American Society of Intercellular Communication (ASIC) was held in Potomac, Maryland on October 12th-15th, 2022. The hybrid format of this meeting was similar to the previous year, with both in-person and virtual attendees. The vast majority of conference participants attended in person, while remote presenters submitted pre-recorded oral and poster presentations that were shared via Zoom, and live Q&A sessions were held, facilitating dynamic discussions among participants from both modalities.The second annual meeting of the This year’s meeting drew more attendees than the previous year, with 152 participants, and was supported by 11 sponsors, including Alpha Nano Tech, BioTrac, Ceres Nanosciences, Extracellular Vesicles and Circulating Nucleic Acids (EVCNA), Izon, Kimera Labs, Kinetic River, ONI Bio, Particle Metrix, Unchained labs, and Virogny Biosciences. This three-day meeting had 61 talks (47 of which were given in person), a Grant writing workshop, and 33 posters presented during a session on the evening of day two.The meeting started with an informative pre-program NIH workshop moderated by Shilpa Buch  and Amanda Brown (Johns Hopkins University). Several NIH program officers, including Christine Happel  Anna Sadusky , Aniruddha Ganguly , and Martha Lundberg  gave presentations focusing on various funding mechanisms related to extracellular vesicles (EVs) and extracellular RNA (exRNA), research priorities in various subject areas, and several grant writing tips.in vitro was found to be mediated by a long non-coding (lnc)RNA. This work also suggested that astrocyte-derived EVs (ADEVs) may be carriers of senescence cargo which could be taken up by neurons, leading to synaptodendritic injury and neuronal senescence. In vivo evidence showed that morphine-administered mice exhibited an aging phenotype and cognitive deficits. Collectively, these data suggest that lncRNAs may play a role in mediating astrocytic senescence and ADEVs may, in part, mediate synaptodendritic injury associated with aging.This funding-focused session was followed by a series of scientific talks, the first of which was the keynote lecture given by Shilpa Buch , whose talk focused on the role of morphine-mediated astrocytic senescence. Astrocytic senescence induced by morphine The next talk was by Nicole Noren Hooten , which focused on the role of EVs in aging and age-related conditions.Next, Hameeda Sultana (University of Tennessee) presented work on the exosome-mediated transmission of flaviviruses to vertebrate hosts from tick and mosquito saliva. When these insects bite a host, inflammatory and wound healing pathways are activated. Interestingly, these pathways can be modulated by tick-derived salivary EVs delivered to the host at the bite site, and these EVs have the capacity to bind to skin barrier cells, including keratinocytes. Further, tick cells treated under various salt, pH, and temperature conditions release EVs that can modulate viral transmission and replication in human skin cells.Chioma Okeoma (Stony Brook University Renaissance School of Medicine) presented next, focusing on human immunodeficiency virus (HIV) and drugs of abuse, specifically Δ9-THC. Using the simian immunodeficiency virus (SIV) non-human primate model of HIV, it was found that during infection, the basal ganglia release pathogenic EVs associated with neuroinflammation with distinct microRNA (miRNA) profiles. Treatment with Δ9-THC was shown to modulate basal ganglia-derived EV miRNAs, many of which have predicted targets associated with inflammation, immune regulation, and cell death pathways. SIV basal ganglia EVs were also shown to alter astrocytes and microglia, but Δ9-THC exposure reduces these changes.The next presenter was Ursula Sandau , who shared recent data focusing on the relationship between the clinical features of methamphetamine use disorder and EV miRNA profiles. Plasma EVs from humans with active methamphetamine use were found to contain miRNAs that correlated to a number of variables, including frequency of methamphetamine use, age of onset, and lifetime exposure, as well as neuropsychiatric function, , inflammation, and CNS injury compared to healthy controls. These addiction-relevant EV miRNAs could be potential targets for the creation of novel therapeutics for treating methamphetamine use disorders.in vitro, into microglial-like cells. These cells expressed a number of common microglial markers after approximately one week in culture, and several of these markers persisted for three weeks at both the gene and protein levels. Importantly, these cells were cultured under serum-free conditions and expressed CD45, making them ideal candidates for studying both EV biogenesis and HIV infection.Amanda Brown (Johns Hopkins University) gave the next presentation on studying HIV infection by use of human microglial cells. This work demonstrated that bone marrow myeloid progenitor cells could be isolated from adult human blood and differentiated, The next talk was given by Carlos Osterman , which focused on lipid metabolism and prostate cancer. Prostate cancer is the 5th leading cause of cancer-related deaths worldwide and the 1st in Puerto Rico. Prostate cancer tumors undergo shifts in their metabolic profiles, including increased lipid metabolism and fatty acid synthesis, which allows them to escape existing therapies. In this work, cell-based models of prostate cancer therapy resistance were used for metabolic profiling and found that pathways utilized for building fatty acids and lipids were upregulated in these cells. One enzyme, fatty acid synthase, has been shown to be upregulated by cancer progression and metastatic stage. Further, this enzyme was also identified in EVs released by prostate cancer cells. Incubation of EVs derived from drug-resistant prostate cancer cells with macrophages resulted in a shift towards M2 polarization, indicating that these EVs may influence the tumor-immune microenvironment.The next presentation was given by Gurudutt Pendyala . In this work, nanoplasmonics-based single EV analysis was used to identify differences in brain-derived EVs (BDEVs) from mice with acute or chronic methamphetamine use. First, EVs were assessed via quantitative mass spectrometry-based proteomics and revealed distinct profiles for the two substance use paradigms. Then, EVs were analyzed through the nanoplasmonics-based single EV multiplexing platform, which validated the mass-spec proteomic data at the single-EV level. Together, these platforms indicate that specific pathways in the CNS are activated in each of the substance use paradigms.Next, David Greening  presented recent work on the surface proteome of EVs. The membrane surface of an EV (the surfaceome) serves as the fundamental gateway between intra and extracellular signaling networks and dictates an EV’s capacity to communicate and interact with its environment. Understanding the surfaceome of EVs would provide insight into the biodistribution and diagnostic potential of EVs and allow for EV surface engineering to alter things such as uptake by modulating the expression of ligand receptors. Expanding our knowledge of the EV surfaceome will allow for a deeper understanding of EV biology, thereby expanding the utilization of EVs as diagnostic and therapeutic agents.Eva Poveda  gave the next presentation on the role of EVs in inflammation and cardiovascular disease (CVD) during HIV infection. Rates of CVD in people living with HIV (PLWH) tend to be higher than in the uninfected population, and CVD leads to a greater risk of stroke, myocardial infarction, and heart failure. A subpopulation of PLWH known as elite controllers spontaneously control HIV replication without antiretroviral therapy (ART); this can be transient or persistent but offers a model of functional cure. This work showed that plasma levels of EV-associated cytokines are different across a number of different conditions including persistent elite controllers, transient elite controllers, PLWH whose treatment plan includes ART, ART naïve PLWH, and healthy uninfected controls. These EV-associated cytokines may play a role in mediating the activation of inflammatory pathways and controlling HIV replication.The last talk of the pre-program workshop was delivered by Gary Linz (Particle Metrix), who spoke about the importance of tools and technologies used to profile EVs, as there are many considerations that must be taken into account when deciding which type of particle counting platform to utilize for a specific experiment. Good results start with good samples and triplicate measurements should be made for each sample to ensure data accuracy.The evening session was moderated by Julie Saugstad  and Ursula Sandau .The keynote speaker for this session was Thomas Sudhof (Stanford University), who gave a presentation centered on trans-synaptic adhesion molecule signaling and its role in controlling postsynaptic membrane traffic. Extra and intracellular vesicle trafficking is critical for physiology, yet for decades it was not clear how these processes were mediated. Synapsins were thought to be the most important proteins in synaptic vesicles for neurotransmitter release, and a number of highly sophisticated experiments were required to elucidate its mechanism of action. For example, neurons with synapsin-1 deletion have approximately 1/3 fewer synaptic vesicles relative to wild-type neurons, and these neurons cannot sustain synaptic transmission to the same level as wild-type neurons during stimulus trains.in vivo IF EVs from a syngeneic murine cancer model without disrupting the tumor tissue histology. These EVs were found to be different than EVs isolated from in vitro cultured cancer cells, suggesting that the 3D environment affects EV profiles. Further, IF EVs were also found to contain full-length fission mitophagy proteins, indicating that these EVs can lend insight into the status of tumor cell mitochondrial biogenesis and destruction.The next speaker of the evening session was Lance Liotta (George Mason University), whose talk focused on tumor-derived EVs found in interstitial fluid. As tumors increase in size, they exert higher interstitial fluid (IF) pressure, which is relieved via the lymphatics. The IF is rich with tumor-derived EVs, and this work demonstrated a novel approach for extracting The next speaker in this session was Jonathan Geiger (University of North Dakota), who presented work on the endolysosomal stress response. The greater endolysosomal system plays a significant role in various cellular processes, including phagocytosis, antigen presentation and immune responses, cholesterol homeostasis, plasma membrane repair, mitochondrial division, mitophagy, exocytosis, and cell death. Its pathological relevance extends to aging and age-related neurological disorders, HIV-associated neurocognitive disorder (HAND), glioblastoma, and other neurogenerative disorders. Drugs that affect the endolysosomal system have been shown to affect the production, secretion, and content of EVs. Endolysosomes also act as master regulators of iron metabolism, and altering their pH has profound effects. The release of iron from endolysosomes increases iron levels in the cytosol and mitochondria, resulting in oxidative stress and cell death. Modulation of endolysosomal pH and iron release may be early events associated with EV release and may play a key role in the pathophysiology of various neurodegenerative diseases.Jeff Franklin (Vanderbilt School of Medicine) gave the next presentation on the use of large-scale bioreactors for EV and non-vesicular extracellular particle production. Hollow-fiber bioreactors were employed to achieve a 20-fold increase in particle yield compared to traditional 2D cell culture growth. Interestingly, this work showed that EVs generated from hollow-fiber bioreactors and 2D cell cultures had similar proteomes. FPLC purification revealed distinct peaks for exomeres and supermeres, with the first peak containing membrane-associated proteins such as CD63, indicating an EV-enriched fraction. These findings underscore the potential of bioreactors in producing abundant secreted material for a number of applications.The next talk was