Neisseria gonorrhoeae, a pathogen associated with a high burden of disease and antibiotic resistance and the development of genotype-based diagnostics. We show that patient characteristic-informed sampling is not a reliable strategy for efficient variant detection. In contrast, sampling informed by pathogen characteristics, such as genomic diversity and genomic background, is significantly more efficient than random sampling in identifying genetic variants associated with resistance and diagnostic escape.Genotype-based diagnostics for antibiotic resistance represent a promising alternative to empiric therapy, reducing inappropriate antibiotic use. However, because such assays infer resistance based on known genetic markers, their utility will wane with the emergence of novel resistance. Maintenance of these diagnostics will therefore require surveillance to ensure early detection of novel resistance variants, but efficient strategies to do so remain undefined. We evaluate the efficiency of targeted sampling approaches informed by patient and pathogen characteristics in detecting antibiotic resistance and diagnostic escape variants in  Nucleic acid-based diagnostics that enable rapid pathogen identification and prediction of drug susceptibility profiles can improve clinical decision-making, reduce inappropriate antibiotic use, and help address the challenge of antibiotic resistance . HoweverNeisseria gonorrhoeae, Chlamydia trachomatis, Staphylococcus aureus, and Plasmodium falciparum, resulting in false negative diagnostic errors only detected when using another diagnostic platform  not accounted for in the diagnostic’s panel of resistance markers  for pathogen identification and genotype-based diagnostics for antibiotic resistance can select for genetic variants that escape detection . Mutatioplatform . Diagnos markers  and reque.g., demographics and/or geographic regions) may be more likely to be sampled than others, and clonal transmission may result in repeated sampling of closely related isolates  may help improve sampling efficiency. Similarly, given historical patterns of antibiotic use, novel resistance may emerge on a background of existing resistance , anatomical sites of isolate collection (niche-aware sampling), and geographic regions (geography-aware sampling) increased detection efficiency of resistance variants by ameliorating some of the demographic, niche, or geographic sampling biases. We further investigated whether preferentially sampling patients with recent overseas sexual encounters or recent sex work, two characteristics hypothesized to be associated with the introduction and/or increased transmission of resistance , increaspenA XXXIV was significantly enriched in MSM compared to men who have sex with women and women who have sex with men (MSW/WSM) in dataset 2 , there was no significant difference in the proportions of MSM and MSW/WSM with penA XXXIV in dataset 1 . Similarly, while the AZM-R-associated RplD G70D mutation in dataset 3 was at highest prevalence in patients from Malta and Greece  and absent from patients from Denmark, the AZM-R-associated 23S C2611T variant was at highest prevalence in patients from Denmark (5.45%) and absent from patients from Malta or Greece.The detection efficiency was not improved by demography-, niche-, geography-aware sampling compared to random sampling for any of the resistance variants . In sevepenA XXXIV allele, as these were at marginally higher prevalence in isolates from patients with recent overseas sex compared to those from patients who had only engaged in sex locally . In contrast, the 23S C2611T mutation was exclusively present in isolates from patients who had engaged in sex locally  maximization of the phylogenetic distance covered with each isolate sampled (distance maximization) and 2) even sampling across phylogenetic lineages .While the distance maximization approach increased detection efficiency compared to random sampling for some variants, there were numerous instances in which this approach, which led to preferential sampling of isolates associated with long branches, substantially decreased detection efficiency .e.g., penA XXXIV and 23S rRNA C2611T mutations, respectively, The clonal group sampling approach prevents repeated sampling of very closely related isolates until all unique phylogenetic clusters have been sampled. Thus, for both rare variants that are clonally distributed and rare variants that are more randomly dispersed throughout the phylogeny , the effective prevalence of the variants would be 0.020, greater than the actual prevalence of 0.012. Similarly, using the 134 SNP threshold, if one additional isolate that was >134 SNPs from any other isolates in this dataset had the 23S rRNA C2611T mutation, the average prevalence of the variant across clonal groups would be 0.036, greater than the actual prevalence of 0.016, and thus the clonal group approach would outperform random sampling.In cases where the clonal group sampling approach did not perform better than random sampling, adjusting the threshold for clonal grouping and/or a marginal increase in the prevalence of variant-positive isolates could elevate the relative performance of this targeted approach. We chose 134 SNPs as an example threshold for clonal grouping, as it represents the lower 95% confidence interval of the mean of SNP distances between each CFX-R resistant and the closest susceptible isolate in datasets 1–5 (see Methods). In the case of the 23S rRNA C2611T variant in dataset 4, the average prevalence of the variant across clonal groups  is 0.005, lower than the actual prevalence of 0.012. However, if the threshold for clonal grouping was lower in this instance ; relative performance of clonal group sampling using MLSTs, however, was less consistent and was significantly worse than random sampling for several variants D-E. TogeN. gonorrhoeae  within and/or across different antibiotics when screening for a novel resistance variant. For example, as ciprofloxacin was the recommended first-line therapy for uncomplicated gonorrhea through 2005 in the United Kingdom  into surveillance programs may ultimately decrease the cost of surveillance to maintain the sensitivity of these diagnostic tools.With sequencing becoming more integral to routine pathogen surveillance and diagnostics, it is important to ensure that models mapping genotypic information to expected pathogen phenotype and/or clinical outcome are comprehensive and current . In the Collection of patient metadata, including demographic and geographic information, is crucial to understanding the epidemiology of drug resistance. However, it may be difficult to obtain data on the relevant patient features, and the predictive power of such features may rapidly decay because of patient mobility and interactions . While aIncorporation of WGS into routine pathogen surveillance by public health agencies  may faciN. gonorrhoeae  that could be prioritized for confirmatory phenotyping.The phylogeny-aware sampling approaches presented here are based on the assumption that genomic data will be available for the pool of potential isolates from incident cases that may undergo confirmatory phenotyping. However, using information on isolate features to increase surveillance efficiency may be feasible even in the absence of mass prospective sequencing. For example, under the general assumption that novel resistance variants are more likely to appear in underrepresented lineages, phylogeny-aware surveillance could be paired with a diagnostic approach such as genomic neighbor typing , where ahttps://www.cdc.gov/narms/) could adopt these targeted sampling approaches to prioritize isolates for phenotypic testing.While the focus of this study was to introduce and evaluate approaches to increase the efficiency of surveillance programs for maintaining marker-based AMR diagnostics, these approaches may be broadly applicable to surveillance programs aimed at tracking AMR in general and/or other phenotypes of interest that may be time- and/or resource-intensive to directly measure. For example, programs such as the National Antimicrobial Resistance Monitoring System for Enteric Bacteria .Gubbins v2.3.4  was usedpenA XXXIV allele in dataset 3, as the prevalence of these variants in these datasets was >10%.For each sampling approach/dataset/variant combination, 100 simulations were carried out with isolate sampling continuing until variant detection. We defined ‘detection efficiency’ as one minus the fraction of isolates sampled prior to variant detection (excluding any samples for which the presence or absence of the variant could not be determined). As detection efficiencies were not normally distributed, differential performance between random sampling and targeted sampling was assessed by Mann Whitney U tests of differences in mean ranks of detection efficiencies. Because the purpose of this study was to compare the rare variant detection efficiency between random sampling and targeted sampling approaches, we did not evaluate RplD G70D in datasets 1 and 4 or for the In demography-aware sampling (datasets 1 and 2), the first isolate was selected at random, and each successive isolate was randomly selected from alternating demographic groups (men vs. women and men who have sex with men [MSM] vs. men who have sex with women [MSW] or women who have sex with men [WSM]). For anatomical site (niche)-aware sampling (datasets 1 and 2), the first isolate was