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Cells employ regulated transport mechanisms to ensure that their plasma membranes (PMs) are optimally supplied with cholesterol derived from uptake of low-density lipoproteins (LDL) and synthesis. To date, all inhibitors of cholesterol transport block steps in lysosomes, limiting our understanding of post-lysosomal transport steps. Here, we establish the cholesterol-binding domain 4 of anthrolysin O (ALOD4) as a reversible inhibitor of cholesterol transport from PM to endoplasmic reticulum (ER). Using ALOD4, we: (1) deplete ER cholesterol without altering PM or overall cellular cholesterol levels; (2) demonstrate that LDL-derived cholesterol travels from lysosomes first to PM to meet cholesterol needs, and subsequently from PM to regulatory domains of ER to suppress activation of SREBPs, halting cholesterol uptake and synthesis; and (3) determine that continuous PM-to-ER cholesterol transport allows ER to constantly monitor PM cholesterol levels, and respond rapidly to small declines in cellular cholesterol by activating SREBPs, increasing cholesterol uptake and synthesis. Cells are surrounded by a plasma membrane made mostly from oily molecules known as lipids. One of these lipids, called cholesterol, is essential for keeping this membrane stable. Cholesterol is partly produced within the cells at a specialized structure called the endoplasmic reticulum, and partly imported from the blood surrounding the cell. In the blood, cholesterol is shielded inside particles called low-density lipoprotein (or LDL for short), which is taken into the cell and then sent to another structure called the lysosome. Inside the cell, cholesterol that is freshly produced in the endoplasmic reticulum or freshly imported into the lysosome, must be moved to the plasma membrane, where most of the cholesterol is located. Cholesterol levels are regulated by a ‘control machinery’ of proteins located in the endoplasmic reticulum. To keep the cholesterol levels constant, the endoplasmic reticulum needs to be in continual communication with the plasma membrane. However, the mechanisms by which cholesterol is transported between membranes are still poorly understood. Here, Infante and Radhakrishnan report a new tool to study how cholesterol is transported in human and hamster cells. The tool, which is based on part of a bacterial protein, traps cholesterol in the plasma membrane and prevents it from moving to the endoplasmic reticulum, and thus from updating the control machinery about cholesterol levels. From this inhibition, it is inferred that a stream of cholesterol constantly travels from the plasma membrane back to endoplasmic reticulum. This way, proteins in the endoplasmic reticulum can monitor the cholesterol levels in the plasma membrane in real-time. The endoplasmic reticulum responded rapidly even to small declines in cholesterol levels by activating genes that increase cholesterol production or the amount of cholesterol imported via the LDL pathway. Further work showed that cholesterol derived from LDL travels from the lysosome directly to the plasma membrane to maintain optimal cholesterol levels. It then moves to the endoplasmic reticulum to signal that cholesterol levels in the cell have been satisfied. The findings and tools described in this study will help to further investigate the mechanisms underlying the transport of cholesterol between the different membranes and structures in a cell. A next step will be to see if the mechanisms that apply to distribution of imported cholesterol from lysosomes, also apply to the cholesterol produced in the endoplasmic reticulum.