delivered by Michael Bukrinsky (George Washington University), which focused on EV-associated HIV Nef. The HIV accessory protein, Nef, was found to impact cholesterol metabolism and immune responses in macrophage and myeloid cells. Interestingly, less than 1% of Nef produced by Nef-transfected cells is associated with EVs. Isolation via ultracentrifugation revealed that the majority of Nef released by these cells is in the non-vesicular supernatant. Furthermore, EV-associated Nef was found to be preferentially located on the outside of EVs and is significantly more biologically potent than recombinant Nef.Anaplasma phagocytophilum, which was found to induce EV production in tick cells. Interestingly, A. phagocytophilum type IV effector gene transcripts were found in EVs derived from tick and mammalian cells. These data collectively suggest that A. phagocytophilum infection may alter EV release and composition, and these EVs may be involved in the pathophysiology of infection.Girish Neelakanta (University of Tennessee) next presented work on tick-derived EVs. The prevalence of several tickborne illnesses including Lyme disease, Rocky Mountain spotted fever, ehrlichiosis, and anaplasmosis, are on the rise. Anaplasmosis is caused by the bacterium The next presenter, Xandra Breakefield (Harvard University), shared recent work on EV communication in the brain. Glioblastoma-derived EVs were shown to be taken up by microglia and alter their ability to sense things around them, including the tumor itself and other pathogens. These EVs appear to serve a protective function that prevents the tumor from being detected by microglia. Glioma cells and their released EVs contain high levels of miR-21, and intracranial injection of glioma-derived GFP EVs into miR-21-null mice resulted in the transfer of these EVs to microglia and downregulation of miR-21 target genes. Work from the Breakefield lab further showed that neuron-derived EVs could spread in all directions within the brain and modify the physiologic function of neighboring cells, which has large implications for the role of EVs in the pathophysiology of numerous neurological diseases.N-glycans to RNAs. A number of RNA species have been found to be glycosylated, including small non-coding RNAs. The localization of glycoRNAs is primarily on the cell surface, which presents new opportunities for exploring the involvement of glycoRNAs in exRNA biology.Ryan Flynn (Harvard University) gave the last talk of the evening, which focused on glycoRNAs. The major building blocks of cells can be glycosylated, creating glycoproteins, glycolipids, and glycoRNAs. GlycoRNAs are predominately formed from the attachment of sialylated, fucosylated The morning of the second day of the conference began with a session on heterogeneity and EVs, moderated by Lucia Languino (Thomas Jefferson University) and Heather Branscome .Lucia Languino (Thomas Jefferson University) kicked off this session with a keynote address focusing on the role of pro-tumorigenic EVs in cancer progression. Small EV (sEV) proteomics revealed differentially expressed proteins that are involved in cellular assembly and movement, inflammatory responses, and lipid metabolism. Integrins present in prostate cancer sEVs were shown to be functionally active upon uptake by macrophages and endothelial cells, and push macrophages towards the M2 phenotype, which may promote cellular reprogramming towards a pro-tumorigenic tumor microenvironment.The next presentation was given by Qin Zhang (Vanderbilt School of Medicine) and described the functional role of supermeres. Supermeres are described as extracellular nanoparticles distinct from EVs and exomeres, which can be obtained via differential ultracentrifugation. Exomeres are separated from the supernatant after pelleting EVs, and similarly, supermeres are separated from the supernatant after pelleting exomeres. Supermeres were shown to have unique biodistributions and proteomic and RNA profiles, with clinical diagnostic potential.Uta Erdbrügger  gave the next presentation on the role of EVs in hypertension (HTN). Approximately 1 in 3 Americans have HTN, which is a major risk factor for CVD and kidney disease. These patients have higher levels of circulating EVs, typically of endothelial or leukocyte origin, which correlate with disease severity and may reduce endothelial-dependent vasodilation in resistance arteries. Elevated levels of endothelial-derived EVs are observed as early as two weeks after HTN onset and may be clinically meaningful biomarkers. Further, T-cells have been implicated in the development of HTN, and T cell-derived EVs are also elevated in arterial HTN and correlate with blood pressure levels. EVs from kidney tubules also play functional roles in HTN and have been shown to carry functional units of sodium transporters; urinary EVs containing these kidney-derived EVs may serve as liquid biopsy for HTN as they show changes in protein expression in the kidney over time.13 EVs per week that express the canonical EV markers and are cell fusion competent in culture. Further, these EVs can also be taken up in vivo in a non-human primate model to study biodistribution. Some important questions to consider when studying EV composition are whether EV membranes are homogenous or if they have lipid microdomains; if two tetraspanins can be present on the same EV or if there are just mixed populations of multiple types of EVs; and if two tetraspanins can be located on the same EV, are they present within the same microdomain? CryoEM reveals that EV morphology is mostly round with protein protrusions; super-resolution microscopy (dSTORM) strives to visualize these EVs and the protein composition of their microdomains. dSTORM data shows similar size profiles to nanoparticle tracking analysis, while also revealing that EVs have local membrane domains through fluorescent labeling of the EV membrane and the CD81 tetraspanin. While the technological advances in this area are encouraging, more work is needed to allow for the delineation between multiple proteins on the surface of a single EV.Next, Dirk Dittmer (University of North Carolina Chapel Hill) presented recent work on the use of super-resolution imaging of single EVs and their protein components. Using a four-step EV isolation pipeline, Dr. Dittmer’s group can generate approximately 10Setty Magana (Nationwide Children’s and Ohio State University) shared recent work on the role of EVs and non-coding RNAs in multiple sclerosis (MS) across the lifespan. MS onset typically occurs around 20-40 years of age, but 3%-10% have childhood or adolescent onset, termed pediatric MS; this leads to earlier and higher relapse rates, early cognitive impairment, and brain atrophy. While there is shared pathophysiology between pediatric and adult MS, adult observations cannot be extrapolated to pediatric cases. Although the etiology is unknown, obesity and elevated body mass index (BMI) in genetically susceptible individuals are associated with an increased risk of developing pediatric MS. Adipose-associated cytokines (adipokines) and chronic low-grade metabolic inflammation are implicated in both pediatric and adult MS, and adiponectin positive EVs were detected in the serum from both MS patient populations. Interestingly, these EVs had distinct miRNA profiles between active and stable MS, as well as adult versus pediatric MS, with some identified miRNAs implicated in blood-brain barrier dysfunction. There is a need for the development of a precision neuroimmune EV-omics pipeline that would allow for biomarker discovery and individualized therapeutics.in vivo mouse experiments which show that EVs administered subcutaneously after a punch wound have healing abilities in a dose-dependent fashion. Further, the functional effects of EVs on 3D cellular models of repair are also being studied.The next speaker was Heather Branscome , who spoke about large-scale EV manufacturing and its functional assessment. There is a strong need for EV reference materials, and ATCC has vesicles from both cancerous, non-cancerous, and stem cell lines that are available to the research community. Their EV manufacturing pipeline is highly reproducible with low lot-to-lot variability, robust quality standards, and high EV stability for up to 3 years. Interestingly, cancer and stem cell-derived EVs were profiled and were shown to have overlapping proteomes, but differential mapping of RNA to chromosomes. The functional properties of these EVs have also been studied with in vivo biodistribution studies show uptake of all three in various organs. Distant primary tumors were shown to alter liver metabolism in multiple murine models, and interestingly, tumor-derived nanoparticles were shown to contribute to fatty liver generation and decreased drug metabolism in the liver. However, ablation of Rab27a diminishes tumor-induced fatty liver formation.Haiying Zhang (Cornell University) gave the next presentation on the identification of distinct subsets of EVs and other nanoparticles and their role in cancer. Asymmetric flow field-flow fractionation (AF4) is a technique for separating EVs and from fluids; in this work, a heterogeneous sample was separated via AF4 and revealed three distinct populations of extracellular nanoparticles: exomeres (< 50 nm), small exosomes (50-80 nm), and large exosomes (90-120 nm). Proteomic analysis showed differences in protein expression in the three nanoparticle subsets, and The last speaker of this session was Leif Anderson (Unchained Labs), who spoke about the ExoView EV characterization platform, which analyzes single vesicles to provide data on size, concentration, and tetraspanins profiles. Fluorescent measurements allow for multiplex analysis of samples and the identification of single proteins on single EVs. EV concentrations and subpopulations can be profiled based on the number of events bound to a specific antibody spot on the ExoView chips and up to five biomarkers can be simultaneously assayed at the same time. Captured vesicles can also be permeabilized to allow researchers to determine if specific proteins are on the inside or outside of the EV.The second morning session was on EVs and the CNS and was moderated by Avi Nath (NIH) and Norman Haughey (Johns Hopkins University).The keynote speaker for this session, Julie Saugstad , gave a presentation focusing on the effects of APOE genotype and sex on cerebrospinal fluid (CSF) EVs in Alzheimer’s disease (AD). AD is the most common form of dementia and affects 6.2 million Americans over the age of 65. While the etiology of AD is unknown, mutations in the apolipoprotein E-e4 (APOE4) variant may play a key role in the development and pathophysiology of the disease. By the time AD is discovered, it is too late, and there are currently no effective therapies to treat AD; as such, there is a massive need for early diagnostic biomarkers and therapeutic interventions. Currently, increases in CSF amyloid beta-42 (Aβ42) levels with concurrent decreases in tau can sometimes be used as a diagnostic tool for identifying AD, but better biomarkers are needed. miRNA profiling from CSF revealed 36 miRNAs that differentiate AD from control patients, with slight increases in performance when APOE4 genotype and Aβ 42:tau ratio are also considered. The longitudinal stability of miRNAs is also being considered, as patients typically present with mild cognitive impairment (MCI) prior to progressing into AD, and being able to predict which patients will progress to AD has high clinical relevance. Understanding the plasma profiles of potential miRNA biomarkers is also extremely important because plasma is much easier to obtain than CSF. CSF EV miRNAs were also profiled and found AD-associated miRNAs in EVs, and when sex is considered, differential expression of specific miRNAs is observed in males versus females. Future work aims to characterize EV surface proteins in AD and other neurodegenerative diseases and better understand how the expression of various AD-associated miRNAs is regulated.in vitro with primary microglia and siRNA. When microglia are stimulated with ATP or lipopolysaccharide (LPS), they are transformed into a proinflammatory