Recent Developments in Machine Learning for Mass Spectrometry.

Statistical analysis and modeling of mass spectrometry (MS) data have a long and rich history with several modern MS-based applications using statistical and chemometric methods. Recently, machine learning (ML) has experienced a renaissance due to advents in computational hardware and the development of new algorithms for artificial neural networks (ANN) and deep learning architectures. Moreover, recent successes of new ANN and deep learning architectures in several areas of science, engineering, and society have further strengthened the ML field. Importantly, modern ML methods and architectures have enabled new approaches for tasks related to MS that are now widely adopted in several popular MS-based subdisciplines, such as mass spectrometry imaging and proteomics. Herein, we aim to provide an introductory summary of the practical aspects of ML methodology relevant to MS. Additionally, we seek to provide an up-to-date review of the most recent developments in ML integration with MS-based techniques while also providing critical insights into the future direction of the field.

Senescent glia link mitochondrial dysfunction and lipid accumulation.

Senescence is a cellular state linked to ageing and age-onset disease across many mammalian species1,2. Acutely, senescent cells promote wound healing3,4 and prevent tumour formation5; but they are also pro-inflammatory, thus chronically exacerbate tissue decline. Whereas senescent cells are active targets for anti-ageing therapy6-11, why these cells form in vivo, how they affect tissue ageing and the effect of their elimination remain unclear12,13. Here we identify naturally occurring senescent glia in ageing Drosophila brains and decipher their origin and influence. Using Activator protein 1 (AP1) activity to screen for senescence14,15, we determine that senescent glia can appear in response to neuronal mitochondrial dysfunction. In turn, senescent glia promote lipid accumulation in non-senescent glia; similar effects are seen in senescent human fibroblasts in culture. Targeting AP1 activity in senescent glia mitigates senescence biomarkers, extends fly lifespan and health span, and prevents lipid accumulation. However, these benefits come at the cost of increased oxidative damage in the brain, and neuronal mitochondrial function remains poor. Altogether, our results map the trajectory of naturally occurring senescent glia in vivo and indicate that these cells link key ageing phenomena: mitochondrial dysfunction and lipid accumulation.

Lesion-remote astrocytes govern microglia-mediated white matter repair.

Spared regions of the damaged central nervous system undergo dynamic remodeling and exhibit a remarkable potential for therapeutic exploitation. Here, lesion-remote astrocytes (LRAs), which interact with viable neurons, glia and neural circuitry, undergo reactive transformations whose molecular and functional properties are poorly understood. Using multiple transcriptional profiling methods, we interrogated LRAs from spared regions of mouse spinal cord following traumatic spinal cord injury (SCI). We show that LRAs acquire a spectrum of molecularly distinct, neuroanatomically restricted reactivity states that evolve after SCI. We identify transcriptionally unique reactive LRAs in degenerating white matter that direct the specification and function of local microglia that clear lipid-rich myelin debris to promote tissue repair. Fueling this LRA functional adaptation is Ccn1 , which encodes for a secreted matricellular protein. Loss of astrocyte CCN1 leads to excessive, aberrant activation of local microglia with (i) abnormal molecular specification, (ii) dysfunctional myelin debris processing, and (iii) impaired lipid metabolism, culminating in blunted debris clearance and attenuated neurological recovery from SCI. Ccn1 -expressing white matter astrocytes are specifically induced by local myelin damage and generated in diverse demyelinating disorders in mouse and human, pointing to their fundamental, evolutionarily conserved role in white matter repair. Our findings show that LRAs assume regionally divergent reactivity states with functional adaptations that are induced by local context-specific triggers and influence disorder outcome. Astrocytes tile the central nervous system (CNS) where they serve vital roles that uphold healthy nervous system function, including regulation of synapse development, buffering of neurotransmitters and ions, and provision of metabolic substrates 1 . In response to diverse CNS insults, astrocytes exhibit disorder-context specific transformations that are collectively referred to as reactivity 2-5 . The characteristics of regionally and molecularly distinct reactivity states are incompletely understood. The mechanisms through which distinct reactivity states arise, how they evolve or resolve over time, and their consequences for local cell function and CNS disorder progression remain enigmatic. Immediately adjacent to CNS lesions, border-forming astrocytes (BFAs) undergo transcriptional reprogramming and proliferation to form a neuroprotective barrier that restricts inflammation and supports axon regeneration 6-9 . Beyond the lesion, spared but dynamic regions of the injured CNS exhibit varying degrees of synaptic circuit remodeling and progressive cellular responses to secondary damage that have profound consequences for neural repair and recovery 10,11 . Throughout these cytoarchitecturally intact, but injury-reactive regions, lesion-remote astrocytes (LRAs) intermingle with neurons and glia, undergo little to no proliferation, and exhibit varying degrees of cellular hypertrophy 7,12,13 . The molecular and functional properties of LRAs remain grossly undefined. Therapeutically harnessing spared regions of the injured CNS will require a clearer understanding of the accompanying cellular and molecular landscape. Here, we leveraged integrative transcriptional profiling methodologies to identify multiple spatiotemporally resolved, molecularly distinct states of LRA reactivity within the injured spinal cord. Computational modeling of LRA-mediated heterotypic cell interactions, astrocyte-specific conditional gene deletion, and multiple mouse models of acute and chronic CNS white matter degeneration were used to interrogate a newly identified white matter degeneration-reactive astrocyte subtype. We define how this reactivity state is induced and its role in governing the molecular and functional specification of local microglia that clear myelin debris from the degenerating white matter to promote repair.