selected at random, and each successive isolate was randomly selected from alternating anatomical sites of isolate collection . For geography-aware sampling (datasets 3 and 4), the first isolate was selected at random, and each successive isolate was randomly selected from alternating geographic regions (countries or prefectures). For geography- and distance-aware sampling (datasets 3 and 4), the first isolate was selected at random, and each successive isolate was selected randomly from the region (country or prefecture) with the largest product of geographic distances from previously sampled regions, only re-sampling from a given region after all regions had been sampled in that round. For travel history- and sex work-aware sampling (dataset 2), isolates were selected at random either limiting the pool to isolates from patients who had recently engaged in overseas sex or sex work, respectively .penA XXXIV allele and the closest isolate without the resistance variant. The clonal group sampling approach was further tested by alternating sampling across fastBAPS and MLST groups.For phylogeny-aware sampling (datasets 1-5), the first isolate was selected at random, and each successive isolate was either selected to maximize the product of phylogenetic distances from each of the previously sampled isolates (“distance maximization”) or selected randomly with the exception of ensuring even sampling across phylogenetic groups  or to isolates with a mutation at PorB G120 and/or PorB A121, which have been associated with a range of resistance pathways in multiple classes of antibiotics . Genomic In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Identification of antibiotic resistance is shifting from culture based to genetic identification of drug resistant strains. However, how best to use these data is unclear – can we move beyond searching for common and known variants to identify new mutations? This manuscript addresses the critical question of how to rapidly identify antibiotic resistance from sequence data. It compares how inclusion of different clinical and genetic data affects these predictions. It finds a limited role for inclusion of clinical data but suggests that inclusion of data on phylogeny and background may be informative.Decision letter after peer review:eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Eduardo Franco as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Michael Feldgarden (Reviewer #1); Nicholas Medland (Reviewer #2).Thank you for submitting your article "Targeted surveillance strategies for efficient detection of novel antibiotic resistance variants" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as Summary:This paper addresses a critical shortcoming of the transition from conventional culture-based N. gonorrhoea AMR testing to molecular based systems, which otherwise have the potential to transform both diagnostics and surveillance globally. Determining the extent of the research flatform required support molecular AMR testing and how it is applied to real world sampling is critical. In particular, knowing that resistance develops according to known mechanisms and that population and anatomical distribution is not random, are sampling frames able to be manipulated to increase the probability that new resistant variants will be detected sooner? Using five historical datasets with established genotype and culture-based resistance results but with varying degrees of clinical and epidemiological data (from highly detailed to unavailable), the authors simulated whether different sampling based on demographic, anatomic and/or geographic sampling frames would detect markers of clinically important azithromycin and ceftriaxone resistance known to occur in low prevalence in those datasets. They found that although some targeted sampling, in particular of returned travellers, helps to identify resistant mutants, on the whole it did not do so reliably.So as to better target sampling at strains that are genetically different from those previously sampled the authors propose two phylogenetic strategies: sampling maximally unrelated isolates and sampling from each phylogenetically related clone. These approaches led to some improvement in efficiency in detecting resistant mutants, particularly after post-hoc adjustment of sensitivity thresholds (for the latter) and in some data sets with particular characteristics (for the former).A third type of strategy was to sample strains what had already identified markers of resistant to other antibiotics, in particularly to ciprofloxacin whose resistance genotype is extremely well studied and well characterised.The first approach uses metadata, which is considered essential in surveillance but is nonetheless not always available, and which the later approaches have the advantage of not requiring. However, the second and third approaches clearly require some preliminary molecular testing of specimens to determine which to sample for whole genome sequencing.Essential revisions:1) How would a low rate of either sequencing or phenotyping error affect the different approaches? Presumably, these effects would not qualitatively affect the outcomes, but would such error rates, which are often observed, falsely improve or weaken one approach?.2) The resistance markers used are mostly point mutations or recombinant alleles. What are the expectations for the performance of these sampling approaches for acquired resistance genes ?3) There are other large datasets with genomic and phenotypic information  that could be used to test this-and find this approach useful. While I do not expect (nor want) the authors to examine these datasets, recognizing that this technique would be useful for large surveillance systems should be mentioned. It would be a shame for surveillance systems to be unaware of these findings. Essential revisions:1) How would a low rate of either sequencing or phenotyping error affect the different approaches? Presumably, these effects would not qualitatively affect the outcomes, but would such error rates, which are often observed, falsely improve or weaken one approach?.Thank you for bringing this up and giving us the opportunity to clarify and address this.While false-positive phenotyping errors  would presumably be further investigated and ultimately corrected, we agree that false-negative phenotyping errors  could absolutely delay detection of a novel AMR variant. However, we don’t believe there is reason to think that this should disproportionately affect detection efficiency of any of the targeted sampling approaches compared to random sampling or compared to each other.Sequencing errors could affect the efficiency of the phylogeny-aware sampling approaches. The differential prevalence of resistance variants among datasets might raise the concern that the improved detection efficiency by phylogeny-aware sampling arose from study-dependent sequencing artifacts. However, we evaluated each dataset separately, so variation in sequencing methods across datasets should not have confounded our analyses. When applied in a surveillance setting, we do agree that sequencing errors could in theory result in closely related isolates appearing to be more distantly related, thus reducing the increased efficiency of phylogeny-aware sampling compared to random sampling. However, we don’t expect that the opposite would occur , so sequencing errors are unlikely to make the clonal group approach worse than random sampling. Further, we expect that the influence of sequencing errors should be largely ameliorated by inspecting sequencing quality prior to analysis. We have now added some discussion of sequencing errors .2) The resistance markers used are mostly point mutations or recombinant alleles. What are the expectations for the performance of these sampling approaches for acquired resistance genes ?Thank you for bringing up this point. We agree that it is not entirely clear how phylogeny-aware sampling  will perform in detecting novel variants associated with gene acquisition. While the gonococcal resistance variants associated with plasmids are too prevalent to be useful for our evaluations here, there is some evidence for a relationship between the core genome and the presence/absence of these plasmids, suggesting that core genome-based phylogeny-aware sampling may still be useful for these kinds of resistance variants. We also suspect that with the genomic data required for phylogeny-informed sampling, it may be possible to rapidly identify some novel resistance by screening for homologs of known resistance genes from other species. Further, k-mer based methods that allow for clustering based on both core and accessory genome similarity may be more useful in the context of novel resistance associated with gene acquisition. We have now expanded our discussion of this .3) There are other large datasets with genomic and phenotypic information  that could be used to test this-and find this approach useful. While I do not expect (nor want) the authors to examine these datasets, recognizing that this technique would be useful for large surveillance systems should be mentioned. It would be a shame for surveillance systems to be unaware of these findings.Thank you for this suggestion. We agree that these targeted sampling approaches may be more broadly applicable outside of the context of maintaining diagnostics. We have now highlighted this in the Discussion (eighth paragraph).


