Biological Principles Research Articles

Patient-Derived Models of Cancer in the NCI PDMC Consortium: Selection, Pitfalls, and Practical Recommendations.

For over a century, early researchers sought to study biological organisms in a laboratory setting, leading to the generation of both in vitro and in vivo model systems. Patient-derived models of cancer (PDMCs) have more recently come to the forefront of preclinical cancer models and are even finding their way into clinical practice as part of functional precision medicine programs. The PDMC Consortium, supported by the Division of Cancer Biology in the National Cancer Institute of the National Institutes of Health, seeks to understand the biological principles that govern the various PDMC behaviors, particularly in response to perturbagens, such as cancer therapeutics. Based on collective experience from the consortium groups, we provide insight regarding PDMCs established both in vitro and in vivo, with a focus on practical matters related to developing and maintaining key cancer models through a series of vignettes. Although every model has the potential to offer valuable insights, the choice of the right model should be guided by the research question. However, recognizing the inherent constraints in each model is crucial. Our objective here is to delineate the strengths and limitations of each model as established by individual vignettes. Further advances in PDMCs and the development of novel model systems will enable us to better understand human biology and improve the study of human pathology in the lab.

Biological processes and factors involved in soft and hard tissue healing.

Wound healing is a complex and iterative process involving myriad cellular and biologic processes that are highly regulated to allow satisfactory repair and regeneration of damaged tissues. This review is intended to be an introductory chapter in a volume focusing on the use of platelet concentrates for tissue regeneration. In order to fully appreciate the clinical utility of these preparations, a sound understanding of the processes and factors involved in soft and hard tissue healing. This encompasses an appreciation of the cellular and biological mediators of both soft and hard tissues in general as well as specific consideration of the periodontal tissues. In light of good advances in this basic knowledge, there have been improvements in clinical strategies and therapeutic management of wound repair and regeneration. The use of platelet concentrates for tissue regeneration offers one such strategy and is based on the principles of cellular and biologic principles of wound repair discussed in this review.

The Giardia lamblia ribosome structure reveals divergence in several biological pathways and the mode of emetine function

Giardia lamblia is a deeply branching protist and a human pathogen. Its unusual biology presents the opportunity to explore conserved and fundamental molecular mechanisms. We determined the structure of the G.lamblia 80S ribosome bound to tRNA, mRNA, and the antibiotic emetine by cryo-electron microscopy, to an overall resolution of 2.49Å. The structure reveals rapidly evolving protein and nucleotide regions, differences in the peptide exit tunnel, and likely altered ribosome quality control pathways. Examination of translation initiation factor binding sites suggests these interactions are conserved despite a divergent initiation mechanism. Highlighting the potential of G. lamblia to resolve conserved biological principles; our structure reveals the interactions of the translation inhibitor emetine with the ribosome and mRNA, thus providing insight into the mechanism of action for this widely used antibiotic. Our work defines key questions in G. lamblia and motivates future experiments to explore the diversity of eukaryotic gene regulation.

Decoding the DNA methylome of central nervous system tumors: An emerging modality for integrated diagnosis.

The definitive diagnosis and classification of individual cancers are crucial for patient care and cancer research. To achieve a robust diagnosis of central nervous system (CNS) tumors, a genotype-phenotype integrated diagnostic approach was introduced in recent versions of the World Health Organization classification, followed by the incorporation of a genome-wide DNA methylome-based classification. Microarray-based platforms are widely used to obtain DNA methylome data, and the German Cancer Research Center (Deutsches Krebsforschungszentrum [DKFZ]) has a webtool for a DNA methylation-based classifier (DKFZ classifier). Integration of DNA methylome will further enhance the precision of CNS tumor classification, especially in diagnostically challenging cases. However, in the clinical application of DNA methylome-based classification, challenges related to data interpretation persist, in addition to technical caveats, regulations, and limited accessibility. Dimensionality reduction (DMR) can complement integrated diagnosis by visualizing a profile and comparing it with other known samples. Therefore, DNA methylome-based classification is a highly useful research tool for auxiliary analysis in challenging diagnostic and rare disease cases, and for establishing novel tumor concepts. Decoding the DNA methylome, especially by DMR in addition to DKFZ classifier, emphasizes the capability of grasping the fundamental biological principles that provide new perspectives on CNS tumors.

From Homogeneity to Turing Pattern: Kinetically Controlled Self-Organization of Transmembrane Protein.

