Equilibrium points and their stability of COVID-19 in US.

This study aims to develop an advanced mathematic model and investigate when and how will the COVID-19 in the US be evolved to endemic. We employed a nonlinear ordinary differential equations-based model to simulate COVID-19 transmission dynamics, factoring in vaccination efforts. Multi-stability analysis was performed on daily new infection data from January 12, 2021 to December 12, 2022 across 50 states in the US. Key indices such as eigenvalues and the basic reproduction number were utilized to evaluate stability and investigate how the pandemic COVD-19 will evolve to endemic in the US. The transmissional, recovery, vaccination rates, vaccination effectiveness, eigenvalues and reproduction numbers ([Formula: see text] and [Formula: see text]) in the endemic equilibrium point were estimated. The stability attractor regions for these parameters were identified and ranked. Our multi-stability analysis revealed that while the endemic equilibrium points in the 50 states remain unstable, there is a significant trend towards stable endemicity in the US. The study's stability analysis, coupled with observed epidemiological waves in the US, suggested that the COVID-19 pandemic may not conclude with the virus's eradication. Nevertheless, the virus is gradually becoming endemic. Effectively strategizing vaccine distribution is pivotal for this transition.

Rapid divergence in expression between duplicate genes inferred from microarray data.

For more than 30 years, expression divergence has been considered as a major reason for retaining duplicated genes in a genome, but how often and how fast duplicate genes diverge in expression has not been studied at the genomic level. Using yeast microarray data, we show that expression divergence between duplicate genes is significantly correlated with their synonymous divergence (K(S)) and also with their nonsynonymous divergence (K(A)) if K(A) 80% for K(S) > 1.5. Only a small fraction of ancient gene pairs do not show expression divergence.

Human Gas7 isoforms homologous to mouse transcripts differentially induce neurite outgrowth.

Gas7, a growth-arrest-specific protein, is expressed preferentially in the brain and is required for neurite outgrowth in cultured cerebellar and peripheral murine neurons. Gas7 interacts with F-actin and colocalizes with the terminal part of actin microfilament in cells in which membrane outgrowth is present. Gas7 isoforms were discovered in murine brain by alternative splicing. This work reports the identification of two human Gas7 cDNA: hGas7-a with 2,427 nucleotides, which encodes 330 amino acids, and hGas7-b with 2,610 nucleotides, which encodes 412 amino acids according to predicted open-reading-frames. The predicted hGas7-b protein is 97% homologous to murine homologues, whereas the hGas7-a is homologous to the mouse Gas7-cb form that is expressed preferentially in cerebellum. Alignment analysis of the Gas7 protein sequences revealed a high homology to that in humans: 99% for the monkey, 97% in murine, and around 75% for the puffer fish and chicken. The hGas7-b protein comprises a WW domain, which often associates with other domains that are typically present in proteins in signal transduction processes, and an FCH domain, which participates in rearranging the cytoskeleton. The hGas7-a comprises only the FCH domain. Analysis of the human Gas7 sequences using the DNA database revealed that the two forms resulted from the canonical alternative splicing of a Gas7 genomic sequence. The abundance of both hGas7 mRNA levels, determined by quantitative PCR in tissues including brain, breast cancer, placenta, and head-neck cancer, revealed that the level of hGas7-a was 14 times that of hGas7-b in these tissues. Transfection of cells with hGas7-a or hGas7-b cDNA yielded the predicted 38-kDa or 50-kDa protein, respectively. The ectopic expression of hGas7 caused neurite-like cell processes in both mouse Neuro-2a and human SH-SY5Y neuroblastoma cells. Interestingly, the hGas7-a preferentially elicited the small lamellipodia, whereas the hGas7-b elicited the small filopodia phenotype. These findings reveal the evolutionary conservation of the structure and function of Gas7. They also suggest that the FCH domain in Gas7 may participate in the development of lamellipodia, and the WW domain may participate in the fine-tuning of the filopodia.

Patterns of segmental duplication in the human genome.

We analyzed the completed human genome for recent segmental duplications (size > or = 1 kb and sequence similarity > or = 90%). We found that approximately 4% of the genome is covered by duplications and that the extent of segmental duplication varies from 1% to 14% among the 24 chromosomes. Intrachromosomal duplication is more frequent than interchromosomal duplication in 15 chromosomes. The duplication frequencies in pericentromeric and subtelomeric regions are greater than the genome average by approximately threefold and fourfold. We examined factors that may affect the frequency of duplication in a region. Within individual chromosomes, the duplication frequency shows little correlation with local gene density, repeat density, recombination rate, and GC content, except chromosomes 7 and Y. For the entire genome, the duplication frequency is correlated with each of the above factors. Based on known genes and Ensembl genes, the proportion of duplications containing complete genes is 3.4% and 10.7%, respectively. The proportion of duplications containing genes is higher in intrachromosomal than in interchromosomal duplications, and duplications containing genes have a higher sequence similarity and tend to be longer than duplications containing no genes. Our simulation suggests that many duplications containing genes have been selectively maintained in the genome.

Evolution of the yeast protein interaction network.

To study the evolution of the yeast protein interaction network, we first classified yeast proteins by their evolutionary histories into isotemporal categories, then analyzed the interaction tendencies within and between the categories, and finally reconstructed the main growth path. We found that two proteins tend to interact with each other if they are in the same or similar categories, but tended to avoid each other otherwise, and that network evolution mirrors the universal tree of life. These observations suggest synergistic selection during network evolution and provide insights into the hierarchical modularity of cellular networks.