The transition period between early childhood and late adolescence is characterized by pronounced changes in social competence, or the capacity for flexible social adaptation. Here, we propose that two processes, self-control and prosociality, are crucial for social adaptation following social evaluation. We present a neurobehavioral model showing commonalities in neural responses to experiences of social acceptance and rejection, and multiple pathways for responding to social context. The Leiden Consortium on Individual Development (L-CID) provides a comprehensive approach towards understanding the longitudinal developmental pathways of, and social enrichment effects on, social competence, taking into account potential differential effects of such enrichment. Using Neurosynth based brain maps we point towards the medial prefrontal cortex as an important region integrating social cognition, self-referential processing and self-control for learning to respond flexibly to changing social contexts. Based on their role in social evaluation processing, we suggest to examine medial prefrontal cortex connections with lateral prefrontal cortex and the ventral striatum as potential neural differential susceptibility markers, in addition to previously established markers of differential susceptibility. Whereas adults have developed (self-) adaptative mechanisms in response to experienced or observed negative social feedback, these mechanisms may not yet be in place during childhood and adolescence, making this a period of higher sensitivity to social evaluation signals . The stuInsights in the effects of social evaluation on neural processes at a micro level  have been informed by the use of functional magnetic resonance neuroimaging (fMRI) paradigms signaling acceptance and rejection by others. Functionally, prior studies suggest a coordinating role of the medial prefrontal cortex when responding to social evaluation . The medThe study of neural responses to experimental tasks that mimic social evaluation experiences may provide a powerful means to understanding the association between experimentally induced moment-to-moment experiences of social evaluation and more prolonged real-life social experiences that may affect the development of social competence processes. Many scientists have examined prolonged developmental trajectories of social competence, possibly because in periods of developmental change the processes involved can be fostered and shaped through social experiences . The socand for worse, such that their social competence is fostered to a greater extent in a positive environment, but also harmed more in a negative environment compared to individuals who are less susceptible to environmental influences. An experimental ‘micro-trial’ with Cyberball has shown, for example, that aggression in response to exclusion is differentially affected by (MAOA) genotype ; an experimental accelerated cohort-sequential longitudinal twin intervention-study that includes children between ages of 3−13-years see . The reaThe L-CID program has two aims: 1) to unravel the developmental trajectories, differences and commonalities of behavioral profiles and neural correlates for self and other-oriented social evaluation, which are two important components of social competence  or disliked (rejection) based on first impression . These sTo examine self-control in relation to social evaluation, Achterberg and colleagues developed a novel neuroimaging paradigm, which is referred to as the Social Network Aggression Task (SNAT) appropriate for older children, adolescent and adults . This paThis paradigm was developed to also examine neural responses to acceptance and rejection feedback using fMRI. By including a neutral condition to the SNAT-paradigm, it was possible to examine the brain regions that were generally sensitive to social feedback (positive or negative) and regions that were responding to the specific valence of feedback (negative > positive). Prior research had left undecided which brain regions were responding to valence , saliencThe same paradigm was also used separately in 7−10-year old children  and 7–9-In the SNAT paradigm participants were given the opportunity to retaliate following negative feedback, compared to positive and neutral feedback, by blasting a noise towards the source of the social feedback. Interestingly, stronger activation in DLPFC following rejection was associated with shorter noise blasts, that is, less aggression following rejection, in both adults  and 7–9-Taken together, these studies suggest that social evaluation and associated self-control rely on both medial and lateral prefrontal cortex, together with the bilateral insula and ventral striatum. The experience of social evaluation was associated with activation in medial prefrontal cortex, consistent with prior studies showing that distinct subregions in the medial prefrontal cortex are involved in processing social evaluative cues . The conEven though few studies have examined social evaluation processes across development, developmental trajectories have been observed for the ability to control behavior in a non-social context, such as for the ability to delay gratification. When deciding between smaller immediate rewards or larger future rewards, impulsivity declines between childhood and adulthood . It curr2.2The experience of social inclusion and exclusion can be directed to self, but can also be observed in others. Witnessing social exclusion of others can lead to punishment of excluders  and to pA particular strong paradigm to trigger feelings of social exclusion is the Cyberball paradigm . This coPrior studies that made use of two-person interaction games that include a division of goods  reported that social distribution behavior benefitting self and others is associated with a network or regions including the medial prefrontal cortex, superior temporal cortex and temporal-parietal junction (TPJ) . ParticiThese studies inspired the study of helping behavior in the context of social evaluation using an adapted prosocial Cyberball Game (PCG) . This gaBrain imaging studies using the PCG revealed that in adults, tossing to the excluded player is associated with more activation in the ventral striatum and the TPJ, regions that are often implicated in reward processing and perspective taking , whereas in middle childhood prosocial helping is associated with increased activity in precuneus and performance-dependent insula . A prior2.3The studies reported by Achterberg and colleagues  and Van 2.4An interesting approach for future research concerns the bi-dimensional influences of social evaluation sensitivity for self and others on developmental outcomes . Self-prThe overlap in neural activation in the medial prefrontal cortex suggests that this region is an important connecting region that responds to both negative social or rejection feedback of self and others. Behavioral responses to evaluations of self and other can be organized according to two axes: (i) the dimension of aggressive, self-protective acting-out tendencies: variance on this dimension may lead individuals to respond aggressively to others versus controlling their anger; and (ii) the dimension of prosocial tendencies: variance on this dimension may lead individuals to prosocially help others versus showing no signs of prosocial helping. This taxonomy leads to four groups (for ease of interpretation but continuous variation can be projected on the axes): The first group consists of individuals who show self-protective aggression combined with low levels of prosocial helping and who could be classified as anti-social revenge takers .Fig. 6Be3differential susceptibility on future outcomes. What are characteristics of youth who are particularly susceptible to better and worse (changes in) environments? Are there time windows in which differential susceptibility is enhanced? Can we identify neural markers of differential susceptibility?The prolonged development of brain regions implicated in social evaluation suggests a window of sensitivity to environmental experiences. Regions from the social brain network, including the medial prefrontal cortex, TPJ and posterior STS show grey matter increases and decreases until the early twenties . We argu3.1One approach to understand inter-individual differences in processes associated with social evaluation is examining the relative genetic influence on brain development and behavior . The claIt has been shown that total grey matter volumes are highly heritable in adults . HeritabThe L-CID studies referred to in this review made use of the classic ACE twin design in two overlapping cohorts of 238 twin pairs (ages 3−9-years) and 256 twin pairs (ages 7−13-years). We found considerable heritability estimates for questionnaire trait phenotypes of prosociality and effort-full control , modest In spite of the absence of behavioral evidence for genetic contributions, there was some evidence for genetic influences on neural signals in the range of 10–20 %, specifically for the DLPFC and supplementary motor area following positive feedback in the SNAT paradigm , and the3.2Even though a real test of differential susceptibility requires measures of longitudinal within-person change , some initial evidence for heightened susceptibility to the environment may already be obtained by studying how the variation in susceptibility of children and adolescents varies over time. We examined moment-to-moment task influences , as a m3.3Susceptibility to the environment can also be affected by previous supportive or aversive experiences as their stress-regulatory system might be pre-programmed to the environment they have to cope with at a later stage in their development . For exa3.4Neural measures have previously been suggested as a possible new avenue for detection of early markers for  susceptibility to the environment . One areHere we propose that reactivity of the medial prefrontal cortex may be a similar differential susceptibility marker for sensitivity to social evaluation. The medial prefrontal cortex is strongly connected to both the ventral striatum and the lateral prefrontal cortex in terms of white matter connections , as well3.5Another challenging task for future research is to study the commonalities and differences between the various markers of differential susceptibility see . First, In L-CID markers of differential susceptibility have been assessed at several longitudinal assessments. Furthermore, the longitudinal accelerated cohort-sequential design of the study covers an age range from early childhood to early adolescence. Lastly, the design includes a randomized control trial required for sufficient statistical power to test the moderating effects of the markers . The uni4In this review, we present a neuroscientific differential susceptibility model that can be tested in future research and that is the driving motivation for the Leiden Consortium on Individual Development (L-CID) study. Several of the hypotheses can only be examined with longitudinal models including a randomized intervention, but the cross-sectional analyses provide important starting points for unraveling the dynamics of social evaluation. In future research, we will be able to extend these insights to contribute to answering the question: which children are most susceptible to environmental influences and at what time-points or windows in development are influences from the environment most pronounced, thus contributing to the perennial question in policy, prevention and therapeutic approaches: what works for whom at what time in development?The L-CID study provides several new directions for understanding social evaluation in the context of self-protective mechanisms as well as other-oriented motivations. We proposed that the bi-directional relations between these processes will provide an important starting point for understanding social competence development and other developmental outcomes. Several important factors potentially explaining differences in social competence were not explicitly covered in this review, such as helping members of ingroup versus outgroup, and the influence of twin-sibling relationships. It is our ambition that in the future L-CID will provide a rich open data set for researchers to examine the processes involved in social competence and extend our work to new domains. By using a multi-method, multi-informant and multi-time-points approach, we hope to contribute to better operationalization of the core concepts, which ultimately can lead to better characterization of developmental problems and psychopathologies.Although our study primarily aims at behaviors related to social competence, future studies may focus more strongly on strategic considerations or motivations for self-control and prosociality. This question has received most attention in the study of motivations for prosocial behavior . ParadigIn sum, we point towards activity and connectivity in the medial prefrontal cortex and the ventral striatum as potential neural differential susceptibility markers. In future research, these markers will be combined with insights from the intervention trial and other differential susceptibility markers  to unravel why some children are more susceptible to environmental influences than others. An important aim will be to test stability and change of neural signals over time in order to contribute to a better understanding of reliability of measurement versus context-dependent change . TogetheEAC and MHvIJ drafted the manuscript. MJBK contributed to the study design and commented on the first draft of this manuscript. All other authors contributed to the design, data collection, analysis and final manuscript and are listed in alphabetical order.


