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Brain organoids can be trained to solve a goal-directed task

This research is the first rigorous academic demonstration of goal-directed learning in lab-grown brain organoids, and lays the foundation for adaptive organoid computation—exploring the capacity of lab-grown brain organoids to learn and solve tasks.

Using organoids derived from mouse stem cells and an electrophysiology system developed by industry partners Maxwell Biosciences, the researchers use electrical simulation to send and receive information to and from neurons. By using stronger or weaker signals, they communicate to the organoid the angle of the pole, which exists in a virtual environment, as it falls in one direction or the other. As this happens, the researchers observe as the organoid sends back signals of how to apply force to balance the pole, and they apply this force to the virtual pole.

For their pole-balancing experiments, the researchers observe as the organoid controls the pole until it drops, which is called an episode. Then, the pole is reset and a new episode begins. In essence, the organoid plays a video game in which the goal is to balance the pole upright for as long as possible.

The researchers observe the organoid’s progress in five-episode increments. If the organoid keeps the pole upright for longer on average in the past five episodes as compared to the past 20, it receives no training signal since it has been improving. If it does not improve the average time it keeps the pole upright, it receives a training signal.

Training feedback is not given to the organoid while it is balancing the pole—only at the end of an episode. An AI algorithm called reinforcement learning is used to select which neurons within the organoid get the training signal.

The results of this study prove that the reinforcement learning algorithm can guide the brain organoids toward improved performance at the cart-pole task—meaning organoids can learn to balance the pole for longer periods of time.

The researchers adopted a rigorous framework for success to make sure they were observing true improvement, and not just random success, including a threshold for the minimum time an organoid needs to balance the pole to “win” the game.

Continue reading “Brain organoids can be trained to solve a goal-directed task” | >

Tumor-immune-neural circuit disrupts energy homeostasis in cancer cachexia

Tumor-immune-neural circuit in cancer cachexia.

The mechanisms involved in cancer-mediated cachexia and anorexia are not well understood.

The researchers in this study delineate an interplay among tumor cells, immune cells, and the nervous system that drives cancer cachexia and anorexia.

The authors show thay loss of GDF15 protects against appetite loss, muscle wasting, and fat loss in pancreatic, lung, and skin cancers.

Disrupting this feedforward loop with GDF15-neutralizing antibody, anti-CSF1R antibody, or Rearranged during Transfection (RET) inhibitor alleviates cachexia and anorexia across cancer models. sciencenewshighlights ScienceMission https://sciencemission.com/Tumor-immune-neural-circuit

Shi et al. delineate an interplay among tumor cells, immune cells, and the nervous system that drives cancer cachexia and anorexia. Specifically, tumor-derived CSF1 induces macrophage GDF15, which signals through the GFRAL-RET neural axis to enhance β-adrenergic activity and systemic wasting. Disrupting this feedforward loop alleviates cachexia across cancer models.

Continue reading “Tumor-immune-neural circuit disrupts energy homeostasis in cancer cachexia” | >

Neurons receive precisely tailored teaching signals as we learn

How does the brain know which neurons to adjust during learning in order to optimize behavior? MIT researchers discovered that brains can use cell-by-cell error signals to do this — surprisingly similar to how AI systems are trained via backpropagation.

When we learn a new skill, the brain has to decide—cell by cell—what to change. New research from MIT suggests it can do that with surprising precision, sending targeted feedback to individual neurons so each one can adjust its activity in the right direction.

The finding echoes a key idea from modern artificial intelligence. Many AI systems learn by comparing their output to a target, computing an “error” signal, and using it to fine-tune connections within the network. A longstanding question has been whether the brain also uses that kind of individualized feedback. In a study published in the February 25 issue of the journal Nature, MIT researchers report evidence that it does.

A research team led by Mark Harnett, a McGovern Institute investigator and associate professor in the Department of Brain and Cognitive Sciences at MIT, discovered these instructive signals in mice by training animals to control the activity of specific neurons using a brain-computer interface (BCI). Their approach, the researchers say, can be used to further study the relationships between artificial neural networks and real brains, in ways that are expected to both improve understanding of biological learning and enable better brain-inspired artificial intelligence.

Better reporting is better science: Community-defined minimal reporting requirements for light microscopy

Accessible minimal requirements for reproducible light microscopy. This viewpoint from Paula Montero Llopis, Chloë van Oostende-Triplet, the QUAREP-LiMi consortium and colleagues presents a community-endorsed checklist defining minimal light microscopy metadata to improve rigor, reproducibility, and transparency in research.

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Lack of PCK1 in hepatic stellate cells causes liver fibrosis by fueling tricarboxylic acid cycle and increasing glycolysis

Online now: This study shows that a key metabolic enzyme, PCK1, protects the liver from scarring by keeping fibrogenic cells in a quiescent state. When PCK1 is reduced, these cells undergo metabolic reprogramming characterized by increased glycolysis, become aberrantly activated, and promote liver fibrosis in mice.

