Combinatorial Possibilities Research Articles

Focal adhesion kinase signaling - tumor vulnerabilities and clinical opportunities.

Focal adhesion kinase (FAK; encoded by PTK2) was discovered over 30 years ago as a cytoplasmic protein tyrosine kinase that is localized to cell adhesion sites, where it is activated by integrin receptor binding to extracellular matrix proteins. FAK is ubiquitously expressed and functions as a signaling scaffold for a variety of proteins at adhesions and in the cell cytoplasm, and with transcription factors in the nucleus. FAK expression and intrinsic activity are essential for mouse development, with molecular connections to cell motility, cell survival and gene expression. Notably, elevated FAK tyrosine phosphorylation is common in tumors, including pancreatic and ovarian cancers, where it is associated with decreased survival. Small molecule and orally available FAK inhibitors show on-target inhibition in tumor and stromal cells with effects on chemotherapy resistance, stromal fibrosis and tumor microenvironment immune function. Herein, we discuss recent insights regarding mechanisms of FAK activation and signaling, its roles as a cytoplasmic and nuclear scaffold, and the tumor-intrinsic and -extrinsic effects of FAK inhibitors. We also discuss results from ongoing and advanced clinical trials targeting FAK in low- and high-grade serous ovarian cancers, where FAK acts as a master regulator of drug resistance. Although FAK is not known to be mutationally activated, preventing FAK activity has revealed multiple tumor vulnerabilities that support expanding clinical combinatorial targeting possibilities.

Multimodal Learning for Mapping the Genotype-Phenotype Dynamics.

How complex phenotypes emerge from intricate gene expression patterns is a fundamental question in biology. Quantitative characterization of this relationship, however, is challenging due to the vast combinatorial possibilities and dynamic interplay between genotype and phenotype landscapes. Integrating high-content genotyping approaches such as single-cell RNA sequencing and advanced learning methods such as language models offers an opportunity for dissecting this complex relationship. Here, we present a computational integrated genetics framework designed to analyze and interpret the high-dimensional landscape of genotypes and their associated phenotypes simultaneously. We applied this approach to develop a multimodal foundation model to explore the genotype-phenotype relationship manifold for human transcriptomics at the cellular level. Analyzing this joint manifold showed a refined resolution of cellular heterogeneity, enhanced precision in phenotype annotating, and uncovered potential cross-tissue biomarkers that are undetectable through conventional gene expression analysis alone. Moreover, our results revealed that the gene networks are characterized by scale-free patterns and show context-dependent gene-gene interactions, both of which result in significant variations in the topology of the gene network, particularly evident during aging. Finally, utilizing contextualized embeddings, we investigated gene polyfunctionality which illustrates the multifaceted roles that genes play in different biological processes, and demonstrated that for VWF gene in endothelial cells. Overall, this study advances our understanding of the dynamic interplay between gene expression and phenotypic manifestation and demonstrates the potential of integrated genetics in uncovering new dimensions of cellular function and complexity.

Morpho-syntactic structure of code-switched sentences produced by Albanian bilingual speakers

This paper aims to analyze the structure of code-switched sentences uttered by Albanian bilingual students. It examines the predictions made by two theoretical viewpoints, namely Myers-Scotton’s Matrix Language Frame (MLF) and MacSwan’s approach within the Minimalist Program (MP). The students were observed in informal environments within Prishtina international school settings, such as during recess time, on the playground, etc. Tape recordings of the conversations were used to record this naturalistic data, which was then transcribed. In particular, examples from the Albanian/English pair were analyzed, and the MLF and MP predictions regarding combinatorial possibilities were tested. The findings show that our data can only partially be accounted for by the MLF and MP approaches. Switching is mainly unidirectional, with insertions from English into an Albanian syntactic frame. Determiners, such as demonstrative pronouns, indefinite pronouns, adverbs of quantity, as well as copular verbs, auxiliary verbs, and clitics, come from the Matrix Language (ML), complying with the MLF model. However, violations of the MLF model are encountered as well, such as the non-occurrence of stem/affix switching, the occurrence of bare forms, and Embedded Language (EL) islands not always constituting the maximal projection of the phrase, which are further described and predicted in MP model. The paper provides evidence that neither MLF nor MP are able to adequately account for the possible combinations in the mixed clause. According to what the literature to date indicates, integrating the approaches rather than using each one individually results in a better understanding of the grammar of code-switching.