Understanding the spatial organization of membrane proteins is crucial for unraveling key principles in cell biology. The reaction-diffusion model is commonly used to understand biochemical patterning; however, applying reaction-diffusion models to subcellular phenomena is challenging because of the difficulty in measuring protein diffusivity and interaction kinetics in the living cell. In this work, we investigated the self-organization of the plasmalemma vesicle-associated protein (PLVAP), which creates regular arrangements of fenestrated ultrastructures, using single-molecule tracking. We demonstrated that the spatial organization of the ultrastructures is associated with a decrease in the association rate by actin destabilization. We also constructed a reaction-diffusion model that accurately generates a hexagonal array with the same 130 nm spacing as the actual scale and informs the stoichiometry of the ultrastructure, which can be discerned only through electron microscopy. Through this study, we integrated single-molecule experiments and reaction-diffusion modeling to surpass the limitations of static imaging tools and proposed emergent properties of the PLVAP ultrastructure.

Sustainable Product Lifecycle Management – Implementation of a Digital Twin of a Biologically Transformed Product-Ecosystem

Biological transformation is the transfer of principles of natural systems to technical materials, processes and systems. The essential concepts of biological transformation - inspiration (learning from the observation of nature for the adaptation of technology), integration (symbiosis of technical systems based on biological principles) and interaction (interweaving of nature with technology) - can be transferred to Industry 4.0 solutions. One of these solutions is the Digital Twin, which can be used to provide transparency of an individual product’s environmental impact and to positively influence it throughout all lifecycle phases. A Digital Twin can be seen a digital ecosystem that inherits various biological principles itself, but also serves as an enabler of biologically transformed products. The application of the principles of biological transformation to Industry 4.0 helps achieve sustainable value creation. Manufacturing and operating companies, leveraging operational data with the help of Digital Twins, are equipped to better understand a product ecosystem’s performance and identify constraining resources that determine its lifecycle sustainability. This paper demonstrates the concept development of a Digital Twin for a biologically transformed product-ecosystem with integrated sustainability assessment focused on the production phase and its corresponding user interface.

A Physiological-Informed Generative Model for Improving Breast Lesion Classification in Small DCE-MRI Datasets.

In biomedical image processing, Deep Learning (DL) is increasingly exploited in various forms and for diverse purposes. Despite unprecedented results, the huge number of parameters to learn, which necessitates a substantial number of annotated samples, remains a significant challenge. In medical domains, obtaining high-quality labelled datasets is still a challenging task. In recent years, several works have leveraged data augmentation to face this issue, mostly thanks to the introduction of generative models able to produce artificial samples having the same characteristics as the acquired ones. However, we claim that biological principles must be considered in this process, as all medical imaging techniques exploit one or more physical laws or properties directly associated with the physiological characteristics of the tissues under analysis. A notable example is the Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI), in which the kinetic of the contrast agent (CA) highlights both morphological and physiological aspects. In this paper, we introduce a novel generative approach explicitly relying on Physiologically Based Pharmacokinetic (PBPK) modelling and on an Intrinsic Deforming Autoencoder (DAE) to implement a physiologically-aware data augmentation strategy. As a case of study, we consider breast DCE-MRI. In particular, we tested our proposal on two private and one public datasets with different acquisition protocols, demonstrating that the proposed method significantly improves the performance of several DL-based lesion classifiers.

Current research on mechanisms of limb bud development, and challenges for the next decade.

The developmental mechanisms of limb buds have been studied in developmental biology as an excellent model of pattern formation. Chick embryos have contributed to the discovery of new principles in developmental biology, as it is easy to observe live embryos and manipulate embryonic tissues. Herein, I outline recent findings and future issues over the next decade regarding three themes, based on my research: limb positioning, proximal-distal limb elongation and digit identity determination. First, how hindlimb position is determined at the molecular level is described, with a focus on the transforming growth factor-β signaling molecule GDF11. Second, I explain how the cell population in the limb bud deforms with developmental progress, shaping the limb bud with elongation along the proximal-distal axis. Finally, I describe the developmental mechanisms that determine digit identity through the interdigits.

Proliferative activity of normal tissues and malignant tumors during infestation of the organism by a biotic ecopathogen

The article shows the role of metabolites of metacercariae and opisthorchiae in the induction of proliferative activity of somatic cells of the hepatobiliary system and other organs. The importance of cellular and tissue bioregulators in increasing the level of proliferative activity of various tissues in organisms infested by the trematode Opisthorchis felineus is considered. It follows from the data obtained that the biological function of a tissue-specific keilon–containing effector produced by differentiated cells and inhibiting cell proliferation based on the biological feedback principle, in comparison with the background of prolonged parasitization of this ecopathogenic helminth in the hepatobiliary system of the body, decreases. There is also a decrease in the sensitivity of somatic cells to a tissue-specific growth inhibiting factor. It follows that the activation of cellular and tissue proliferation of animals longterm infested by opisthorchiasis is also due to a violation of the mechanisms of regulation of cellular and tissue homeostasis. This is confirmed by an increase in the growth rate of syngenic malignant tumors, as well as a modification of the effect of homologous leukocyte interferon from an inhibitor of the malignant process to an activator.

