Gibbs free energy as a measure of complexity correlates with time within C. elegans embryonic development

Analyzing Molecular Traits of H9N2 Avian Influenza Virus Isolated from a Same Poultry Farm in West Java Province, Indonesia, in 2017 and 2023

Background

Indonesia is one of the countries that is endemic to avian influenza virus subtype H9N2. This study aims to compare the molecular characteristics of avian influenza virus (AIV) subtype H9N2 from West Java.

Methods

Specific pathogen-free (SPF) embryonated chicken eggs were used to inoculate samples. RNA extraction and RT-qPCR confirmed the presence of H9 and N2 genes in the samples. RT-PCR was employed to amplify the H9N2-positive sample. Nucleotide sequences were obtained through Sanger sequencing and analyzed using MEGA 7. Homology comparison and phylogenetic tree analysis, utilizing the neighbor-joining tree method, assessed the recent isolate's similarity to reference isolates from GenBank. Molecular docking analysis was performed on the HA1 protein of the recent isolate and the A/Layer/Indonesia/WestJava-04/2017 isolate, comparing their interactions with the sialic acids Neu5Ac2-3Gal and Neu5Ac2-6Gal.

Results

RT-qPCR confirmed the isolate samples as AIV subtype H9N2. The recent virus exhibited 11 amino acid residue differences compared to the A/Layer/Indonesia/WestJava-04/2017 isolate. Phylogenetically, the recent virus remains within the h9.4.2.5 subclade. Notably, at antigenic site II, the recent isolate featured an amino acid N at position 183, unlike A/Layer/Indonesia/WestJava-04/2017. Molecular docking analysis revealed a preference of HA1 from the 2017 virus for Neu5Ac2-3Gal, while the 2023 virus displayed a tendency to predominantly bind with Neu5Ac2-6Gal.

Conclusion

In summary, the recent isolate displayed multiple mutations and a strong affinity for Neu5Ac2-6Gal, commonly found in mammals.

Demystifying neuroblastoma malignancy through fractal dimension, entropy, and lacunarity

PURPOSE

Neuroblastoma is a pediatric solid tumor with a prognosis associated with histology and age of the patient, which are the parameters of the well-established current classification (Shimada classification). Despite the development of new treatment options, the prognosis of high-risk neuroblastoma patients is still poor. Therefore, there is a continuous need to stratify the children suffering from this tumor. A mathematical and computational approach is proposed to enable automatic and precise cancer diagnosis on the histological slide.

METHODS

We targeted the complexity of neuroblastoma by calculating its image entropy (S), fractal dimension (FD), and lacunarity (λ) in a combined mathematical code. First, we tested the proposed method for patient-derived glioma images. It allowed distinguishing between normal brain tissue, grade II, and grade III glioma, which harbor different outcomes.

RESULTS

In neuroblastoma, our analysis of image's FD, S, and λ combined with a machine learning algorithm automatically predicted tumor malignancy with a receiver operating characteristic curve of 0.82. FD, S, and λ distinguish between neuroblastoma and ganglioneuroma, but they only partially differentiate between the normal samples and the other classes. Ganglioneuroma, the most differentiated form, and poorly-differentiated neuroblastoma display different values of FD, S, and λ.

CONCLUSIONS

FD, S, and λ of imaging recognize groups in neuroblastic tumors. We suggest that future studies including these features may challenge the current Shimada classification of neuroblastoma with categories of favorable and unfavorable histology. It is expected that this methodology could trigger multicenter studies and potentially find practical use in the clinical setting of children's hospitals worldwide.

Application of Thermodynamics and Protein–Protein Interaction Network Topology for Discovery of Potential New Treatments for Temporal Lobe Epilepsy

In this paper, we propose a bioinformatics-based method, which introduces thermodynamic measures and topological characteristics aimed to identify potential drug targets for pharmaco-resistant epileptic patients. We apply the Gibbs homology analysis to the protein–protein interaction network characteristic of temporal lobe epilepsy. With the identification of key proteins involved in the disease, particularly a number of ribosomal proteins, an assessment of their inhibitors is the next logical step. The results of our work offer a direction for future development of prospective therapeutic solutions for epilepsy patients, especially those who are not responding to the current standard of care.

Cooking up the perfect insect: Aristotle's transformational idea about the complete metamorphosis of insects

Aristotle made important contributions to the study of developmental biology, including the complete metamorphosis of insects. One concept in particular, that of the perfect or complete state, underlies Aristotle's ideas about metamorphosis, the necessity of fertilization for embryonic development, and whether morphogenesis involves an autonomous process of self-assembly. Importantly, the philosopher erroneously views metamorphosis as a necessary developmental response to lack of previous fertilization of the female parent, a view that is intimately connected with his readiness to accept the idea of the spontaneous generation of life. Aristotle's work underpins that of the major seventeenth century students of metamorphosis, Harvey, Redi, Malpighi and Swammerdam, all of whom make frequent reference to Aristotle in their writings. Although both Aristotle and Harvey are often credited with inspiring the later prolonged debate between proponents of epigenesis and preformation, neither actually held firm views on the subject. Aristotle's idea of the perfect stage also underlies his proposal that the eggs of holometabolous insects hatch 'before their time', an idea that is the direct precursor of the much later proposals by Lubbock and Berlese that the larval stages of holometabolous insects are due to the 'premature hatching' from the egg of an imperfect embryonic stage. This article is part of the theme issue 'The evolution of complete metamorphosis'.