Cognitive impairment and dementia are major medical, social, and economic public health issues worldwide with significant implications for life quality in older adults. The leading causes are Alzheimer’s disease (AD) and vascular cognitive impairment/dementia (VCID). In both conditions, pathological alterations of the cerebral microcirculation play a critical pathogenic role. Currently, the main pathological biomarkers of AD—β-amyloid peptide and hyperphosphorylated tau proteins—are detected either through cerebrospinal fluid (CSF) or PET examination. Nevertheless, given that they are invasive and expensive procedures, their availability is limited. Being part of the central nervous system, the retina offers a unique and easy method to study both neurodegenerative disorders and cerebral small vessel diseases in vivo. Over the past few decades, a number of novel approaches in retinal imaging have been developed that may allow physicians and researchers to gain insights into the genesis and progression of cerebromicrovascular pathologies. Optical coherence tomography (OCT), OCT angiography, fundus photography, and dynamic vessel analyzer (DVA) are new imaging methods providing quantitative assessment of retinal structural and vascular indicators—such as thickness of the inner retinal layers, retinal vessel density, foveal avascular zone area, tortuosity and fractal dimension of retinal vessels, and microvascular dysfunction—for cognitive impairment and dementia. Should further studies need to be conducted, these retinal alterations may prove to be useful biomarkers for screening and monitoring dementia progression in clinical routine. In this review, we seek to highlight recent findings and current knowledge regarding the application of retinal biomarkers in dementia assessment. Dementia is a growing global health concern with increasing prevalence owing to the aging population. The total number of people with dementia is estimated to be in the region of 50 million worldwide and is projected to reach 82 million by 2030 and 152 million in 2050 . S. S137]. Optical coherence tomography angiography (OCTA) is an emerging non-invasive imaging technique that is able to separately visualize the different retinal and choroidal vascular layers without the need for intravenous dye injection . OCTA prStimulation of the retina with flickering light induces a form of neurovascular coupling (NVC)/functional hyperemia which manifests as increases in retinal vessel diameter and dynamic adjustment of blood flow to the retina and optic nerve. This is similar to NVC in the brain, where blood flow is dynamically adjusted to provide increased oxygen and glucose delivery to activated neurons and effective wash-out of toxic metabolites , 162. ThAs NVC responses assessed in the eye correlate with NVC in the brain, early detection of endothelial dysfunction/neurovascular impairment using DVA in the retina may enable earlier non-invasive diagnosis of VCID and AD, allowing time for lifestyle and pharmacological interventions to prevent or delay the pathogenesis of dementia. Several studies have reported reduced flicker light–induced arterial vasodilation in diabetes, hypertension, hyperlipidemia, and obesity . The senWith advancing years, alterations in retinal structure have been observed by histological studies including a reduction in density of photoreceptors, ganglion cells, and pigment epithelial cells . SeveralThe main feature of the aging retinal microvasculature is a progressive loss of complexity with age . SeveralAging adversely affects not only the neuronal tissue but also the microcirculation resulting in hypoperfusion. Decreased oxygen and glucose delivery exert adverse effects on tissues with high metabolic demand including the brain and the retina. It is well known that with advancing aging, cerebral blood flow decreases in older adults . Given tThe first evidence of optic nerve degeneration in AD was reported by Hinton et al. in 1986 . In the Over the past two decades, numerous publications evaluated the ocular OCT characteristics in AD patients. The majority of these reports were cross-sectional studies comparing AD patients with healthy controls. Consistent with previous histological examinations, several studies reported thinning of the peripapillary retinal nerve fiber layer (pRNFL) and significant reduction in macular thickness in AD to age-matched healthy individuals , 194. GiPrevious imaging studies described multifaceted morphological changes in cerebral blood vessels including CAA, decreased vascular density, decreased vessel caliber, increased vessel curvature, and reduced cerebral blood flow in AD brains . Due to Previously published reports demonstrated that patients with AD are more likely to manifest changes in retinal microvascular structure—including less complex retinal vasculature and smaller, more tortuous retinal vessels—compared with age-matched control individuals. These retinal features have been presumed to reflect similar changes affecting the cerebral microcirculation that may contribute to cognitive deterioration. Furthermore, a connection between the presence of clinically visible retinal microvascular alterations and clinical and subclinical white matter lesions on MRI in cerebral small vessel disease was observed .Numerous studies using fundus photography with a semiautomated computer-assisted program have consistently found decreased retinal vascular fractal dimension (FD) indicating a sparser retinal microvascular branching network in association with AD and cognitive impairment , 212. InRetinal vessel tortuosity is a common feature frequently associated with aging and vascular disease. Hammes et al. indicated that increased vessel tortuosity is suggestive of vessel wall dysfunction and blood-retinal barrier damage . AlthougThe relationship between retinal vessel caliber measurements and AD remains controversial in the literature. Cheung et al. and Frost et al. reported retinal venular narrowing in AD—which may be due to collagen deposition in the veins leading to increased venular wall thickness , 218. InA few studies evaluated changes in retinal vascular structure to explore the assumption that fundus image analysis could distinguish between dementia subtypes. de Jong et al. found that larger venular calibers are associated with increased risk of VCID, but not with AD . In the et al. identified peripheral biomarkers, including increased number of drusen deposits, increased venular widening and decreased arterial fractal dimension in AD [The assessment of more peripheral retinal vessels using ultra-wide field retinal images has been suggested to represent a better overall measure of retinal vessel caliber . A recenon in AD .It is important to note that the strength of the relation between retinal vascular changes with cognitive impairment and AD is modest and non-specific—owing largely to the normal variation in retinal vascular parameters and common retinal alterations appearing in vascular diseases . ProspecOver the past few years, studies have been performed evaluating retinal blood flow in AD using OCTA. According to the first report investigating OCTA parameters in AD subjects—presented by Bulut et al.—the superficial retinal capillary vessel density is significantly decreased and the FAZ area is significantly larger in patients with AD compared with normal individuals . It has Life expectancy around the world has steadily increased over the last few decades that is mainly attributed to the advancements of healthcare and lifestyle. Aging is the major risk factor for developing both AD and VCID, whose prevalence is rapidly increasing worldwide. Being a public health concern worldwide, identifying retinal biomarkers of dementia is crucial for early diagnosis as well as evaluating the efficacy of novel therapies. Given the pathophysiological homology between the retina and the brain, evaluating changes in retinal structure and vasculature is a highly promising approach to study both AD and VCID. With the advancements in retinal imaging, retinal structure and blood flow now can be visualized easily and non-invasively. Several studies have reported that retinal structural and vascular alterations occur in AD using OCT and fundus photography with image analysis programs, respectively. In addition, OCT angiography allows assessment of the retinal blood flow without the use of intravenous dye injection. Recently, dynamic functional measures of retinal microcirculation including retinal oximetry and dynamic vessel analysis has been used to provide further valuable insights into cerebral hemodynamics in dementia. It is expected that a combination of OCT and DVA will provide an unparalleled insight into the structural and functional microvascular alterations for the diagnosis of preclinical form of AD prior to clinically detectable cognitive symptoms. Although retinal biomarkers are extremely promising in screening for cognitive impairment and dementia, there is a lack of data regarding their sensitivity and specificity, the most important statistical measures of a diagnostic test. Apart from being non-invasive—compared with the detection of biomarkers using CSF and PET scans—retinal examination is cost-effective and widely available. Because the existing results of retinal biomarkers in AD and VCID diagnosis are highly encouraging, further longitudinal studies are warranted to determine the accuracy of retinal biomarkers in routine screening to identify these patients even in preclinical form before the onset of cognitive symptoms.


