systems biology approaches in order to integrate this information into dynamic models that predict and explain mechanisms of cardiac healing post-MI. In this review, we summarize the systems biology approaches needed to computationally simulate post-MI remodeling, including data acquisition, data analysis for biomarker classification and identification, data integration to build dynamic models, and data interpretation for biological functions. An example for applying a systems biology approach to ECM remodeling is presented as a reference illustration.

Bayesian parameter estimation for nonlinear modelling of biological pathways.

BACKGROUND: The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. RESULTS: We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. CONCLUSIONS: Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.