3D Model-Based Large-Volume Metrology Supporting Smart Manufacturing and Digital Twin Concepts

New automated laser radar measurement systems at the Saab Inc. West Lafayette, USA, facility will make airframe assembly of the aft body for the new eT7-A aircraft a quicker, more cost-efficient process. Digital twin concepts realized through simulation and off-line programming show advantageous results when studying future state scenarios or investigating how a current large-volume dimensional metrology system acts and behaves. The aim of this exploration has been to examine how to facilitate the design and programming of automated laser radar concepts by means of novel simulation-based software. High-speed computing algorithms efficiently solve tasks and sequence problems related to many statistical combinatorial possibilities in calculations. However, this approach requires accurate and reliable models and digital twins that are continuously updated with real world data and information. In this paper, the main contributions are to create procedures to define the dimensional metrology workflow at Saab and to model and simulate the laser radar process, enhancing and tailoring existing offline programming software by specific new functionalities. A case study conducted at Saab Aeronautics premises in Linköping acted as a clinical laboratory to generate our research findings. The exploratory work indicates that a reliable simulation-based development method can be used advantageously in the early-stage design layout of automated dimensional metrology systems to verify and guarantee the line-of-sight of, e.g., a laser light path and its allowed inclinations to a specific geometrical feature to be measured, extracted, and evaluated.

Microscale Combinatorial Libraries for the Discovery of High-Entropy Materials.

Polyelemental material systems, specifically high-entropy alloys, promise unprecedented properties. Due to almost unlimited combinatorial possibilities, their exploration and exploitation is hard. This challenge is addressed by co-sputtering combined with shadow masking to produce a multitude of microscale combinatorial libraries in one deposition process. These thin-film composition spreads on the microscale cover unprecedented compositional ranges of high-entropy alloy systems and enable high-throughput characterization of thousands of compositions for electrocatalytic energy conversion reactions using nanoscale scanning electrochemical cell microscopy. The exemplary exploration of the composition space of two high-entropy alloy systems provides electrocatalytic activity maps for hydrogen evolution and oxygen evolution as well as oxygen reduction reactions. Activity optima in the system Ru-Rh-Pd-Ir-Pt are identified, and active noble-metal lean compositions in the system Co-Ni-Mo-Pd-Pt are discovered. This illustrates that the proposed microlibraries are a holistic discovery platform to master the multidimensionality challenge of polyelemental systems.

Synthetic activation of yeast stress response improves secretion of recombinant proteins

Yeasts, such as Pichia pastoris (syn Komagataella spp.), are particularly suitable expression systems for emerging classes of recombinant proteins. Among them, recombinant antibody fragments, such as single-chain variable fragments (scFv) and single-domain antibodies (VHH), are credible alternatives to monoclonal antibodies. The availability of powerful genetic engineering and synthetic biology tools has facilitated improvement of this cell factory to overcome certain limitations. However, cell engineering to improve secretion often remains a trial-and-error approach and improvements are often specific to the protein produced. Where multiple genetic interventions are needed to remove bottlenecks in the process of recombinant protein secretion, this leads to a high number of combinatorial possibilities for creation of new production strains. Therefore, our aim was to exploit whole transcriptional programs (stress response pathways) in order to simplify the strain engineering of new production strains. Indeed, the artificial activation of the general stress response transcription factor Msn4, as well as synthetic versions thereof, could replace the secretion enhancing effect of several cytosolic chaperones. Greater than 4-fold improvements in recombinant protein secretion were achieved by overexpression of MSN4 or synMSN4, either alone or in combination with Hac1 or ER chaperones. With this concept we were able to successfully engineer strains reaching titers of more than 2.5 g/L scFv and 8 g/L VHH in bioreactor cultivations. This increased secretion capacity of different industrially relevant model proteins indicates that MSN4 overexpression most likely represents a general concept to improve recombinant protein production in yeast.