R = 0.91), suggesting a surprising degree of temporal stationarity. Data Mechanics visualizations, however, revealed heterogeneous non-stationary among subgroups of animals in the center of the group and herd-level temporal outliers. A repeated measures model recovered inconsistent evidence of a relationships between entry position and cow attributes. Mutual conditional entropy tests, a permutation-based approach to assessing bivariate correlations robust to non-independence, confirmed a significant but non-linear association with peak milk yield, but revealed the age effect to be potentially confounded by health status. Finally, queueing records were related back to behaviors recorded via ear tag accelerometers using linear models and mutual conditional entropy tests. Both approaches recovered consistent evidence of differences in home pen behaviors across subsections of the queue.Sensor technologies allow ethologists to continuously monitor the behaviors of large numbers of animals over extended periods of time. This creates new opportunities to study livestock behavior in commercial settings, but also new methodological challenges. Densely sampled behavioral data from large heterogeneous groups can contain a range of complex patterns and stochastic structures that may be difficult to visualize using conventional exploratory data analysis techniques. The goal of this research was to assess the efficacy of unsupervised machine learning tools in recovering complex behavioral patterns from such datasets to better inform subsequent statistical modeling. This methodological case study was carried out using records on milking order, or the sequence in which cows arrange themselves as they enter the milking parlor. Data was collected over a 6-month period from a closed group of 200 mixed-parity Holstein cattle on an organic dairy. Cows at the front and rear of the queue proved more consistent in their entry position than animals at the center of the queue, a systematic pattern of heterogeneity more clearly visualized using entropy estimates, a scale and distribution-free alternative to variance robust to outliers. Dimension reduction techniques were then used to visualize relationships between cows. No evidence of social cohesion was recovered, but Diffusion Map embeddings proved more adept than PCA at revealing the underlying linear geometry of this data. Median parlor entry positions from the pre- and post-pasture subperiods were highly correlated ( For much of its history, ethological research in livestock has relied on human observers to encode behaviors of interest . While dUnfortunately, the inherent quality of such data imposes practical limitations on the quantity that can be produced. This can restrict both the number of animals utilized in a study and the period of time over which they are observed. The later limitation can overlook important dynamic features of the behavioral patterns under consideration. Restrictions on the number of animals that can be studied, on the other hand, can fundamentally alter the behavioral mechanisms at play in a herd. For example, the linearity of dominance hierarchies are known to change with group size . As comma priori. Such insights must instead be drawn directly from the data itself, but here again, standard visualization tools may not scale to such large datasets.In recent years, livestock sensor technologies have become a popular alternative to visual observation –8. WhileUnsupervised machine learning (UML) tools offer a distinct empirical approach to knowledge discovery that are purpose built for large and complex datasets . WhereasMilking order, or the sequence in which cows enter the parlor to be milked, is recorded in all RFID (Radio Frequency Identification) equipped milking systems, making such records one of the most universal automated data streams to be found on modern dairies. Despite their ubiquity, such records are seldom used to inform individual or herd-level management strategies. This lack of utility, however, has not been for lack of study. Milking order has been the subject of scientific study since 1950's , with eaData for this case study was repurposed from a feed trial assessing the effect of an organic fat supplement on cow health and productivity through the first 150 days of lactation . All aniRaw milk logs were exported from the rotary parlor following each morning milking , and were processed using data wrangling tools available in R version 3.5.1 . To accoThe first 55 days of records were excluded from analyses to allow all animals to enter the herd over the rolling enrollment period and become established in their parlor entry position . To avoiq). To compute these values, the queue was divided into 20 equally-sized segments . For each queue segment, counts were generated to determine how frequently each individual cow had been observed in that range of entry quantiles. Shannon's entropy was then calculated conditional of queue segment (q) using the formula in Equation 1  = 6.83. To visually contrast differences in stochasticity across the queue, the observed entropy values were plotted against the median entry quantile of the corresponding queue segment using the ggplot2 package, with maximum theoretical entropy added as a horizontal reference line , count data was used to recalculate Shannon's entropy conditional on cow ID (c) using Equation 2  = 4.32. Observed entropy and variance values were visually compared using the ggplot2 package  is commonly employed to visualize relationships between observational units in high dimensional datasets. In this approach, redundancy between variables, here each milking record, is captured using either covariance or correlation assessed across all data points, here all animals. An eigenvector decomposition is then used to linearly compress the information contained in the data via rotation of the orthogonal axes. New axes (loadings) are added iteratively such that each new dimension is pointed in the direction of greatest remaining variability until only noise remains . Each da package  was thenWhile PCA provides a computationally expedient means of visualizing high dimensional data, the underlying assumption of linearity is not always appropriate , 27. In plotly package  has here been accounted for by fitting a random effect for each cow, but non-independence between animals has not been accommodated. The results of the diffusion map and data mechanics visualizations did not recover overwhelming evidence of coordinated movements between animals through the queue, which would have signified non-independence due to social cohesion ; however, we both visualized via data mechanics and know intuitively that in this physically constrained system any cow moving forward in the queue must be countered with other cows being forced backwards and vice versa. If this effect extends beyond isolated fluctuations in daily formation of the queue, then the presence of some animals in the herd might systematically dampen or even completely prevent other animals from demonstrating behavioral patterns that they would otherwise display independently or in another herd with a different social composition . This would not only serve to confound the behavioral mechanisms at play, but such cows whose behaviors are suppressed by their herd mates cannot be said to be contributing fully to the model, potentially reducing the effective sample size. This could allow sampling fluctuations to produce misleading statistical inferences, even in this large sample of animals –43.p-value for the significance of the bivariate association. Mutual conditional entropy tests were performed for all significant or marginally significant linear effects for both regression models. While the number of clusters used to discretize the cow attribute and queue records may be specified a priori provided strong biological reasoning or empirical evidence, mutual conditional entropy tests were here preformed on a grid from two clusters up to the highest visible granularity of the corresponding clustering tree, and the optimal metaparameter values selected by minimizing the average marginal rank.UML algorithms cannot recover information about behaviors that were never expressed, and so are also not immune to the biasing effects of non-independence between animals. These tools can, however, provide model-free tests of association that may serve as a sanity check for statistical inferences when degrees of freedom may be uncertain. We explore this option here by again combining modern clustering tools with a flexible information theoretic approach to pattern detection . First, Previous studies seeking to identify factors that predict an animal's parlor entry position have focused primarily on biological drivers of queueing behavior related to productivity, health, and traditional measures of fitness such as age and size . As thisnlme package to fit linear mixed models, with cow fit as a random intercept, against each of the five behaviors recorded by the CowManager platform  and also average body temperature  test to identify significant associations between these two behavioral axes . The fle package .Looking first at the entropy calculations for each segment of the queue visualized in In examining the results of the permutation tests, nearly all animals demonstrated significantly less stochasticity in their entry positions at the standard α = 0.05 significance level as compared with a completely randomized queueing process. Only 3 cows out of 114 overlapped with the empirical distribution of entropy estimates under a randomized queueing pattern, and only 1 cow overlapped when variance was used as the estimator of stochasticity. This suggests that nearly all animals in the herd might contribute some information about the underlying non-random patterns in queue formation to subsequent analyses; however, the amount of information they contribute may not be equal, as there is considerable heterogeneity between cows. Of greater concern, this heterogeneity is systematic, as there are no cows showing high consistency in entry quantile in the center of the queue. If this pattern is not driven by variability in the underlying predictors of queue position, but instead reflects either an underlying behavioral mechanism or something even more fundamental to this system such as the inherent domain constraint , this coFinally, the insights gleaned from these entropy-based visualization techniques agree well with the prior literature. Previous studies have repeatedly determined milk order records to be significantly more consistent than would be expected from a random queuing process using an array of correlation and regression-based approaches –18, 47. a priori.Visual inspection of the scree plot produced from PCA analysis revealed only one significant dimension was recovered from the original 80-dimensional dataset. To visualize the resulting projections, the first two principal components were plotted . Cows apEvaluation of eigenvalues returned by the diffusion map embedding identified five significant dimensions. The 3D visualizations of these axes in While the diffusion map embeddings convey a clear linear geometry, there was also unexplained curvature in the band along which cows were projected. This proved not to be an inherent feature of the data itself but a harmonic artifact imposed by the spectral value decomposition of the graph Laplacian used to deduce the shape of the underlying network between cows . Such a Independent visualization of parlor entry records from each individual cow see  revealedp < 2.2e-16) and a Kendal Tau estimate of 0.74 (p < 2.2e-16). These values are, as expected, higher than the estimates of consistency reported for individual milk order samples  axis, data mechanics identified several days with anomalous queuing patterns. In Looking next at the coarser stratifications of the temporal axis, we also see that pen and pasture