Pilus of Streptococcus pneumoniae: structure, function and vaccine potential

The pilus is an extracellular structural part that can be detected in some Streptococcus pneumoniae (S. pneumoniae) isolates (type I pili are found in approximately 30% of strains, while type II pili are found in approximately 20%). It is anchored to the cell wall by LPXTG-like motifs on the peptidoglycan. Two kinds of pili have been discovered, namely, pilus-1 and pilus-2. The former is encoded by pilus islet 1 (PI-1) and is a polymer formed by the protein subunits RrgA, RrgB and RrgC. The latter is encoded by pilus islet 2 (PI-2) and is a polymer composed mainly of the structural protein PitB. Although pili are not necessary for the survival of S. pneumoniae, they serve as the structural basis and as virulence factors that mediate the adhesion of bacteria to host cells and play a direct role in promoting the adhesion, colonization and pathogenesis of S. pneumoniae. In addition, as candidate antigens for protein vaccines, pili have promising potential for use in vaccines with combined immunization strategies. Given the current understanding of the pili of S. pneumoniae regarding the genes, proteins, structure, biological function and epidemiological relationship with serotypes, combined with the immunoprotective efficacy of pilins as protein candidates for vaccines, we here systematically describe the research status and prospects of S. pneumoniae pili and provide new ideas for subsequent vaccine research and development

Genetic polymorphisms of VIP variants in the Tajik ethnic group of northwest China

BACKGROUND: Individual response to medications varies significantly among different populations, and great progress in understanding the molecular basis of drug action has been made in the past 50 years. The field of pharmacogenomics seeks to elucidate inherited differences in drug disposition and effects. While we know that different populations and ethnic groups are genetically heterogeneous, we have not found any pharmacogenomics information regarding minority groups, such as the Tajik ethnic group in northwest China. RESULTS: We genotyped 85 Very Important Pharmacogene (VIP) variants selected from PharmGKB in 100 unrelated, healthy Tajiks from the Xinjiang Uygur Autonomous Region and compared our data with HapMap data from four major populations around the world: Han Chinese (CHB), Japanese in Tokyo (JPT), Utah Residents with Northern and Western European Ancestry (CEU), and Yorubia in Ibadan, Nigeria (YRI). We found that Tajiks differed from CHB, JPT and YRI in 30, 32, and 32 of the selected VIP genotypes respectively (p < 0.005), while differences between Tajiks and CEU were found in only 6 of the genotypes (p < 0.005). Haplotype analysis also demonstrated differences between the Tajiks and the other four populations. CONCLUSION: Our results contribute to the pharmacogenomics database of the Tajik ethnic group and provide a theoretical basis for safer drug administration that may be useful for diagnosing and treating disease in this population. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-014-0102-y) contains supplementary material, which is available to authorized users

Metasurface-based Spectral Convolutional Neural Network for Matter Meta-imaging

Convolutional neural networks (CNNs) are representative models of artificial neural networks (ANNs), that form the backbone of modern computer vision. However, the considerable power consumption and limited computing speed of electrical computing platforms restrict further development of CNNs. Optical neural networks are considered the next-generation physical implementations of ANNs to break the bottleneck. This study proposes a spectral convolutional neural network (SCNN) with the function of matter meta-imaging, namely identifying the composition of matter and mapping its distribution in space. This SCNN includes an optical convolutional layer (OCL) and a reconfigurable electrical backend. The OCL is implemented by integrating very large-scale, pixel-aligned metasurfaces on a CMOS image sensor, which accepts 3D raw datacubes of natural images, containing two-spatial and one-spectral dimensions, at megapixels directly as input to realize the matter meta-imaging. This unique optoelectronic framework empowers in-sensor optical analog computing at extremely high energy efficiency eliminating the need for coherent light sources and greatly reducing the computing load of the electrical backend. We employed the SCNN framework on several real-world complex tasks. It achieved accuracies of 96.4% and 100% for pathological diagnosis and real-time face anti-spoofing at video rate, respectively. The SCNN framework, with an unprecedented new function of substance identification, provides a feasible optoelectronic and integrated optical CNN implementation for edge devices or cellphones with limited computing capabilities, facilitating diverse applications, such as intelligent robotics, industrial automation, medical diagnosis, and astronomy

Review of molten carbonate-based direct carbon fuel cells

Abstract Direct carbon fuel cell (DCFC) is a promising technology with high energy efficiency and abundant fuel. To date, a variety of DCFC configurations have been investigated, with molten hydroxide, molten carbonate or oxides being used as the electrolyte. Recently, there has been particular interest in DCFC with molten carbonate involved. The molten carbonate is either an electrolyte or a catalyst in different cell structures. In this review, we consider carbonate as the clue to discuss the function of carbonate in DCFCs, and start the paper by outlining the developments in terms of molten carbonate (MC)-based DCFC and its electrochemical oxidation processes. Thereafter, the composite electrolyte merging solid carbonate and mixed ionic–electronic conductors (MIEC) are discussed. Hybrid DCFC (HDCFCs ) combining molten carbonate and solid oxide fuel cell (SOFC) are also touched on. The primary function of carbonate (i.e., facilitating ion transfer and expanding the triple-phase boundaries) in these systems, is then discussed in detail. Finally, some issues are identified and a future outlook outlined, including a corrosion attack of cell components, reactions using inorganic salt from fuel ash, and wetting with carbon fuels

Clinical characteristics and prognostic factors for short-term outcomes of autoimmune glial fibrillary acidic protein astrocytopathy: a retrospective analysis of 33 patients

BackgroundAutoimmune glial fibrillary acidic protein astrocytopathy (GFAP-A) is a recently discovered inflammatory central nervous system (CNS) disease, whose clinical characteristics and prognostic factors for short-term outcomes have not been defined yet. We aimed to assess the symptoms, laboratory tests, imaging findings, treatment, and short-term prognosis of GFAP-A.MethodsA double-center retrospective cohort study was performed between May 2018 and July 2022. The clinical characteristics and prognostic factors for short-term outcomes were determined.ResultsWe enrolled 33 patients with a median age of 28 years (range: 2–68 years), 15 of whom were children (&lt;18 years). The clinical spectrum is dominated by meningoencephalomyelitis. Besides, we also found nausea, vomiting, poor appetite, and neuropathic pain in some GFAP-A patients, which were not mentioned in previous reports. And adults were more prone to limb numbness than children. Magnetic resonance imaging revealed lesions involving the brain parenchyma, meninges, and spinal cord, exhibiting patchy, linear, punctate, and strip T2 hyperintensities. First-line immunotherapy, including corticosteroid and gamma globulin, was effective in most patients in the acute phase (P = 0.02). However, patients with overlapping AQP4 antibodies did not respond well to first-line immunotherapy and coexisting neural autoantibodies were more common in women. Additionally, the short-term prognosis was significantly better in children than in adults (P = 0.04). Positive non-neural autoantibodies and proven viral infection were independent factors associated with poor outcomes (P = 0.03, 0.02, respectively).ConclusionWe expanded the spectrum of clinical symptoms of autoimmune GFAP-A. The clinical symptoms and short-term prognosis differed between children and adults. Positive non-neural autoantibodies and proven viral infection at admission suggest a poor short-term prognosis