When human fibroblasts take up plasma low density lipoprotein (LDL), its cholesterol is liberated in lysosomes and eventually reaches the endoplasmic reticulum (ER) where it inhibits cholesterol synthesis by blocking activation of SREBPs. This feedback protects against cholesterol overaccumulation in the plasma membrane (PM). But how does ER know whether PM is saturated with cholesterol? In this study, we define three pools of PM cholesterol: (1) a pool accessible to bind 125I-PFO*, a mutant form of bacterial Perfringolysin O, which binds cholesterol in membranes; (2) a sphingomyelin(SM)-sequestered pool that binds 125I-PFO* only after SM is destroyed by sphingomyelinase; and (3) a residual pool that does not bind 125I-PFO* even after sphingomyelinase treatment. When LDL-derived cholesterol leaves lysosomes, it expands PM's PFO-accessible pool and, after a short lag, it also increases the ER's PFO-accessible regulatory pool. This regulatory mechanism allows cells to ensure optimal cholesterol levels in PM while avoiding cholesterol overaccumulation. Cells are enclosed by a plasma membrane that is made of lipid molecules and proteins. Almost half of the lipid molecules in the plasma membranes of animal cells (including human cells) are cholesterol molecules. Since cholesterol helps to keep the membrane stable, its level in the plasma membrane is tightly regulated. Cholesterol is produced within animal cells, but it can also be taken up from outside the cell, primarily from low density lipoprotein (or LDL for short). When ingested LDL is broken down inside a cell, most of the cholesterol molecules are added to the plasma membrane, but some end up in the membrane of an organelle inside the cell called the endoplasmic reticulum. The amount of cholesterol in the membrane of the endoplasmic reticulum regulates the activation of a protein called SREBP, a transcription factor that is attached to this membrane. If the level of cholesterol becomes too low, this transcription factor travels to the cell nucleus, where it switches on the genes that cause the cell to produce more cholesterol and also to take up more LDL from the environment. When the amount of cholesterol in the membrane is high enough, the SREBP protein remains attached to the endoplasmic reticulum, which reduces the production of cholesterol and the uptake of LDL. Here, Das et al. study the movement of cholesterol molecules between the plasma membrane and the membrane of the endoplasmic reticulum by using a toxin that binds to membranes that are rich in cholesterol. These experiments showed that the plasma membrane contains three different types or ‘pools’ of cholesterol. Das et al. found that only one of these pools is ‘labile’: it grows when there is an excess of LDL, and shrinks when cholesterol is running low in the cell. Furthermore, excess cholesterol is first added to this labile pool in the plasma membrane before it is added to the pool in the endoplasmic reticulum. This suggests that the production, uptake, and breakdown of cholesterol are all controlled by partitioning this molecule between the labile pool in the plasma membrane and the endoplasmic reticulum. The next challenge is to determine how the three pools of cholesterol in the plasma membrane are maintained, and what regulates the distribution of cholesterol between the endoplasmic reticulum and the labile pool in the plasma membrane.

Previously we proposed that transmission of the hedgehog signal across the plasma membrane by Smoothened is triggered by its interaction with cholesterol (Luchetti et al., 2016). But how is cholesterol, an abundant lipid, regulated tightly enough to control a signaling system that can cause birth defects and cancer? Using toxin-based sensors that distinguish between distinct pools of cholesterol, we find that Smoothened activation and hedgehog signaling are driven by a biochemically-defined, small fraction of membrane cholesterol, termed accessible cholesterol. Increasing cholesterol accessibility by depletion of sphingomyelin, which sequesters cholesterol in complexes, amplifies hedgehog signaling. Hedgehog ligands increase cholesterol accessibility in the membrane of the primary cilium by inactivating the transporter-like protein Patched 1. Trapping this accessible cholesterol blocks hedgehog signal transmission across the membrane. Our work shows that the organization of cholesterol in the ciliary membrane can be modified by extracellular ligands to control the activity of cilia-localized signaling proteins.

The gut microbiome is essential for nutrient absorption, immune function, and overall metabolic health. A balanced microbial community allows for the breakdown of carbohydrates, proteins, fats, vitamins, and minerals into maximally absorbed nutrients and provides protection against inflammation. Dysbiosis, or microbial imbalance, disrupts these processes and leads to malabsorption, barrier dysfunction, and toxic metabolite production. These imbalances contribute to a wide variety of diseases, from obesity, diabetes, and cardiovascular disease to anemia, osteoporosis, and nervous system dysfunctions. Advances in sequencing, metabolomics, and functional assays have facilitated an enhanced understanding of the ecological and biochemical complexity of gut microbes. AI-based models are also providing new insights into personalized diet and therapeutic approaches. Through the redefinition of malnutrition and chronic disease within microbial ecology, science proves the potential for engineered probiotics, precision prebiotics, and gut-targeted therapies. These innovations hold the potential to improve global health and propel precision medicine in nutrition.