After Print: Eighteenth-Century Manuscript Cultures, ed. Rachael Scarborough King

<i>After Print: Eighteenth-Century Manuscript Cultures</i>, ed. Rachael Scarborough King

EXTH-41. COMBINED PHARMACOLOGICAL AND GENETIC SCREENING TO IDENTIFY DEPENDENCIES AND COMBINATIONS IN ACVR1-MUTANT DIFFUSE MIDLINE GLIOMA

Abstract Somatic mutations in ACVR1, which encodes the serine/threonine kinase ALK2, are found in 20-25% of DMG-H3K27 patients. Treatment of ACVR1-mutant patient-derived models with multiple chemotypes of ALK2 inhibitors (ALK2i) results in reduced cell viability in vitro and extended survival in orthotopic xenografts in vivo but, as single agents, these inhibitors were unable to achieve a complete anti-tumour response. Recently we reported that combinatorial treatment of ACVR1-mutant DIPG cells with vandetanib (RTK inhibitor) and everolimus (mTOR/ABC transporter inhibitor) was synergistic both in vitro and in vivo and was shown to be a feasible combination to trial clinically in this setting. To identify specific dependencies in ACVR1-mutant cells which may be translatable with novel synergistic drug combinations alongside ALK2i, we have implemented both candidate and unbiased drug and genetic screening approaches. Using a panel of 13 patient-derived ACVR1-mutant models (and 6 wild-type controls), we identified synergy between multiple chemotypes of ALK2i (M4K2009/LDN-214117) and PI3K/mTOR (AZD8055/everolimus) and MEK inhibitors (trametinib), reflecting the common co-segregation of PIK3CA/PIK3R1 alterations in these tumours. Whole-genome CRISPR/Cas9 screening of ACVR1-mutant SU-DIPG-IV cells in combination with two ALK2i (M4K2009/LDN-193189), confirmed a specific MTOR genetic dependency, as well as for the protein phosphatase regulatory subunit PPP2R1A, known to play a role in MAPK pathway activation. Additional hits include the serine/threonine kinase PKMYT1, a negative regulator of the G2/M checkpoint via a functionally redundant phosphorylation of CDK1/CCNB1 alongside WEE1; confirmatory drug assays with the WEE1 inhibitor AZD1775 resulted in a synergistic interaction with ALK2i in ACVR1-mutant cells. Hits were integrated with DepMap using ‘gene effect’ scores (Chronos) enabling filtering of common essential genes. Preliminary pathway enrichment analysis (MAGeCKFlute) identified ALK2i-specific vulnerabilities involving TGFB1/SMAD signalling and histone deacetylation. These data highlight functionally rational and novel combinatorial possibilities for children with ACVR1-mutant DMG, with systematic preclinical assessment required for prioritisation for the clinic.

Inverse Kinematics Analysis of Novel 6-Dof Robotic Arm Manipulator for Oil and Gas Welding Using Grey Wolf Algorithm

his paper presents a grey-wolf algorithm for solving the inverse kinematics of a newly designed 6-degree-of-freedom robotic arm for oil and gas pipeline welding which has not been used in the literature. Consequently, due to the robot’s multiple joints with compounding combinatory possibilities of joint angles, analysis of the inverse kinematics is relatively complex. In this research, grey-wolf algorithm, a swarm-based meta-heuristic algorithm, has been used to solve for the inverse kinematics of the robotic arm with respect to tracking a rectangular trajectory with six sets of waypoints in the 3D [X, Y, Z] space. The results were further analyzed in terms of the accuracy of the position of end effector from the accurate position of the rectangular target trajectory via a mean squared error cost function. Furthermore, results of comparison between the grey-wolf algorithm and the particle swarm optimisation, an alternate swarm algorithm with respect to position error from the inverse kinematics task is also presented. The results obtained via simulation clearly demonstrates the superior performance of the grey-wolf algorithm compared to particle swarm optimisation with respect to the solving an inverse kinematics task

From urban form to information: Cellular configurations in different spatial cultures

