A Small Virus to Deliver Small Antibodies: New Targeted Therapies Based on AAV Delivery of Nanobodies

Nanobodies are camelid-derived single-domain antibodies that present some advantages versus conventional antibodies, such as a smaller size, and higher tissue penetrability, stability, and hydrophilicity. Although nanobodies can be delivered as proteins, in vivo expression from adeno-associated viral (AAV) vectors represents an attractive strategy. This is due to the fact that AAV vectors, that can provide long-term expression of recombinant genes, have shown an excellent safety profile, and can accommodate genes for one or several nanobodies. In fact, several studies showed that AAV vectors can provide sustained nanobody expression both locally or systemically in preclinical models of human diseases. Some of the pathologies addressed with this technology include cancer, neurological, cardiovascular, infectious, and genetic diseases. Depending on the indication, AAV-delivered nanobodies can be expressed extracellularly or inside cells. Intracellular nanobodies or “intrabodies” carry out their function by interacting with cell proteins involved in disease and have also been designed to help elucidate cellular mechanisms by interfering with normal cell processes. Finally, nanobodies can also be used to retarget AAV vectors, when tethered to viral capsid proteins. This review covers applications in which AAV vectors have been used to deliver nanobodies, with a focus on their therapeutic use.

Deep_Saliency: A Deep Learning based Saliency Approach to detect Covid-19 through x-ray images

Covid-19 a small virus has created a havoc in the world. The pandemic has already taken over 4 lakh lives. The tests to detect a Covid-19 positive takes time and is costly. Moreover, the ability of the virus to mutate surprises the doctors every day. Present paper proposes a saliency-based model called Deep_Saliency. The model works on chest x-rays of healthy, unhealthy, and covid-19 patients. An x-ray repository of Covid-19, available in public domain, is taken for the study. Deep_Saliency uses visual, disparity, and motion saliency to create a feature dataset of the x-rays. The collected features are tested and trained using Long Short-Term Memory (LSTM) network. A predictive analysis is performed using the x-ray of a new patient to confirm a Covid-19 positive case. The first objective of the paper is to detect Covid-19 positive cases from x-rays. The other objective is to provide a benchmark dataset of biomarkers. The proposed work achieved an accuracy of 96.66%.

Asynchrony between virus diversity and antibody selection limits influenza virus evolution

Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. Using a mathematical model, we show that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection could limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously-infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results provide a theoretical explanation for how virus antigenic evolution can be highly selective at the global level but nearly neutral within-host. They also suggest new avenues for improving influenza control.

Deep_Saliency: A Deep Learning based Saliency Approach to detect Covid-19 through x-ray images

Covid-19 a small virus has created a havoc in the world. The pandemic has already taken over 4 lakh lives. The tests to detect a Covid-19 positive takes time and is costly. Moreover, the ability of the virus to mutate surprises the doctors every day. Present paper proposes a saliency-based model called Deep_Saliency. The model works on chest x-rays of healthy, unhealthy, and covid-19 patients. An x-ray repository of Covid-19, available in public domain, is taken for the study. Deep_Saliency uses visual, disparity, and motion saliency to create a feature dataset of the x-rays. The collected features are tested and trained using Long Short-Term Memory (LSTM) network. A predictive analysis is performed using the x-ray of a new patient to confirm a Covid-19 positive case. The first objective of the paper is to detect Covid-19 positive cases from x-rays. The other objective is to provide a benchmark dataset of biomarkers. The proposed work achieved an accuracy of 96.66%.

Protection Level and Reusability of a Modified Full-Face Snorkel Mask as Alternative Personal Protective Equipment for Healthcare Workers During the COVID-19 Pandemic

The worldwide outbreak of the COVID-19 drastically increased pressure on medical resources and highlighted the need for rapidly available, large-scale and low-cost personal protective equipment (PPE). In this work, an alternative full-face mask is adapted from a modified snorkel mask to be used as PPE with two medical grade filters and a 3D-printed adapter. As the mask covers the eyes, mouth and nose, it acts as a full-face shield, providing additional protection to healthcare workers. The filtration efficiency of different medical filters is measured for particles below 300 nm to cover the size of the SARS-CoV-2 and small virus-laden droplets. The filtration performance of the adapted full-face mask is characterized using NaCl particles below 500 nm and different fitting scenarios. The mask is compared to a commercial respirator and characterized according to the EN 149 standard, demonstrating that the protection fulfills the requirements for the FFP2 level (filtering face-piece 2, stopping at least 94% of airborne particles). The device shows a good resistance to several cycles of decontamination (autoclaving and ethanol immersion), is easy to be produced locally at low cost and helps addressing the shortage in FFP2 masks and face shields by providing adequate protection to healthcare workers against particles below 500 nm.

How a small virus changed our world and the special role of anosmia

In January 2020 we encountered the first news on a novel coronavirus (SARS-CoV-2) infecting the population of the Chinese city Wuhan and resulting for some patients in a potentially deadly pneumonia. Currently, coronavirus disease 2019 (COVID-19) is spreading rapidly around the globe. For many years we have been warned that we would face a new pandemic, most likely with a zoonotic virus. For COVID-19 it was shown that transmission can occur via droplets and aerosols that can remain in the air for some hours and also via contaminated surfaces. Extra risks have been suggested to exists for aerosol producing surgery in sinus- and skull-base surgery. Ongoing transmission is especially difficult to prevent when the pathogen can be transmitted during the incubation period before the patient experiences symptoms. In March, Claire Hopkins and colleagues warned the rhinologic community and later health authorities about the significant increase in anosmia (and dysgeusia) related to (often further) asymptomatic COVID-19 and pointed to the possibility of recognizing COVID-19 patients by unexplained anosmia without other symptoms.

Asynchrony between virus diversity and antibody selection limits influenza virus evolution

Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. Using a mathematical model, we show that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection could limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results provide a theoretical explanation for how virus antigenic evolution can be highly selective at the global level but nearly neutral within host. They also suggest new avenues for improving influenza control.

Asynchrony between virus diversity and antibody selection limits influenza virus evolution

Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. We find that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection can limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results explain how virus antigenic evolution can be highly selective at the global level but nearly neutral within hosts. They also suggest new avenues for improving influenza control.

Music in times of Corona - We Shall Overcome

Humankind has faced a myriad of life-threatening challenges in our history, reaching from the so-called Black Death (Yersinia Pestis) killing 40% of Europe´s population during the Middle Ages to Chernobyl and Harrisburg. This time a small virus, a simple chemical particle exploits our global way of life and has served as fertile ground for spreading around the world. Counter measures from medical sciences are rare, and specific drugs or vaccinations at the time of this writing thus far, do not exist. Death tolls are rising, and we are forced to lock down or shut down our social life and stay at home to slow down the travel speed of Corona, thus gaining time to develop therapeutic approaches.