LINgroups as a Robust Principled Approach to Compare and Integrate Multiple Bacterial Taxonomies.

As a central organizing principle of biology, bacteria and archaea are classified into a hierarchical structure across taxonomic ranks from kingdom to subspecies. Traditionally, this organization was based on observable characteristics of form and chemistry but recently, bacterial taxonomy has been robustly quantified using comparisons of sequenced genomes, as exemplified in the Genome Taxonomy Database (GTDB). Such genome-based taxonomies resolve genomes down to genera and species and are useful in many contexts yet lack the flexibility and resolution of a fine-grained approach. The Life Identification Number (LIN) approach is a common, quantitative framework to tie existing (and future) bacterial taxonomies together, increase the resolution of genome-based discrimination of taxa, and extend taxonomic identification below the species level in a principled way. Utilizing LINgroup as an organizational concept helps resolve some of the confusion and unforeseen negative effects resulting from nomenclature changes of microorganisms that are closely related by overall genomic similarity (often due to genome-based reclassification). Our experimental results demonstrate the value of LINs and LINgroups in mapping between taxonomies, translating between different nomenclatures, and integrating them into a single taxonomic framework. They also reveal the robustness of LIN assignment to hyper-parameter changes when considering within-species taxonomic groups.

Tillage techniques in grass crop rotations in Western Kazakhstan

The transition to new technologies is predetermined by global and domestic scientific and production experience and general trends in the development of agriculture. The basis of grass crop rotations is the general biological principle of the different effects of perennial grasses on the soil. To the problem of forage production for the conditions of the arid steppe of Western Kazakhstan with an annual rainfall of 250-300 mm, a method of using forage crops based on grass crop rotation is proposed. Periodic change of different crops in crop rotation plays a positive phytosanitary role in clearing the soil of weeds. The article discusses three types of soil cultivation techniques based on the principles of sustainable production of grain crops and stabilization of soil fertility in the conditions of Western Kazakhstan. The research was carried out on the basis of the Ural Agricultural Experimental Station LLP. The purpose of the research is to develop methods of soil cultivation in grass crop rotations for the accumulation, conservation and rational use of soil moisture in resource-saving technologies for cultivating basic field crops, ensuring the preservation of soil fertility, improving the phytosanitary condition of crops in the dry steppe zone of Western Kazakhstan. The objective of the research is to study the influence of methods for processing turf of perennial grasses in the structure of crop rotations in order to stabilize soil fertility and the phytosanitary condition of crops. Three types of processing were used in the studies: flat cutter, slotting + cultivation, cultivation. Grass crop rotation was sown over a layer of perennial grasses and included the following forage crops: sorghum, corn and millet. The best results in terms of yield were observed based on the joint interaction of technologies for factor B (slotting + cultivation).

Promoters and Synthetic Promoters in Trichoderma reesei.

Trichoderma reesei holds immense promise for large-scale protein production, rendering it an excellent subject for deeper exploration using genetic engineering methods to achieve a comprehensive grasp of its cellular physiology. Understanding the genetic factors governing its intrinsic regulatory network is crucial, as lacking this knowledge could impede the expression of target genes. Prior and ongoing studies have concentrated on advancing new expression systems grounded in synthetic biology principles. These methodologies involve utilizing established potent promoters or engineered variations. Genomic and transcriptomic analyses have played a pivotal role in identifying robust promoters and expression systems, including light-responsive, copper-inducible, L-methionine-inducible, and Tet-On systems, among others. This chapter seeks to highlight various research endeavors focusing on tunable and constitutive promoters, the impact of different promoters on both native and foreign protein expression, the discovery of fresh promoters, and strategies conducive to future research aimed at refining and enhancing protein expression in T. reesei. Characterizing new promoters and adopting innovative expression systems hold the potential to significantly expand the molecular toolkit accessible for genetically engineering T. reesei strains. For instance, modifying potent inducible promoters such as Pcbh1 by replacing transcriptional repressors (cre1, ace1) with activators (xyr1, ace2, ace3, hap2/3/5) and integrating synthetic expression systems can result in increased production of crucial enzymes such as endoglucanases (EGLs), β-glucosidases (BGLs), and cellobiohydrolases (CBHs). Similarly, robust constitutive promoters such as Pcdna1 can be converted into synthetic hybrid promoters by incorporating activation elements from potent inducible promoters, facilitating cellulase induction and expression even under repressive conditions. Nevertheless, further efforts are necessary to uncover innovative promoters and devise novel expression strategies to enhance the production of desired proteins on an industrial scale.