Mapping ADHD Heterogeneity and Biotypes by Topological Deviations in Morphometric Similarity Networks

Normative modeling of morphometric similarity networks in ADHD identified three distinct biotypes with unique clinical-neural profiles, supporting more neurobiologically informed stratification for ADHD management.

Question Can normative modeling of topological properties derived from brain morphometric similarity networks yield robust stratification biomarkers for pediatric populations with attention-deficit/hyperactivity disorder (ADHD)?

Findings This multisite case-control study included 1,154 participants, characterizing ADHD heterogeneity through hub-centric topological deviations derived from morphometric similarity networks. Three distinct biotypes emerged, each exhibiting unique clinical-neural profiles with characteristic neurochemical and functional correlates, validated in an independent transdiagnostic cohort of 554 ADHD cases.

Meaning The integration of normative modeling with heterogeneity through discriminative analysis (HYDRA) clustering yielded both dimensional and categorical insights into ADHD heterogeneity, thereby enhancing our understanding of the ADHD’s neurobiological complexity.

Nanoparticles for Targeted Drug Delivery to Cancer Stem Cells: A Review of Recent Advances

Cancer stem cells (CSCs) are a subpopulation of cells that can initiate, self-renew, and sustain tumor growth. CSCs are responsible for tumor metastasis, recurrence, and drug resistance in cancer therapy. CSCs reside within a niche maintained by multiple unique factors in the microenvironment. These factors include hypoxia, excessive levels of angiogenesis, a change of mitochondrial activity from aerobic aspiration to aerobic glycolysis, an upregulated expression of CSC biomarkers and stem cell signaling, and an elevated synthesis of the cytochromes P450 family of enzymes responsible for drug clearance. Antibodies and ligands targeting the unique factors that maintain the niche are utilized for the delivery of anticancer therapeutics to CSCs. In this regard, nanomaterials, specifically nanoparticles (NPs), are extremely useful as carriers for the delivery of anticancer agents to CSCs.

Signaling pathways in the regulation of cancer stem cells and associated targeted therapy

The concept of stem cells dates back to the 18th century when scientists tried to elucidate how lower organisms developed tissues and organs. 1 These stem cells produce daughter cells that later undergo different biological processes, either continuous self‐renewal division, or differentiation into specialized cells with a limited lifespan. Normal tissue stem cells provide a life‐long source of cells for self‐renewal of tissues, which leads us to speculate that whether stem cells are capable of deriving a malignant cell population, and this lies the foundation of cancer stem cells (CSCs) theory. CSCs are defined as a subpopulation of malignant tumor cells with selective capacities for tumor initiation, self‐renewal, metastasis, and unlimited growth into bulks. 2

Despite decades of research on cancer treatment, it has been proved extremely challenging to achieve complete remission (CR) in cancer patients. Tumor relapse may be explained by the fact that antitumor therapeutics mainly target proliferative cancer cells but remain ineffective in quiescent CSCs. The role of CSC in tumor initiation was first identified in acute myeloid leukemia (AML). Since its isolation from a number of solid tumors and hematological malignancies, the CSC is believed to form the clonogenic core of these tumors. 3 Growing evidence now suggests that CSCs are responsible for multiple progressive tumor phenotypes, including recurrence, metastasis, and treatment failure. 4, 5 The intrinsic treatment resistance of tumors has partially attributed to the presence of the CSC subpopulation, 6, 7 and may also be induced by extrinsic factors, such as treatments and environments. 8, 9

Major signaling pathways are involved in the maintenance of stem cell properties and survival of CSCs, such as the Notch, Wnt, and Hedgehog (HH) pathways. 10 There is also intricate interplay network between these signal cascades and other oncogenic pathways. 11, 12, 13 Thus, targeting pathway molecules that regulate CSCs provides a new option for the treatment of therapy‐resistant or ‐refractory tumors. This review aims to provide an overview of the regulating networks and their immune interactions involved in CSC development. We also summarized the update on the development of CSC‐directed therapeutics, with a special focus on those with application approval or under clinical evaluation.

Electromotility can be disassociated from gating charge movement in outer hair cells of conditional alpha2 spectrin knockout mice

New in JBC press| Scientists examine the effects of conditional knockouts of alpha2 spectrin in postnatal outer hair cells.

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Electromotility in mammalian outer hair cells (OHC) is the mechanism underlying cochlear amplification. It is brought about by the piezoelectric-like property of the membrane protein prestin (Slc26a5) that lies in the OHCs lateral plasma membrane. Prestin connects to an underlying cytoskeletal network of circumferential actin filaments that bridge longitudinal spectrin filaments. This network, in turn, lies between the plasma membrane and a closely apposed ER-like tubular array of subsurface cisternae (SSC).

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