Lifeboat Foundation

Nobel laureate details new applications at Kuh Distinguished Lecture.

Jennifer Doudna, Nobel laureate and Li Ka Shing Chancellor’s Chair and Professor in the Departments of Chemistry and of Molecular and Cell Biology, presented this year’s Ernest S. Kuh Distinguished Lecture, “Delivering the Future of CRISPR-Based Genome Editing,” on February 2 at UC Berkeley. The sold-out event — produced by Berkeley Engineering in collaboration with the Society of Women Engineers — marks the 11th talk in the lecture series, which features scientists and engineers tackling the world’s most pressing problems.

Doudna is known for developing CRISPR-Cas9, a groundbreaking technology that some call “genetic scissors.” With it, scientists can snip and edit DNA — the genetic code of life — unlocking remarkable possibilities in biology, including treatments for thousands of intractable diseases. This work has changed the course of genomics research, allowing scientists to rewrite DNA with unprecedented precision, and won Doudna and collaborator Emmanuelle Charpentier the 2020 Nobel Prize in Chemistry.

A new stool test appears to detect colorectal cancer precursors better than the current fecal immunochemical test. This could further reduce the number of new colorectal cancer cases as well as the number of people dying from the disease. A study led by the Netherlands Cancer Institute compared both tests.

Their results are published in The Lancet Oncology.

Each year worldwide, approximately 1.9 million people are diagnosed with colorectal cancer, and 935,000 people lose their lives as a result of the condition. If detected early, colorectal cancer is curable. However, by the time symptoms such as weight loss or blood in the stool appear, it is often too late. That is why many countries have introduced population-based screening programs. In The Netherlands, for example, people between the ages of 55 and 75 are invited to be tested every two years.

A new study claims that low-frequency ultrasound can reverse aspects of replicative and chemically induced senescence in vitro [1].

The age-related increase in senescent cell burden is thought to contribute to many processes of aging. Most of the attempts to deal with it involve senolytics: drugs that eliminate senescent cells.

However, it may be possible to re-educate them instead. Senomorphics are compounds that change senescent cells in a way that renders them benign, but they are much less common. The authors of this new pre-print study (it has not yet been peer-reviewed) claim to have found an even more impressive way to solve the senescent cell problem: by rejuvenating them with ultrasound.

The ability to distinguish between left-and right-handed molecules using mass spectrometry could streamline a laborious part of drug discovery.

Immunotherapy has rapidly advanced the field of medicine and has saved countless lives. The approach is much different than using an external chemical, such as in the case of chemotherapy. Immunotherapy leverages the body’s own immune system to recognize and attack foreign pathogens, specifically cancer. While there are many versions of immunotherapy, one rising star among them is known as Chimeric Antigen Receptor (CAR) T cell therapy. This therapy (usually) takes a patient’s own cells in the blood to generate engineered immune or T cells to fight the tumor. T cells are a critical immune cell population responsible for killing or lysing infected cells. In the case of CAR T cell therapy, the T cells from the patient are engineered to recognize receptors on the tumor. The CAR T-cells are then triggered to release different proteins and lyse the tumor cells. This type of therapy has revolutionized the way we treat patients with hematopoietic malignancies or blood cancers.

Jenniskens’ collaborators at the Museum für Naturkunde officially announced that the first examinations of one of these pieces with an electron beam microprobe prove the typical mineralogy and chemical composition of an achondrite of the aubrite type.

The official classification now aligns with what many suspected from merely looking at the images of the strange meteorites that fell near Berlin on January 21, 2024. They belong to a rare group called “aubrites.”

“They were devilishly difficult to find because, from a distance, they look like other rocks on Earth,” said SETI Institute meteor astronomer Dr. Peter Jenniskens. “Close up, not so much.”

A collaborative research team has fabricated a soccer ball-shaped construction using edge-to-edge assembly of 2D semiconductor materials. The research has been featured on the cover of the online edition of the Angewandte Chemie International Edition journal.

The research team, led by Professor In Su Lee and Ph.D. candidate Sun Woo Jang from the Department of Chemistry at Pohang University of Science and Technology (POSTECH), along with Professor Kwangjin An from the Department of Energy and Chemical Engineering at Ulsan National Institute of Science and Technology (UNIST), successfully controlled the interaction between the edges of 2D-silica nanosheets (2D-SiNS) to create a soccer ball-like structure.

The planar structure of 2D nanosheets exhibit unique mechanical and optical properties, making them versatile in semiconductor devices, catalysts, sensors, and many other sectors. The strong attraction of intermolecular forces (van der Waals) between sheets typically results in a structure where faces are in direct contact, compromising mechanical stability for catalytic functionality.

In the XXI century, the world of orbital launchers has started a revolution, a fundamental change of paradigm: the replacement of expendable rockets with reusable ones is well underway. This presentation summarizes the situation at the beginning of year 2024.

A short bio.
Alberto Cavallo is an Electrical Engineer, graduated at the Politecnico di Torino in 1985. He began his activity with designing electric systems in Fiat Engineering, the engineering and construction company of the FIAT Group, moving soon to control and automation systems in the same company. He was involved in all business areas of the company, which included revamping and new projects of car factories for the FIAT Group as well as large infrastructures, power and cogeneration plants for external clients. Among the projects of that time were the new FIAT factories in Melfi and Pratola Serra, the high speed railways Torino-Milano and Bologna-Firenze, the district heating system of Torino Sud, combined cycle power plants for several hundred megawatts in Italy and in Brazil. Since Fiat Engineering was transferred from the FIAT Group to a new EPC group and then merged with a large EPC company in Milan, he has been involved in large oil and gas and petrochemical projects all over the world. Besides his professional activity, he has always taken part in several cultural activities. He was a member of the Associations of Alumni of the Liceo Classico Vittorio Alfieri of Turin, active in promoting humanistic culture as well as its connection to the technical and scientific area. He manages his own website www.eurinome.it (in Italian only) about philosophy, science and politics/geopolitics. Due to this he got in contact with Adriano Autino and his TDF, then becoming one of the founding members of Space Renaissance International. Besides several papers in his professional area he has written several articles for his own site, for TDF and SRI, coauthoring the book “Three Theses for the Space Renaissance” with Adriano Autino and Patrick Q. Collins. He is currently member of the Board of SRI.

We are in the middle of a data-driven science boom. Huge, complex data sets, often with large numbers of individually measured and annotated ‘features’, are fodder for voracious artificial intelligence (AI) and machine-learning systems, with details of new applications being published almost daily.

But publication in itself is not synonymous with factuality. Just because a paper, method or data set is published does not mean that it is correct and free from mistakes. Without checking for accuracy and validity before using these resources, scientists will surely encounter errors. In fact, they already have.

In the past few months, members of our bioinformatics and systems-biology laboratory have reviewed state-of-the-art machine-learning methods for predicting the metabolic pathways that metabolites belong to, on the basis of the molecules’ chemical structures¹. We wanted to find, implement and potentially improve the best methods for identifying how metabolic pathways are perturbed under different conditions: for instance, in diseased versus normal tissues.