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Protein misfolding and aggregation in Alzheimer’s disease and Type 2 Diabetes Mellitus

In a diseased condition, most of the time, target proteins attain toxicity following their transition from a α-helix to a β-sheet form [18]. Although numerous functional native proteins possess β-sheet conformations within them, the transition from an α-helix to a β-sheet is characteristic of amyloid deposits [19], and often associated with the change of a physiological function to a pathological one. Such abnormal conformational transition exposes hydrophobic amino acid residues and promotes protein aggregation [18, 20]. The toxic proteins often interact with other native proteins and may catalyze their transition into a toxic sate, and hence they are called infective conformations [18]. The newly formed toxic proteins can repeat this cycle to intiate a self-sustaining loop; thereby amplifying the toxicity to generate a catastrophic effect, beyond homeostatic reparative mechanisms, to eventually impair cellular function or induce cellular demise [21].

Proteins function properly when their constituent amino acids fold correctly [22]. On the other hand, misfolded proteins assemble into insoluble aggregates with other proteins and can be toxic for the cells [18, 20]. Ataxin-1 is highly prone to misfolding due to inherited gene defects that cause neurodegenerative diseases (NDDs), which is mainly due the repetition of glutamine within its amino acid chain; the toxicity of this protein being directly proportional to the number of glutamines [23]. There are 21 proteins that mainly interact with ataxin-1 and influence its folding or misfolding, 12 of which increase the toxicity of ataxin-1 for nerve cells, while 9 of the identified proteins reduce its toxicity [23]. Ataxin-1 resembles a double twisted spiral or helix and has a special structure, termed a “coiled coil domain”, that promotes aggregation. Proteins which possess “coiled coil domain” and interact with ataxin-1 have been reported to enhance promotion of ataxin-1 aggregation and toxic effects [24].

The gradual accumulation of misfolded proteins in the absence of their appropriate clearance can cause amyloid disease, the most prevalent one being AD. Parkinson’s disease and Huntington’s disease have similar amyloid origins [25]. These diseases can be sporadic or familial and their incidence increases dramatically with age. The mechanistic explanation for this correlation is that as we age (and are subjected to increasing numbers of mutations and/or oxidative stress causing changes to protein structure, etc.), the delicate balance of the synthesis, folding, and degradation of proteins is disturbed, ensuing in the production, accumulation and aggregation of misfolded proteins [26].

The sleep switch: How one brain signal turns sleep on and off

People spend about a third of their lives asleep. Yet, surprisingly little is known about how our brains control falling asleep and waking up. Now, researchers led by Prof. Henrik Bringmann at the Biotechnology Center (BIOTEC) of TUD Dresden University of Technology discovered another piece of this puzzle. The team showed that a single brain signal acts like a biological switch—both triggering sleep and ending it.

Their findings, published in the journal Current Biology, were made possible by studying a tiny roundworm, C. elegans, a powerful model organism in biology.

“It is really important to be able to fall asleep, but just as important to wake up too,” says Prof. Bringmann, research group leader at BIOTEC who led the study.

Clinical trial on artificial blood cells to begin in Japan

A clinical study of artificial red blood cells that can be stored for transfusions in times of emergency will begin in Japan by next March, according to Nara Medical University.

The university aims to put the artificial cells into practical use by around 2030, it said in early July, in what would likely be a world first.

The development of the blood cells, designed for use in remote areas and disasters, comes as a blood shortage is expected at medical facilities due to a declining number of donors amid the country’s shrinking population.

Olfactory neurons use unexpected ‘solid’ clusters to achieve genetic precision

A new study published in Nature reveals how olfactory sensory neurons (OSNs) achieve extraordinary precision in selecting which genes to express.

The mechanism is surprising in that it involves solid-like molecular condensates that last for days, helping to solve a long-standing puzzle in genome organization.

The research, led by Prof. Stavros Lomvardas from Columbia University, addresses one of biology’s most intriguing questions: How do in the nose manage to express only one (OR) gene out of approximately 1,000 available options?

The impact of perilesional heatsink structures on ablation volumes and symmetry in laser interstitial thermal therapy for the treatment of primary central nervous system tumors

Laser interstitial thermal therapy (LITT) has emerged as a minimally invasive treatment for primary CNS tumors. While LITT offers advantages over traditional approaches, perilesional intracranial heatsinks can lead to asymmetrical ablation, impacting patient outcomes. Understanding heatsink effects is crucial for optimizing LITT efficacy.

The authors retrospectively analyzed primary CNS tumors treated with LITT at a single tertiary care center. Ablation outcomes were quantified using the Heatsink Effect Index (HEI), measured on a scale of 0–1 (0 = total symmetry, 1 = complete asymmetry), and extent of ablation (EOA). The heatsink types evaluated were sulci, meninges, vasculature, and CSF spaces, inclusive of ventricles, resection cavities, and CSF cisterns. Statistical analyses were performed to assess the relationship between heatsink proximity and type and ablation outcomes.

A total of 99 patients satisfied all selection criteria. The cohort was 53% female, with a mean age of 61 years. Glioblastoma was the most predominant tumor type (78%), followed by low-grade glioma (15%) and meningioma (4%). Heatsink proximity significantly correlated with ablation asymmetry (HEI) (p < 0.001), particularly at the midpoint of the catheter trajectory. The correlation between closest heatsink distance and HEI varied across the different heatsink types, with distance to vasculature and CSF spaces correlating the strongest with ablation asymmetry. When assessing the relationship between EOA and medial HEI during suboptimal ablations (EOA < 100%), a negative correlation was demonstrated, showing improved EOA as HEI was reduced. Optimal cutoff catheter-heatsink distances for predicting ablation asymmetry ranged from 6.6 to 13.0 mm, emphasizing the impact of heatsink proximity on LITT efficacy.

View a PDF of the paper titled AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges, by Ranjan Sapkota and 2 other authors

This study critically distinguishes between AI Agents and Agentic AI, offering a structured conceptual taxonomy, application mapping, and challenge analysis to clarify their divergent design philosophies and capabilities. We begin by outlining the search strategy and foundational definitions, characterizing AI Agents as modular systems driven by Large Language Models (LLMs) and Large Image Models (LIMs) for narrow, task-specific automation. Generative AI is positioned as a precursor, with AI Agents advancing through tool integration, prompt engineering, and reasoning enhancements. In contrast, Agentic AI systems represent a paradigmatic shift marked by multi-agent collaboration, dynamic task decomposition, persistent memory, and orchestrated autonomy. Through a sequential evaluation of architectural evolution, operational mechanisms, interaction styles, and autonomy levels, we present a comparative analysis across both paradigms. Application domains such as customer support, scheduling, and data summarization are contrasted with Agentic AI deployments in research automation, robotic coordination, and medical decision support. We further examine unique challenges in each paradigm including hallucination, brittleness, emergent behavior, and coordination failure and propose targeted solutions such as ReAct loops, RAG, orchestration layers, and causal modeling. This work aims to provide a definitive roadmap for developing robust, scalable, and explainable AI agent and Agentic AI-driven systems. >AI Agents, Agent-driven, Vision-Language-Models, Agentic AI Decision Support System, Agentic-AI Applications