Lifeboat Foundation: Safeguarding Humanity
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Category: biotech/medical – Page 1,044

Lasers find applications across several fields ranging from telecommunications and remote sensing to medicine. There are many ways in which one can generate laser emission, or lasing, from a device or material. Consequently, there are many types of lasers with different principles of operation.

One emerging and promising method to achieve lasing with high energy efficiency is by leveraging what are known as “ in the continuum” (BICs). In simple terms, these states describe waves that remain highly localized in space but coexist with a continuous spectrum of waves that are not localized (traveling waves). When dealing with light, an , BICs can be realized by carefully designing the geometry of a confining periodic structure.

Although scientists have already reported a few types of BIC-based lasers, most of them can only emit a beam in a perfectly or almost perfectly vertical direction away from the surface of the device. This limitation hinders the use of such BIC lasers in applications where angling the emitted beam is necessary.

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In a recent study posted to the bioRxiv server, researchers in Germany investigated the effectiveness of the antibiotic nitroxoline against the currently circulating mpox viruses, previously called monkeypox virus (MPXV). This antibiotic has been used in Europe for about fifty years and has been proven effective in fighting biofilm infections.

Study: Repurposing of the antibiotic nitroxoline for the treatment of mpox. Image Credit: Dotted Yeti / Shutterstock.

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Benjamin Franklin stated, “If you would not be forgotten as soon as you are dead and rotten, either write things worth reading, or do things worth the writing.”

MIT’s well-known late Director of Artificial Intelligence Laboratory, Patrick Winston, expanded upon this adage, saying, “Your success in life will be determined largely by your ability to speak, your ability to write, and the quality of your ideas. In that order.”

We are at a precarious point in human development, with the positive and negative impact of technology surrounding us as individuals and as a society. Technology has helped improve our living standards, extended our lives, cured diseases, fed our growing populations, and expanded our frontiers. But it has also helped create greater economic and digital divides, increased pollution and harm to our environment, and potentially endangered the intellectual development of our human population.

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The United States is considering sampling wastewater taken from international aircraft to track any emerging new Covid-19 variants as infections surge in China, as UK-based health experts estimate about 9,000 people a days are now dying of the disease in China.

The proposed of testing wastewater by the US Centers for Disease Control and Prevention would provide a better solution to tracking the virus and slowing its entry into the US than new travel restrictions announced this week, three infectious disease experts said.

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BRUSSELS, Jan 3 (Reuters) — The European Union has offered free COVID-19 vaccines to China, the EU executive said on Tuesday, as infections there surged following Beijing’s relaxation of its “zero-COVID” policies.

China has not responded to the offer yet, a spokesperson for the European Commission told journalists at a regular briefing. He did not specify the amount of vaccines the EU was offering or their manufacturers.

“In view of the COVID situation in China, (Health) Commissioner Stella Kyriakides has reached out to her Chinese counterparts to offer EU solidarity and support,” he said.

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Year 2022 😗

Testing multiple treatments for heterogeneous (varying) effectiveness with respect to many underlying risk factors requires many pairwise tests; we would like to instead automatically discover and visualize patient archetypes and predictors of treatment effectiveness using multitask machine learning. In this paper, we present a method to estimate these heterogeneous treatment effects with an interpretable hierarchical framework that uses additive models to visualize expected treatment benefits as a function of patient factors (identifying personalized treatment benefits) and concurrent treatments (identifying combinatorial treatment benefits). This method achieves state-of-the-art predictive power for COVID-19 in-hospital mortality and interpretable identification of heterogeneous treatment benefits. We first validate this method on the large public MIMIC-IV dataset of ICU patients to test recovery of heterogeneous treatment effects. Next we apply this method to a proprietary dataset of over 3,000 patients hospitalized for COVID-19, and find evidence of heterogeneous treatment effectiveness predicted largely by indicators of inflammation and thrombosis risk: patients with few indicators of thrombosis risk benefit most from treatments against inflammation, while patients with few indicators of inflammation risk benefit most from treatments against thrombosis. This approach provides an automated methodology to discover heterogeneous and individualized effectiveness of treatments.

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Year 2022 😗

Automation is not just for high-throughput screening anymore. New devices and greater flexibility are transforming what’s possible throughout drug discovery and development. This article was written by Thomas Albanetti, AstraZeneca; Ryan Bernhardt, Biosero; Andrew Smith, AstraZeneca and Kevin Stewart, AstraZeneca for a 28-page DDW eBook, sponsored by Bio-Rad. Download the full eBook here.

A utomation has been a part of the drug discovery industry for decades. The earliest iterations of these systems were used in large pharmaceutical companies for high-throughput screening (HTS) experiments. HTS enabled the testing of libraries of small molecule compounds by a single or a series of multiple experimental conditions to i dentify the potential of those compounds as a treatment for a target disease. HTS has evolved to enable screening libraries of millions of compounds, but the high cost of equipment has largely resulted in automation occurring primarily in large pharmaceutical companies. Today, though, new types of robots paired with sophisticated software tools have helped to democratise access to automation, making it possible for pharma and biotechnology companies of almost any size to deploy these solutions in their labs.

Originally, automated solutions were only implemented for projects that involved a lot of repetitive tasks, which is typical of high-throughput experiments and assays. The equipment used in early automation efforts was expensive, specialised, and physically integrated together, effectively making the equipment unavailable for any non-automated use. Now, both the approaches and equipment are far more adaptive and flexible. The latest automation software is also much simpler to program, making it easier to swap in different instruments and robots as needed. For example, labs can run a particular HTS assay for a few weeks and then quickly pivot to run a new assay. Labs can also create and run bespoke standard operating procedures, assays, and experiments for drug targets they are interested in pursuing.

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While “protein” often evokes pictures of chicken breasts, these molecules are more similar to an intricate Lego puzzle. Building a protein starts with a string of amino acids—think a myriad of Christmas lights on a string— which then fold into 3D structures (like rumpling them up for storage).

DeepMind and Baker both made waves when they each developed algorithms to predict the structure of any protein based on their amino acid sequence. It was no simple endeavor; the predictions were mapped at the atomic level.

Designing new proteins raises the complexity to another level. This year Baker’s lab took a stab at it, with one effort using good old screening techniques and another relying on deep learning hallucinations. Both algorithms are extremely powerful for demystifying natural proteins and generating new ones, but they were hard to scale up.

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