Comprehensive Lipidomic Automation Workflow using Large Language Models.

Lipidomics generates large data that makes manual annotation and interpretation challenging. Lipid chemical and structural diversity with structural isomers further complicates annotation. Although, several commercial and open-source software for targeted lipid identification exists, it lacks automated method generation workflows and integration with statistical and bioinformatics tools. We have developed the Comprehensive Lipidomic Automated Workflow (CLAW) platform with integrated workflow for parsing, detailed statistical analysis and lipid annotations based on custom multiple reaction monitoring (MRM) precursor and product ion pair transitions. CLAW contains several modules including identification of carbon-carbon double bond position(s) in unsaturated lipids when combined with ozone electrospray ionization (OzESI)-MRM methodology. To demonstrate the utility of the automated workflow in CLAW, large-scale lipidomics data was collected with traditional and OzESI-MRM profiling on biological and non-biological samples. Specifically, a total of 1497 transitions organized into 10 MRM-based mass spectrometry methods were used to profile lipid droplets isolated from different brain regions of 18-24 month-old Alzheimer's disease mice and age-matched wild-type controls. Additionally, triacyclglycerols (TGs) profiles with carbon-carbon double bond specificity were generated from canola oil samples using OzESI-MRM profiling. We also developed an integrated language user interface with large language models using artificially intelligent (AI) agents that permits users to interact with the CLAW platform using a chatbot terminal to perform statistical and bioinformatic analyses. We envision CLAW pipeline to be used in high-throughput lipid structural identification tasks aiding users to generate automated lipidomics workflows ranging from data acquisition to AI agent-based bioinformatic analysis.

Identification of Monomethyl Branched-Chain Lipids by a Combination of Liquid Chromatography Tandem Mass Spectrometry and Charge-Switching Chemistries.

While various mass spectrometric approaches have been applied to lipid analysis, unraveling the extensive structural diversity of lipids remains a significant challenge. Notably, these approaches often fail to differentiate between isomeric lipids─a challenge that is particularly acute for branched-chain fatty acids (FAs) that often share similar (or identical) mass spectra to their straight-chain isomers. Here, we utilize charge-switching strategies that combine ligated magnesium dications with deprotonated fatty acid anions. Subsequent activation of these charge inverted anions yields mass spectra that differentiate anteiso-branched- from straight-chain and iso-branched-chain FA isomers with the predictable fragmentation enabling de novo assignment of anteiso branch points. The application of these charge-inversion chemistries in both gas- and solution-phase modalities is demonstrated to assign the position of anteiso-methyl branch-points in FAs and, with the aid of liquid chromatography, can be extended to de novo assignment of additional branching sites via predictable fragmentation patterns as methyl branching site(s) move closer to the carboxyl carbon. The gas-phase approach is shown to be compatible with top-down structure elucidation of complex lipids such as phosphatidylcholines, while the integration of solution-phase charge-inversion with reversed phase liquid chromatography enables separation and unambiguous identification of FA structures within isomeric mixtures. Taken together, the presented charge-switching MS-based technique, in combination with liquid chromatography, enables the structural identification of branched-chain FA without the requirement of authentic methyl-branched FA reference standards.