observations are not equally dispersed among the column clusters. As the animal (row) axis is more finely stratified to allow for social heterogeneity within the herd, the source of the temporal heterogeneity between these two environments comes into resolution. In Finally, some preliminary insights can be gleaned from the cow attributes added to the row margins of both heat maps. In p < 0.0001). With the model fit to cows with no recorded health events, significant linear associations were recovered for two fixed effects. Cows with higher peak milk yields demonstrated a tendency to enter nearer the rear of the queue , this sample may simply contain too few older cows with low productivity levels by which to disentangle the positive association with peak yield from the negative association with cow age. Alternatively, if a diseased state permanently alters a cow's queueing pattern and if risk of health complications in turn varies with age, then health status may be a lurking variable masquerading as an age effect. In either case, a relatively small number of animals may be unduly influencing statistical inferences.In contrasting the results of these two models, the loss of significant association between entry quantile values and peak yield with the addition of sick animals is perhaps not surprising. If a disease challenge early in the trial curtailed peak lactation in these cows but did not cause chronically deficient production, then the 95th quantile value of milk yield used here to estimate peak lactation level may not adequately reflected the overall productivity of these animals across the duration of this extended trial, obscuring the underlying biological mechanism. The emergence of a nearly significant association between entry quantile and age with the addition sick animals, however, is more difficult to explain. Given that peak yield and age are highly correlated biological parameters . For the full dataset, where the linear effect is marginally significant, the MCE test does not . This suggests that either that age effect is only discernable after adjusting for peak yield or that the association is not robust.Visual examination of predicted queue positions plotted against age and peak yield for both the full dataset see  and healp3,5 = 0.036), but also within the full dataset  where the linear effect was only suggestive. Visualization of the contingency table for this later result revealed no distinctive pattern among the lowest and highest yielding clusters, but a nearly perfect division of roughly 50 moderate-yielding cows into the leading queue cluster. This result suggests that the MCE tests may also be used in mixed modeling analyses to recover non-random patterns that are not well-represented by linear trends. Such a non-linear trend here could belie more complex interaction effects between these or other unmeasured biological drivers of queue position. Alternatively, a multilevel model may be necessary to disentangle complex hierarchical relationships between the drivers of position preference and a cow's ability to assert that preference.Looking next at peak yield, a clear global trend could not be discerned. Among the lower-yielding cows, a group comprised predominantly of heifers, a linear trend is difficult to discern, but amongst older cows a slight positive gradient is perhaps perceptible. Results of the mutual conditional entropy tests not only confirmed this trend among the healthy animals. Group-by-date interaction effects were also significant for activity, high activity, and temperature models (p < 0.05). This suggests that these models should not be simplified to a single cyclical or longitudinal trend, which would allow overall differences between groups to be tested via a single group intercept term. Targeted hypotheses comparing comprehensive trends between groups would instead require formulation of linear contrasts—a daunting task with so many fixed effects terms used to accommodate the high sampling frequency and extended observation period of this dataset. Further, as with the linear models with cow attributes, behavioral synchronization due to social cohesion or compensatory use of physical resources in the pen could again create non-independence between animals in such sensor records. Any such issues in estimation of model degrees of freedom, compounded with the inability to fit behaviorally and empirically compelling correlation and variance models, would only serve to further confound the estimation of appropriate p-values from these models.While the preceding analyses revealed few statistically significant differences at individual time points, collective analysis of days and subsets of the 24 h management cycle would uundoubtedly return statistically significant differences for the broader qualitative trends visually identified via mean plots. Within a linear modeling framework, however, this constitutes no small task. For all of the above models, Wald's tests revealed Group-by-Hour interactions effects to be highly significant components of the model  have been identified as the main driver of delayed entry into the parlor , 17, 51.One potential explanation for these results might be a dominance gradient. Previous studies have found that animals of low social status frequent the rear of the herd in voluntary movements , 52, andAs with previous studies of milk order records, these analyses perhaps raise more questions than answers. As dairy record management systems grow to accommodate an ever wider range data streams, perhaps future work considering more herds from a wider range of management strategies will succeed in further untangling the complex web of explanatory variables at the individual, herd, and farm levels that drive variation in queueing patterns. This dataset has, none the less, demonstrated the utility of unsupervised machine learning tools in ethological studies using sensor platforms to study larger groups of animals over extended periods of time. While these analyses recovered no evidence of social cohesion amongst large or temporally consistent subgroups, information theoretic approaches succeeded in clarifying the underlying pattern of heterogeneity in error variance between animals and also demonstrated an advantage in recovering evidence of non-uniform patterns in temporal non-stationary over basic EDA tools. After incorporating these insights into the structure of subsequent linear models, these model-free tools then showed some capacity to confirm inferential results where probabilistic assumptions were not strictly met, as well as an aptitude for recovering significant associations not captured by a simple linear effect. This flexible clustering-based approach to identifying significant bivariate associations was then easily extended to accommodate two high dimensional behavioral axes, providing equivalent insights to more computationally taxing mixed effect models. While UML approaches are by no means infallible, as seen here with artifacts produced by the spectral embeddings, these analyses have demonstrated that such tools can add value at every stage of the standard hypothesis-driven linear analysis pipeline, and may even offer an advantages over model-based approaches in early-stage exploratory projects. While many new methodological developments are doubtless on the ethological horizon, we hope this algorithmic toolset will provide a meaningful step forwards to meet the challenges of a future defined by ever larger and more complex data.The datasets generated for this study are available on request to the corresponding author.The animal study was reviewed and approved by Colorado State University IACUC (protocol ID: 16-6704AA). Written informed consent was obtained from the owners for the participation of their animals in this study.DM and PP contributed to experimental design and data collection. CM and FH contributed to data analysis. CM contributed to manuscript preparation. All authors contributed to manuscript writing and revisions.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Regulation of stem cell fate is best understood at the level of gene and protein regulatory networks, though it is now clear that multiple cellular organelles also have critical impacts. A growing appreciation for the functional interconnectedness of organelles suggests that an orchestration of integrated biological networks functions to drive stem cell fate decisions and regulate metabolism. Metabolic signaling itself has emerged as an integral regulator of cell fate including the determination of identity, activation state, survival, and differentiation potential of many developmental, adult, disease, and cancer-associated stem cell populations and their progeny. As the primary adenosine triphosphate-generating organelles, mitochondria are well-known regulators of stem cell fate decisions, yet it is now becoming apparent that additional organelles such as the lysosome are important players in mediating these dynamic decisions. In this review, we will focus on the emerging role of organelles, in particular lysosomes, in the reprogramming of both metabolic networks and stem cell fate decisions, especially those that impact the determination of cell identity. We will discuss the inter-organelle interactions, cell signaling pathways, and transcriptional regulatory mechanisms with which lysosomes engage and how these activities impact metabolic signaling. We will further review recent data that position lysosomes as critical regulators of cell identity determination programs and discuss the known or putative biological mechanisms. Finally, we will briefly highlight the potential impact of elucidating mechanisms by which lysosomes regulate stem cell identity on our understanding of disease pathogenesis, as well as the development of refined regenerative medicine, biomarker, and therapeutic strategies. Stem cell fate decisions, including the determination of cellular identity, are intimately linked to gene expression networks with each decision driven by wide-spread transcriptional changes . TranscrCellular metabolism is broadly defined by the numerous biochemical pathways that participate in the processing of nutrients including amino acids, carbohydrates, and lipids, into their primary molecular building blocks along with energy in the form of adenosine triphosphate (ATP). The ATP produced through metabolic pathways is necessary to fuel the myriad of biological processes that take place within a cell to support its growth and viability. Metabolic bioenergetic signaling pathways are closely integrated with organelle-based processes, which together focus on balancing anabolic and catabolic cellular activities . RespectIn addition to the production of ATP, metabolic signaling is now known to exert wide-ranging effects within a cell and has in fact emerged as a primary biological process underlying the regulation of cell fate decisions in a wide range of cell types, including stem cell populations. These impacts are achieved through mechanisms that include regulation of transcription factor expression and localization, integration of metabolic networks with growth factor and developmental signaling pathways, and the production of cell type and context-specific metabolites that permit chemical modification of signaling cascades and epigenetic regulation of DNA and histone proteins . Specifiin vitro pluripotent stem cells (PSCs), including maintenance of their self-renewing state and the initial establishment of induced PSCs (iPSCs) from somatic cells such as fibroblasts. Transition to a glycolytic state from an oxidative one typical of somatic cells is universally required for both the acquisition and maintenance of pluripotency, critical for activation of self-renewal programs and inhibition of differentiation  represents an exception to the paradigm that exit from pluripotency requires reprogramming to an OxPhos-dependent state , as a prMetabolic pathways and