Theory in Biosciences最新文献

In an effort to expand the domain of mathematical chemistry and inspire research beyond the realms of graph theory and quantum chemistry, we explore five mathematical chemistry spaces and their interconnectedness. These spaces comprise the chemical space, which encompasses substances and reactions; the space of reaction conditions, spanning the physical and chemical aspects involved in chemical reactions; the space of reaction grammars, which encapsulates the rules for creating and breaking chemical bonds; the space of substance properties, covering all documented measurements regarding substances; and the space of substance representations, composed of the various ontologies for characterising substances.

Herbal medicines are frequently blended in the form of multi-drug combinations primarily based on the precept of medicinal compatibility, to achieve the purpose of treating diseases. However, due to the lack of appropriate techniques and the multi-component and multi-target nature of Chinese medicine compounding, it is tough to explain how the drugs interact with each other. As a rising discipline, cyber pharmacology has formed a new approach characterized by using holistic and systematic "network targets" via the cross-fertilization of computer technology, bioinformatics, and different multidisciplinary disciplines. It can broadly screen the active ingredients of traditional Chinese medicine, enhance the effective utilization of drugs, and elucidate the mechanism of drug action. We will overview the principles of Chinese medicine compounding and dispensing, the research methods of network pharmacology, and the software of network pharmacology in the lookup of compounded Chinese medicines, aiming to supply thoughts for the better application of network pharmacology in the research of Chinese medicines.

Until the mid-nineteenth century, "physiology" was a comprehensive theory of life, expounded and shaped by Johannes P. Müller (1801-1858). Biologists and medical doctors still refer to him today. In the summer term of 1851, Müller gave a lecture on the Comparative Anatomy of animals. This lecture was attended and recorded by Ernst Zeller (1830-1902), a future physician and zoologist, and has recently been published together with a German transcript. In this paper, we situate Johannes Müller within the intellectual history of his time. Through his "empirical idealism," we show how he opposed the speculative tendencies of the romantic understanding of nature, the emerging evolutionism, and the growing splits in the natural sciences. Müller focused on recognizing living nature as a whole and realizing ideal "phenomena" through his empirical research. He considered the notion of the soul of the world. Müller's lecture transcript serves as a poignant testament to German scientific culture in the mid-nineteenth century, a few years before the publication of Darwin's Origin of Species. It also provides valuable insights into the self-contained epistemological foundations of morphology.

The definition, origin and recreation of life remain elusive. As others have suggested, only once we put life into reductionist physical terms will we be able to solve those questions. To that end, this work proposes the phenomenon of life to be the product of two dissipative mechanisms. From them, one characterises extant biological life and deduces a testable scenario for its origin. The proposed theory of life allows its replication, reinterprets ecological evolution and creates new constraints on the search for life.

Cervical cancer is one of the most severe threats to women worldwide and holds fourth rank in lethality. It is estimated that 604, 127 cervical cancer cases have been reported in 2020 globally. With advancements in high throughput technologies and bioinformatics, several cervical candidate genes have been proposed for better therapeutic strategies. In this paper, we intend to prioritize the candidate genes that are involved in cervical cancer progression through a fractal time series-based cross-correlations approach. we apply the chaos game representation theory combining a two-dimensional multifractal detrended cross-correlations approach among the known and candidate genes involved in cervical cancer progression to prioritize the candidate genes. We obtained 16 candidate genes that showed cross-correlation with known cancer genes. Functional enrichment analysis of the candidate genes shows that they involve GO terms: biological processes, cell-cell junction assembly, cell-cell junction organization, regulation of cell shape, cortical actin cytoskeleton organization, and actomyosin structure organization. KEGG pathway analysis revealed genes' role in Rap1 signaling pathway, ErbB signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling pathway, Acute myeloid leukemia, chronic myeloid leukemia, Breast cancer, Thyroid cancer, Bladder cancer, and Gastric cancer. Further, we performed survival analysis and prioritized six genes CDH2, PAIP1, BRAF, EPB41L3, OSMR, and RUNX1 as potential candidate genes for cervical cancer that has a crucial role in tumor progression. We found that our study through this integrative approach an efficient tool and paved a new way to prioritize the candidate genes and these genes could be evaluated experimentally for potential validation. We suggest this may be useful in analyzing the nucleotide sequences and protein sequences for clustering, classification, class affiliation, etc.