Harnessing the Spatial Foundation of Mind in Breaking Vicious Cycles in Anxiety, Insomnia, and Depression: The Future of Virtual Reality Therapy Applications.

Mental Illnesses, particularly anxiety, insomnia, and depression often involve vicious cycles which are self-perpetuating and can trap one into a more chronic state. For example in the case of insomnia, sympathetic overactivity, intrusive thoughts, and emotional instability due to sleep loss can perpetuate further sleep loss the next night and so on. In this article, we put forward a perspective on breaking these vicious cycles based on preeminent theories in global and spatial cognition, that the foundation of the conscious mind is a spatial coordinate system. Based on this we discuss the potential and future of virtual reality therapeutic applications which utilize massive virtual spaces along with biofeedback designed to help break perpetual cycles in depression, anxiety, and insomnia. "Massive spaces" are those which are truly expansive such as when looking to the clear night sky. These virtual realities may take the form of a night sky, fantastical cosmic scenes, or other scenes such as mountain tops. We also hope to inspire research into such a spatial foundation of mind, use of perceived massive spaces for therapy, and the integration of biofeedback into virtual therapies.

Respiratory Rhythm, Autonomic Modulation, and the Spectrum of Emotions: The Future of Emotion Recognition and Modulation.

Pulmonary ventilation and respiration are considered to be primarily involved in oxygenation of blood for oxygen delivery to cells throughout the body for metabolic purposes. Other pulmonary physiological observations, such as respiratory sinus arrhythmia, Hering Brewer reflex, cardiorespiratory synchronization, and the heart rate variability (HRV) relationship with breathing rhythm, lack complete explanations of physiological/functional significance. The spectrum of waveforms of breathing activity correlate to anxiety, depression, anger, stress, and other positive and negative emotions. Respiratory pattern has been thought not only to be influenced by emotion but to itself influence emotion in a bi-directional relationship between the body and the mind. In order to show how filling in gaps in understanding could lead to certain future developments in mind-body medicine, biofeedback, and personal health monitoring, we review and discuss empirical work and tracings to express the vital role of bodily rhythms in influencing emotion, autonomic nervous system activity, and even general neural activity. Future developments in measurement and psychophysiological understanding of the pattern of breathing in combination with other parameters such as HRV, cardiorespiratory synchronization, and skin conductivity may allow for biometric monitoring systems to one day accurately predict affective state and even affective disorders such as anxiety. Better affective prediction based on recent research when incorporated into personal health monitoring devices could greatly improve public mental health by providing at-home biofeedback for greater understanding of one's mental state and for mind-body affective treatments such as breathing exercises.

On the Hierarchical Organization of Oscillatory Assemblies: Layered Superimposition and a Global Bioelectric Framework.

Bioelectric oscillations occur throughout the nervous system of nearly all animals, revealed to play an important role in various aspects of cognitive activity such as information processing and feature binding. Modern research into this dynamic and intrinsic bioelectric activity of neural cells continues to raise questions regarding their role in consciousness and cognition. In this theoretical article, we assert a novel interpretation of the hierarchical nature of "brain waves" by identifying that the superposition of multiple oscillations varying in frequency corresponds to the superimposing of the contents of consciousness and cognition. In order to describe this isomorphism, we present a layered model of the global functional oscillations of various frequencies which act as a part of a unified metastable continuum described by the Operational Architectonics theory and suggested to be responsible for the emergence of the phenomenal mind. We detail the purposes, functions, and origins of each layer while proposing our main theory that the superimposition of these oscillatory layers mirrors the superimposition of the components of the integrated phenomenal experience as well as of cognition. In contrast to the traditional view that localizations of high and low-frequency activity are spatially distinct, many authors have suggested a hierarchical nature to oscillations. Our theoretical interpretation is founded in four layers which correlate not only in frequency but in evolutionary development. As other authors have done, we explore how these layers correlate to the phenomenology of human experience. Special importance is placed on the most basal layer of slow oscillations in coordinating and grouping all of the other layers. By detailing the isomorphism between the phenomenal and physiologic aspects of how lower frequency layers provide a foundation for higher frequency layers to be organized upon, we provide a further means to elucidate physiological and cognitive mechanisms of mind and for the well-researched outcomes of certain voluntary breathing patterns and meditative practices which modulate the mind and have therapeutic effects for psychiatric and other disorders.