A long-standing mystery in vertebrate Hedgehog signaling is how Patched 1 (PTCH1), the receptor for Hedgehog ligands, inhibits the activity of Smoothened, the protein that transmits the signal across the membrane. We previously proposed (Kinnebrew et al., 2019) that PTCH1 inhibits Smoothened by depleting accessible cholesterol from the ciliary membrane. Using a new imaging-based assay to directly measure the transport activity of PTCH1, we find that PTCH1 depletes accessible cholesterol from the outer leaflet of the plasma membrane. This transport activity is terminated by binding of Hedgehog ligands to PTCH1 or by dissipation of the transmembrane potassium gradient. These results point to the unexpected model that PTCH1 moves cholesterol from the outer to the inner leaflet of the membrane in exchange for potassium ion export in the opposite direction. Our study provides a plausible solution for how PTCH1 inhibits SMO by changing the organization of cholesterol in membranes and establishes a general framework for studying how proteins change cholesterol accessibility to regulate membrane-dependent processes in cells.

Most of the cholesterol in the plasma membranes (PMs) of animal cells is sequestered through interactions with phospholipids and transmembrane domains of proteins. However, as cholesterol concentration rises above the PM’s sequestration capacity, a new pool of cholesterol, called accessible cholesterol, emerges. The transport of accessible cholesterol between the PM and the endoplasmic reticulum (ER) is critical to maintain cholesterol homeostasis. This pathway has also been implicated in the suppression of both bacterial and viral pathogens by immunomodulatory oxysterols. Here, we describe a mechanism of depletion of accessible cholesterol from PMs by the oxysterol 25-hydroxycholesterol (25HC). We show that 25HC-mediated activation of acyl coenzyme A: cholesterol acyltransferase (ACAT) in the ER creates an imbalance in the equilibrium distribution of accessible cholesterol between the ER and PM. This imbalance triggers the rapid internalization of accessible cholesterol from the PM, and this depletion is sustained for long periods of time through 25HC-mediated suppression of SREBPs and continued activation of ACAT. In support of a physiological role for this mechanism, 25HC failed to suppress Zika virus and human coronavirus infection in ACAT-deficient cells, and Listeria monocytogenes infection in ACAT-deficient cells and mice. We propose that selective depletion of accessible PM cholesterol triggered by ACAT activation and sustained through SREBP suppression underpins the immunological activities of 25HC and a functionally related class of oxysterols.