Parylene-MoOx crossbar memristors as a volatile reservoir and non-volatile readout: a homogeneous reservoir computing system.

From the very beginning, the emulation of biological principles has been the primary avenue for the development of energy-efficient artificial intelligence systems. Reservoir computing, which has a solid biological basis, is particularly appealing due to its simplicity and efficiency. So-called memristors, resistive switching elements with complex dynamics, have proved beneficial for replicating both principal parts of a reservoir computing system. However, these parts require distinct behaviors found in differing memristive structures. The development of a homogeneous memristive reservoir computing system will significantly facilitate and reduce the fabrication process cost. The following work employs the co-existence of volatile and non-volatile regimes in parylene-MoOx crossbar memristors controlled by compliance current for this aim. The stable operation of the memristors under study is confirmed by low cycle-to-cycle and device-to-device variations of the switching voltages. For the transition between the volatile and non-volatile regimes, factors such as compliance current and reading voltage along with possible intrinsic origins are discussed. The results provide a foundation for the future hardware development of a homogeneous parylene-based reservoir computing system, considering high MNIST dataset classification accuracy (∼96%).

SLInterpreter: An Exploratory and Iterative Human-AI Collaborative System for GNN-based Synthetic Lethal Prediction.

Synthetic Lethal (SL) relationships, though rare among the vast array of gene combinations, hold substantial promise for targeted cancer therapy. Despite advancements in AI model accuracy, there is still a significant need among domain experts for interpretive paths and mechanism explorations that align better with domain-specific knowledge, particularly due to the high costs of experimentation. To address this gap, we propose an iterative Human-AI collaborative framework with two key components: 1) HumanEngaged Knowledge Graph Refinement based on Metapath Strategies, which leverages insights from interpretive paths and domain expertise to refine the knowledge graph through metapath strategies with appropriate granularity. 2) Cross-Granularity SL Interpretation Enhancement and Mechanism Analysis, which aids experts in organizing and comparing predictions and interpretive paths across different granularities, uncovering new SL relationships, enhancing result interpretation, and elucidating potential mechanisms inferred by Graph Neural Network (GNN) models. These components cyclically optimize model predictions and mechanism explorations, enhancing expert involvement and intervention to build trust. Facilitated by SLInterpreter, this framework ensures that newly generated interpretive paths increasingly align with domain knowledge and adhere more closely to real-world biological principles through iterative Human-AI collaboration. We evaluate the framework's efficacy through a case study and expert interviews.

Bionic dual-scale structured films for efficient passive radiative cooling accompanied by robust durability.

Passive radiative cooling (PRC), as an energy-free cooling approach, is ingeniously harnessed for certain natural organisms to withstand extreme high-temperature climates, which has inspired numerous bionic designs. However, it is a great challenge to enhance the durability of the designed materials in practical scenarios while inheriting the natural biological principles. We demonstrate bionic dual-scale structured (BDSS) films for efficient passive radiative cooling accompanied by robust durability after discovering the excellent thermoregulatory properties of the inner surface of Hawaiian scallop shell. We found that the inner surface of the shell consists of large-scale triangular ridges scattered with small-scale terrace steps. This dual-scale structure can enhance the reflectivity of sunlight by efficient Mie scattering and increase the emissivity in the mid-infrared range by lengthening the propagation of photons, thereby decreasing the surface temperature. Underpinned by this finding, we developed a BDSS film that features a strong solar spectrum reflectivity of 0.95 and a high mid-infrared emissivity of 0.98, achieving a sub-ambient cooling of 10.8 °C under direct sunlight. Additionally, the designed films possess robust durability including excellent self-cleaning, flexibility, mechanical strength, chemical stability, and anti-ultraviolet radiation, which is promising for thermal thermoregulation in various harsh scenarios.

