Recent progress in pneumococcal protein vaccines

Pneumococcal infections continue to pose a significant global health concern, necessitating the development of effective vaccines. Despite the progress shown by pneumococcal polysaccharide and conjugate vaccines, their limited coverage and the emergence of non-vaccine serotypes have highlighted the need for alternative approaches. Protein-based pneumococcal vaccines, targeting conserved surface proteins of Streptococcus pneumoniae, have emerged as a promising strategy. In this review, we provide an overview of the advancements made in the development of pneumococcal protein vaccines. We discuss the key protein vaccine candidates, highlight their vaccination results in animal studies, and explore the challenges and future directions in protein-based pneumococcal vaccine

A Soluble C1b Protein and Its Regulation of Soluble Type 7 Adenylyl Cyclase†

Adenylyl cyclase (AC) is a prototypical cell-signaling molecule expressed in virtually all organisms from bacteria to man. While C1b, a poorly conserved region within mammalian AC, has been implicated in numerous isoform-specific regulatory properties, no one has purified the C1b region as a functional protein to homogeneity in order to study its role in enzyme function. We hypothesize that C1b is an internal regulatory subunit. To pursue this hypothesis, we constructed several soluble C1b proteins from type VII AC, arriving at one, 7C1b-S, which can be expressed and purified from Escherichia coli. 7C1b-S is relatively stable, as demonstrated by limited proteolytic analysis, circular dichroism, and UV Raman spectroscopy. Using size-exclusion chromatography and co-immunoprecipitation we demonstrate that 7C1b-S interacts with a cardinal activator of AC (Gsα) and with the conserved first catalytic domain (C1a) of type VII AC. We show that 7C1b-S inhibits Gsα-stimulated and Gsα-forskolin stimulated activity in our soluble ACVII model system. On the basis of these results, we suggest that 7C1b-S meets basic criteria to serve as a model protein for the C1b region and may be used as a prototype to develop other isoform C1b soluble model proteins to further investigate the role of this domain in isoform-specific regulation of adenylyl cyclase

A Dynamic-Order Fractional Dynamic System

Multi-system interaction is an important and difficult problem in physics. Motivated by the experimental result of an electronic circuit element "Fractor", we introduce the concept of dynamic-order fractional dynamic system, in which the differential-order of a fractional dynamic system is determined by the output signal of another dynamic system. The new concept offers a comprehensive explanation of physical mechanism of multi-system interaction. The properties and potential applications of dynamic-order fractional dynamic systems are further explored with the analysis of anomalous relaxation and diffusion processes.Comment: 10 pages, 5 figure

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants