Mechanical loading in articular cartilage drives interstitial fluid flow through the porous collagen proteoglycan matrix, generating electrokinetic signals. We investigate whether the structural organization of cartilage histology can be translated into a computational representation capable of predicting its electrokinetic behavior. Histological pictures were analyzed to build a pore-network graph representing potential pathways for interstitial fluid transport. Pressure driven flow was simulated using hydraulic conductance relations, while electrical potentials were estimated through electrokinetic coupling between pressure gradients and ion displacement. Simulations comparing networks derived from healthy and degenerative cartilage showed that pathological structures exhibited fragmented connectivity and lower predicted signal amplitudes, whereas physiological architecture generated more coherent transport trajectories and stronger electrical responses. Our simulations yield testable predictions, depth-dependent electrical signals across cartilage layers with directional anisotropy relative to collagen orientation. Potential applications include improved experimental assessment of cartilage transport biomechanics and integration of microstructural imaging with computational models of charged porous biomaterials.
Living systems self-organize in ways that conventional physical frameworks-based on forces, energies, and continuous fields-cannot fully capture. Processes like gene regulation and cellular decision-making involve rule-based logic and computational interactions. Here, I introduce the concept of non-equilibrium capacity (NEC) to denote the finite capacity of living systems to generate and sustain life-associated dynamics-the very capacity that defines viability-and whose irreversible loss constitutes death. I argue that two lines of inquiry are especially promising for understanding why this capacity is inevitably lost. First, experiments that slow or suspend all cellular processes reveal "low speed limits" below which life collapses. Second, generalized cellular automata-where cells interact over diffusion-defined neighborhoods and obey discrete rules-provide a framework to understand how order emerges or persists. Together, these approaches suggest a new grammar of biology that complements energy-based physics and explains how living systems sustain and ultimately lose their NEC.
Jürgen Duchenne, Camilla K. Larsen, Marta Cvijic
et al.
Background and aim: The presence of mechanical dyssynchrony on echocardiography is associated with reverse remodelling and decreased mortality after cardiac resynchronization therapy (CRT). Contrarily, myocardial scar reduces the effect of CRT. This study investigated how well a combined assessment of different markers of mechanical dyssynchrony and scarring identifies CRT responders. Methods: In a prospective multicentre study of 170 CRT recipients, septal flash (SF), apical rocking (ApRock), systolic stretch index (SSI), and lateral-to-septal (LW-S) work differences were assessed using echocardiography. Myocardial scarring was quantified using cardiac magnetic resonance imaging (CMR) or excluded based on a coronary angiogram and clinical history. The primary endpoint was a CRT response, defined as a ≥15% reduction in LV end-systolic volume 12 months after implantation. The secondary endpoint was time-to-death. Results: The combined assessment of mechanical dyssynchrony and septal scarring showed AUCs ranging between 0.81 (95%CI: 0.74–0.88) and 0.86 (95%CI: 0.79–0.91) for predicting a CRT response, without significant differences between the markers, but significantly higher than mechanical dyssynchrony alone. QRS morphology, QRS duration, and LV ejection fraction were not superior in their prediction. Predictive power was similar in the subgroups of patients with ischemic cardiomyopathy. The combined assessments significantly predicted all-cause mortality at 44 ± 13 months after CRT with a hazard ratio ranging from 0.28 (95%CI: 0.12–0.67) to 0.20 (95%CI: 0.08–0.49). Conclusions: The combined assessment of mechanical dyssynchrony and septal scarring identified CRT responders with high predictive power. Both visual and quantitative markers were highly feasible and demonstrated similar results. This work demonstrates the value of imaging LV mechanics and scarring in CRT candidates, which can already be achieved in a clinical routine.
Fadhil G. Al-Amran, Abbas M. Hezam, Salman Rawaf
et al.
