Tyler O'Neal, Staff Editor SYSTEMS

University of Technology Sydney models what happens when we inhale coronavirus aerosols

When we inhale isolated coronavirus particles, more than 65% reach the deepest region of our lungs where damage to cells can lead to low blood oxygen levels, new research has discovered, and more of these aerosols reach the right lung than the left.

The lead author of the study Dr. Saidul Islam, from the University of Technology Sydney, said while previous research has revealed how virus aerosols travel through the upper airways including the nose, mouth, and throat - this study was the first to examine how they flow through the lower lungs.

"Our lungs resemble tree branches that divide up to 23 times into smaller and smaller branches. Due to the complexity of this geometry, it is difficult to develop a computer simulation, however, we were able to model what happens in the first 17 generations, or branches, of the airways," said Dr. Islam.

"Depending on our breathing rate, between 32% and 35% of viral particles are deposited in these first 17 branches. This means around 65% of virus particles escape to the deepest regions of our lungs, which includes the alveoli or air sacs," he said. A new study models what happens when we inhale coronavirus aerosols. CREDIT Image: Mohamed Hassan / Pixabay cc

The alveolar system is critical to our ability to absorb oxygen, so significant amounts of virus in this region, along with inflammation caused by our body's immune response, can cause severe damage, reducing the amount of oxygen in the blood and increasing the risk of death.

The study also revealed that more virus particles are deposited in the right lung, especially the right upper lobe and the right lower lobe, than in the left lung. This is due to the highly asymmetrical anatomical structure of the lungs and the way air flows through the different lobes.

The research is backed up by a recent study of chest CT scans of COVID-19 patients showing greater infection and disease in the regions predicted by the model.

The researchers modeled three different flow rates - 7.5, 15, and 30 liters per minute. The model showed greater virus deposition at lower flow rates.

As well as improving our understanding of coronavirus transmission, the findings have implications for the development of targeted drug delivery devices that can deliver medicine to the areas of the respiratory system most affected by the virus.

"Normally when we inhale drugs from a drug delivery device most of it is deposited in the upper airways, and only a minimum amount of drugs can reach the targeted position of the lower airways. However, with diseases like COVID-19 we need to target the areas most affected," said Dr. Islam.

"We are working to develop devices that can target specific regions, and we also hope to build age and patient-specific whole lung models to increase understanding of how SARS CoV-2 aerosols affect individual patients," said co-author and group leader of the UTS Computer Simulations and Modelling group, Dr. Suvash Saha.

The World Health Organisation recently updated its advice about the importance of aerosol transmission, warning that because aerosols can remain suspended in the air, crowded indoor settings and areas with poor ventilation pose a significant risk for transmission of Covid-19.

"When we use an aerosol deodorant, the smallest particles of that liquid fall on us under extreme pressure in the form of gas. Similarly, when an infected person speaks, sings, sneezes, or coughs, the virus is spread through the air and can infect those nearby," said Dr. Saha.

The study has further applications, with researchers using portable devices to examine air quality - including PM2.5 and PM10 concentration and gasses such as carbon dioxide, formaldehyde, and sulfur dioxide - in spaces such as train carriages. The researchers can then use this data to model the impact on our lungs.

The study, SARS CoV-2 aerosol: How far it can travel to the lower airways, was recently published in the journal Physics of Fluids.

Rice wins NIH grant that boosts computational search for cancer drugs

Tyler O'Neal, Staff Editor SYSTEMS

Computer scientist Lydia Kavraki of Rice University's Brown School of Engineering has won a prestigious National Institutes of Health U01 grant to develop a new approach to model and analyze protein-ligand interactions in cancer research.

The end goal is to create a proteomics toolkit, PROTEAN-CR, focused on the structural analysis of protein-ligand interactions. Researchers will use PROTEAN-CR to understand key biological mechanisms of cancer as well as to suggest novel cancer therapies. Pilot projects will include peptide-based cancer vaccination and analysis of mutations in the context of T-cell-based immunotherapy.

The three-year, $1.2 million grant from the National Cancer Institute (NCI) will advance Kavraki's ongoing collaboration with co-investigator Gregory Lizee at the University of Texas MD Anderson Cancer Center. Lydia Kavraki is Rice University's Noah Harding Professor of Computer Science, a professor of bioengineering, mechanical engineering and electrical and computer engineering, and director of Rice's Ken Kennedy Institute.

In cancer, proteins can suffer modifications that favor the maintenance and proliferation of malignant cells. One way to fight cancer is using ligands with anti-tumor properties to inhibit these proteins. But the discovery of molecules with anticancer properties isn't easy. There are hundreds of thousands of different proteins and possible ligands to assess. Proteins and ligands can assume different three-dimensional conformations, and even the same protein can have multiple mutations; both these issues affect protein-ligand binding. Kavraki said PROTEAN-CR is needed because of these challenges and a persistent knowledge gap with structural analyses of protein-ligand interactions.

