Secondary bacterial infections that follow infection with influenza virus result in considerable morbidity and mortality in young children, the elderly, and immunocompromised individuals and may also significantly increase mortality in normal healthy adults during influenza pandemics. We herein describe a mouse model for investigating the interaction between influenza virus and the bacterium Haemophilus influenzae. Sequential infection with sublethal doses of influenza and H. influenzae resulted in synergy between the two pathogens and caused mortality in immunocompetent adult wild-type mice. Lethality was dependent on the interval between administration of the bacteria and virus, and bacterial growth was prolonged in the lungs of dual-infected mice, although influenza virus titers were unaffected. Dual infection induced severe damage to the airway epithelium and confluent pneumonia, similar to that observed in victims of the 1918 global influenza pandemic. Increased bronchial epithelial cell death was observed as early as 1 day after bacterial inoculation in the dual-infected mice. Studies using knockout mice indicated that lethality occurs via a mechanism that is not dependent on Fas, CCR2, CXCR3, interleukin-6, tumor necrosis factor, or Toll-like receptor-4 and does not require T or B cells. This model suggests that infection with virulent strains of influenza may predispose even immunocompetent individuals to severe illness on secondary infection with H. influenzae by a mechanism that involves innate immunity, but does not require tumor necrosis factor, interleukin-6, or signaling via Toll-like receptor-4.

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Stepwise elevation of MACC1 expression in key points of colorectal cancer development suggests that MACC1 may contribute to cancer initiation and early invasive growth. High expression of both MACC1 and MET may relate to distant metastasis.

The anatomic pathology discipline is slowly moving toward a digital workflow, where pathologists will evaluate whole-slide images on a computer monitor rather than glass slides through a microscope. One of the driving factors in this workflow is computer-assisted scoring, which depends on appropriate selection of regions of interest. With advances in tissue pattern recognition techniques, a more precise region of the tissue can be evaluated, no longer bound by the pathologist's patience in manually outlining target tissue areas. Pathologists use entire tissues from which to determine a score in a region of interest when making manual immunohistochemistry assessments. Tissue pattern recognition theoretically offers this same advantage; however, error rates exist in any tissue pattern recognition program, and these error rates contribute to errors in the overall score. To provide a real-world example of tissue pattern recognition, 11 HER2-stained upper gastrointestinal malignancies with high heterogeneity were evaluated. HER2 scoring of gastric cancer was chosen due to its increasing importance in gastrointestinal disease. A method is introduced for quantifying the error rates of tissue pattern recognition. The trade-off between fully sampling tumor with a given tissue pattern recognition error rate versus randomly sampling a limited number of fields of view with higher target accuracy was modeled with a Monte-Carlo simulation. Under most scenarios, stereological methods of sampling-limited fields of view outperformed whole-slide tissue pattern recognition approaches for accurate immunohistochemistry analysis. The importance of educating pathologists in the use of statistical sampling is discussed, along with the emerging role of hybrid whole-tissue imaging and stereological approaches.

A 52-year-old female was admitted for hysterectomy secondary to leiomyomata. A preoperative radiograph uncovered a well-circumscribed 3.5 3 3.0 3 3.0 cm lesion in the right lower lobe. CT-guided fine-needle aspiration (FNA) was ordered to discover the nature of the pulmonary lesion. The air-dried smears were sparsely cellular and showed a monotonous population of epitheliod cells interspersed with a fibrillar