This study presents a novel approach at the intersection of genomic analysis and artificial intelligence (AI) to predict viral mutations and assess the risks of future pandemics. Through comprehensive genomic analysis, genetic markers associated with increased virulence and transmissibility are identified. Advanced machine learning algorithms are employed to analyze genetic data and forecast viral mutations, taking into account factors such as replication rates, host-pathogen interactions, and environmental influences. The research also evaluates the risk of future pandemics by examining zoonotic reservoirs, human-animal interfaces, and climate change impacts. AI-powered risk assessment models provide insights into potential outbreak hotspots, facilitating targeted surveillance and preventive measures. This research offers a proactive approach to pandemic preparedness, enabling early intervention and the development of effective containment strategies and vaccines. The fusion of genomic analysis and AI enhances our ability to mitigate the impact of infectious diseases on a global scale, emphasizing the importance of proactive measures in safeguarding public health.
The aim of this study was to determine the germination ability and seedling growth of the apple of Sodom by soaking in water, gibberellin (GA3), naphthylacetic acid (NAA), and salicylic acid (SA), separately. The findings showed that NAA at 50 mgL-1 produced superior germination (77.78%), germination speed (1.43 seeds/time interval), hypocotyl length (1.01 cm), hypocotyl diameter (1.13 mm), leaf number (2.66), and root number (17.25), followed by 50 and 100 mgL-1 GA3, particularly in germination percentage. The best root length (5.33 cm) was detected at 100 mgL-1 SA. In contrast, control seeds and water-soaked seeds showed inferior results. The seeds of the apple of Sodom can be germinated successfully as a result of treatment with NAA at 50 mgL-1, followed by GA3 at 50 and 100 mgL-1.
Cancer, as the uncontrollable cell growth, is related to many branches of biology. In this review, we will discuss three mathematical approaches for studying cancer biology: population dynamics, gene regulation, and developmental biology. If we understand all biochemical mechanisms of cancer cells, we can directly calculate how the cancer cell population behaves. Inversely, just from the cell count data, we can use population dynamics to infer the mechanisms. Cancer cells emerge from certain genetic mutations, which affect the expression of other genes through gene regulation. Therefore, knowledge of gene regulation can help with cancer prevention and treatment. Developmental biology studies acquisition and maintenance of normal cellular function, which is inspiring to cancer biology in the opposite direction. Besides, cancer cells implanted into an embryo can differentiate into normal tissues, which provides a possible approach of curing cancer. This review illustrates the role of mathematics in these three fields: what mathematical models are used, what data analysis tools are applied, and what mathematical theorems need to be proved. We hope that applied mathematicians and even pure mathematicians can find meaningful mathematical problems related to cancer biology.
Ana Mariya Anhel, Lorea Alejaldre, Manuel Gimenez
et al.
This protocol is meant to create a PCR mastermix with 1 or more primer sets, distribute it in 1 or more 96-well plates, inoculate from 1 or more 96-well plates containing the template and run the reaction in an OT-2 thermocycler (if available). This protocol is run by using a LAP format script and its corresponding .xlsx file were different customizable variables such as volumes of transfer, type of plates, number of primers per set, and availability of OT-2 thermocycler are indicated. Specifically, this protocol provides a set of instructions or description of the LAP repository entry LAP-PCR-OT2-2.0.0. You can find the script and complementary information for this specific version of the protocol in the LAP entry link and GitHub link to LAP entry documents In our laboratory, this protocol has been used as part of the "High-throughput workflow for the genotypic characterization of transposon insertion library variants" also available in protocols.io to prepare arbitrary and spurious PCR samples. The current version incorporates the following modifications: Description of robot and protocol setup in a separate protocols.io entry (Setting and Customizing OT-2 for LAP Entries) When transferring the polymerase and primers, change tip every time it aspirates from source tubes Wells with controls can be anywhere in the plate New variable in Sheet 'ModuleVariables' called 'Max Volume Per Mix Tube In Shaker'
The ubiquity of computation in modern scientific research inflicts new challenges for reproducibility. While most journals now require code and data be made available, the standards for organization, annotation, and validation remain lax, making the data and code often difficult to decipher or practically use. I believe that this is due to the documentation, collation, and validation of code and data only being done in retrospect. In this essay, I reflect on my experience contending with these challenges and present a philosophy for prioritizing reproducibility in modern biological research where balancing computational analysis and wet-lab experiments is commonplace. Modern tools used in scientific workflows (such as GitHub repositories) lend themselves well to this philosophy where reproducibility begins at project inception, not completion. To that end, I present and provide a programming-language agnostic template architecture that can be immediately copied and made bespoke to your next paper, whether your lab work is wet, dry, or somewhere in between.