state and release EVs. However, siRNA-based silencing of several genes inhibited ATP/LPS-induced EV release from microglia. These genes may be important targets for reducing microglial-EV tau propagation in diseases like AD.The next speaker for this session was Tsuneya Ikezu (Mayo Clinic Florida), who shared recent work on microglial EVs. Following the tau propagation mechanism, these microglial EVs have been shown to spread tau pathology in AD. As extracellular aggregates of Aβ negatively impact synapse function, microglia begin to take up tau and release it in EVs and spread disease pathology in the AD brain. To identify genes necessary for microglial EV release, the Ikezu lab performed a genome-wide screen from cultured murine microglia and validated potential targets Travis Thompson  presented next on the potential role of EVs in the regulation of synaptic plasticity. A large majority of the genome appears to be viral-like and contains retrotransposons. In the drosophila, the neuromuscular junction is a tractable interface and the pre- to postsynaptic transfer of dArc1 retrotransposon-like transcript can be observed. The transfer of which behaves like a capsid and the 3’ UTR is necessary and sufficient for transfer. The transposon, Copia, is also present in neuromuscular junction EVs. If it is knocked down, the synapse is expanded and about 50%-60% more synaptic boutons are formed; however, they are abnormal. Interestingly, there appears to be a balance between dArc1 and Copia in that the knockdown of one results in the upregulation of the other. They also appear to be mutually exclusive in EVs; understanding the expression of these two genes and how they affect synaptic plasticity warrants further investigation.The next presenter was Gagan Deep (Wake Forest School of Medicine), whose work focused on plasma BDEV-miRNAs. Many studies have focused on total or neuron-derived EVs, but other BDEVs may play important roles in disease pathology and may serve as blood-based biomarkers for AD. Total EVs were isolated from blood plasma and further separation based on protein markers associated with specific cell types  was performed. Several miRNAs associated with pericyte and endothelial-derived EVs were able to distinguish control, MCI, MCI conversion to AD, and AD with high accuracy, suggesting vascular impairment may be implicated in these diseases.Norman Haughey (Johns Hopkins University) gave the last presentation of the morning; this talk focused on the clearance of Aβ into peripheral circulation, which activates an innate immune response and induces leukocyte transmigration into the brain. ADEVs released in response to IL-1β or ATP stimulation alter the functionality of recipient neurons by promoting the translation and amyloidogenic processing of amyloid precursor protein. Interestingly, these ADEVs can leave the CNS and communicate with the periphery, which may indicate a mechanism through which the brain signals inflammation. For example, in a mouse model of AD (APP/PS1), total brain EVs are reduced, while circulating plasma EVs are increased.The first afternoon session was a continuation of talks focusing on EVs and the CNS and was moderated by Dirk Dittmer (University of North Carolina Chapel Hill) and Ramin Hakami (George Mason University).in vitro model. The SARS-CoV-2 spike protein itself can cause endothelial damage, while viral RNA can induce a proinflammatory response. The spike protein and viral RNA appear to persist in the circulation of PASC patients, and circulating sEVs from these patients were found to have the spike protein present on their surface.The keynote speaker for this session was Navneet Dhillon , who gave a presentation on circulating EVs in long COVID-19. Post-acute sequelae of COVID-19 (PASC), commonly referred to as ‘long-COVID’, occurs in a subset of patients and has a wide range of symptoms, but key physiological changes that occur after COVID-19 infection including endothelial injury, vascular remodeling, and coagulopathy, likely participate in PASC pathogenesis. As EVs play major roles in inflammatory responses and regulation of vascular function, it is likely that they are implicated in PASC. EVs isolated from asymptomatic, moderate (no oxygen), moderate (oxygen), and severe COVID-19 patients revealed higher levels of proinflammatory, thrombosis, and coagulation markers in sEVs from severe COVID-19 patients. EVs from critically ill patients also induce pulmonary microvascular endothelial injury in an The next presenter of this session was Sowmya Yelamanchil , whose talk focused on the role of mitochondrial-derived vesicles (MDVs) in HAND. MDVs, also termed mitovesicles, are heterogenous and may play key roles in mitochondrial quality control and allow for crosstalk between organelles within a cell. MDVs were isolated and characterized from the brains of a transgenic rat model of HIV and found reduced expression of mitochondrial complex proteins in the transgenic MDVs relative to controls. It is possible that these MDVs reflect pathological changes in mitochondria or that they themselves may contribute to disease pathology.In vitro experiments demonstrate that sEVs from ischemic cerebral endothelial cells (CECs) deliver miRNAs to neural stem cells (NSCs) and enhance their proliferation and differentiation. NSC-EVs increase capillary tube formation and migration of recipient CECs by transferring miRNAs. Interestingly, inhibition of EV release impairs miRNA transfer, both from CEC-EVs to recipient NSCs and from NSC-EVs to recipient CECs. Further, in an animal model CEC-EVs cross the blood-brain barrier and improve post-stroke recovery as assessed via several behavioral assays.Xian Shuang Liu  gave the next talk on the role of sEVs and their miRNAs on post-stroke neurogenesis and angiogenesis. Stroke-induced angiogenesis is coupled with neurogenesis and contributes to spontaneous functional recovery as neuroblasts migrate along blood vessels to reach peri-infarct regions of the brain. in vivo versus in vitro. In the brain, cells and their released EVs interact with other populations of neighboring cells, whereas in culture, the extracellular environment is less enriching. To better understand EV dynamics in vivo, a transgenic CD81NeonGreen mouse line was crossed with a transgenic dopamine mouse line so that EVs from dopaminergic neurons could be monitored. Super-resolution microscopy revealed EVs in the ventral tegmental area, which is part of the reward pathway; when nicotinic receptors on the surface of the presynaptic terminal were activated with nicotine, an increase in EV release was observed.Next, Christie Fowler  presented work on the characterization of EV release in the prefrontal cortex and nucleus accumbens. There are inherent differences between the way cells and the EVs they release interact The last speaker for this session was Navneet Dogra (Icahn School of Medicine at Mount Sinai), who shared recent work on characterizing the neurosecretome. Brain tissue was gently dissociated and EVs were isolated from the extracellular space via SEC. Each fraction was profiled based on its size and protein concentration to determine which fractions likely contain cellular debris and microvesicles, sEVs, and extracellular proteins, nucleic acids, and nucleic proteins. Diverse RNA profiles show distinct clustering of extracellular proteins and nucleic acids, sEVs, and cell debris.The second afternoon session of Day 2 was on Cancer and EVs and was moderated by Lance Liotta (George Mason University) and Meta Kuehn (Duke University).The keynote speaker for this session was Aurelio Lorico (Touro University Nevada), who presented work on targeting spathasome-based nuclear transport for cancer and viral therapy. Rab7+ late endosomes come together with nuclear envelope invaginations (NEIs) to form spathasomes, which are newly discovered cellular organelles that deliver biological information from EVs to the nucleus. Both HeLa and T cells typically have round nuclei; however, after exposure to HIV or EVs, NEI is activated, likely to deliver cargo to the cell’s nucleus. Endosomes arrive at the NEI and interestingly have different NEIs depending on what they were exposed to, and the type of NEI that is formed correlates with productive infection. The molecular interactions between late endosomes and NEIs rely upon the VOR complex, VAP-A, ORP3, and Rab7, allowing tethering of the late endosome to the NEI. Interestingly, the knockdown of VAP-A or ORP3 inhibits the transport of CD9 to the nucleus.Diloram Sass  presented next on the use of EVs as biomarkers of clinical outcomes in cancer and brain injury survivors. EVs are being utilized as prognostic tools for cancer and neurodegenerative diseases, but very few groups utilize EVs as potential biomarkers of clinical outcomes, especially patient-reported outcomes. Hierarchical clustering revealed differential expression of some protein markers in the soluble versus EV fraction from cancer patients. Further, EV-associated cytokines correlated with symptom burden reported by these patients. EVs isolated from traumatic brain injury patients with post-traumatic stress disorder revealed higher levels of neurofilament light chain, further suggesting that patient-reported outcomes correlate with differences observed in EV profiles.in vitro, relative to uptake by other PDAC cells and normal epithelial and endothelial cells. EV uptake can also be monitored in vivo by using the PalmGRET reporter in a mouse model of PDAC to determine which cells in the tumor microenvironment take up PDAC EVs.Next, Jennifer Finan  spoke about pancreatic ductal adenocarcinoma (PDAC) EVs. Two major struggles with PDAC are early detection and response to therapy; typically, by the time the cancer has been detected, it is too late for effective therapy. This cancer is supported by noncancerous cells in the tumor microenvironment, and these cells have been shown to uptake PDAC EVs, which may induce a pro-tumorigenic phenotype. Cancer-associated fibroblasts were especially shown to uptake PDAC EVs Olivier Loudig (Center for Discovery and Innovation) was the next speaker in this session and presented novel findings on exhaled EVs (exh-EVs). EVs present in breath condensate exhaled from the lungs may provide important information about the health and physiology of the lung. Within just 10 minutes of breathing, 2 mL of liquid can be obtained with a specialized device. Various techniques for isolating these EVs were utilized, and it was found that magnetic beads hinder the discovery of circulating sEV-based miRNA biomarkers and non-specifically capture EVs. Instead, a novel method was developed termed EV-CATCHER(Extracellular Vesicle Capture by AnTibody of CHoice and Enzymatic Release) to capture EVs from the exhaled breath condensate. These exh-EVs have significant potential to serve as biomarkers for the detection of lung cancer, as differences in miRNA profiles were detected relative to healthy age-matched controls.The next presenter was Bojan Losic , who gave a talk focusing on the use of unannotated small RNA clusters in circulating EVs as biomarkers for early-stage liver cancer. Hepatocellular carcinoma (HCC) is the most dominant form of liver cancer and can be caused by chronic hepatitis and cirrhosis and patients with these conditions are good candidates for surveillance. Small RNA in plasma EVs sequencing reveals that most hg38 alignments tile to unannotated loci; therefore, the strategy was to utilize data-driven small RNA gene quantitation to classify and identify EV RNA de novo alignment patterns. Small unannotated RNAs are strongly expressed in high-risk patients, and this unannotated EV RNA signature performed better than the current clinical standard in early HCC detection. Additionally, a new point-of-care liquid biopsy platform was developed to quickly quantify EV RNAs from low-volume clinical samples to help identify HCC patients.Xiaoli Yu  presented next on glioblastoma EV-specific peptides. Glioblastoma is the most common and lethal primary brain tumor and its diagnosis relies on imaging and postoperative pathological diagnosis. Proteomic analysis revealed that glioblastoma EVs possess unique features, and