the biological processes that fuel anabolic and catabolic activities are partitioned among distinct subcellular locations. Over the past decade, however, it has become increasingly clear that communication between organelles and cytoplasmic signaling pathways is critical for the dynamic regulation of bioenergetic networks that underlies cell and tissue homeostasis (reviewed in 2+), and other ions. These interactions are essential for bioenergetic integrity, and consequently for the regulation of multiple facets of tissue development and maintenance  and the lipid chaperone LBP-8. All three elements of this signaling pathway are structurally or functionally conserved in mammals   family of transcription factors (herein referred to as ‘TFE’), critical regulators of genes that drive lysosome biogenesis and metabolic reprogramming . Additioeceptors . Nucleareceptors . Biochem by OEA) , thus si2+ and iron that function as cofactors for biochemical reactions  mediated through tethering proteins. These connections permit the transport of metabolites and signaling molecules, lipid moieties, and ions like Caeactions . They aleactions . Membraneactions . Despite2+ uptake from the ER. This was shown to be dependent on the mitochondrial fusion protein Mitofusin 2 (Mfn2), and thus is linked to dynamics in mitochondrial structure  divide asymmetrically to control their fate, Lysosomes have long been viewed as the primary effectors of the cellular waste disposal system, functioning to degrade excess or damaged organelles and macromolecules by the greater than 60 hydrolytic enzymes present within their acidic lumen . LysosomLysosomal degradation reduces its substrates to fundamental building blocks of macromolecules including amino acids, sugars, lipids, and nucleic acids. These metabolites are either retained in the lysosome lumen to buffer their cytoplasmic concentrations, or are actively secreted into the cytoplasm by membrane permeases where they are reused by the cell to fuel biochemical and bioenergetic pathways, or exported out of the cell . It is bMetabolic pathways and the cell biological processes with which they integrate are dynamic. Given that cells are regularly exposed to changing environmental conditions, mechanisms to finely regulate the balance between anabolic and catabolic activities are critical for cell viability, proper function, and homeostasis. This coordination is achieved by hard-wired signaling mechanisms that sense the level of available nutrients and other environmental signals like oxygen, energy status, stress markers, and growth factors, and accordingly relay downstream signals through phosphorylation events. The mammalian target of rapamycin complex 1 (mTORC1) and AMP-activated kinase (AMPK) are the primary mammalian nutrient-sensing kinases, and they function in opposition to one another to control the catabolic–anabolic balance. A major breakthrough in our understanding of metabolic coordination, and one that underscored a profound physical connection between metabolic signaling and the lysosome, is that the activity status of these kinases is in fact regulated on the lysosome surface . In the Hyper-active mTORC1 functions at the lysosome to phosphorylate downstream targets that promote anabolic cellular processes including protein translation, ribosome and lipid biogenesis, cell growth, and mitochondrial metabolism . ConversAMP-activated kinase is activated in response to low nutrient levels, when intracellular ATP levels are low and AMP is high, and functions to promote catabolism and inhibit anabolism largely by countering mTORC1 activities . mTORC1 Metabolic signaling pathways centered at the lysosome are in fact important regulators of cell fate transitions. The ability to balance mTORC1 activity is critical for proper stem cell fate decisions between self-renewal and differentiation in development and aging in a number of somatic cell types, with mTORC1 hyper-activation typically driving aberrant lineage differentiation . Loss ofWe and others have additionally found that the capacity to repress the mTORC1 pathway is essential for the reprogramming of both mouse and human somatic cells to iPSCs . This rein vitro differentiation of PSCs to downstream lineages correlates with further metabolic changes . These two lineages are the presumed derivative cell types of the diverse lesions and tumors in tuberous sclerosis patients (TSC2–/– PSCs commit to an NSC or NC fate, we employed RNA-sequencing and functional analysis approaches to identify the primary biological processes at play during the transition from pluripotency to the new cellular identity. An increase in lysosome content, driven by an acute activation of a proteostasis stress response, was evident at very early stages of PSC–NSC induction, but not during NC specification. This was observed in WT cells and was further exacerbated in cells lacking TSC2. Of note, a recent study revealed that cells undergoing NSC specification undergo a reprogramming of protein chaperone networks, which are intimately connected with proteostatic mechanisms; this finding underscores the importance of proteostasis signaling integrity during early NSC development (TSC2–/– cells, and these patterns correlated with alterations in the expression of cell fate markers (Our recent work further implicates lysosome activation as a critical requirement for NSC fate regulation, in the initial determination of neural lineage identity . We devepatients . Seekingelopment . Further markers .TSC2–/– NSCs (The aberrant lysosome activation driven by TSC2-deficiency was transient during neural development but became reactivated with time as NSC cultures were aged, in a manner that paralleled altered expression of cell fate markers . These f–/– NSCs . This de–/– NSCs .Many human disorders, ranging from developmental to aging-induced conditions and various forms of cancer, exhibit aberrant lysosome activity as a known or predicted factor contributing to pathogenic phenotypes. The over 50 rare genetic metabolic conditions under the umbrella of “lysosomal storage diseases” typically present early in life, yet we now know that they share many clinical, pathological and genetic features with age-related neurological conditions, including frontotemporal dementia, Alzheimer’s and Parkinson’s disease . Shared It is therefore clear that the brain, and the neural cell lineage that builds this organ, are highly dependent on the lysosome for proteostasis regulation and is particularly sensitive to developing disease when faced with lysosome dysfunction. This neural lineage proteostasis sensitivity is often attributed to the fact that neurons are highly active biologically but unable to divide and thereby have no progeny through which to dilute protein aggregates and aberrant regulatory machinery. Our recent work and that of others discussed in this review  suggest Hard-wiring of lysosomal signaling in NSCs has implications for understanding susceptibility to neurological disease, as well as the stage-specific drivers of diseases that are associated with changes in markers of cell fate and identity, such as cancer . SimilarMany new and developing therapeutic strategies for cancer are directed toward targeting metabolic vulnerabilities of the tumor. Inhibition of lysosome activity by targeting autophagy signaling, using lysosomotropic agents like bafilomycin or chloroquine derivatives, or degradative capacity and ion transport are popular among these approaches . Yet, deEfforts aimed at elucidating the extent to which lysosome dynamics influence cell fate specification in stem cell populations are likely to yield important therapeutic insights. Using CSCs as an example, an important approach is to discern whether altered lysosome signaling in a given tumor type is an early precipitating event in cell fate and metabolic dysfunction, as we observed in our human stem cell model of tuberous sclerosis , or instLysosomes are complex organelles, with an ever-growing list of associated biological functions with the potential to impact stem cell fate and identity determination . Beyond It is likely that many more functions remain to be uncovered by which the lysosome impacts stem cell fate. For instance, mTORC1 and AMPK are not the only signaling hubs located at the lysosome surface; additionally, there are likely many more mechanisms to be uncovered that contribute to mTORC1-dependent molecular sensing . Moving Regulation of stem cell fate decisions is heavily predicated on the integration of transcriptional and metabolic signaling networks. Our understanding of the metabolic impacts on cell fate have been largely limited to the mitochondria, yet it is becoming increasingly evident that multiple organelles interact with one another in diverse ways to regulate cell fate. The lysosome is now well appreciated as not only the waste disposal center of the cell but as an active and multifunctional player in coordinating metabolic networks; exciting work over the past few years has provided compelling evidence that lysosome-based activities are in fact crucial for regulating cell identity determination and other fate decisions. The lysosome is a multi-functional organelle whose activities and regulatory partners are still being uncovered. Thus, focusing efforts on unraveling the biological impacts of lysosome signaling on cell fate regulation has high potential to significantly impact our understanding of tissue development and aging, disease predisposition and pathogenesis, as well as disease treatment and regenerative medicine strategies.LJ wrote the manuscript and prepared the figures. WS reviewed and edited the manuscript, provided intellectual insights, and acquired funds for publication. Both authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Marakasova and Baranova make a good, incremental step trying to explain the results of our paper, “Analysis of Measles-Mumps-Rubella (MMR) Titers of Recovered COVID-19 Patients” . This is possible and may represent the initial step required to impact the disease development indicated by the correlation we saw between MMR II vaccine persistence and coronavirus disease 2019 (COVID-19) severity.The structures provided would likely represent weak to moderate affinity binding of some antibodies generated by the multivalent vaccine, MMR II. This binding would not provide much activation of local immunity if the weak to moderate affinity antibodies were present at low levels but would likely provide much more activation if a large quantity of low to moderate affinity antibodies were present to yield a high avidity binding situation that would persist long enough to activate monocytes, macrophages, and dendritic cells in the local tissues of the respiratory tract. Epithelial cells also carry FcRn on their surface that can interact with IgG and transport them for intracellular disruption of viral replication . Thus, hVaccination, particularly with multiviral live vaccines, tends to produce many different memory clones with a broad range of affinities. In contrast, natural disease, particularly if severely acute, tends to induce somatic mutation in antibody clones that yields very high affinity clones of memory cells of a narrow specificity. This may contribute to the difference seen between those with antibodies from MMR II and natural disease. The narrow specificity may not provide sufficient recognition of the weakly or moderately comparable targets to induce a cascade effect to slow the SARS-CoV-2 infection.It is possible that measles vaccine-induced T cell memory is partly responsible for the effect leading to the correlation we observed. Only moderate affinity is required for reactivation of T cell memory clones to undergo a few rounds of expansion, leading to production of cytokines and other products that circulate to aid the innate response on local mucosal tissues. The antigen similarity shown in their letter may be sufficient to accomplish this.