Individuals infected with SARS-CoV-2, the virus that causes COVID-19, may shed the virus in stool before developing symptoms, suggesting that measurements of SARS-CoV-2 concentrations in wastewater could be a "leading indicator" of COVID-19 prevalence. Multiple studies have corroborated the leading indicator concept by showing that the correlation between wastewater measurements and COVID-19 case counts is maximized when case counts are lagged. However, the meaning of "leading indicator" will depend on the specific application of wastewater-based epidemiology, and the correlation analysis is not relevant for all applications. In fact, the quantification of a leading indicator will depend on epidemiological, biological, and health systems factors. Thus, there is no single "lead time" for wastewater-based COVID-19 monitoring. To illustrate this complexity, we enumerate three different applications of wastewater-based epidemiology for COVID-19: a qualitative "early warning" system; an independent, quantitative estimate of disease prevalence; and a quantitative alert of bursts of disease incidence. The leading indicator concept has different definitions and utility in each application.
We introduce a digital twin of the classical compartmental SIR (Susceptible, Infected, Recovered) epidemic model and study the interrelation between the digital twin and the system. In doing so, we use Stieltjes derivatives to feed the data from the real system to the virtual model which, in return, improves it in real time. As a byproduct of the model, we present a precise mathematical definition of solution to the problem. We also analyze the existence and uniqueness of solutions, introduce the concept of Main Digital Twin and present some numerical simulations with real data of the COVID-19 epidemic, showing the accuracy of the proposed ideas.
Ability of smooth muscles to contract in response to distension plays a crucial role in motor function of intestine. Qualitative analysis of dynamical models using myogenic active property of smooth muscles has shown well agreement with physiologic data. Considered as a self-regulatory unit, function of gastrointestinal (GI) segment is assumed to be regulated by integration of basis patterns providing accumulation and propagation of intestinal content. By implementing external, depending on neural system, variable to the previous model, and considering two attaches to one another reservoirs as a physical analogue of the segmental partition of intestine, a system of six ODE equations, three for each reservoir, describes coordinated wall motions and propagation of the content from one reservoir to another. It was shown that besides negative feedback (NFB), other functional patterns, namely positive feedback (PFB) and reciprocal links (RL) are involved in regulations of filling-emptying cycle. Being integrated in a whole functional system these three patterns expressed in a matrix form represent basis elements of imaginary part of coquaternion which with identity basis component is an algebraically closed structure under addition and multiplication of its elements. A coquaternion ring may be considered as a model of inner self-regulatory functional structure providing coordinated wall motions of GI tract portions.
Cytoskeletons are self-organized networks based on polymerized proteins: actin, tubulin, and driven by motor proteins, such as myosin, kinesin and dynein. Their positive Darwinian evolution enables them to approach optimized functionality (self-organized criticality). The principal features of the eukaryotic evolution of the cytoskeleton motor protein myosin-1 parallel those of actin and tubulin, but also show striking differences connected to its dynamical function. Optimized (long) hydropathic waves characterize the molecular level Darwinian evolution towards optimized functionality (self-organized criticality). The N-terminal and central domains of myosin-1 have evolved in eukaryotes at different rates, with the central domain hydropathic extrema being optimally active in humans. A test shows that hydropathic scaling can yield accuracies of better than 1% near optimized functionality. Evolution towards synchronized level extrema is connected to a special function of Mys-1 in humans involving Golgi complexes.
