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Positron emission tomography (PET) constitutes a functional imaging technique that is harnessed to probe biological processes in vivo. PET imaging has been used to diagnose and monitor the progression of diseases, as well as to facilitate drug development efforts at both preclinical and clinical stages. The wide applications and rapid development of PET have ultimately led to an increasing demand for new methods in radiochemistry, with the aim to expand the scope of synthons amenable for radiolabeling. In this work, we provide an overview of commonly used chemical transformations for the syntheses of PET tracers in all aspects of radiochemistry, thereby highlighting recent breakthrough discoveries and contemporary challenges in the field. We discuss the use of biologicals for PET imaging and highlight general examples of successful probe discoveries for molecular imaging with PET – with a particular focus on translational and scalable radiochemistry concepts that have been entered to clinical use. Positron emission tomography is widely used to diagnose and monitor different disease states and interest in the technique has led to the demand for the development of new method for radiolabelling. Here the authors review the recent progress in the development of new PET probes.

The blood-brain barrier (BBB) is a continuous endothelial membrane within brain microvessels that has sealed cell-to-cell contacts and is sheathed by mural vascular cells and perivascular astrocyte end-feet. The BBB protects neurons from factors present in the systemic circulation and maintains the highly regulated CNS internal milieu, which is required for proper synaptic and neuronal functioning. BBB disruption allows influx into the brain of neurotoxic blood-derived debris, cells and microbial pathogens and is associated with inflammatory and immune responses, which can initiate multiple pathways of neurodegeneration. This Review discusses neuroimaging studies in the living human brain and post-mortem tissue as well as biomarker studies demonstrating BBB breakdown in Alzheimer disease, Parkinson disease, Huntington disease, amyotrophic lateral sclerosis, multiple sclerosis, HIV-1-associated dementia and chronic traumatic encephalopathy. The pathogenic mechanisms by which BBB breakdown leads to neuronal injury, synaptic dysfunction, loss of neuronal connectivity and neurodegeneration are described. The importance of a healthy BBB for therapeutic drug delivery and the adverse effects of disease-initiated, pathological BBB breakdown in relation to brain delivery of neuropharmaceuticals are briefly discussed. Finally, future directions, gaps in the field and opportunities to control the course of neurological diseases by targeting the BBB are presented.

Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.

Patients with Alzheimer’s disease (AD) present with both extracellular amyloid-β (Aβ) plaques and intracellular tau-containing neurofibrillary tangles in the brain. For many years, the prevailing view of AD pathogenesis has been that changes in Aβ precipitate the disease process and initiate a deleterious cascade involving tau pathology and neurodegeneration. Beyond this ‘triggering’ function, it has been typically presumed that Aβ and tau act independently and in the absence of specific interaction. However, accumulating evidence now suggests otherwise and contends that both pathologies have synergistic effects. This could not only help explain negative results from anti-Aβ clinical trials but also suggest that trials directed solely at tau may need to be reconsidered. Here, drawing from extensive human and disease model data, we highlight the latest evidence base pertaining to the complex Aβ–tau interaction and underscore its crucial importance to elucidating disease pathogenesis and the design of next-generation AD therapeutic trials.Busche and Hyman review emerging evidence for an interaction between Aβ and tau during Alzheimer’s disease (AD) progression that challenges the classical linear trajectory model and offers a new perspective on AD pathophysiology and therapy.

Key Points The neuronal correlates of consciousness (NCC) are the minimum neuronal mechanisms jointly sufficient for any one specific conscious experience. It is important to distinguish full NCC (the neural substrate supporting experience in general, irrespective of its specific content), content-specific NCC (the neural substrate supporting a particular content of experience — for example, faces, whether seen, dreamt or imagined) and background conditions (factors that enable consciousness, but do not contribute directly to the content of experience — for example, arousal systems that ensure adequate excitability of the NCC). The no-report paradigm allows the NCC to be distinguished from events or processes — such as selective attention, memory and response preparation — that are associated with, precede or follow conscious experience. In such paradigms, trials with explicit reports are included along with trials without explicit reports, during which indirect physiological measures are used to infer what the participant is perceiving. The best candidates for full and content-specific NCC are located in the posterior cerebral cortex, in a temporo-parietal-occipital hot zone. The content-specific NCC may be any particular subset of neurons within this hot zone that supports specific phenomenological distinctions, such as faces. The two most widely used electrophysiological signatures of consciousness — gamma range oscillations and the P3b event-related potential — can be dissociated from conscious experiences and are more closely correlated with selective attention and novelty, respectively. New electroencephalography- or functional MRI-based variables that measure the extent to which neuronal activity is both differentiated and integrated across the cortical sheet allow the NCC to be identified more precisely. Moreover, a combined transcranial magnetic stimulation–electroencephalography procedure can predict the presence or absence of consciousness in healthy people who are awake, deeply sleeping or under different types of anaesthesia, and in patients with disorders of consciousness, at the single-person level. Extending the NCC derived from studies in people who can speak about the presence and quality of consciousness to patients with severe brain injuries, fetuses and newborn infants, non-mammalian species and intelligent machines is more challenging. For these purposes, it is essential to combine experimental studies to identify the NCC with a theoretical approach that characterizes in a principled manner what consciousness is and what is required of its physical substrate. Several brain regions and physiological processes have been proposed to constitute the neural correlates of consciousness. In this Review, Koch and colleagues discuss studies that distinguish the neural correlates of consciousness from other neural processes that precede, accompany or follow it, and suggest that the neural correlates of consciousness are localized to posterior cortical regions. There have been a number of advances in the search for the neural correlates of consciousness — the minimum neural mechanisms sufficient for any one specific conscious percept. In this Review, we describe recent findings showing that the anatomical neural correlates of consciousness are primarily localized to a posterior cortical hot zone that includes sensory areas, rather than to a fronto-parietal network involved in task monitoring and reporting. We also discuss some candidate neurophysiological markers of consciousness that have proved illusory, and measures of differentiation and integration of neural activity that offer more promising quantitative indices of consciousness.

