Lifeboat Foundation

The Netherlands Cancer Institute has found that the estrous cycle stage significantly influences mammary tumors’ sensitivity to chemotherapy. In mouse models of breast cancer, treatment initiated during the diestrus stage resulted in reduced responses to chemotherapy compared to initiation during the estrus stage.

The human body contains internal timekeeping clocks to adapt to environmental changes, including infradian rhythms like the menstrual cycle. Fluctuating hormone levels during these cycles regulate physiological adaptations, which may impact responses to therapies.

Understanding factors that contribute to the heterogeneity in chemotherapy responses is crucial for improving treatment outcomes in breast cancer.

Siddarth Kara’s bestseller, “Cobalt Red: How the Blood of Congo Powers Our Lives,” focuses on problems surrounding the sourcing of cobalt, a critical component of lithium-ion batteries that power many technologies central to modern life, from mobile phones and pacemakers to electric vehicles.

“Perhaps many of us have read how lithium-ion batteries are vital for energy storage technologies,” says Eric Schelter, the Hirschmann-Makineni Professor of Chemistry at the University of Pennsylvania. “But how materials that make up such batteries are sourced can be concerning and problematic, both ethically and environmentally.”

Schelter says that cobalt mining in the Democratic Republic of Congo, which supplies about 70% of the world’s cobalt, raises concerns due to environmental degradation and unsafe working conditions, and that large-scale mining disrupts ecosystems and can contaminate water supplies, leaving lasting environmental damage. In addition, he notes that a looming cobalt shortage threatens to strain global supply chains as demand for battery technologies continues to grow.

HITS-Bio is the first tool to bioprint directly on a wound.

Despite technological advances like electronic health records (EHRs) and dictation tools, the administrative load on healthcare providers has only grown, often overshadowing the time and energy dedicated to direct patient care. This escalation in clerical tasks is a major contributor to physician burnout and dissatisfaction, affecting not only the well-being of providers but also the quality of care they deliver.

During consultations, the focus on documentation can detract from meaningful patient interactions, resulting in fragmented, rushed, and sometimes impersonal communication. The need for a solution that both streamlines documentation and restores the patient-centred nature of healthcare has never been more pressing. This is where AI-powered medical scribes come into play, offering a promising path from traditional dictation to fully automated, integrated documentation support.

AI medical scribe software utilises advanced artificial intelligence and machine learning to transcribe, in real time, entire patient-physician consultations without the need for traditional audio recordings. Leveraging sophisticated speech recognition and natural-language processing (NLP) algorithms, AI scribes are capable of interpreting and processing complex medical conversations with impressive accuracy. These systems can intelligently filter out non-essential dialogue, such as greetings and small talk, to create a streamlined and detailed clinical note.

Researchers at Kyushu University have revealed how spatial distance between specific regions of DNA is linked to bursts of gene activity. Using advanced cell imaging techniques and computer modeling, the researchers showed that the folding and movement of DNA, as well as the accumulation of certain proteins, changes depending on whether a gene is active or inactive.

The study, published on December 6 in Science Advances, sheds insight into the complicated world of gene expression and could lead to new therapeutic techniques for diseases caused by improper regulation of gene expression.

Gene expression is a fundamental process that occurs within cells, with two main phases: transcription, where DNA is copied into RNA, and translation, where the RNA is used to make proteins. For each cell to carry out its specific functions in the body, or to respond to changing conditions, the right amount of a protein must be produced at the right time, meaning genes must be carefully switched on and off.

Major findings on the inner workings of a brittle star’s ability to reversibly control the pliability of its tissues will help researchers solve the puzzle of mutable collagenous tissue (MCT) and potentially inspire new “smart” biomaterials for human health applications.

The work is directed by Denis Jacob Machado—assistant professor in Bioinformatics at The University of North Carolina at Charlotte Center for Computational Intelligence to Predict Health and Environmental Risks (CIPHER)—and Vladimir Mashanov, staff scientist at Wake Forest Institute for Regenerative Medicine.