the use of an unbiased approach for EV identification may provide a way to see the surface of EVs that do not necessarily express the typical tetraspanins. Glioblastoma EVs derived from patient plasma as well as from a cell line were shown to kill neuronal cells. Interestingly, when specific peptides were blocked, EV-induced neuronal death was inhibited.The last presenter for this session was Guoku Hu , who shared recent work on ADEVs and their effects on neuronal primary cilia in morphine tolerance. Opioid overdose is the leading cause of accidental death and opioid tolerance increases the risk of overdose death. The primary cilium is a singular organelle within cells that can detect extracellular cues and play a role during development and tissue homeostasis. Interestingly, changes to the primary cilia number and length have been implicated in drug resistance in cancer, and morphine exposure promotes primary ciliogenesis in neurons. Morphine exposure also increases the release of EVs from astrocytes, and these morphine-induced ADEVs promote primary ciliogenesis in neurons. Interestingly, inhibition of EV release or primary ciliogenesis prevents morphine tolerance in mice.At the conclusion of this session, an NIH grant writing workshop facilitated by Fatah Kashanchi (George Mason University), Avi Nath (NIH), and Philip Askenase  was held. This workshop focused on how the grant review process typically proceeds and had an interactive component in which participants worked to write a specific aims page as a group during the session. The grant writing workshop was followed by a poster session.The morning of the third day of the conference began with a session on Infectious Diseases and was moderated by Christie Fowler  and Sowmya Yelamanchil .The keynote speaker for this session was Meta Kuehn (Duke University), who presented work on cargo selectivity of bacterial EVs. Both gram-positive and gram-negative bacteria produce EVs with a wide variety of functions, determined by their wide variety of cargo, which can be impacted by changes in environmental conditions. Additionally, the SigmaE stress pathway can also alter EV release and cargo composition by preferentially packing specific proteins into EVs. Further, the physical tethering of various proteins can also play a role in whether a protein is incorporated or excluded from an EV. Mechanisms of cargo enrichment and sorting can further our understanding of both general biology and application-based research.Ramin Hakami (George Mason University) gave the next presentation on the regulation of EV release during infection with cytoplasmic RNA viruses. Rift Valley fever virus (RVFV) is an endemic RNA virus that is predominately located in Sub-Saharan Africa and is typically transmitted via mosquito bites. This disease results in hemorrhagic fever, neurological impairments, blindness, and liver failure. Cells infected with this virus produce both EVs and viral particles, which can be separated with density gradient centrifugation. Cells pretreated with EVs isolated from cells infected with RVFV and then infected with the virus had reduced viral loads, indicating a protective effect from these EVs. It is hypothesized that this antiviral effect is mediated through the IFN pathway and activation of autophagy.The next presentation was given by Jay Debnath , whose presentation focused on the role of autophagy in EV cargo selection and release. Autophagy involves the activation of LC3/ATG8 proteins, and LC3 plays an important role in capturing cargo to package into autophagosomes. Activation of the secretory autophagy pathway leads to the incorporation of proteins lacking an N-terminal ER signal sequence into autophagosomes, which are then released from the cell, as opposed to fusing with the lysosome. The LC3-dependent EV loading and secretion (LDELS) pathway enables secretory autophagy through EVs, primarily carrying RNA binding proteins and endosomal transmembrane proteins such as the transferrin receptor. Interestingly, inhibition of lysosomal acidification promotes the release of EVs and/or particles through the secretory autophagy during lysosome inhibition (SALI) pathway. LEDLS and SALI are two distinct secretory autophagy pathways that can result in EV release from cells.Sergey Iordanskiy  presented next on recent work focusing on the impacts of endogenous retroviruses on macrophage differentiation and their effect on bystander cells. Activation of monocytes and macrophages under conditions of stress leads to an increase in the expression of IFN-1, interferon-stimulated genes, chemokines, and proinflammatory cytokines, and some of these cytokines are localized in EVs. Exposure to radiation-induced stress, pathogen-associated molecular patterns, and cytokines upregulates transcription of several human endogenous retroviruses in monocytes and macrophages. These human endogenous retroviruses may then amplify the inflammatory response in these cells and mediate changes in the EVs they release.Next, Yisel Cantres-Rosario  gave a presentation on the association of soluble insulin receptor levels in plasma EVs and HAND. Diabetes and insulin resistance are common comorbidities for PLWH, and these metabolic disorders are associated with an increased risk of neurocognitive impairment and dementia. PLWH who have symptomatic cognitive impairment have elevated levels of soluble insulin receptors in plasma and CSF relative to PLWH who are not cognitively impaired, as well as HIV- controls. Interestingly, BDEV levels are elevated in the plasma of PLWH and correlate with EV-associated reactive oxygen species.The last talk of this session was given by Nazar Filovio (Alpha Nano Tech), which focused on the isolation and characterization of EVs. Commercially available standards may be a useful tool for researchers to implement in their experiments to aid in quality control.The second morning session entitled “Technology and Therapeutics” was moderated by Ashley Russell (Penn State Erie) and Sergey Iordanskiy .The keynote speaker for this session was David Walt , whose talk focused on ultrasensitive digital technologies for measuring EVs. The overarching goal of this work is to identify EVs from any tissue or organ by capturing them on a magnetic bead with a capture antibody, then utilizing detector antibodies to probe for the presence of specific proteins on the captured EV. Additionally, if vesicles are treated with proteinase K to remove all extracellular/surface proteins, the vesicles can then be burst, and their internal cargo assessed. The single molecule array assay allows individual EVs to be captured and assessed at the single-molecule level. Through this, it was found that Ras is a universal protein in circulating EVs and is highly enriched in the plasma of pancreatic cancer patients compared to healthy controls. This new technology holds promising diagnostic potential for a number of diseases through the assessment of single EVs.The next talk was given by Reka Haraszti , whose presentation focused on the use of sEVs for the delivery of siRNA to neurons and immune cells. Cholesterol’s hydrophobic properties play a crucial role in anchoring siRNA to EV membranes. Conjugating siRNA to lipids enables efficient incorporation into EVs, making them promising carriers. EVs over or underloaded with siRNA do not have strong effects on target mRNAs in recipient cells; approximately 3,000 siRNAs per EV seems to be the ideal amount for loading and delivery. Cells that are stressed via serum starvation release EVs with altered protein and lipid compositions and are better at delivering siRNAs than EVs derived from non-stressed cells.Elena Batrakova (University of North Carolina at Chapel Hill) gave the next talk on the development of biomimetic drug delivery systems for the treatment of neurodegenerative disorders. EVs are thought to be natural drug carriers that enable long-distance intercellular communication by facilitating the transfer of proteins and functional nucleic acids with high stability and biocompatibility and low toxicity. As such, EVs can deliver drug-loaded nanoparticles to recipient cells very efficiently. The route of administration is an important consideration when determining how to administer EVs, as intrathecal, intraperitoneal, intravenous, and intranasal all result in slightly different uptake patterns throughout the body. For example, intranasal administration of EVs in mice resulted in greater uptake in the brain relative to intravenous administration, while intrathecal administration of EVs in non-human primates resulted in greater CNS uptake compared to intraperitoneal and intravenous administrations. Interestingly, intrathecal administration of peripheral blood mononuclear cells into the non-human primate model resulted in more CNS uptake than the EVs.Next, Chulee Choi (ILIAS Biologics Incorporated) shared recent advances in the development of new strategies for loading cargo into EVs and compared various techniques, including passive loading, anchored cargo loading, and non-anchored cargo loading. Using a Cre-based reporter system, it was found that non-anchored Cre loaded into EVs resulted in the highest amount of biodistribution relative to anchored Cre. Surface engineering of EVs was also found to enhance the targeted delivery of EVs to specific tissues.Yuntao Wu (George Mason University) presented next on the involvement of the actin cytoskeleton in viral and EV uptake. The actin cytoskeleton plays a fundamental role in cells by providing structural support, facilitating cell movement, and participating in various cellular processes. Viral infection can trigger remodeling of the cortical actin underlying the cell’s surface and promote viral entry into the cell. For example, the knockdown of ARP2/3 impairs HIV-1 viral uptake, while actin-stimulating peptides can promote HIV-1 infection. These principles can also be applied to the cellular uptake of EVs and warrant further study.The last presentation of the conference was given by Jia Wang (Oxford Nanoimaging), who shared information on the ONI Nanoimager. This equipment allows for super-resolution imaging of both live cells and EVs on the benchtop. Its four lasers allow for multiplex analysis and imaging of EV biogenesis, release and transport, uptake, and assessment of EV cargo.The session concluded with a prize distribution ceremony for the best oral & poster presentations. The recipients of the best oral presentations were Navneet Dogra (Icahn School of Medicine at Mount Sinai), Carlos Diaz-Osterman , and Ursula Sandau . The best poster presentation awards went to Sameh Almousa (Wake Forest School of Medicine), Tzu-Yi Chen (Icahn School of Medicine at Mount Sinai), Edgar Gonzalez-Kozlova (Icahn School of Medicine at Mount Sinai), and Sarah Baker . Aurelio Lorico (Touro University Nevada) received an award for the most innovative talk award.in vivo were also heavily discussed. The clinical translational potential of EVs was highlighted at this meeting, with several presentations focusing on the use of EVs as biomarkers for neurodegenerative disorders and various cancers, as well as their use as engineered drug delivery vehicles. Overall, this meeting provided a space for EV enthusiasts to share novel, exciting work, exchange ideas, and forge new collaborations with the hopes of paving the way for future advancements in our understanding of basic and translational EV biology.The meeting provided an informative and comprehensive overview of the EV field, with work spanning from cell culture and animal model-based studies to cutting-edge clinical research. Notably, advancements in understanding the mechanisms by which EV biogenesis, cargo loading, and uptake are controlled were a common theme throughout the meeting. Additionally, state-of-the-art techniques for visualization and characterization of EVs at the single EV level, as well as their biodistribution ASIC would like to thank the Organizing Committee for organizing this meeting, especially given the continued use of the hybrid format, which allowed for enhanced scientific exchange. Special thanks are also extended to Gwen Cox for her commitment to ensuring this meeting ran smoothly.


