Hypothesis-driven Design Research Articles

The scienthetic method: from Aristotle to AI and the future of medicine.

While AI holds immense potential for accelerating advances in oncology, we must be intentional in developing and applying these technologies responsibly, equitably, and ethically. One path forward is for cancer care providers and researchers to be among the architects of AI and its adoption in medicine. Given the limitations of traditional top-down, hypothesis-driven design in an exponentially expanding data universe, on one hand, and the danger of spiraling into artificial ignorance (ai) from rushing into a purely 'synthetic' method on the other, this article proposes a 'scienthetic' method that synergizes AI with human wisdom. Tracing philosophical underpinnings of the scientific method from Socrates, Plato, and Aristotle to the present, it examines the critical juncture at which AI stands to either augment or undermine new knowledge. The scienthetic method seeks to harness the power and capabilities of AI responsibly, equitably, and ethically to transcend the limitations of both the traditional scientific method and purely synthetic methods, by intentionally weaving machine intelligence together with human wisdom.

Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment: A multicenter study in 1568 stroke patients.

Post-stroke cognitive impairment (PSCI) occurs in up to 50% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear. We determined if WMH in strategic white matter tracts explain cognitive performance after stroke. Individual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus. The total study sample consisted of 1568 patients (39.9% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume. These results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH. The Meta VCI Map consortium is dedicated to data sharing, following our guidelines.

Effects of amyloid-β-mimicking peptide hydrogel matrix on neuronal progenitor cell phenotype

Self-assembling peptide-based hydrogels have become a highly attractive scaffold for three-dimensional (3D) in vitro disease modeling as they provide a way to create tunable matrices that can resemble the extracellular matrix (ECM) of various microenvironments. Alzheimer's disease (AD) is an exceptionally complex neurodegenerative condition; however, our understanding has advanced due to the transition from two-dimensional (2D) to 3D in vitro modeling. Nonetheless, there is a current gap in knowledge regarding the role of amyloid structures, and previously developed models found long-term difficulty in creating an appropriate model involving the ECM and amyloid aggregates. In this report, we propose a multi-component self-assembling peptide-based hydrogel scaffold to mimic the amyloid-beta (β) containing microenvironment. Characterization of the amyloid-β-mimicking hydrogel (Col-HAMA-FF) reveals the formation of β-sheet structures as a result of the self-assembling properties of phenylalanine (Phe, F) through π−π stacking of the residues, thus mimicking the amyloid-β protein nanostructures. We investigated the effect of the amyloid-β-mimicking microenvironment on healthy neuronal progenitor cells (NPCs) compared to a natural-mimicking matrix (Col-HAMA). Our results demonstrated higher levels of neuroinflammation and apoptosis markers when NPCs were cultured in the amyloid-like matrix compared to a natural brain matrix. Here, we provided insights into the impact of amyloid-like structures on NPC phenotypes and behaviors. This foundational work, before progressing to more complex plaque models, provides a promising scaffold for future investigations on AD mechanisms and drug testing. Statement of significanceIn this study, we engineered two multi-component hydrogels: one to mimic the natural extracellular matrix (ECM) of the brain and one to resemble an amyloid-like microenvironment using a self-assembling peptide hydrogel. The self-assembling peptide mimics β-amyloid fibrils seen in amyloid-β protein aggregates. We report on the culture of neuronal progenitor cells within the amyloid-mimicking ECM scaffold to study the impact through marker expressions related to inflammation and DNA damage. This foundational work, before progressing to more complex plaque models, offers a promising scaffold for future investigations on AD mechanisms and drug testing.

Gran1: A Granulysin-Derived Peptide with Potent Activity against Intracellular Mycobacteriumtuberculosis.

Granulysin is an antimicrobial peptide (AMP) expressed by human T-lymphocytes and natural killer cells. Despite a remarkably broad antimicrobial spectrum, its implementation into clinical practice has been hampered by its large size and off-target effects. To circumvent these limitations, we synthesized a 29 amino acid fragment within the putative cytolytic site of Granulysin (termed “Gran1”). We evaluated the antimicrobial activity of Gran1 against the major human pathogen Mycobacterium tuberculosis (Mtb) and a panel of clinically relevant non-tuberculous mycobacteria which are notoriously difficult to treat. Gran1 efficiently inhibited the mycobacterial proliferation in the low micro molar range. Super-resolution fluorescence microscopy and scanning electron microscopy indicated that Gran1 interacts with the surface of Mtb, causing lethal distortions of the cell wall. Importantly, Gran1 showed no off-target effects (cytokine release, chemotaxis, cell death) in primary human cells or zebrafish embryos (cytotoxicity, developmental toxicity, neurotoxicity, cardiotoxicity). Gran1 was selectively internalized by macrophages, the major host cell of Mtb, and restricted the proliferation of the pathogen. Our results demonstrate that the hypothesis-driven design of AMPs is a powerful approach for the identification of small bioactive compounds with specific antimicrobial activity. Gran1 is a promising component for the design of AMP-containing nanoparticles with selective activity and favorable pharmacokinetics to be pushed forward into experimental in vivo models of infectious diseases, most notably tuberculosis.