Cities are different worldwide, but does this fact have any relation to culture? The idea that urban form embodies idiosyncrasies related to cultural identities captures the imagination of many in urban studies, but it is an assumption yet to be carefully examined. At its heart, the question of whether cities can be seen as cultural artefacts is informational: whether or not cultural traces can be encoded in the physical configuration of cities. Approaching spatial configuration as a proxy of urban culture, we investigate this possibility by focussing on buildings as the primary components shaping cities. Looking into how buildings aggregate in combinations and complexes, we explore Shannon’s information theory to introduce an entropy measure and analyse frequencies of cellular configurations of built form. We apply this method to downtown areas of 45 cities from different regions around the world. Assessing differences and similarities in cellular configurations, we identify clusters of cities potentially consistent with specific spatial cultures. Our findings suggest a classification scheme that sheds light on the ‘cultural hypothesis’: the possibility that different cultures and regions find different ways of ordering space. We conclude our analysis by arguing that the endless combinatorial possibilities of building configurations, missing from street network approaches, add complexity to cities and prompt a renewed interest in built form systems.

DIPG-40. Combined pharmacological and genetic screening to identify dependencies and combinations in ACVR1-mutant diffuse midline glioma

Somatic mutations in ACVR1, which encodes the serine/threonine kinase ALK2, are found in 20-25% of DMG-H3K27 patients. Treatment of ACVR1-mutant patient-derived models with multiple chemotypes of ALK2 inhibitors (ALK2i) results in reduced cell viability in vitro and extended survival in orthotopic xenografts in vivo but, as single agents, these inhibitors were unable to achieve a complete anti-tumour response. Recently we reported that combinatorial treatment of ACVR1-mutant DIPG cells with vandetanib (RTK inhibitor) and everolimus (mTOR/ABC transporter inhibitor) was synergistic both in vitro and in vivo and was shown to be a feasible combination to trial clinically in this setting. To identify specific dependencies in ACVR1-mutant cells which may be translatable with novel synergistic drug combinations alongside ALK2i, we have implemented both candidate and unbiased drug and genetic screening approaches. Using a panel of patient-derived ACVR1-mutant and wild-type models, we identified synergy between multiple chemotypes of ALK2i (M4K2009/LDN-214117) and PI3K/mTOR (AZD8055/everolimus) and MEK inhibitors (trametinib), reflecting the common co-segregation of PIK3CA/PIK3R1 alterations in these tumours. Whole-genome CRISPR/Cas9 screening of ACVR1-mutant SU-DIPG-IV cells in combination with two ALK2i (M4K2009/LDN-193189), confirmed a specific MTOR genetic dependency, as well as for the protein phosphatase regulatory subunit PPP2R1A, known to play a role in MAPK pathway activation. Additional hits include the serine/threonine kinase PKMYT1, a negative regulator of the G2/M checkpoint via a functionally redundant phosphorylation of CDK1/CCNB1 alongside WEE1; confirmatory drug assays with the WEE1 inhibitor AZD1775 resulted in a synergistic interaction with ALK2i in ACVR1-mutant cells. Hits were integrated with DepMap using ‘gene-effect’ scores (Chronos) enabling filtering of common essential genes. Preliminary pathway enrichment analysis (MAGeCKFlute) identified ALK2i-specific vulnerabilities involving TGFB1/SMAD signalling and histone deacetylation. These data highlight functionally rational and novel combinatorial possibilities for children with ACVR1-mutant DMG, with systematic preclinical assessment required for prioritisation for the clinic.

Differential place marking beyond place names: Evidence from two Amazonian languages

Not all spatial adjuncts behave alike. In some languages, certain spatial adjuncts display different marking or different combinatorial possibilities than others. Recent functional-typological studies make two claims about this differential place marking phenomenon: (1) it is primarily motivated by noun semantics, opposing place names and other nouns; and (2) it is primarily realized as a contrast between zero-marking and overt marking of spatial adjunct function. We evaluate this view against new fieldwork data from two Indigenous Amazonian languages, Dâw (Naduhup) and Ticuna (isolate). In Dâw and Ticuna, differential place marking is conditioned not only by noun semantics, but also by the perceptual properties of noun referents and by morphosyntactic and semantic properties of verbs. Further, the phenomenon is realized not only by alternations between zero and overt marking, but also by alternations among overt markers and alternations in the set of markers with which the adjunct can combine. These findings suggest that differential place marking – like other differential case phenomena, such as split ergativity – is conditioned by a cross-linguistically diverse suite of factors within and beyond the noun phrase.