Obesity is a multifactorial disorder that is remarkably heterogeneous. It presents itself in a variety of phenotypes that can be metabolically unhealthy or healthy, associate with no or multiple metabolic risk factors, gain extreme body weight (super-responders), as well as resist obesity despite the obesogenic environment (non-responders). Progression to obesity is ultimately linked to the overall net energy balance and activity of different metabolic fluxes. This is particularly evident from variations in fatty acids oxidation, metabolic fluxes through the pyruvate-phosphoenolpyruvate-oxaloacetate node, and extracellular accumulation of Krebs cycle metabolites, such as citrate. Patterns of fat accumulation with a focus on visceral and ectopic adipose tissue, microbiome composition, and the immune status of the gastrointestinal tract have emerged as the most promising targets that allow personalization of obesity and warrant further investigations into the critical issue of a wider and long-term weight control. Advances in understanding the biochemistry mechanisms underlying the heterogenous obesity phenotypes are critical to the development of targeted strategies to maintain healthy weight. The prevalence of obesity worldwide has increased in the last several decades indicating a global obesity trend . BetweenBMI, however, is a simple and convenient index to monitor the obesity that overlooks the remarkable heterogeneity of obesity when people with similar body weights or BMI can present with different sets of metabolic risk factors and comorbidities despite similar stratifications . This heThe variety of individual responses to obesogenic environment and the onset of obesity and their relationship to various health outcomes are not fully understood. Apart from the compounding genetic and lifestyle variables, two parameters are considered as the main contributors to an individual’s response to obesity: metabolic perturbations in visceral fat alongside ectopic accumulation of fat in the liver and enhanced inflammatory responses associated with visceral fat activation. Our understanding of the altered cellular metabolism, often driven by mitochondrial dysfunction to produce metabolic disparity, which in turn influences inflammation and energy balance in the metabolically active tissues, is critically lacking. These areas are the focus of the present review. Adipose weight gain may appear at any age with certain trends in different age groups, including children, adolescents, and adults, with differences between genders . It is mProgression to obesity is ultimately linked to the overall energy balance of the body when energy intake (EI) exceeds energy expenditure (EE) . The excAn important factor in the control of body weight is dietary energy density (DED) as it correlates with increase in body weight . Energy Even though twin studies suggested significant heritability for the amounts of foods and fluids ingested, short-term energy intake appears to be unregulated and varies spontaneously within a relatively wide range . HoweverThe second major variable in the relationship of obesity with energy imbalances is energy expenditure . Daily eEnergy expenditure was found in the reciprocal compensatory adaptation loop with dietary intake . First, Typical variance in individual body weights is very small over both short-term (0.5% over 6–10 weeks) and long-term, even when associated with chronic metabolic disorders (3–4% over 5 years) . The obsSuch a nearly precise control of body weight over long periods of time then questions the notion that the onset and progression to obesity are major disturbances of metabolic homeostasis. The emerging evidence suggests that the primary inability to maintain weight is linked to the rate of replacement of energy lost due to caloric restriction (dieting) or increased physical activity (expenditure). In obese states, the reduction of caloric intake was not compensated only when low-energy dense foods were consumed . In otheAs such, a variety of fasting forms and food restriction practices will be effective for promoting initial weight loss  but willHuman subjects spending several days in the metabolic chambers typically show low variations in energy expenditure (2%) and high variations in food intake (20%) , thus poThree macronutrients found in all foods in different proportions have different efficiencies of nutrient utilization, with different fats (2–3%), carbohydrates (6–8%), and proteins (25–30%) associated with energy losses due to differences in their metabolism and storage . DigestiThe macronutrient capacity to promote satiety follows a similar pattern (protein > carbohydrate > fat), with fats typically more likely to promote overconsumption of energy and the subsequent weight gain. However, subjects with increased capacity to oxidize fat appear to gain little weight under these conditions and therefore, present with a non-responder phenotype . A hiddeOne of the key substrates that connects utilization of macronutrients is oxaloacetate, a Krebs cycle intermediate. Oxaloacetate is typically regenerated within the Krebs cycle; however, this molecule forms a core metabolism node that connects to gluconeogenesis and the regeneration of glucose in the liver from non-carbohydrate substrates, such as amino acids and glycerol, during prolonged fasting or diabetes . When diSeveral Krebs cycle metabolites can exit mitochondria, including citrate and malate. Plasma citrate levels are typically elevated in obesity, and inhibition of the mitochondrial citrate carrier, Slc25a1, reverts steatosis, glucose intolerance, and inflammation in metabolic disorders . CitrateTo better understand how macronutrients interact to maintain a stable body weight, we need to evaluate the typical energy stores available to the body and how newly ingested energy is partitioned into these stores . In healIn contrast, dietary fat is primarily targeted for deposition. This is achieved via a series of hydrolysis and re-esterification steps during which triglycerides are broken down to free fatty acids and glucose in the intestine, reassembled in the intestinal cells, secreted into the mesenteric lymphatic system, hydrolyzed on the surface of the epithelial cells of the adipose tissue capillaries, and re-esterified once again when they enter adipocytes for storage . InsulinWhen compared with fat energy reserves typically available to the body , short-tAdipose weight gain may appear at any age with certain trends in different age groups, including major developmental shifts, such as puberty, adolescence, pregnancy, menopause, and normal physiological aging. Adipose tissue tends to increase in middle age and decrease in the elderly, and this change is often accompanied by fat redistribution from subcutaneous tissue to abdominal and ectopic locations . The widUnequal distribution of the adipose tissue among individuals paired together with different levels of ectopic fat deposition and inflammatory dysregulation add another level of complexity to homeostatic control of the body weight . DiffereThe major striking difference between individual fat depots is observed in the subcutaneous versus visceral  adipose tissue, where transplantation of the subcutaneous fat into the visceral cavity improves body weight, adiposity, and carbohydrate metabolism but not vice versa . Increas2 = 0.737, p < 0.001) and the one for exercise was modest  [Both dietary change and aerobic exercise  were correlated with weight loss and preferential loss of visceral fat; however, the correlation for diet was strong (R< 0.001) . This ef< 0.001) . Prolong< 0.001) . The subsequent failures of subcutaneous and visceral fat to increase lipid storage capacity under the conditions of excessive energy reserves culminates in ectopic partitioning of fat to other organs and tissues, such as muscle and liver. Excess fat can be deposited intracellularly in the form of triglycerides as observed in liver hepatocytes under the condition of the nonalcoholic fatty liver disease (NAFLD) or alternatively deposited into newly developed adipocytes that infiltrate the parenchyma of other organs, such as pancreas . SubsequLocal paracrine affects the visceral cavity as expected for mesenteric, pararenal, and epicardial fat depots and could be partially responsible for detrimental metabolic effects associated with the expansion of visceral fat; however, they remain virtually not explored. Direct and potentially continuous delivery of gluconeogenic substrates , such asThe reduced capacity to oxidize fatty acids in the muscle due to disturbances in mitochondrial metabolism (metabolic inflexibility)  is one oSomewhat surprising, lactate derived from anaerobic glycolysis showed the major contribution to metabolic fluxes through the Krebs cycle in all tissues except the brain  Table 2Table 2. Dietary factors, the intestinal microbiota that partially digests them , and the9–1012 CFU/mL [Firmicutes (104), Bacteroidetes (29), Proteobacteria (22), Actinobacteria (12), Fusobacteria (2), Verrucomicrobia (1), and Euryarchaeota (1) [Lentisphaerae, Spirochaetes, Thermotogae, Synergistetes, Tenericutes, Elusimicrobia, and Cyanobacteria [The human body hosts a complex community of microorganisms, such as bacteria, fungi, protozoa, and viruses, that makeup the microbiome. The gastrointestinal microbiome is dominated by bacteria, the majority of which inhabit the colon at a concentration range of 10eota (1) . Trace pbacteria . As gut bacteria .Age, race, geographical location, and ethnicity often present with variations in gut microbiota, which are larger than interpersonal differences and may be attributed to dietary patterns, food composition, and its availability . The majBacteroides, Alistipes, and Bilophila. Both obese ob/ob mice as well as obese human subjects had marked reductions in Bacteroidetes and compensatory increases in Firmicutes, thus showing abnormal Bacteroidetes/Firmicutes ratios [Bacterial fermentation of complex carbohydrates as a part of plant-based dietary patterns that are especially evident in vegetarian or vegan diets contributes to lower pH levels of the intestinal lumen and feces . Healthys ratios . In the s ratios .Metabolic fates of different short-chain fatty acid metabolites are different, suggesting that certain microbiome profiles and host–microbiome