Utilizing a Biology-Driven Approach to Map the Exposome in Health and Disease: An Essential Investment to Drive the Next Generation of Environmental Discovery.

Background:Recent developments in technologies have offered opportunities to measure the exposome with unprecedented accuracy and scale. However, because most investigations have targeted only a few exposures at a time, it is hypothesized that the majority of the environmental determinants of chronic diseases remain unknown.Objectives:We describe a functional exposome concept and explain how it can leverage existing bioassays and high-resolution mass spectrometry for exploratory study. We discuss how such an approach can address well-known barriers to interpret exposures and present a vision of next-generation exposomics.Discussion:The exposome is vast. Instead of trying to capture all exposures, we can reduce the complexity by measuring the functional exposome—the totality of the biologically active exposures relevant to disease development—through coupling biochemical receptor-binding assays with affinity purification–mass spectrometry. We claim the idea of capturing exposures with functional biomolecules opens new opportunities to solve critical problems in exposomics, including low-dose detection, unknown annotations, and complex mixtures of exposures. Although novel, biology-based measurement can make use of the existing data processing and bioinformatics pipelines. The functional exposome concept also complements conventional targeted and untargeted approaches for understanding exposure-disease relationships.Conclusions:Although measurement technology has advanced, critical technological, analytical, and inferential barriers impede the detection of many environmental exposures relevant to chronic-disease etiology. Through biology-driven exposomics, it is possible to simultaneously scale up discovery of these causal environmental factors. https://doi.org/10.1289/EHP8327

Deciphering structure and aggregation in asphaltenes: hypothesis-driven design and development of synthetic model compounds.

Asphaltenes comprise the heaviest and least understood fraction of crude petroleum. The asphaltenes are a diverse and complex mixture of organic and organometallic molecules in which most of the molecular constituents are tightly aggregated into more complicated suprastructures. The bulk properties of asphaltenes arise from a broad range of polycyclic aromatics, heteroatoms, and polar functional groups. Despite much analytical effort, the precise molecular architectures of the material remain unresolved. To understand asphaltene characteristics and reactivity, the field has turned to synthetic model compounds that mirror asphaltene structure, aggregation behavior, and thermal chemistry, including the nucleation of coke. Historically, molecular asphaltene modeling was limited to commercial compounds, offering little illumination and few opportunities for hypothesis-driven research. More recently, however, rational molecular design and modern organic synthesis have started to impact this area. This review provides an overview of commercially available model compounds but is principally focused on the design and synthesis of structurally advanced and appropriately functionalized compounds to mimic the physical and chemical behavior of asphaltenes. Efforts to model asphaltene aggregation are briefly discussed, and a prognosis for the field is offered. A referenced tabulation of the synthetic compounds reported to date is provided.

Phosphothreonine (pThr)-Based Multifunctional Peptide Catalysis for Asymmetric Baeyer-Villiger Oxidations of Cyclobutanones.

Biologically inspired phosphothreonine (pThr)-embedded peptides that function as chiral Brønsted acid catalysts for enantioselective Baeyer-Villiger oxidations (BV) of cyclobutanones with aqueous H2O2 are reported herein. Complementary to traditional BINOL-derived chiral phosphoric acids (CPAs), the functional diversity of the peptidic scaffold provides the opportunity for multiple points of contact with substrates via hydrogen bonding, and the ease of peptide synthesis facilitates rapid diversification of the catalyst structure, such that numerous unique peptide-based CPA catalysts have been prepared. Utilizing a hypothesis-driven design, we identified a pThr-based catalyst that contains an N-acylated diaminopropionic acid (Dap) residue, which achieves high enantioselectivity with catalyst loadings as low as 0.5 mol%. The power of peptide-based multi-site binding is further exemplified through reversal in the absolute stereochemical outcome upon repositioning of the substrate-directing group (ortho- to meta). Modifications to the i+3 residue (LDap to LPhe) lead to an observed enantiodivergence without inversion of any stereogenic center on the peptide catalyst, due to noncovalent interactions. Structure-selectivity and 1H-1H-ROESY studies revealed that the proposed hydrogen bonding interactions are essential for high levels of enantioinduction. The ability for the phosphopeptides to operate as multifunctional oxidation catalysts expands the scope of pThr catalysts and provides a framework for the future selective diversification of more complex substrates, including natural products.

Streamlining Simulation Experiments with Agent-Based Models in Demography

In the last decade, the uptake of agent-based modeling in demography and other population sciences has been slowly increasing. Still, in such areas, where traditional data-driven, statistical approaches prevail, the hypothesis-driven design of agent-based models leads to questioning the validity of these models. Consequently, suitable means to increase the confidence into models and simulation results are required. To that end, explicit, replicable simulation experiments play a central role in model design and validation. However, the analysis of more complex models implies executing various experiments, each of which combines various methods. To streamline these experimentation processes a flexible computational simulation environment is necessary. With a new binding between SESSL – an internal domain-specific language for simulation experiments – and ML3 – a simulator for linked lives designed specifically for agent-based demographic models – we cater for these objectives and provide a powerful simulation tool. The proposed approach can serve as a foundation for current efforts of employing advanced and statistical model analysis of agent-based demographic models, as part of a wider process of iterative model building. We demonstrate its potential in specifying and executing different experiments with a simple model of return migration and a more complex model of social care.