Multimodal Integration and Phenomenal Spatiotemporal Binding: A Perspective From the Default Space Theory.

How does the integrated and unified conscious experience arise from the vastly distributed activities of the nervous system? How is the information from the many cones of the retina bound with information coming from the cochlea to create the association of sounds with objects in visual space? In this perspective article, we assert a novel viewpoint on the "binding problem" in which we explain a metastable operation of the brain and body that may provide insight into this problem. In our view which is a component of the Default Space Theory (DST), consciousness arises from a metastable synchronization of local computations into a global coherence by a framework of widespread slow and ultraslow oscillations coordinated by the thalamus. We reinforce a notion shared by some consciousness researchers such as Revonsuo and the Fingelkurts that a spatiotemporal matrix is the foundation of phenomenological experience and that this phenomenology is directly tied to bioelectric operations of the nervous system. Through the oscillatory binding system we describe, cognitive neuroscientists may be able to more accurately correlate bioelectric activity of the brain and body with the phenomenology of human experience.

Unraveling the role of genetics in the pathogenesis of diabetic retinopathy.

Diabetic retinopathy (DR) is a microvascular disease of the retina and the leading cause of visual disability in diabetic patients. Genetic factors have shown to play a pivotal role in DR onset, and several candidate genes have been associated with its progression. A literature search was performed to identify the genes known to be associated with DR through linkage analysis, candidate gene association, and genome-wide association studies (GWAS). A further literature search was performed to discover their potential connection with various biological pathways. A total of 65 genes were found and several of these genes belong to major signaling pathways known to play a significant role in DR, including systemic inflammation, angiogenesis, and neurogenesis. A comprehensive analysis presented in this review will be helpful in unraveling the role of genetics in the pathogenesis of DR.

Top Mysteries of the Mind: Insights From the Default Space Model of Consciousness.

Aside from the nature of consciousness itself, there are still many unsolved problems in the neurosciences. Despite the vast and quickly growing body of work in this field, we still find ourselves perplexed at seemingly simple qualities of our mental being such as why we need to sleep. The neurosciences are at least beginning to take a hold on these mysteries and are working toward solving them. We hold a perspective that metastable consciousness models, specifically the Default Space Model (DSM), provide insights into these mysteries. In this perspective article, we explore some of these curious questions in order to elucidate the interesting points they bring up. The DSM is a dynamic, global theory of consciousness that involves the maintenance of an internal, 3D simulation of the external, physical world which is the foundation and structure of consciousness. This space is created and filled by multiple frequencies of membrane potential oscillations throughout the brain and body which are organized, synchronized and harmonized by the thalamus. The veracity of the DSM is highlighted here in its ability to further understanding of some of the most puzzling problems in neuroscience.

Self-Regulation of Breathing as an Adjunctive Treatment of Insomnia.

Sleep is a quiescent behavioral state during which complex homeostatic functions essential to health and well-being occur. Insomnia is a very common psychiatric disorder leading to a myriad of detrimental effects including loss of concentration, memory, and performance as well as disease. Current pharmaceutical treatments can be expensive, impairing, unhealthy, and habit-forming. Relaxation techniques, such as meditation target the brain and body in contrast to pharmaceutical interventions which solely target neurotransmitter systems in the brain. In this article we present a viewpoint on the treatment of insomnia that techniques of slow, deep breathing (0.1 Hz) in adjunct to sleep hygiene and relaxation therapies may be highly effective in initiating sleep as well as facilitating falling back asleep. The autonomic nervous system is integral to sleep initiation, maintenance, and disruption. Understanding the relationship between the autonomic nervous system and sleep physiology along with the nature of sleep itself remains a challenge to modern science. We present this perspective in light of a prevailing "dysevolution" theory on the pathology of insomnia that proposes hyper-arousal characterized in part by chronic sympathetic hyperactivation and/or parasympathetic hypoactivation disrupts normal sleep onset latency, sleep quality, and sleep duration. We additionally discuss physiological mechanisms responsible for the effectiveness of the breathing treatment we describe. A better understanding of these mechanisms and autonomic pathologies of insomnia may provide support for the effectiveness of such techniques and provide relief to sufferers of this health epidemic.