interactions may be more beneficial than others. While bacteria-derived butyrate has a rapid turnover flux similar to 3-hydroxybutyrate and are mostly consumed in situ to support colonic epithelium, propionate is targeted by the liver into the gluconeogenesis pathway, and acetate feeds into lipid metabolism . LikewisInflammatory cells that infiltrate the hypertrophic adipose tissue find themselves in the ischemic environment that promotes their polarization towards pro-inflammatory states. Both lipid-overloaded adipocytes and associated inflammatory cells provoke insulin resistance  in an efInflammation of the adipose tissues promotes de novo lipogenesis, reduces fat oxidation in mitochondria, and accumulates ceramides and diacylglycerides in the metabolically active cells that inhibit insulin signaling . SimilarThe etiology of obesity is very complex, with individual genetic, metabolic, microbiome, and lifestyle factors defining multiple pathophysiological states of this disorder. To achieve and sustain meaningful weight loss as well as support individuals with different obesity types, we need to understand the molecular mechanism behind this classification. Variations in fatty acids oxidation, metabolic fluxes of different energy substrates with a particular focus on pyruvate-phosphoenolpyruvate-oxaloacetate node, high turnover rates of lactate, and extracellular accumulation of Krebs cycle metabolites, such as citrate, emerged as the most promising metabolic targets that allow personalization of obesity and warrant further investigations. The additional modulation of gut microbiota  and brai


Introduction: Multiple tools have been developed for facial feature measurements and analysis using facial recognition machine learning techniques. However, several challenges remain before these will be useful in the clinical context for reconstructive and aesthetic plastic surgery. Smartphone-based applications utilizing open-access machine learning tools can be rapidly developed, deployed, and tested for use in clinical settings. This research compares a smartphone-based facial recognition algorithm to direct and digital measurement performance for use in facial analysis. Methods: Facekit is a camera application developed for Android that utilizes ML Kit, an open-access computer vision Application Programing Interface developed by Google. Using the facial landmark module, we measured 4 facial proportions in 15 healthy subjects and compared them to direct surface and digital measurements using intraclass correlation (ICC) and Pearson correlation. Results: Measurement of the naso-facial proportion achieved the highest ICC of 0.321, where ICC > 0.75 is considered an excellent agreement between methods. Repeated measures analysis of variance of proportion measurements between ML Kit, direct and digital methods, were significantly different . Facekit measurements of orbital, orbitonasal, naso-oral, and naso-facial ratios had overall low correlation and agreement to both direct and digital measurements . Conclusion: Facekit is a smartphone camera application for rapid facial feature analysis. Agreement between Facekit's machine learning measurements and direct and digital measurements was low. We conclude that the chosen pretrained facial recognition software is not accurate enough for conducting a clinically useful facial analysis. Custom models trained on accurate and clinically relevant landmarks may provide better performance. Facial analysis is a fundamental component of any plastic, reconstructive, or maxillofacial consultation. Years of training and experience enable plastic surgeons to rapidly analyze an individual's face and quickly determine an impression of facial pathology, dysmorphism, and beauty. Much like the common proverb: “beauty is in the eye of the beholder,” individual plastic surgeons may have varying ideals when it comes to facial analysis—thus making this form of “gestalt” analysis truly subjective in nature.2 The ability to accurately extract facial landmarks and subsequently precisely calculate various proportions is integral to successful facial analysis. Multiple objective techniques for the measurement of soft tissue facial landmark measurements have been described and validated in prior literature.4 Direct surface measurements, popularized and standardized by Farkas, have yielded an extensive list of facial indices and population averages across ethnicities.57 Direct measurements, however, are operator dependent, time-consuming, subject to human error and require close, in-person contact with patients. Advances in photography and computer software have enabled highly accurate capture of human faces using precise markup tools, 3-dimensional reconstruction, and incorporation of computed tomography (CT) cephalometric imaging.811 Although powerful, these techniques are limited by their center-dependent availability, cost, and time.The objective measurement of facial landmarks and proportions has become increasingly used to highlight areas of interest in preoperative assessments, detect post-operative changes in facial reanimation or cosmetic surgery, provide an objective measurement tool for researchers, or assist with the diagnosis of various cranial dysmorphologies.1214 Unfortunately, most ML tools rarely progress beyond initial prototype development and clinical translation to wide adoption and deployment are not typically seen. Thus, there remains a need for a fast, cost-effective, scalable, and accurate tool for the detection and analysis of human facial landmarks in clinical settings to serve as a reliable foundation on which to build these valuable and powerful tools.Machine learning (ML)-derived facial recognition algorithms have increasingly been proven useful for automatic feature extraction, objective beauty measurements, and the diagnosis and management of craniofacial dysmorphology. ML Kit offers a fast, powerful, easy-to-use pretrained face detection model that was developed by experts in the field of computer vision. This model is capable of real-time facial landmark recognition and provides 133 coordinate points representing the eyes, eyebrows, nose, cheeks, mouth, and facial outline. This open-source Application Programing Interface (API) offers novel opportunities for wider development and deployment of automated tools for facial analysis.Facial recognition technology is becoming ever more prevalent and accessible on everyday devices. Recently, Google has published a collection of open-access computer vision models (ML Kit) for deployment in phone-based applications.The purpose of this study is to build a proof-of-concept smartphone-based camera application leveraging the ML Kit facial landmark detector for basic facial analysis. We were also interested in the algorithm's ability to detect cranial dysmorphology. We developed an android based phone app, “Facekit,” available for download in the Google Play Store for compatible devices. The app first guides users to capture optimal frontal images of the face and then automatically extracts key facial landmarks and calculates a common set of facial proportions for automated facial analysis. Our goal was to assess the accuracy and utility of this pretrained ML model in measuring facial proportions compared to digital and direct surface measurements. Our app provides a platform for rapid scalability and incremental refinement of an easy-to-use clinical tool for facial analysis.A smartphone camera app was developed for Android devices that leverage ML Kit for facial landmark extraction. It was optimized for clinical use by guiding image capture to a standardized frontal view of faces. Automated measurements of 4 horizontal proportions were calculated and compared to direct surface and digital measurements from 15 healthy volunteers. Facekit is a camera-based application capable of detecting and analyzing landmarks of human faces for analysis. To control face image consistency, real-time face detection is activated in the camera preview that displays a bounding box around the face as well as head rotation and tilt information  and deployed on a Google Pixel 5 (Google LLC) phone with a 12MP back-camera resolution.ormation . The appormation . By swipormation .ML Kit is a mobile SDK developed by Google engineers that provide best-in-class machine learning models for on-device deployment in both Android and iOS apps. This API allows researchers and clinicians to utilize premade computer vision models that would otherwise take too much time, compute power, or human resources to train. Input data processed by this API happens on-device and is not sent to any Google or cloud-based servers. The face detection module can detect human faces, identify key facial features, and get the contours of facial landmarks. The output is a list of Cartesian pixel coordinates representing several facial landmarks that are used in the calculation of facial proportions. Since true length calculations require a pixel to centimeter conversion for each image, the values compared in this study are ratios of lengths instead of the lengths themselves. These chosen proportions were considered easily measurable based on digital photographs and the algorithm's output. Direct surface measurements were taken by one author (ON). The landmarks measured were as follows: eye width (ex-en), intraocular distance (en-en), nose width , mouth width (ch-ch), and face width (zy-zy)  with diverse ethnic backgrounds and skin tones, and with no identified facial deformities. Participants provided informed verbal consent to be included in this study. Additional written consent was obtained from one participant for whom identifying information is included in this article. In this study, we focused on 4 neoclassical canons of facial proportions which have shown consistency across ethnic backgrounds: orbital (∼1), orbitonasal (∼1), naso-oral (∼1.5), and naso-facial (∼0.25) .6 Thes (zy-zy) . SubsequStatistical analysis was performed using Excel (Microsoft Inc) and the Real-Statistics resource pack software . The mean and standard deviations of errors between measurements were calculated between direct-ML, digital-ML, and direct-digital methods. One factor repeated measures analysis of variance (ANOVA) (RMA) was used to assess significant differences between the measurement methods. The reliability