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While psychologists have extensively discussed the notion of a "theory crisis" arising from vague and incorrect hypotheses, there has been no debate about such a crisis in biology. However, biologists have long discussed communication failures between theoreticians and empiricists. We argue such failure is one aspect of a theory crisis because misapplied and misunderstood theories lead to poor hypotheses and research waste. We review its solutions and compare them with methodology-focused solutions proposed for replication crises. We conclude by discussing how promoting inclusion, diversity, equity, and accessibility (IDEA) in theoretical biology could contribute to ameliorating breakdowns in the theory-empirical cycle. [ABSTRACT FROM AUTHOR]

Background: Respiratory tract infections (RTIs) are one of the leading causes of morbidity and mortality worldwide. The increase in antimicrobial resistance in respiratory pathogens poses a major challenge to the effective management of these infections. Objective: To investigate the distribution of major pathogens of RTIs and their antimicrobial resistance patterns in a tertiary care hospital and to develop a mathematical model to explore the relationship between pathogen distribution and antimicrobial resistance. Methods: Five hundred patients with RTIs were included in the study and 475 bacterial strains were isolated from their respiratory specimens. Antimicrobial susceptibility testing and analysis of influencing factors were performed. A mathematical model was developed to simulate the relationship between pathogen distribution and drug resistance. Results: The most common pathogens were Streptococcus pneumoniae (30%), Haemophilus influenzae (20%), Pseudomonas aeruginosa (15%), Staphylococcus aureus (10%) and Klebsiella pneumoniae (10%). The distribution of pathogens varied according to age group and type of RTIs, with higher proportions of Pseudomonas aeruginosa and Staphylococcus aureus in hospital-acquired and ventilator-associated pneumonia. Isolated pathogens showed high and increasing rates of resistance to commonly used antibiotics. Model simulations suggest that a shift in the distribution of pathogens toward more resistant strains may lead to a significant increase in overall resistance rates, even if antibiotic use patterns remain unchanged. Conclusion: This study emphasizes the importance of regular monitoring of respiratory pathogen distribution and antimicrobial resistance patterns and the need for a comprehensive approach to managing RTIs, including implementation of antibiotic stewardship programs, infection control measures, and development of new therapies. [ABSTRACT FROM AUTHOR]

The high-level risk perception diffusion caused by public health emergencies seriously threatens public mental health and social stability. Much scholarly attention focused on the traditional epidemic models or simply combined content and social attributes, overlooking the differences in public individual characteristics. This paper proposes an S 1 S 2 EI pos I neu I neg R model of risk perception diffusion by innovatively subdividing susceptible people and infectious people. Then, taking the Xi'an epidemic as an example (N = 105,417), this paper employs the sentiment analysis model of Word2Vec and Bi-LSTM to calculate the emotional value of microblog text to quantify public risk perception. Finally, numerical experiments are conducted to explore the effects of cross-evolution and emotional difference on risk perception diffusion under different scenarios. Findings reveal that a larger initial density of infectious people accelerates diffusion, with negative emotions playing a dominant role. In addition, the higher the risk perception level and the lower the heterogeneity, the greater the maximum impact and the final scale of diffusion. When the public health emergency deteriorates, the cross-evolution tends to shift to a high-risk perception. Otherwise, it tends to tilt to a low-risk perception. These findings provide critical insights for developing precise risk perception guidance strategies and enhancing public health governance capabilities., (© 2024 International Association of Applied Psychology.)