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Immunosuppression in Sepsis: Biomarkers and Specialized Pro-Resolving Mediators

Severe infection can lead to sepsis. In sepsis, the host mounts an inappropriately large inflammatory response in an attempt to clear the invading pathogen. This sustained high level of inflammation may cause tissue injury and organ failure. Later in sepsis, a paradoxical immunosuppression occurs, where the host is unable to clear the preexisting infection and is susceptible to secondary infections. A major issue with sepsis treatment is that it is difficult for physicians to ascertain which stage of sepsis the patient is in. Sepsis treatment will depend on the patient’s immune status across the spectrum of the disease, and these immune statuses are nearly polar opposites in the early and late stages of sepsis. Furthermore, there is no approved treatment that can resolve inflammation without contributing to immunosuppression within the host.

Vesicle-based method sidesteps detergents to reveal proteins in their natural state

Membrane proteins are crucial for numerous biological processes and serve as important drug targets. For decades, scientists have relied on detergents to extract membrane proteins from cell membranes for structural studies.

While detergent-based approaches have significantly advanced our understanding of membrane protein structures, they present certain limitations, such as resource-intensive detergent screening and the absence of native membrane lipids, which can hinder investigations into lipid-mediated regulation.

To address these challenges, a research team led by Prof. Dang Shangyu from the Division of Life Science at the Hong Kong University of Science and Technology (HKUST) has developed a novel vesicle-based method that preserves the native lipid environment of , which can advance structural and functional studies.

Computer Has One Instruction, Many Transistors

There’s always some debate around what style of architecture is best for certain computing applications, with some on the RISC side citing performance per watt and some on the CISC side citing performance per line of code. But when looking at instruction sets it’s actually possible to eliminate every instruction except one and still have a working, Turing-complete computer. This instruction is called subleq or “subtract and branch if less-than or equal to zero ”. [Michael] has built a computer that does this out of discrete components from scratch.

We’ll save a lot of the details of the computer science for [Michael] or others to explain, but at its core this is a computer running with a 1 kHz clock with around 700 transistors total. Since the goal of a single-instruction computer like this is simplicity, the tradeoff is that many more instructions need to be executed for equivalent operations. For this computer it takes six clock cycles to execute one instruction, for a total of about 170 instructions per second. [Michael] also created an assembler for this computer, so with an LCD screen connected and mapped to memory he can write and execute a simple hello world program just like any other computer.

[Michael] does note that since he was building this from Logisim directly he doesn’t have a circuit schematic, but due to some intermittent wiring issues might have something in the future if he decides to make PCBs for this instead of using wire on a cardboard substrate. There’s plenty of other information on his GitHub page though. It’s a unique project that gets to the core of what’s truly needed for a working computer. There are a few programming languages out there that are built on a similar idea.

Bilu Huang — CSO, Fuzhuang Therapeutics — Conquering Aging Via TRCS

Conquering aging via TRCS — the telomere DNA AND ribosomal DNA co-regulation model for cell senescence — bilu huang — CSO, fuzhuang therapeutics.

Bilu Huang (https://biluhuang.com/) is a visionary scientist dedicated to finding solutions to some of the most pressing challenges facing humanity. His interdisciplinary work spans multiple fields, including biological aging, dinosaur extinction theories, geoengineering for carbon removal, and controlled nuclear fusion technology.

Born in Sanming City, Fujian Province, Huang is an independent researcher whose knowledge is entirely self-taught. Driven by curiosity and a relentless pursuit of scientific exploration, he has achieved numerous research results through his dedication and passion for science.

As a talented theoretical gerontologist, he proposed the Telomere DNA and ribosomal DNA co-regulation model for cell senescence (TRCS) and he is now using this latest theory to develop biotechnology to rejuvenate cells which will be used to completely cure various age-related degenerative diseases and greatly extend human life at Fuzhuang Therapeutics (https://lab.fuzhuangtx.com/en/).

#Aging #Longevity #BiluHuang #FuzhuangTherapeutics #TelomereDNAAndRibosomalDNACoRegulationModelForCell #Senescence #TRCS #DinosaurExtinctionResearch #CarbonRemovalTechnology #ControlledNuclearFusion #TelomereDNA #RibosomalDNA #CellularAging #GeneticProgram #Telomere #P53

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MIT engineers develop a magnetic transistor for more energy-efficient electronics

Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.

MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity.

The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.

Breakthrough: Quantum Entanglement Achieved Between The Hearts of Two Atoms

Quantum entanglement – once dismissed by Albert Einstein as “spooky action at a distance” – has long captured the public imagination and puzzled even seasoned scientists.

But for today’s quantum practitioners, the reality is rather more mundane: entanglement is a kind of connection between particles that is the quintessential feature of quantum computers.

Though these devices are still in their infancy, entanglement is what will allow them to do things classical computers cannot, such as better simulating natural quantum systems like molecules, pharmaceuticals, or catalysts.

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