The genesis of the stand genetic code is considered as a result of a fusion of two AU- and GC-codes distributed in two dominant and two recessive domains. The fusion of these codes is described with simple empirical rules. This formal approach explains the number of the proteinogenic amino acids and the codon assignment in the resulting standard genetic code. It shows how norleucine, pyrrolysine, selenocysteine and two other unknown amino acids, included into the prebiotic codes, disappeared after the fusion. The properties of these two missing amino acids were described. The ambiguous translation observed in mitochondria is explained. The internal structure of the codes allows a more detailed insights into molecular evolution in prebiotic time. In particular, the structure of the oldest single base-pair code is presented. The fusion concept reveals the appearance of the DNA machinery on the level of the single dominant AU-code. The time before the appearance of standard genetic code is divided into four epochs: pre-DNA, 2-code, pre-fusion, and after-fusion epochs. The prebiotic single-base-pair codes may help design novel peptide-based catalysts.
Velvet worms, or onychophorans, are animals of extraordinary importance in the study of evolution. This is the first history of their study. They were described by Lansdown Guilding (1797-1831). This paper identifies the landmarks of their study, in a worldwide level, for almost 200 years. The beginning, 1826-1879, was based on describing their anatomy with light miscroscopy, mostly by famous French naturalists such as Milne-Edwards and Blanchard. In 1880-1929 peiord, work concentrated in anatomy, physiology, behavior, biogeography and ecology, but the most important work was Bouvier`s mammoth monograph. The next period, 1930-1979, was important for the discovery of Cambrian species; Vachons explanation of how ancient distribution defined the existence of two families; Pioneer DNA and electron microscopy from Brazil; and primitive attempts at systematics using embryology or isolated anatomical characteristics. Finally, the 1980-2020 period, with research centered in Australia, Brazil, Costa Rica and Germany, is marked by an evolutionary approach to everything, from body and behavior to distribution; for the solution of the old problem of how they form their adhesive net and how the glue works; the reconstruction of Cambrian onychophoran communities, the first experimental taphonomy; the first countrywide map of conservation status (from Costa Rica); the first model of why they survive in cities; the discovery of new phenomena like food hiding, parental feeding investment and ontogenetic diet shift; and for the birth of a new research branh, Onychophoran Etnobiology, founded in 2015,
Ever since the advent of molecular biology in the 1970s, mechanical models have become the dogma in the field, where a "true" understanding of any subject is equated to a mechanistic description. This has been to the detriment of the biomedical sciences, where, barring some exceptions, notable new feats of understanding have arguably not been achieved in normal and disease biology, including neurodegenerative disease and cancer pathobiology. I argue for a "mechanism-plus-X" paradigm, where mainstay elements of mechanistic models such as hierarchy and correlation are combined with nomological principles such as general operative rules and generative principles. Depending on the question at hand and the nature of the inquiry, X could range from proven physical laws to speculative biological generalizations, such as the notional principle of cellular synchrony. I argue that the "mechanism-plus-X" approach should ultimately aim to move biological inquiries out of the deadlock of oft-encountered mechanistic pitfalls and reposition biology to its former capacity of illuminating fundamental truths about the world.
Reza Pourimani, Sedigheh Kashian, Ali Asghar Fathivand
In this work, the specific mass of twelve elements were determined in five of the most commonly used medicinal plants as Caraway (Carum carvi), Savory (Satureia hortensis), Purslane (Portulaca oleracea), Fenugreek (Trigonella foenum-graecum) and Milk thistle (Silibum marianum) prepared from herbal pharmacies. Multi elemental Instrumental Neutron Activation Analysis (INAA) method was applied to analyze the samples. Tehran research reactor was used as a neutron source and gamma ray spectra registered using high purity germanium (HPGe) detector. Among analyzed samples, highest concentrations of Fe (8789 ppm), Cr (8 ppm) and Na (517 ppm) were found in Caraway. Maximum levels of Mn (95 ppm), Cl (3702 ppm), Ca (18328 ppm) , K (21562 ppm) and V (2.7 ppm) were detected in Savory and Fenugreek contains the lowest concentrations of Fe (195 ppm), Zn (13 ppm), Ca (2243 ppm), Al (99ppm), Mn (26 pm) and Mg (177ppm).