Bacillus subtilis spores as adjuvants against avian influenza H9N2 induce antigen-specific antibody and T cell responses in White Leghorn chickens

Low-pathogenicity avian influenza H9N2 remains an endemic disease worldwide despite continuous vaccination, indicating the need for an improved vaccine strategy. Bacillus subtilis (B. subtilis), a gram-positive and endospore-forming bacterium, is a non-pathogenic species that has been used in probiotic formulations for both animals and humans. The objective of the present study was to elucidate the effect of B. subtilis spores as adjuvants in chickens administered inactivated avian influenza virus H9N2. Herein, the adjuvanticity of B. subtilis spores in chickens was demonstrated by enhancement of H9N2 virus-specific IgG responses. B. subtilis spores enhanced the proportion of B cells and the innate cell population in splenocytes from chickens administered both inactivated H9N2 and B. subtilis spores (Spore + H9N2). Furthermore, the H9N2 and spore administration induced significantly increased expression of the pro-inflammatory cytokines IL-1β and IL-6 compared to that in the H9N2 only group. Additionally, total splenocytes from chickens immunized with inactivated H9N2 in the presence or absence of B. subtilis spores were re-stimulated with inactivated H9N2. The subsequent results showed that the extent of antigen-specific CD4+ and CD8+ T cell proliferation was higher in the Spore + H9N2 group than in the group administered only H9N2. Taken together, these data demonstrate that B. subtilis spores, as adjuvants, enhance not only H9N2 virus-specific IgG but also CD4+ and CD8+ T cell responses, with an increase in pro-inflammatory cytokine production. This approach to vaccination with inactivated H9N2 together with a B. subtilis spore adjuvant in chickens produces a significant effect on antigen-specific antibody and T cell responses against avian influenza virus.This study and medical writing support were funded by Sanofi Genzyme and Regeneron Pharmaceuticals, Inc

Tiny Medicine: Nanomaterial-Based Biosensors

Tiny medicine refers to the development of small easy to use devices that can help in the early diagnosis and treatment of disease. Early diagnosis is the key to successfully treating many diseases. Nanomaterial-based biosensors utilize the unique properties of biological and physical nanomaterials to recognize a target molecule and effect transduction of an electronic signal. In general, the advantages of nanomaterial-based biosensors are fast response, small size, high sensitivity, and portability compared to existing large electrodes and sensors. Systems integration is the core technology that enables tiny medicine. Integration of nanomaterials, microfluidics, automatic samplers, and transduction devices on a single chip provides many advantages for point of care devices such as biosensors. Biosensors are also being used as new analytical tools to study medicine. Thus this paper reviews how nanomaterials can be used to build biosensors and how these biosensors can help now and in the future to detect disease and monitor therapies

METHOD AND APPARATUS TO PROVIDE BLOOD VESSEL ANALYSIS INFORMATION USING MEDICAL IMAGE

A blood vessel analysis information providing method includes emitting an ultrasonic signal on a body portion where a blood vessel exists and sensinga reflected ultrasonic signal, generating a color mode image by using the reflected ultrasonic signals, and determining diameters of the blood vessels based on pixel values of the generated color mode image.</p

METHOD FOR PRODUCING ELASTIC IMAGE AND ULTRASONIC DIAGNOSTIC APPARATUS

A method of generating an elastography image includes transmitting unfocused push signals comprising a plurality of ultrasound signals to an object in different directions; transmitting a detection ultrasound signal to the object in which a shear wave is generated by the unfocused push signals; receiving a response signal in response to the detection ultrasound signal from the object; and generating the elastography image of the object based on the response signal.</p