Kavraki, Rice's Noah Harding Professor of Computer Science, a professor of bioengineering, mechanical engineering and electrical and computer engineering, and director of the Ken Kennedy Institute said the long-term goal of the U01 grant is to enable a broad structural analysis of protein-ligand interactions so cancer researchers can mix, match and test small anti-tumor molecules for personalized cancer therapies.

PROTEAN-CR will also allow researchers to manipulate the 3D structures of known molecules and their possible forms, making it easier for researchers to screen possible protein-ligand complexes and predict how they will bind to and destroy tumor cells. To assess the best binding modes, machine learning methods will be used to create new scoring functions. PROTEAN-CR also will be linked to publicly available biological databases to retrieve updated information on protein mutations and modifications.

Kavraki said her unified data science-inspired approach will accelerate cancer research by complementing wet-lab and clinical studies. Additional collaborators include Dinler Antunes at the University of Houston and Jin Wang at Baylor College of Medicine.

"There is a real gap in incorporating large-scale structural analysis to understand the role of proteins and protein-ligand interactions in complex diseases such as cancer," Kavraki said. "Our work will fill this gap and complement the tools that are currently in development through NCI's informatics program."

Kavraki's lab has already developed some PROTEAN-CR core functions through a prototype web server being tested by MD Anderson researchers for drug discovery and immunotherapy applications. Since March 2017, it has had more than 9,752 unique users from 109 countries.

Marvell launches 1.6T Ethernet PHY with 100G PAM4 I/Os in 5nm for cloud data centers

Tyler O'Neal, Staff Editor SYSTEMS

Marvell has introduced the industry's first 1.6T Ethernet PHY with 100G PAM4 electrical input/outputs (I/Os) in 5nm. The demand for increased bandwidth in the data center to support massive data growth is driving the transition to 1.6T (Terabits per second) in the Ethernet backbone. 100G serial I/Os play a critical role in the cloud infrastructure to help move data across compute, networking, and storage in a power-efficient manner. The new Marvell Alaska C PHY is designed to accelerate the transition to 100G serial interconnects and doubles the bandwidth speeds of the previous generation of PHYs to bring scalability for performance-critical cloud workloads and applications such as artificial intelligence and machine learning.

Marvell's 1.6T Ethernet PHY solution, the 88X93160, enables next-generation 100G serial-based 400G and 800G Ethernet links for high-density switches. The doubling of the signaling rate creates signal integrity challenges, driving the need for retimer devices for high port count switch designs. It's critical that retimer and gearboxes used for these applications are extremely power efficient. Implemented in the latest 5nm node, the Marvell 800GbE PHY provides a 40% savings in I/O power compared to the existing 50G PAM4 based I/Os.  Webp

"100G serial electrical signaling is vitally important because it serves as the foundational speed for the next generation of high-speed networks," said Alan Weckel, founder and technology analyst of 650 Group. "Challenges in signal integrity typically arise as I/O speeds increase. As the industry transitions to 100G serial electrical signaling on high-density switches and optics, Marvell's 1.6T PHY is the only solution that's available in the market today to support this transition."

Marvell's 88X93160 is the industry's first PHY device fully compliant with IEEE's 802.3ck standards for 100G serial I/Os and the Ethernet Technology Consortium's 800GbE specifications. The device supports Gearboxing functionality which helps data center operators get the full bandwidth capabilities of the switch ASICs with 100G serial I/Os while interfacing with existing 50G PAM4 based 400G optical modules.

"Data center demand for 400GbE and beyond is experiencing exponential growth," said Achyut Shah, senior vice president, and general manager of Marvell's PHY business unit. "We are very proud to offer the industry's first dual 1.6T PHY with 100G PAM4 I/Os designed for cloud data centers. Our 112G SerDes in 5nm boasts industry-leading power and greatly enhances the value that high-speed Ethernet brings to cloud data center applications."

With the introduction of the new PHY, Marvell is further extending its leadership in the high-speed Retimer and Gearbox segment with a broad portfolio spanning speeds from 10GbE to 800GbE and support for MACsec encryption and Class C compliant IEEE1588 PTP timestamping. With support for Ethernet speeds up to 800GbE, the new 88X93160 enables customers to build systems that comply with the latest IEEE and Ethernet Technology Consortium standards.

The Marvell 1.6T PHY incorporates the company's 112G 5nm SerDes solution that was announced in November of last year, offering breakthrough performance with the ability to operate at 112G PAM4 across channels with >40dB insertion loss. This 112G 5nm SerDes technology will be designed in Marvell's industry-proven Prestera switch portfolio across data center, enterprise, and carrier segments. It has also been adopted for use by multiple customers of Marvell's 5nm ASIC offering in high-performance infrastructure applications across a variety of markets.