Combined AURKA and H3K9 Methyltransferase Targeting Inhibits Cell Growth By Inducing Mitotic Catastrophe.

The current integrative pathobiologic hypothesis states that pancreatic cancer (PDAC) develops and progresses in response to an interaction between known oncogenes and downstream epigenomic regulators. Congruently, this study tests a new combinatorial therapy based on the inhibition of the Aurora kinase A (AURKA) oncogene and one of its targets, the H3K9 methylation-based epigenetic pathway. This therapeutic combination is effective at inhibiting the in vitro growth of PDAC cells both, in monolayer culture systems, and in three-dimensional spheroids and organoids. The combination also reduces the growth of PDAC xenografts in vivo Mechanistically, it was found that inhibiting methyltransferases of the H3K9 pathway in cells, which are arrested in G2-M after targeting AURKA, decreases H3K9 methylation at centromeres, induces mitotic aberrations, triggers an aberrant mitotic check point response, and ultimately leads to mitotic catastrophe. Combined, these data describe for the first time a hypothesis-driven design of an efficient combinatorial treatment that targets a dual oncogenic-epigenomic pathway to inhibit PDAC cell growth via a cytotoxic mechanism that involves perturbation of normal mitotic progression to end in mitotic catastrophe. Therefore, this new knowledge has significant mechanistic value as it relates to the development of new therapies as well as biomedical relevance.Implications: These results outline a model for the combined inhibition of a genetic-to-epigenetic pathway to inhibit cell growth and suggest an important and provocative consideration for harnessing the capacity of cell-cycle inhibitors to enhance the future use of epigenetic inhibitors. Mol Cancer Res; 15(8); 984-97. ©2017 AACR.

Insomnia disorder is associated with increased amygdala reactivity to insomnia-related stimuli.

Alterations in emotional reactivity may play a key role in the pathophysiology of insomnia disorder (ID). However, only few supporting experimental data are currently available. We evaluated in a hypothesis-driven design whether patients with ID present altered amygdale responses to emotional stimuli related and unrelated to the experience of insomnia and, because of chronic hyperarousal, less habituation of amygdala responses. Case-control study. Departments of Psychiatry and Psychotherapy and of Radiology of the University of Freiburg Medical Center. There were 22 patients with ID (15 females; 7 males; age 40.7 ± 12.6 y) and 38 healthy good sleepers (HGS, 21 females; 17 males; age 39.6 ± 8.9 y). N/A. In a functional magnetic resonance imaging session, five different blocks of pictures with varying emotional arousal, valence, and content (insomnia-relatedness) were presented. Pictures were presented twice to test for habituation processes. Results showed that patients with ID, compared to HGS, presented heightened amygdala responses to insomnia-related stimuli. Moreover, habituation of amygdale responses was observed only in HGS, but not in patients with ID who showed a mixed pattern of amygdala responses to the second presentation of the stimuli. The results provide evidence for an insomnia-related emotional bias in patients with ID. Cognitive behavior treatment for ID could benefit from strategies dealing with the emotional charge associated with the disorder. Further studies should clarify the role of ID with respect to habituation of amygdala responses.

Genomic Analysis of Left Ventricular Remodeling

The left ventricle (LV) of the heart remodels in response to hemodynamic load through the processes of physiological or pathophysiological hypertrophy.1–3 Despite extensive study of the molecular basis of cardiac hypertrophy and LV remodeling,1,4 the mainstay of medical treatment of maladaptive remodeling remains based on therapies initially devised for treating hypertension. The limited progress in the development of specific therapies for LV remodeling has led some to refer to “the impossible task of developing a new treatment for heart failure” and is the reason why, in part, device therapies have received such recent attention.5–8 To gain a better understanding of the biology of maladaptive LV remodeling, with a view to identifying therapeutic targets, new paradigms and experimental approaches are needed, and genomics provides one such methodology. Genomics is the study of genome-scale data sets, at the DNA or RNA level, and when combined with studies of physiological traits or disease phenotypes, genomics can be used to infer molecular insights. Unlike single-gene studies, which are the favored hypothesis-driven design,4 genomic approaches examine variation in up to gigabases of sequences to find statistical associations between transcripts and traits in a hypothesis-free system. These hypothesis-free studies have often been criticized as unfocused, but following the successes of genome-wide association studies (GWAS) and the recent achievements of integrated genetic and genomic analyses, a new era of genomic experimentation presents itself.9–14 It is notable that GWAS and integrated genomic studies in humans often identify regions associated with disease rather than specific genes and that effect sizes are small; nevertheless, these data remain highly informative.15–17 In this article, we review the genomic analysis of LV remodeling in the context of the recent past, the state of the art, and the imminent use of next-generation sequencing. A glossary of terms is …