Lifeboat Foundation

The SARS-CoV-2 pandemic has had an unprecedented impact on global public health and the economy. Although vaccines and antivirals have provided effective protection and treatment, the development of new small molecule-based antiviral candidates is imperative to improve clinical outcomes against SARS-CoV-2. In this study, we identified UNI418, a dual PIKfyve and PIP5K1C inhibitor, as a new chemical agent that inhibits SARS-CoV-2 entry into host cells. UNI418 inhibited the proteolytic activation of cathepsins, which is regulated by PIKfyve, resulting in the inhibition of cathepsin L-dependent proteolytic cleavage of the SARS-CoV-2 spike protein into its mature form, a critical step for viral endosomal escape. We also demonstrated that UNI418 prevented ACE2-mediated endocytosis of the virus via PIP5K1C inhibition. Our results identified PIKfyve and PIP5K1C as potential antiviral targets and UNI418 as a putative therapeutic compound against SARS-CoV-2.

Despite the ongoing threat posed by new viruses following the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which led to the coronavirus disease 2019 (COVID-19) pandemic, new antiviral drugs continue to be developed to effectively block viral entry into the human body.

Professor Kyungjae Myung and his research team in the Department of Biomedical Engineering, affiliated with the IBS Center for Genomic Integrity, has discovered UNI418, a compound that effectively prevents the penetration of the coronavirus. This compound works by regulating dielectric homeostasis, thereby inhibiting the virus’s entry into human cells.

The Allen Institute for Immunology has released its first Human Immune Health Atlas, a comprehensive single-cell reference dataset that offers unprecedented insight into the landscape of healthy human immune cells from childhood through adulthood.

Comprehensive dataset maps the landscape of healthy immune cells across the human lifespan.

Question Can microplastics reach the olfactory bulb in the human brain?

Findings This case series analyzed the olfactory bulbs of 15 deceased individuals via micro-Fourier transform infrared spectroscopy and detected the presence of microplastics in the olfactory bulbs of 8 individuals. The predominant shapes were particles and fibers, with polypropylene being the most common polymer.

Meaning The presence of microplastics in the human olfactory bulb suggests the olfactory pathway as a potential entry route for microplastics into the brain, highlighting the need for further research on their neurotoxic effects and implications for human health.

How can machine learning help individuals with type 1 diabetes (T1D)? This is what a study presented at this year’s Annual Meeting of the European Association for the Study of Diabetes (EASD) hopes to address as a team of researchers have developed a system using machine learning capable of managing blood sugars levels with such proficiency that those using system were able to lead lives far more active than the average T1D patient.

For the study, the researchers developed the AID system, which uses closed-loop technology that delivers insulin based on readings from the machine learning algorithm, resulting in a 50-year-old man, a 40-year-old man, and a 34-year-old woman with T1D being able to run hours-long marathons in Tokyo, Santiago, and Paris, respectively. This study holds the potential to help develop better technology capable of allowing T1D diabetes patients to stay in shape without constantly fearing for their blood sugar levels, which can lead to long-term health problems, including hyperglycemia, nerve damage, or a heart attack.

“Despite better systems for monitoring blood sugars and delivering insulin, maintaining glucose levels in target range during aerobic training and athletic competition is especially difficult,” said Dr. Maria Onetto, who is in the Department of Nutrition at the Pontifical Catholic University of Chile and lead author of the study. “The use of automated insulin delivery technology is increasing, but exercise continues to be a challenge for individuals with T1D, who can still struggle to reach the recommended blood sugar targets.”

A new study has uncovered significant differences in how male and female mice process threats, even as they exhibit similar behavioural responses. The discovery suggests that including both male and female subjects in neuroscience research will lead to more accurate conclusions and ultimately better health outcomes. Understanding the influence of sex on brain function can help explain why males and females develop certain psychiatric disorders at different rates or with different symptoms, the researchers said. ‘Unless we thoughtfully and rigorously integrate sex into biomedical research, a huge amount of the population may be underserved by scientific knowledge,’ said McGill University Associate Professor and Canada Research Chair in Behavioural Neurogenomics Rosemary Bagot, who led the study. ‘Our work shows that sex is an important variable to consider, even if initial observations don’t necessarily show clear sex differences,” said Bagot. “If males and females are using different brain circuits to solve similar problems, they may be differently vulnerable to stress and respond differently to treatments.’ How brain circuits process threats and cues The study focused on two related brain circuits and their roles in processing information about threats and the cues that predict them. The researchers trained mice to recognize a sound that signalled a threat and another sound that meant safety. By observing brain activity, the team saw how communication between different brain areas processed these signals. Then, they temporarily turned off each brain connection to see how it affected the mice’s reactions, helping them understand how the brain handles threats. ‘We found that even though male and female mice respond similarly to threats, the brain circuits underlying these responses are not the same,’ Bagot said. For female mice, a connection between two specific brain areas (the medial prefrontal cortex and the nucleus accumbens) played a key role. The study found that in male mice, a different connection (between the ventral hippocampus and the nucleus accumbens) was more important for handling the same situation. It was previously assumed that similar behavior meant similar brain function. Now, the researchers are exploring how sex impacts brain circuits in processing threats, focusing on the role of sex hormones and different learning strategies. This research is supported by funding from CIHR. About the study Sex-biased neural encoding of threat discrimination in nucleus accumbens afferents drives suppression of reward behavior by Jessie Muir, Eshaan Iyer et al., was published in Nature Neuroscience.