Obesity and type 2 diabetes are the most frequent metabolic disorders, but their causes remain largely unclear. Insulin resistance, the common underlying abnormality, results from imbalance between energy intake and expenditure favouring nutrient-storage pathways, which evolved to maximize energy utilization and preserve adequate substrate supply to the brain. Initially, dysfunction of white adipose tissue and circulating metabolites modulate tissue communication and insulin signalling. However, when the energy imbalance is chronic, mechanisms such as inflammatory pathways accelerate these abnormalities. Here we summarize recent studies providing insights into insulin resistance and increased hepatic gluconeogenesis associated with obesity and type 2 diabetes, focusing on data from humans and relevant animal models. A Review of studies into insulin resistance and hepatic gluconeogenesis associated with obesity and type 2 diabetes.

Key Points Semantic cognition refers to our ability to use, manipulate and generalize knowledge that is acquired over the lifespan to support innumerable verbal and non-verbal behaviours. Semantic cognition relies on two principal interacting neural systems: representation and control. We refer to this two-system view as the controlled semantic cognition framework. Coherent, generalizable concepts are formed through the hub-and-spoke representational system with the hub localised to the anterior temporal region (bilaterally) and spokes localised in modality-specific association cortices that are distributed across the cortex. Convergent clinical and cognitive neuroscience data show that the anterior temporal lobe hub has graded variations of semantic function that follow its pattern of connectivity. Category-specific differences in semantic function reflect the contributions of different parts of the connectivity-constrained version of the hub-and-spoke framework. Semantic control is implemented within a distributed frontal and temporoparietal neural network. Semantic control supports executive mechanisms that constrain how activation propagates through the network for semantic representation. Our ability to use conceptual knowledge to support various behaviours is termed semantic cognition. In this Review, Lambon Ralph et al . argue that this ability arises from two interacting neural systems, one for representation and one for control. Semantic cognition refers to our ability to use, manipulate and generalize knowledge that is acquired over the lifespan to support innumerable verbal and non-verbal behaviours. This Review summarizes key findings and issues arising from a decade of research into the neurocognitive and neurocomputational underpinnings of this ability, leading to a new framework that we term controlled semantic cognition (CSC). CSC offers solutions to long-standing queries in philosophy and cognitive science, and yields a convergent framework for understanding the neural and computational bases of healthy semantic cognition and its dysfunction in brain disorders.

The use of photothermal agents (PTAs) in cancer photothermal therapy (PTT) has shown promising results in clinical studies. The rapid degradation of PTAs may address safety concerns but usually limits the photothermal stability required for efficacious treatment. Conversely, PTAs with high photothermal stability usually degrade slowly. The solutions that address the balance between the high photothermal stability and rapid degradation of PTAs are rare. Here, we report that the inherent Cu 2+ -capturing ability of black phosphorus (BP) can accelerate the degradation of BP, while also enhancing photothermal stability. The incorporation of Cu 2+ into BP@Cu nanostructures further enables chemodynamic therapy (CDT)-enhanced PTT. Moreover, by employing 64 Cu 2+ , positron emission tomography (PET) imaging can be achieved for in vivo real-time and quantitative tracking. Therefore, our study not only introduces an “ideal” PTA that bypasses the limitations of PTAs, but also provides the proof-of-concept application of BP-based materials in PET-guided, CDT-enhanced combination cancer therapy. A balance between high stability and rapid degradation is required for effective photothermal anti-cancer agents. Here, the authors use Cu 2+ to accelerate the degradation of black phosphorus nanosheets while enhancing its photothermal ability and apply this material for PET-guided, CDT-enhanced combination cancer therapy in mice.

Cancer cells characteristically consume glucose through Warburg metabolism 1 , a process that forms the basis of tumour imaging by positron emission tomography (PET). Tumour-infiltrating immune cells also rely on glucose, and impaired immune cell metabolism in the tumour microenvironment (TME) contributes to immune evasion by tumour cells 2 – 4 . However, whether the metabolism of immune cells is dysregulated in the TME by cell-intrinsic programs or by competition with cancer cells for limited nutrients remains unclear. Here we used PET tracers to measure the access to and uptake of glucose and glutamine by specific cell subsets in the TME. Notably, myeloid cells had the greatest capacity to take up intratumoral glucose, followed by T cells and cancer cells, across a range of cancer models. By contrast, cancer cells showed the highest uptake of glutamine. This distinct nutrient partitioning was programmed in a cell-intrinsic manner through mTORC1 signalling and the expression of genes related to the metabolism of glucose and glutamine. Inhibiting glutamine uptake enhanced glucose uptake across tumour-resident cell types, showing that glutamine metabolism suppresses glucose uptake without glucose being a limiting factor in the TME. Thus, cell-intrinsic programs drive the preferential acquisition of glucose and glutamine by immune and cancer cells, respectively. Cell-selective partitioning of these nutrients could be exploited to develop therapies and imaging strategies to enhance or monitor the metabolic programs and activities of specific cell populations in the TME. Positron emission tomography measurements of nutrient uptake in cells of the tumour microenvironment reveal cell-intrinsic partitioning in which glucose uptake is higher in myeloid cells, whereas glutamine is preferentially acquired by cancer cells.