The F₁-ATPase enzyme is the smallest-known molecular motor that rotates in 120° steps, driven by the hydrolysis of ATP. It is a multi-subunit enzyme that contains three catalytic sites. A central question is how the elementary chemical reactions that occur in the three sites are coupled to mechanical rotation. Various models and coupling schemes have been formulated in an attempt to answer this question. They can be classified as 2-site (bi-site) models, exemplified by Boyer's binding change mechanism first proposed 50 years ago, and 3-site (tri-site) models such as Nath's torsional mechanism, first postulated 25 years ago and embellished 1 year back. Experimental data collated using diverse approaches have conclusively shown that steady-state ATP hydrolysis by F₁-ATPase occurs in tri-site mode. Hence older models have been continually modified to make them conform to the new facts. Here, we have developed a pure mathematical approach based on combinatorics and conservation laws to test if proposed models are 2-site or 3-site. Based on this novel combinatorial approach, we have proved that older and modified models are effectively bi‒site models in that catalysis and rotation in F₁-ATPase occurs in these models with only two catalytic sites occupied by bound nucleotide. Hence these models contradict consensus experimental data. The recent 2023 model of ATP hydrolysis by F₁-ATPase has been proved to be a true tri-site model based on our novel mathematical approach. Such pure mathematical proofs constitute an important step forward for ATP mechanism. However, in what must be considered an aspect with great scientific potential, the power of such mathematical proofs has not been fully exploited to solve molecular biological problems, in our opinion. We believe that the creative application of pure mathematical proofs (for another example see Nath in Theory Biosci 141:249-260, 2022) can help resolve with finality various longstanding molecular-level issues that arise as a matter of course in the analysis of fundamental biological problems. Such issues have proved extraordinarily difficult to resolve by standard experimental, theoretical, or computational approaches.

The phenomenon of near death and dying experiences has been both of popular interest and of scientific speculation. However, the reality of mental perception at the point of death is currently a subjective experience and has not been formally evaluated. While postmortem gene expression, even in humans, has been evaluated, restoration of postmortem brain activity has heretofore only been attempted in animal models, at the molecular and cellular levels. Meanwhile, progress has been made to translate brain activity of living humans into speech and images. This paper proposes two inter-related thought experiments. First, assuming progress and refinement of the technology of translating human brain activity into interpretable speech and images, can an objective analysis of death experiences be obtained by utilizing these technologies on dying humans? Second, can human brain function be revived postmortem and, if so, can the relevant technologies be utilized for communication with (recently) deceased individuals? In this paper, these questions are considered and possible implications explored.

We consider the standard neural field equation with an exponential temporal kernel. We analyze the time-independent (static) and time-dependent (dynamic) bifurcations of the equilibrium solution and the emerging spatiotemporal wave patterns. We show that an exponential temporal kernel does not allow static bifurcations such as saddle-node, pitchfork, and in particular, static Turing bifurcations. However, the exponential temporal kernel possesses the important property that it takes into account the finite memory of past activities of neurons, which Green's function does not. Through a dynamic bifurcation analysis, we give explicit bifurcation conditions. Hopf bifurcations lead to temporally non-constant, but spatially constant solutions, but Turing-Hopf bifurcations generate spatially and temporally non-constant solutions, in particular, traveling waves. Bifurcation parameters are the coefficient of the exponential temporal kernel, the transmission speed of neural signals, the time delay rate of synapses, and the ratio of excitatory to inhibitory synaptic weights.

This study proposes a landscape-based scenario for the origin of viruses and cells, focusing on the adaptability of preexisting replicons from the RNP (ribonucleoprotein) world. The scenario postulates that life emerged in a subterranean "warm little pond" where organic matter accumulated, resulting in a prebiotic soup rich in nucleotides, amino acids, and lipids, which served as nutrients for the first self-replicating entities. Over time, the RNA world, followed by the RNP world, came into existence. Replicators/replicons, along with the nutritious soup from the pond, were washed out into the river and diluted. Lipid bubbles, enclosing organic matter, provided the last suitable environment for replicons to replicate. Two survival strategies emerged under these conditions: cell-like structures that obtained nutrients by merging with new bubbles, and virus-like entities that developed various techniques to transmit themselves to fresh bubbles. The presented hypothesis provides the possibility for the common origin of cells and viruses on rocky worlds hosting liquid water, like Earth.

The multilevel model of behavioral selection (MLBS) by Borgstede and Eggert (Behav Process 186:104370. 10.1016/j.beproc.2021.104370 , 2021) provides a formal framework that integrates reinforcement learning with natural selection using an extended Price equation. However, the MLBS is so far only formulated for homogeneous populations, thereby excluding all sources of variation between individuals. This limitation is of primary theoretical concern because any application of the MLBS to real data requires to account for variation between individuals. In this paper, I extend the MLBS to account for inter-individual variation by dividing the population into homogeneous sub-populations and including class-specific reproductive values as weighting factors for an individual's evolutionary fitness. The resulting formalism closes the gap between the theoretical underpinnings of behavioral selection and the application of the theory to empirical data, which naturally includes inter-individual variation. Furthermore, the extended MLBS is used to establish an explicit connection between the dynamics of learning and the maximization of individual fitness. These results expand the scope of the MLBS as a general theoretical framework for the quantitative analysis of learning and evolution.