Biomimicry as a sustainable solution in Architecture: Analytical study

Nature has been the primary inspiration for architecture since its very beginnings, and there are many facets and levels of this inspiration in architecture, starting from the stage of direct imitation of the formal aspects and proportions, passing through the aspects of masses and construction, all the way to the deep levels and principles upon which nature is based and achieving its sustainability. Therefore, the architecture, in the current time and for future times, is directed towards simulating the deep aspects of biological systems and taking advantage of their features, such as self-organization, adaptation, flexibility, and efficiency, in a way that achieves the desired goal of architecture, which is its sustainability. This is also through the emergence of the term (biomimetic), which the research focuses on for its ability to combine biology and architecture. From a review of the literature that dealt with this term, the research problem emerged as “the lack of clarity about biomimicry as a strategy aims at achieving aspects of sustainability.” Hence, the research objective was defined by determining the possibility of benefiting from the trend of biomimicry as a tool and strategy for achieving sustainability while studying its applications in design and architecture. To achieve the research objective, a descriptive and analytical approach was adopted, in addition to several procedural steps, the first related to the theoretical aspects of the topic and building a theoretical framework for it. The second step was the practical study by analyzing a few approved projects. The last (third) procedural step was to draw results and conclusions. The research reached several conclusions that reflect the role of adopting the biomimetic approach in enhancing the efficiency and effectiveness of architecture and its sustainability and emphasizing the achievement of architecture responsive to environmental conditions by enhancing its natural systems to increase their efficiency and suitability to the requirements of development. The research also concluded that this approach will determine the path of contemporary and future architecture by approaching biological principles with architectural principles.

EvolSOM: An R package for analyzing conservation and displacement of biological variables with self-organizing maps.

Unraveling the connection between genes and traits is crucial for solving many biological puzzles. Ribonucleic acid molecules and proteins, derived from these genetic instructions, play crucial roles in shaping cell structures, influencing reactions, and guiding behavior. This fundamental biological principle links genetic makeup to observable traits, but integrating and extracting meaningful relationships from this complex, multimodal data present a significant challenge. We introduce evolSOM, a novel R package that allows exploring and visualizing the conservation or displacement of biological variables, easing the integration of phenotypic and genotypic attributes. It enables the projection of multi-dimensional expression profiles onto interpretable two-dimensional grids, aiding in the identification of conserved or displaced genes/phenotypes across multiple conditions. Variables displaced together suggest membership to the same regulatory network, where the nature of the displacement may hold biological significance. The conservation or displacement of variables is automatically calculated and graphically presented by evolSOM. Its user-friendly interface and visualization capabilities enhance the accessibility of complex network analyses. The package is open-source under the GPL ( 3) and is available at https://github.com/sanprochetto/evolSOM, along with a step-by-step vignette and a full example dataset that can be accessed at https://github.com/sanprochetto/evolSOM/tree/main/inst/extdata.

DNA Computing: A Paradigm Shift from Silicon to Carbon

DNA computing, a fascinating frontier in the realm of biological computing, marks a paradigm shift from traditional silicon-based processing to the innovative realm of carbon-based computation. Rooted in the principles of molecular biology, DNA computing harnesses the inherent parallelism of biological systems, offering a revolutionary approach to data storage, processing, and solving complex problems.

Principles of Cell Biology

Principles of Cell Biology

Biologically Structured Water (BSW) - A Review (Part 3): Structured Water (SW) Generation, BSW Water, Bioenergetics, Consciousness and Coherence

Natural water sources become partially structured when exposed to cold temperatures, aeration, and sunlight in high mountain streams or kosmotropic ions. Drinking water devices that make structured water utilize methods such as resonance, vortex designs, and static magnets to alter H-bond configurations in liquid water. Other methods, such as the Advanced Oxidation Process (AOP) or vortexing, utilize energy or mechanical methods that are strong enough to break the covalent bonds in liquid water. After water splits into hydronium ions (H30+) and hydroxyl radicals (•OH), these molecular species rapidly reform back into SW water with stable H-bonds. Several companies offer AOP water generators for the remediation of wastewater, industrial water treatment, hydroponic, and agricultural uses. Other companies offer vortex generators for SW drinking water for households and institutions. The final section summarizes the interconnectivity and synchronization between BSW water, bioenergetics, consciousness, and quantum coherence. The continuous layer of BSW water within all cells and covering all biological membranes allows it to capture, store, resonate, amplify, and transmit a wide spectrum of EMF energy that forms the basis of bioenergetics. Application of quantum biology principles to BSW water opens promising research fields potent with solutions to enhance human health and longevity. Other SW and BSW water research areas potentially include environmental and wastewater treatment, medical treatments for age-related diseases, energy generation, and possibly even manipulation of rainfall patterns.