of each of the ML measurements was assessed by computing the intraclass correlation (ICC) between ML and either direct surface or digital measurements. An ICC of 0.75 or above is considered excellent, between 0.4 and 0.5 is fair/moderate, and below 0.4 is poor. Pearson correlation coefficients were also calculated between each of the measurement techniques. By calculating limits of agreement using the mean and standard deviations, Bland-Altman plots provided a quantitative estimate of how closely measurements from 2 different methods lie and reveal any hidden systemic bias.The average measurement error between direct surface and digital methods compared to the ML method is shown in The correlation coefficient (R), ICCs, and 95% confidence intervals for both moth methods against the novel ML methods are listed in None of the facial proportions calculated by ML reached an ICC of 0.75. The naso-facial proportion ICC had the highest upper confidence interval of 0.687. Bland-Altman plots of agreement between digital and ML measurements with lower and upper limits of agreement lines are shown in Lastly, the app was tested on publicly available images of craniofacial syndromes that characteristically exhibit hypertelorism: Frontonasal dysplasia, Apert's syndrome, and Crouzon syndrome. ML was unable to correctly identify asymmetrical or disproportionate orbital anatomy and produced orbital ratio measurements within similar ranges to healthy subjects. Facekit was also tested on publicly available images of patients with facial paralysis and was unable to identify the appropriate facial landmarks.We compared the agreement in measurements of 4 neoclassical facial ratios using direct surface, digital, and ML methods. The face detection algorithm used in this paper was developed and distributed for open-access use by Google's ML Kit project. We found that ML measurements performed poorly in facial proportions that rely on intraocular distance, while performing better in measurements relying on nose, mouth, and face widths. Overall, none of the measurements calculated by our app reached an acceptable level of agreement with either digital or direct surface methods, as indicated by ICC values. The poor performance could be attributed to several factors in the development of these algorithms. In the data preparation stage, manually labeled landmark positions may have not been accurate enough for use in facial analysis, creating ratios different than the ground truth. Bias may have been introduced either due to homogenous data or inadequate regularization during the training phase. Lastly, the algorithm appeared biased toward facial symmetry and contours that increase proportionally. This was evident in the analysis of faces with hypertelorism or facial droop where the app would artificially lengthen the eye width to match larger intercanthal distances or correct for the droop, respectively.19 Convolutional neural networks (CNNs), a powerful deep learning network architecture used in computer vision applications, form the backbone of most modern approaches to facial recognition.20 CNNs are increasingly used in medical diagnostics where fast and repetitive pattern recognition is needed. Barriers to the development of these algorithms go beyond knowledge expertise in the field of computer vision. To train a feature extraction model such as a CNN, researchers must first acquire a sizeable database (n>>1000) of images, manually label landmarks of interest, and have access to expensive and energy-intensive computing resources for training and validation of their models.23Machine learning algorithms have potential clinical and research applications within the field of plastic surgery by automating and streamlining data extraction and analysis of clinically important data. Currently, however, the majority of published literature in facial recognition algorithms and plastic surgery has focused on how the performance of preexisting facial recognition algorithms is impacted by patients who have undergone plastic surgery procedures.14 For example, an ML algorithm designed to predict an individual's gender has been shown to be more likely to predict a feminine gender in a patient after facial feminization surgery and this has been qualified as an indicator of successful facial feminization surgery. Although certainly interesting to experiment with, many research projects exploring ML in plastic surgery do not offer or discuss strategies for clinical translation. For clinicians to begin using ML solutions, barriers in the development process from model training to deployment and validation must be addressed. In this study, we examined the utility of a premade facial landmark detection algorithm for performing facial analysis using a smartphone camera application for a potential scalable pathway for clinical adoption.Successful applications of ML in plastic surgery include accurate diagnosis and prognosis of burn patients, identification of congenital facial deformities, and various cosmetic surgery assessment applications.Facegram, Facial Assessment by Computer Evaluation (FACE), and auto-eFACE are ML-based computer software tools capable of analyzing static or dynamic facial measurements with high accuracy.2628 Although they require photography equipment and data transfer to a computer, they demonstrated high sensitivity and specificity in the assessment of facial paralysis before and after reanimation surgery. For cosmetic analysis, one study has demonstrated high accuracy for objective classification of female facial beauty using an algorithm based on decision trees. This study primarily focused on vertical proportions, though values were not compared to digital or surface measurements and the authors did not discuss clinical translation. Aarabi et al proposed an automatic facial feature extraction procedure based on data from 12 judges and a k-nearest neighbor classification. Their method, however, only provides coarse classification into 4 classes of beauty from which real-world applicability is difficult to appreciate. More recently, a deep learning algorithm (RhinoNet) was able to classify the rhinoplasty status of pre/post-operative patients and performed with effectively equivalent accuracy compared to plastic surgery residents. Although the algorithm is limited in utility, the authors successfully deployed RhinoNet on a smartphone application for use in clinical settings. Knoops et al and Mendoza et al developed robust machine learning algorithms capable of diagnostics, risk stratification, and treatment simulation for orthognathic surgery.32 As these models rely on 3D scans from CT or magnetic resonance imaging, they are beneficial for a narrow range of patient populations. Geisler et al. created a labeled database of craniofacial syndrome images and developed a CNN to classify anomalies based on images only. They were able to achieve a high level of sensitivity and specificity in classifying head shapes as metopic, sagittal, and unicoronal. To our knowledge, the tools mentioned above have not been widely deployed in clinical practice and there remains a need for a fast, versatile, and easily deployable automatic facial analysis tool.Automatic facial feature analysis has been previously described in the literature. For facial paralysis assessments,  In this model, the nose consists of only 5 landmarks, far from enough to analyze the complex anatomy of nasal features. Additionally, this model cannot recognize facial landmarks in profile angles, limiting its use in measuring ear and nose proportions. The authors are unaware of any algorithms reported in the literature capable of analyzing profile views of human faces. Lastly, ML models contain bias from their training data. Algorithms may be biased against categories of race, gender, culture, and age if the original training dataset did not adequately represent those categories. As these data likely did not contain photos of cranial dysmorphology, the algorithm often attempts to infer symmetry where symmetry does not exist.The face detection model from ML Kit has several notable limitations. This study focused on facial proportions and not lengths as calibration of pixel to millimeter conversion requires fiduciary markers or complex depth calculation techniques. This model does not capture the forehead, therefore, it is not possible to calculate vertical proportions that include face height. A nasal analysis is particularly important for the rhinoplasty preoperative assessments.Although measurements calculated by the ML Kit algorithm did not reach a level of agreement with direct or digital methods, this study provides a paradigm for clinicians and researchers to assess the clinical utility and translation of open-access ML algorithms in plastic surgery. Additionally, Facekit is built with a modular design that supports the substitution of different algorithms with the potential for better performance on facial analysis tasks.Future work will be required to improve the accuracy of open-access facial recognition software for its use in clinical practice. Specifically, these algorithms require more landmarks and an ability to function in both frontal and profile views. When investigators build high-performing algorithms, more effort should be made to making those accessible via smartphone or web-based interfaces for wider deployment and further validation. Our next step will be to assess the performance of a wider range of state-of-the art algorithms such as those built by Facebook, Microsoft, Amazon, and Apple to generate an index of clinical utility, as well as develop a novel algorithm based on up-to-date concepts in computer vision for specific use in plastic surgery assessments and provide wide deployment.In conclusion, our study built and deployed a smartphone camera application for rapid facial feature extraction and analysis using a premade algorithm built by Google considered to be “best in class.” The performance of this algorithm was overall poor compared to direct surface and digital measurements. We conclude that pretrained facial recognition models are not sufficiently accurate to conduct a clinically useful facial analysis. Custom models trained with carefully labeled landmarks important to the plastic surgeon may offer a better solution to future automation of this task.