Developing next generation immunomodulatory drugs and their combinations in multiple myeloma.

Multiple Myeloma (MM) is an incurable malignancy with current treatment choices primarily comprising combination regimens implemented with a risk-adapted approach. Cereblon (CRBN)-targeting immunomodulatory agents (IMiDs®) lenalidomide (LEN) and pomalidomide (POM) play a central role in combination regimens due to their pleiotropic antitumor/immunomodulatory mechanisms that synergize with many anti-myeloma approved or developmental agents. Currently, more potent next generation cereblon E3 ligase modulators (CELMoDs®) - iberdomide (IBER) and CC-92480 are in clinical development. With an expanding number of active agents/therapeutic modalities and a myriad of combinatorial possibilities, physicians and drug developers share an opportunity and challenge to combine and sequence therapies to maximize long-term patient benefit. Understanding drug mechanisms and their application in combination settings as well as the unique disease biology considerations from newly diagnosed (NDMM), relapsed/refractory (RRMM), and maintenance settings will be vital to guide the development of future MM therapies centered on a backbone of IMiD or CELMoD agents. Key aspects of drug activity are critical to consider while evaluating potential combinations: direct antitumor effects, indirect antitumor cytotoxicity, immune surveillance, and adverse side effects. In addition, the treatment journey from NDMM to early and late MM relapses are connected to genomic and immune changes associated with disease progression and acquisition of resistance mechanisms. Based on the types of combinations used and the goals of therapy, insights into mechanisms of drug activity and resistance may inform treatment decisions for patients with MM. Here we focus on the evolving understanding of the molecular mechanisms of CRBN-binding drugs and how they can be differentiated and suggest a strategic framework to optimize efficacy and safety of combinations using these agents.

More than merely verbal disputes

AbstractIt is fundamental that, in philosophy, we make sure that we are not mistaking merely verbal disputes, or “conceptual” disputes, for substantive ones. This essay presents a tripartite framework that is useful for clarifying cases where it is difficult to tell whether we are engaged in substantive or non‐substantive disputes. For this purpose, the essay offers some combinatorial possibilities between the following levels: verbal, conceptual, and objectual. We need to distinguish whether we are arguing about the world, concepts, or words to avoid talking at cross‐purposes and to recognize when our disputes are not worth the time. Distinguishing between these three levels can also throw light and guide research on conceptual engineering, metalinguistic negotiations, metaontology, and so on.

Using machine learning to disentangle LHC signatures of Dark Matter candidates

We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical WIMP Dark Matter candidate in the form of a SUSY neutralino, a pseudo-Goldstone impostor in the shape of an Axion-Like Particle, and a light Dark Matter impostor whose interactions are mediated by a heavy particle. All these benchmarks are tensioned against each other, and against the main SM background (Z+jets). Our analysis uses both the leading-order kinematic features as well as the information of an additional hard jet. We explore different representations of the data, from a simple event data sample with values of kinematic variables fed into a Logistic Regression algorithm or a Fully Connected Neural Network, to a transformation of the data into images related to probability distributions, fed to Deep and Convolutional Neural Networks. We also study the robustness of our method against including detector effects, dropping kinematic variables, or changing the number of events per image. In the case of signals with more combinatorial possibilities (events with more than one hard jet), the most crucial data features are selected by performing a Principal Component Analysis. We compare the performance of all these methods, and find that using the 2D images of the combined information of multiple events significantly improves the discrimination performance.

Tuning Dzyaloshinskii-Moriya interaction in ferrimagnetic GdCo: A first-principles approach

We present a systematic analysis of our ability to tune chiral Dzyaloshinskii-Moriya Interactions (DMI) in compensated ferrimagnetic Pt/GdCo/Pt1-xWx trilayers by cap layer composition. Using first principles calculations, we show that the DMI increases rapidly for only ~ 10% W and saturates thereafter, in agreement with experiments. The calculated DMI shows a spread in values around the experimental mean, depending on the atomic configuration of the cap layer interface. The saturation is attributed to the vanishing of spin orbit coupling energy at the cap layer and the simultaneous constancy at the bottom interface. Additionally, we predict the DMI in Pt/GdCo/X (X=Ta, W, Ir) and find that W in the cap layer favors a higher DMI than Ta and Ir that can be attributed to the difference in d-band alignment around the Fermi level. Our results open up exciting combinatorial possibilities for controlling the DMI in ferrimagnets towards nucleating and manipulating ultrasmall high-speed skyrmions.