The AI scene is electrified with groundbreaking advancements this month, keeping us all at the edge of our seats. A mind-blowing AI robot with human-like intelligence has the world in shock. Google DeepMind’s JEST AI learns at an astonishing 13x faster pace. OpenAI’s SearchGPT and CriticGPT, the force behind ChatGPT’s prowess, are disrupting industries. STRAWBERRY, their most powerful AI yet, takes center stage. GPT4ALL 3.0 is the AI sensation causing a frenzy, while OpenAI’s AI Health Coach promises personalized wellness solutions. Llama 3.1 emerges as a contender, and NeMo AI boasts a massive 128k context capacity, running locally and free. Microsoft’s new AI Search could redefine how we navigate information, while OpenAI’s latest unnamed model has the tech world buzzing with anticipation.

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Continue reading “AI Shocks Again: AI Robots with Human Brain, AGI, OpenAI, DeepMind & More (July Monthly News)” »

However, the yeast should be treated to rid compounds that can increase the risk of gout if consumed excessively. Even so, treated yeast still meets 41% of the daily protein requirement, comparable to traditional protein sources.

This technology aims to address several global challenges: environmental conservation, food security, and public health. Running on clean energy and CO₂, the system reduces carbon emissions in food production. It uncouples land use from farming, freeing up space for conservation.

Angenent also stresses that it will not outcompete farmers. Instead, the technology will help farmers concentrate on producing vegetables and crops sustainably. The team’s yeast may also help developing nations overcome food scarcity and nutritional deficiencies by delivering protein and vitamin B9.

Wenn wir unsere Augen öffnen, dann fällt es uns ganz leicht, die verschiedene Objekte, Menschen und Tiere um uns herum zu sehen. Bisher war die weitreichende Forschungsmeinung, dass ein ganz wesentliches Ziel unserer Wahrnehmung ist, Objekte zu erkennen und verschiedenen Kategorien zuzuordnen – zum Beispiel, ob dieses Objekt vor uns ein Hund ist und ob ein Hund zur Kategorie der Tiere zählt. Forschende vom Max-Planck-Institut für Kognitions-und Neurowissenschaften in Leipzig und der Justus-Liebig-Universität Gießen in Zusammenarbeit mit den National Institutes of Health in den USA konnte nun zeigen, dass dieses Bild unvollständig ist. In einer aktuellen Studie im Fachjournal Nature Human Behaviour schreiben sie, dass sich die Hirnaktivität beim Sehen von Objekten viel besser mit einer Vielzahl verhaltensrelevanter Dimensionen erklären lässt.

Bisher dachte man, dass das visuelle System in unserem Gehirn die gesehenen Objekte in sehr grundlegende Merkmale zerlegt und dann nach und nach wieder zusammensetzt, mit dem Ziel, deren Erkennen zu ermöglichen. „Unsere Ergebnisse haben gezeigt, dass Erkennen und Kategorisieren zwar wichtige Ziele unseres Sehens sind, aber bei weitem nicht die einzigen.“, sagt Letztautor Martin Hebart, Gruppenleiter am MPI CBS und Professor an der Justus-Liebig-Universität. „Tatsächlich finden wir verhaltensrelevante Signale an allen Verarbeitungsstufen im visuellen System. Dies konnten wir aus der Analyse der von uns entdeckten verhaltensrelevanten Dimensionen ableiten.” Im Vorfeld hatten die Forscher mit einem Computermodell aus Verhaltensdaten von über 12.000 Studienteilnehmer*innen 66 Objektdimensionen identifiziert.

Google researchers have created an innovative AI model called Health Acoustic Representations (HeAR), designed to identify acoustic biomarkers for diseases like tuberculosis.

It can listen to human sounds and flag early signs of disease.

Continue reading “New AI model helps researchers detect disease based on coughs” »