Drosophila heart tube seems simple, yet it has notable anatomic complexity and contains highly specialized structures. In fact, the development of the fly heart tube much resembles that of the earliest stages of mammalian heart development, and the molecular-genetic mechanisms driving these processes are highly conserved between flies and humans. Combined with the fly’s unmatched genetic tools and a wide variety of techniques to assay both structure and function in the living fly heart, these attributes have made Drosophila a valuable model system for studying human heart development and disease. This perspective focuses on the functional and physiological similarities between fly and human hearts. Further, it discusses current limitations in using the fly, as well as promising prospects to expand the capabilities of Drosophila as a research model for studying human cardiac diseases.The  Drosophila heart has distinct morphological features, including an anterior aorta structure that is separated from the posterior heart chamber by an aortic valve to ensure posterior to anterior flow, and it has inflow tracts named ostia  and flows via channel-like trajectories formed by the internal organs and by fibromuscular septa or diaphragms (tinman (tin), was discovered in flies , TBX (T-box), MEF2, and the HAND family, are evolutionarily conserved and have homologs in flies, zebrafish, and mice  which plays a crucial role in heart development is also a hotspot for genetic variants that have been linked to CHD ; silencing its homolog Wds in the fly heart caused complete developmental lethality and abnormal cardiac morphology in late larvae, including reduced cardiac myofibers and increased Pericardin deposition  covering hitherto not associated candidate disease genes in a cohort of 167 patients with CHD , one of the most sequenced human genes. It has hundreds of variants associated with multiple cardiomyopathies including those with pediatric onset , and stiffening of the ventricular walls  mutant flies showed cardiac arrhythmia reminiscent of the clinical observation in patients with Tropomyosin-associated dilated cardiomyopathy (Phosphopantothenoylcysteine synthetase (PPCS) and transgenic flies that caried PPCS with patient variants (Zinc phosphodiesterase ELAC protein 2 (ELAC2) genetic variants in a rare form of severe infantile cardiomyopathy (RNaseZ) displayed cardiac hypertrophy and reduced contraction mimicking the clinical pathology in patients (Myosin light chain 2 (MYL2) associated with hypertrophic cardiomyopathy of infantile onset and characterized by mitral valve dysplasia, resulting in infant death , and ultimately heart failure , dysfunctional ostia , and structural defects and disorganization of the myofibrils  of a high-glucose in vitro model, and maternal diabetic mouse and Drosophila models, revealed a conserved interaction between Notch1 signaling (gene) and high-glucose (environment); controlled by a Jarid2 -mediated epigenetic mechanism  and decreased diastolic function of the left ventricle, even in the absence of major cardiovascular risk factors    . Moreoveyndrome) . A compa rodents . Besides rodents . Taken tDrosophila models have taught us much about the developing and aging heart in health and disease. However, several challenges remain, which when overcome would greatly expand the opportunities to use fly models in studies of cardiac disease. Whereas single-cell RNA sequencing technology has provided detailed transcriptomic profiles of the developing heart in humans (Danio rerio) (Ciona robusta)  , and searobusta) ; for Drolt heart . KnowingIt is worth noting that to accommodate its open circulatory system, the fly carries additional pulsatile organs, known as antennal/frontal accessory pulsatile organ and wing hearts, that ensure circulation of hemolymph (fly blood) throughout its antennae and wings, respectively . The musDrosophila heart is innervated by peripheral neurons  and CUGBP Elav-like family member 1 (CELF1), in the fly heart; this led to dysregulated calcium signaling genes including straightjacket (stj)/α2δ3, which encodes a voltage-gated calcium channel subunit , the atrioventricular node (AV node), the bundle of His, and Purkinje fibers which make up the cardiac conduction system . The SA  neurons  (Figure  neurons . Althoug subunit . In the  defects . Better  defects  and elec defects  are alreDrosophila provides an excellent opportunity to study polygenic causation, which has likewise been difficult to study using conventional animal models. However, Genomic studies have found many patients with CHD or cardiomyopathy that likely have a polygenic cause (Drosophila genome carries little redundancy which facilitates data interpretation. These studies could reveal new disease mechanisms relevant to the human heart.In addition to accommodating studies of gene-environment interactions, like fly models for diabetes, ic cause . For theic cause , thus deDrosophila a very exciting model system to study a wide variety of aspects of human cardiac diseases.The flies’ established track record combined with the latest technology and assays for fly cardiac function, and the many new avenues about to be explored make


The implementation of interventional cardiac procedures and mechanical circulatory support (MCS) devices has led to a fundamental transformation of critical care cardiology. Today, both technological advances and a more nuanced understanding of outcomes allow for the delivery of various complex procedures in high-risk settings and to older patients with severe comorbidities . ConsideModern cardiovascular fellowship programs typically include a 6-month general or CICU rotation, which may be prolonged depending on individual preferences. The goal for this period set forth by the Core Cardiovascular Training Statement (COCATS) 4 Task Force 13 and the 2020 European Society of Cardiology (ESC) curriculum for the cardiologist is to manage the majority of cardiovascular patients in intensive care settings [Many prerequisites for CICU patient care are taught as part of rotations in cardiac imaging, electrophysiology, and emergency medicine. Core training components during the first CICU rotation comprise advanced hemodynamic monitoring, airway and respiratory management, basic circulatory shock management, cardiac arrest algorithms and post-resuscitation care, sedation, monitoring of neurological function, infection control, and management of multi-organ dysfunction. Extracurricular seminars, such as the in-depth courses on acute myocardial ischemia, hypertension, and organ transplantation offered by the European Society of Intensive Care Medicine (ESICM) or the Society of Critical Care Medicine (SCCM) can solidify theoretical knowledge and foster interaction with peers. In general, early scholarly activity and participation in (inter)national meetings is encouraged by teaching institutions and the respective societies.In recent years, we have been witnessing a growing interdependence of interventional and critical care cardiology. Coronary angiography has become a cornerstone of myocardial infarction-related cardiogenic shock management. Beyond that, patients presenting with acute decompensated valvular dysfunction, massive pulmonary embolism, arrhythmia-related hemodynamic instability, or intracardiac shunts may qualify for emergent transcatheter procedures. While expert multidisciplinary teams formulate the most promising treatment approach, CICU fellows play a central role for its successful implementation. Following interventional procedures, the access site vasculature, potential thromboembolic complications, arrhythmias, and end organ function require constant vigilance. Echocardiographic visualization of implanted devices and assessment of their function together with general hemodynamic changes needs to be performed reliably and specific procedure-related complications must be recognized and addressed in a timely manner.Apart from these major advances in interventional cardiology, contemporary cardiogenic shock management became a complex endeavor, particularly due to the widespread usage of MCS devices for patients with severe hemodynamic compromise. Although based on recent data the future role of veno-arterial extracorporeal membrane oxygenation (VA-ECMO), Impella, and other MCS options is uncertain , 5, cardAfter specialization in general cardiovascular or intensive care medicine, accreditation in critical care cardiology necessitates exposure to CICU cases for an extended period of time, ideally within a dedicated sub-specialization program at an accredited tertiary institution. There is consensus on the relevance for offering structured up-to-date training pathways to prepare for the staggering challenges in cardiovascular intensive care and allow for standardized quality assessment. However, sub-specialization models and accreditation standards still vary substantially with respect to training time and curricula.Managing CICU cases independently requires a broad practical skillset, general intensive care expertise, and in-depth knowledge regarding cardiac illnesses and the respective treatment options. Clinical training elements in this career stage include decision-making regarding interventional procedures in high-risk settings, intimate knowledge and skillset required for comprehensive peri-interventional care, familiarity with all forms of circulatory shock and advanced MCS device management including cannulation/decannulation, weaning, LV venting modalities, as well as combined MCS. A contemporary CICU core curriculum should aim to distinguish the milestones for pursuing a career in critical care cardiology from the scope of critical care training that applies to a broader silo of cardiovascular fellows.Beyond patient care, critical care cardiologists must be proficient in many other rapidly evolving areas of competence, such as IT-systems, billing, professional communication skills particularly in end-of-life scenarios, and the legal framework of clinical trials. Palliative care, the allocation of limited financial resources and clinical trial participation involve demanding ethical considerations. Contemporary CICU training programs should incorporate these additional skills as part of a well-rounded education in intensive care medicine.Teaching the vast theoretical and practical armamentarium of critical care cardiology in context of recent advances in the field calls for an updated core curriculum covering all aspects of critical care training for cardiovascular fellows as well as aspiring CICU specialists. Apart from integrating the ever-expanding list of competences, a holistic training concept must be flexible enough to allow for personalization of the candidate’s career pathway. To incentivize fellows to pursue the lengthy and demanding training required to become an expert in critical care cardiology, a modular curriculum seems to be the most applicable basis for tailoring their education to prior professional experience and personal wishes, including the desire for maternity/paternity leave, and international workplace mobility. Importantly, training programs should be conceptualized to allow for interruption of clinical training for research purposes and hybridization with sub-specialization programs in interventional cardiology or advanced heart failure .The evolution of modern critical care cardiology has generated a burgeoning demand for specialists in this domain of cardiovascular medicine, and by extension, a need for an updated concept for sub-specialization that is both comprehensive and flexible. Despite the general consensus that there is a need for such training standards, dedicated sub-specialization tracks or advanced fellowships in cardiac intensive care are rarely available and heterogeneous, which continues to stunt the progression of leaders in the field . A conte


Neurodegenerative disorders (ND) are a common cause of mortality and morbidity worldwide, particularly in older people. As life spans continue to increase, the incidence of neurodegenerative diseases is expected to increase as well [World Health Organization (éd.), ND, such as Alzheimer's Disease (AD) and Parkinson's Disease (PD), develop progressively over many years. After an asymptomatic stage , cognitive and neuropsychiatric symptoms start to appear and then worsen over time, until they lead to a loss of autonomy in activities of daily living. Multi-domain interventions  are showing promising results in delaying ND progression  and biomarkers of tau pathology  can characterize AD pathology before the appearance of clinical symptoms . Similarly, Ma et al. found that the incidence of multiple step saccades in their visually guided reactive saccade task could be a complementary biomarker for the early diagnosis of PD. This approach provides for an easy assessment of ND through eye-tracking.In terms of PD screening, Ali et al. found that kinematic gait parameters of knee peak extension angle during a dual task performance  were sensitive enough to discriminate individuals with MCI from healthy controls.Assessing motor performance and action kinematics is relevant not only for PD detection, but can be employed also to screen for mild cognitive impairment, especially in dual-task conditions. Cai et al. found that diurnal vector magnitude and total time in bed correlated negatively with apathy severity in patients with Cerebral Small Vessels Disease. This confirms that objective motor indicators can be relevant also for the assessment of neuropsychiatric symptoms, such as apathy and depression.Measuring the global level of motor activity and sleep using actigraphy recorded over 7 days, Li et al. showed that objective indicators of brain oxygenation status and cerebral autoregulation function (assessed using near-infrared spectroscopy technology and a non-invasive blood pressure device) can reflect cognitive function, and correlate with the level of cognitive decline in older adults assessed using the MoCa.Other non-invasive biomarkers are also starting to show promising results. For instance, Barthelemy et al. highlighted the importance of monitoring autonomic biomarkers (such as heart rate variability) parameters, in addition to classical cardiovascular risk factors, to increase the prediction of stroke.In their review, Tung et al. confirmed the interest of combining genetic (Apolipoprotein E-ApoE polimorfism) and clinical information to detect cognitive decline and optimize interventions. Interestingly, across comorbidities, functional gastrointestinal disorder was the strongest predicting factor for dementia in ε4 allele carriers.Liang et al. investigated the predictive ability of preoperative plasma biomarkers along with cerebral oxygen saturation for the incidence of post-operative cognitive dysfunction in older patients with MCI. They drafted recommendations on the cerebral oxygen saturation level based on Aβ-42 status to reduce the risk of post-operative cognitive disfunction.Finally, Taken together, these results corroborate the idea that new technologies, non-invasive sensors, and machine learning algorithms can complement and support traditional assessment, and their results converge with traditional biomarker evidence. The important developments from this topic should motivate near term research to examine which markers type of screening should be employed for a patient depending the type of risk factors. Furthermore, large-scale studies are necessary to test the convergent validity compared to traditional biomarkers.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.