Development of ultrahigh-entropy ceramics with tailored oxidation behavior

In the last decade, single-phase high-entropy materials have attracted considerable research interest owing to their unexpected existence and unique combinations of properties. Recent development of 5-cation high-entropy carbides (HECs) has demonstrated alluring properties compared to the rule of mixtures and binary carbides. Proposed here is the development of ultrahigh-entropy carbides (UHECs) containing 6+ principal elements with greater combinatorial possibilities. The use of 6+ multi-cation compositions allows for the design of ceramics with further tunable properties, while likely possessing higher orders of entropic stabilization. There are 133 possible carbide compositions containing 6, 7, 8, or 9 refractory metal cations in equiatomic ratios. Candidate selection for fabrication and material testing was accelerated using a machine learning model that was originally trained to predict the synthesizability of five cation disordered metal carbides. Two compositions from each category of six through eight cations, one containing Cr and one without, plus the one possible nine cation carbide were fabricated and characterized. The potential for these 6+ cation UHECs as improved materials for oxidative environments is demonstrated by comparing the oxidation performance of a 5- and 7-cation system after 10 min at 1973 K in air. The oxidation behavior is correlated with Ellingham diagrams, and it is demonstrated that the 7-cation carbide has the ability to form a transitional stable 5+ cation HEC layer as elements preferentially form oxides, which results in significantly improved oxidation resistance.

In data science we trust: Machine learning for stable halide perovskites

The exploration of the compositional space of halide perovskites is prohibitively costly using traditional experimental research strategies. Sun and colleagues demonstrated a physics-informed, machine-learning-guided, experimental approach that overturns this limitation enabling a rapid and efficient maximization of stability in mixed-cation perovskites.

Borges' Classics: Global Encounters with the Graeco-Roman Past

Borges' Classics: Global Encounters with the Graeco-Roman Past

DISTRIBUTIVE CHARACTERISTICS OF COMBINING

The article is devoted to the study of distributive characteristics of combining forms in Modern English. The material of the study is words and terms taken from the Modern English dictionaries. A number of general scientific (analysis, synthesis, induction, deduction, observation, classification, systematization), as well as purely linguistic methods (method of continuous sampling from lexicographic sources, lexico-semantic analysis, study of vocabulary definitions, contextual interpretation) is applied. The morpheme structure of derivatives with these formants is considered. The positions of the studied units in the morpheme structure of the word are analyzed, as well as the classes of morphemes that are in contact with them. The ways of word formation with the participation of combining forms in Modern English word formation and term formation are singled out. It is revealed that combining forms take an active part in terminological word formation in accordance with the existing patterns and models in the language. In derivation with the participation of the studied elements, depending on the formal means of word formation, affixation, composition and abbreviation are distinguished. The classification of distributive classes with a relatively free and fixed position in the word is given through a detailed study of the sum of all environments of combining forms, order and place, compatibility, properties of their use in relation to other elements are fixed. It was found that the studied elements are characterized by wide combinatorial possibilities, which are manifested in their ability to occupy different positions in the word, which can be relatively free or fixed. Three distributive classes are traced among combining forms the units with relatively free position in a word and fixed position. Bases and prefixes are found in the contact environment of a limited number of combining forms. The vast majority of these forms are combined with elements of the same status and suffixes. Only conditionally complex combining forms are characterized by an identical contact environment on the left and right. Combining forms are mainly characterized by the environment of units with the same status as them (right and left) and suffix environment. A characteristic feature of these elements’ compatibility is the absence of grammatical affixes among the morphemes adjacent to them, and the limited number of prefixes and root morphemes among their contact environment. It seems promising to expand the scope of the study by studying these derivational forms, which function in different terminological systems and in different styles of texts in Modern English. The comparison of combinatorial forms in different modern languages is of particular interest.