In “Unveiling putative modulators of mutable collagenous tissue in the brittle star Ophiomastix wendtii: an RNA-Seq analysis,” published recently in BMC Genomics, the researchers describe using advanced transmission electron microscopy (TEM), RNA sequencing, and other bioinformatics methods to identify 16 potential MCT modulator genes. This research offers a breakthrough towards understanding precisely how echinoderms quickly and drastically transform their collagenous tissue. The first author of the paper, Reyhaneh Nouri, is a Ph.D. student in UNC Charlotte’s Department of Bioinformatics and Genomics.

Cleveland Clinic Genome Center researchers have unraveled how immune cells called microglia can transform and drive harmful processes like neuroinflammation in Alzheimer’s disease. The study, published in the journal Alzheimer’s & Dementia, also integrates drug databases with real-world patient data to identify FDA-approved drugs that may be repurposed to target disease-associated microglia in Alzheimer’s disease without affecting the healthy type.

The researchers, led by study corresponding author Feixiong Cheng, Ph.D., hope their unique approach of integrating genetic, chemical and human health data to identify drug targets and corresponding drugs will inspire other scientists to take similar approaches in their own research.

Microglia are specialized immune cells that patrol our brains, seeking and responding to tissue damage and external threats like bacteria and viruses. Different types of microglial cells use different methods to keep the brain safe. Some may cause neuroinflammation—inflammation in the brain—to fight invaders or kickstart the repair process in damaged cells. Others may work to “eat” dangerous substances in the brain, and clean up damage and debris. However, during Alzheimer’s disease, new types of microglia can form that promote disease progression.

Chaperone-mediated autophagy (CMA) is the lysosomal degradation of individually selected proteins, independent of vesicle fusion. CMA is a central part of the proteostasis network in vertebrate cells. However, CMA is also a negative regulator of anabolism, and it degrades enzymes required for glycolysis, de novo lipogenesis, and translation at the cytoplasmic ribosome. Recently, CMA has gained attention as a possible modulator of rodent aging. Two mechanistic models have been proposed to explain the relationship between CMA and aging in mice. Both of these models are backed by experimental data, and they are not mutually exclusionary. Model 1, the “Longevity Model,” states that lifespan-extending interventions that decrease signaling through the INS/IGF1 signaling axis also increase CMA, which degrades (and thereby reduces the abundance of) several proteins that negatively regulate vertebrate lifespan, such as MYC, NLRP3, ACLY, and ACSS2. Therefore, enhanced CMA, in early and midlife, is hypothesized to slow the aging process. Model 2, the “Aging Model,” states that changes in lysosomal membrane dynamics with age lead to age-related losses in the essential CMA component LAMP2A, which in turn reduces CMA, contributes to age-related proteostasis collapse, and leads to overaccumulation of proteins that contribute to age-related diseases, such as Alzheimer’s disease, Parkinson’s disease, cancer, atherosclerosis, and sterile inflammation. The objective of this review paper is to comprehensively describe the data in support of both of these explanatory models, and to discuss the strengths and limitations of each.

Chaperone-mediated autophagy (CMA) is a highly selective form of lysosomal proteolysis, where proteins bearing consensus motifs are individually selected for lysosomal degradation (Dice, 1990; Cuervo and Dice, 1996; Cuervo et al., 1997). CMA is mechanistically distinct from macroautophagy and microautophagy, which, along with CMA, are present in most mammalian cells types.

Macroautophagy (Figure 1 A) begins when inclusion membranes (phagophores) engulf large swaths of cytoplasm or organelles, and then seal to form double-membrane autophagosomes. Autophagosomes then fuse with lysosomes, delivering their contents for degradation by lysosomal hydrolases (Galluzzi et al., 2017). Macroautophagy was the first branch of autophagy to be discovered, and it is easily recognized in electron micrograms, based on the morphology of phagophores, autophagosomes, and lysosomes (Galluzzi et al., 2017).

Understanding neonatal brain injury — can it teach us about adult-onset neurodegenerative disease?