IntroductionCanada’s health workforce crisis is placing sustained pressure on primary care, particularly in the management of chronic pain, mental health conditions and substance use disorders. Mentoring is a compelling response to workforce, educational and well-being challenges in healthcare, and Adaptive Mentorship Networks (AMNs) have emerged in Canada as an interprofessional model to strengthen provider capacity, psychological safety and compassionate care. Despite widespread interest and demonstrable effectiveness, the determinants that influence successful implementation, spread, adaptation and sustainability of AMNs remain insufficiently understood.Methods and analysisThis 3-year mixed-methods protocol will evaluate implementation of 11 AMNs that are established or in development across Canada. The study will focus on two complementary levels: (1) implementation of AMNs within healthcare ecosystems; and (2) capabilities, opportunities and motivations that contribute to adaptive mentorship between mentors and mentees. The overarching approach to understand the determinants of successful implementation and behavioural influences on adaptive mentorship uses implementation science and systems thinking methodologies to support a pan-Canadian Learning Health System. Work will proceed in three phases. Phase I will explore determinants of implementation (phase Ia) and behavioural influences on adaptive mentorship (phase Ib) through document review, interviews, systems mapping and readiness assessment. Phase II will use a Learning Alliance to identify, select and operationalise fit-for-purpose implementation strategies. Phase III will co-develop AMN-specific logic models and evaluate the feasibility, acceptability and initial utility of selected strategies. The study will be guided by the Active Implementation Framework, the Consolidated Framework for Implementation Research, the Consolidated Framework for Sustainability Constructs, the Capabilities, Opportunities and Motivation for Behaviour model, the Theoretical Domains Framework and the Health Equity Implementation Framework. Outputs from phase Ia will provide a compendium of determinants critical for the implementation of mentorship networks within healthcare arranged by stage of implementation, and the activities that current networks have taken to influence such determinants. Outputs from phase Ib will identify the capabilities, opportunities and motivations deemed critical for facilitating engagement in the act of clinical mentorship. Phase II will identify a contextualised understanding of strategies that are optimally suited to influence critical determinants of implementing AMNs and engaging in clinical mentorship. Our outputs from phases I and II will be pilot tested with each AMN and inform the development of site-specific logic models and a cross-site implementation blueprint that will be evaluated in phase III. This protocol advances a systems-informed approach to implementing AMNs across diverse Canadian health systems, with implications for mentorship-enabled workforce development.Ethics and disseminationEthics approval has been obtained from the Bruyère Health Research Ethics Board (M16-25-001 and M16-25-002) and the Newfoundland and Labrador Health Research Ethics Board (Ref# 2025.047). Participants provide informed consent prior to participating in study interviews acknowledging potential risks and benefits to participation. Findings will be mobilised through integrated knowledge mobilisation with participating AMNs, members of the Learning Alliance, policy and practice partners, conference presentations, publications, AI-enabled knowledge sharing tools and plain-language resources.

Human activity recognition (HAR) is one of the key applications of health monitoring that requires continuous use of wearable devices to track daily activities. The most efficient supervised machine learning (ML)-based approaches for predicting human activity are based on a continuous stream of sensor data. Sensor data analysis for human activity recognition using conventional algorithms and deep learning (DL) models shows promising results, but evaluating their ambiguity in decision-making is still challenging. In order to solve these issues, the paper proposes a novel Wasserstein gradient flow legonet WGF-LN-based human activity recognition system. At first, the input data is pre-processed. From the pre-processed data, the features are extracted using Haar Wavelet mother- Symlet wavelet coefficient scattering feature extraction (HS-WSFE). After that, the interest features are selected from the extracted features using (Binomial Distribution integrated-Golden Eagle Optimization) BD-GEO. The important features are then post-processed using the scatter plot matrix method. Obtained post-processing features are finally given into the WGF-LN for classifying human activities. From these experiments, the results can be obtained and showed the efficacy of the proposed model.

Personalized medicine has been a booming area in clinical research for the past decade, in which the detailed information about the patient genotype and clinical conditions were collected and considered to optimize the therapy to prevent adverse reactions. However, the utility of commercially available personalized medicine has not yet been maximized due to the lack of a structured protocol for implementation. In this narrative review, we explain the role of pharmacogenetics in personalized medicine, next-generation personalized medicine, i.e., patient-centric personalized medicine, in which the patient’s comfort is considered along with pharmacogenomics to be a primary factor. We extensively discuss the classifications, strategies, tools, and drug delivery systems that can support the implementation of patient-centric personalized medicine from an industrial perspective.

Cholesterol synthesis in animals is controlled by the regulated transport of sterol regulatory element-binding proteins (SREBPs) from the endoplasmic reticulum to the Golgi, where the transcription factors are processed proteolytically to release active fragments. Transport is inhibited by either cholesterol or oxysterols, blocking cholesterol synthesis. Cholesterol acts by binding to the SREBP-escort protein Scap, thereby causing Scap to bind to anchor proteins called Insigs. Here, we show that oxysterols act by binding to Insigs, causing Insigs to bind to Scap. Mutational analysis of the six transmembrane helices of Insigs reveals that the third and fourth are important for Insig's binding to oxysterols and to Scap. These studies define Insigs as oxysterol-binding proteins, explaining the long-known ability of oxysterols to inhibit cholesterol synthesis in animal cells.