An out-of-hospital cardiac arrest (OHCA) occurs when the heart stops maintaining its function to pump blood through the body in an out-of-hospital setting, typically due to cardiac arrhythmia. Our recent analysis of sex differences in OHCA incidence, treatment and survival in a large cohort of OHCA patients in the Netherlands demonstrated several important findings across various age groups . First, A SIR (ventricular tachycardia or ventricular fibrillation) is a very fast heart rhythm resulting in no effective pump function (i.e. blood can no longer circulate around the body). If SIR is not shocked back to normal with a defibrillator, it dissolves within minutes into asystole ('flat line') . At thisRecognition by bystanders may be longer in women with OHCA because signs of impending OHCA may be different. For instance, the symptoms of myocardial infarction (MI), a common cause of OHCA, may not be recognised so quickly in women, as women may have nonspecific symptoms such as fatigue, fainting, vomiting and neck or jaw pain . In contHow do the differences between men and women evolve with increasing age? We observed differences between age groups for OHCA incidence, EMS treatment and survival after OHCA. While increasing age is associated with rising OHCA incidence in both sexes, it brings about an increasing disadvantage suffered by women in receiving EMS resuscitation attempts. This is especially relevant, since the majority of OHCA occurs in patients aged >65 years. The finding that older women are less likely to receive an EMS resuscitation attempt may be explained by the higher life expectancy of women, leading to a higher likelihood of being widowed and/or living alone. Persons living alone are more likely to die unwitnessed, because they have much smaller chances of timely resuscitation treatment. With regards to survival chances, we observed that, among patients with SIR, survival chances were higher in women aged <50 years than in same-aged men. Studies suggested that women of reproductive age had better survival rates than women of higher ages or men, possibly due to elevated levels of female sex hormones . AnotherOur findings may have important implications. In particular, the observation that women have a lower chance on a resuscitation attempt might indicate that initial recognition of OHCA in women is lagging behind. It would suggest that people may be less aware that OHCA can occur as often in women as in men, and that women themselves may not recognise the urgency of their symptoms and seek timely help. This provides the incentive for education campaigns and reorganization of health care, e.g. development of systems for quicker access to resuscitation care for elderly women living alone such as remote monitoring systems or provision of more automated external defibrillators at residences of single elderly women.


The mammalian hippocampus generates new neurons that incorporate into existing neuronal networks throughout the lifespan, which bestows a unique form of cellular plasticity to the memory system. Recently, we found that hippocampal adult-born neurons (ABNs) that were active during learning reactivate during subsequent rapid eye movement (REM) sleep and provided causal evidence that ABN activity during REM sleep is necessary for memory consolidation. Here, we describe the potential underlying mechanisms by highlighting distinct characteristics of ABNs including decoupled firing from local oscillations and ability to undergo profound synaptic remodeling in response to experience. We further discuss whether ABNs constitute the conventional definition of engram cells by focusing on their active and passive roles in the memory system. This synthesis of evidence helps advance our thinking on the unique mechanisms by which ABNs contribute to memory consolidation. The hippocampal dentate gyrus (DG) is one of a few regions in the mammalian brain where new neurons are generated throughout the lifespan Altman, . Adult n2+ imaging techniques along with the development of miniaturized fluorescent microscopes , which may serve as a temporal reference for the encoding, processing, and decoding of memory traces. For example, consistent with the idea that theta rhythm may synchronize pre- and postsynaptic activity at entorhinal-DG synapses to induce long-term potentiation (LTP) following Hebbian rules  in the DG correspond to behaviorally relevant populations of neurons that are activated during both learning and memory retrieval  How does learning affect the functional connectivity of ABNs, particularly with inhibitory neurons? Electrophysiological recordings of ABNs during optogenetic manipulation of inhibitory neurons may shed light on this issue. (2) Are ABN spikes coupled to DG oscillations? Is this coupling affected by learning? Multielectrode recording and optogenetic tagging of ABNs may clarify their spiking dynamics, similar to techniques employed for mossy cells in the DG (Senzai and Buzsáki, Conceptualization and Writing—Review & Editing: PV and MS. Visualization and Writing—Original Draft: PV. Funding Acquisition, Resources, and Supervision: MS. All authors discussed and approved the manuscript.The authors declare that this study received funding from GSK Japan. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


R*s, are key traits that link individual physiological demands to the outcome of competition. However, a major question remains unanswered—to what extent are species’ competitive traits able to evolve in response to resource limitation? To address this knowledge gap, we performed an evolution experiment in which we exposed Chlamydomonas reinhardtii for approximately 285 generations to seven environments in chemostats that differed in resource supply ratios  and salt stress. We then grew the ancestors and descendants in a common garden and quantified their competitive abilities for essential resources. We investigated constraints on trait evolution by testing whether changes in resource requirements for different resources were correlated. Competitive abilities for phosphorus improved in all populations, while competitive abilities for nitrogen and light increased in some populations and decreased in others. In contrast to the common assumption that there are trade-offs between competitive abilities for different resources, we found that improvements in competitive ability for a resource came at no detectable cost. Instead, improvements in competitive ability for multiple resources were either positively correlated or not significantly correlated. Using resource competition theory, we then demonstrated that rapid adaptation in competitive traits altered the predicted outcomes of competition. These results highlight the need to incorporate contemporary evolutionary change into predictions of competitive community dynamics over environmental gradients.Competition for limiting resources is among the most fundamental ecological interactions and has long been considered a key driver of species coexistence and biodiversity. Species' minimum resource requirements, their This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’. Contrary to our expectations, salt stress did not increase the number of fixed mutations. Selection treatment had no significant effect on the total number of fixed mutations , but the effect of the ancestor was highly significant .Genetic differences between the ancestral and descendant populations were identified by whole genome re-sequencing. The presence or absence of single nucleotide polymorphisms (SNPs) identified within the populations were compared between the ancestors and descendants for each selection treatment. The number of variable SNPs ranged from 396 to 582 , roughly corresponding to mutation fixation rates of 1.25 × 10(e)P* and N* such that they could possibly coexist. While neither descendant population could coexist with Ancestor 3, the two descendant populations could coexist with one another at a supply point illustrated as a yellow dot. In their ancestral state, out of all pairwise combinations of our five ancestor populations, RCT [The divergence in minimum resource requirements and consumption vectors among populations of the same ancestor selected in different environments  was suffons, RCT  predicts4.C. reinhardtii often adapted to resource limitation by reducing their minimum resource requirements. When exposed to high salt, populations evolved higher salt tolerances. Not only could populations respond adaptively to new environments but they could also adapt within approximately 285 generations. While we observed gleaner–opportunist trade-offs, we did not find evidence for trade-offs in competitive abilities for different resources. Instead, adaptive changes in competitive ability for one resource were often positively associated with improvements in competitive ability for another. Since the ancestral and descendant populations were maintained under identical conditions when quantifying their traits, the changes we observed were heritable. We documented genetic changes as fixed SNPs in each of the descendant lineages , which likely contributed to the heritable phenotypic changes we observed. Owing to a lack of annotational information on the genes in which mutations were fixed, our ability to infer the connection between genotype and phenotype is limited. Future studies investigating the roles of gene expression regulation and epigenetic modification in contributing to heritable trait change of resource requirements would provide additional insights [Resource competition is among the most important processes structuring ecological communities , but cominsights .P* was large (up to 85% decrease relative to ancestors), while the adaptive change in N* was more limited, and change in I* was sometimes maladaptive. It is possible that the lack of adaptive change in N* and I* was because the ancestral populations in our experiment were already at or near a fitness optimum. Although there were no consistent differences in the magnitude of adaptive trait changes when comparing the genotypically diverse populations to the isoclonal populations, in all selection environments the direction of trait change was adaptive in the genotypically diverse populations. However, the absence of replicated genetically diverse populations within each treatment limits our ability to generalize the effects of genotypic diversity on evolutionary outcomes in a given environment.The magnitude of evolutionary change varied among resource-competition traits. When considering all the populations together, adaptive change in Trade-offs in resource-use traits have been invoked to explain changes in dominance across supply ratio gradients and the coexistence of as many species as resources ,19. TradR* at macroevolutionary scales are the result of major metabolic innovations across clades, breaking these metabolic linkages [R* or fitness at multiple evolutionary endpoints, fitness may continue increasing under directional selection for tens of thousands of generations [No evidence for trade-offs in competitive abilities for different resources is in contrast to observations of negative multivariate correlations observed on macroevolutionary timescales . This rulinkages . It is alinkages . A thirdlinkages . This iserations . Howevera), and positive correlations between competitive abilities for different resources . The changes in resource ratios and salt levels represented in our different selection environments are on the same order of magnitude as gradients of resource ratios and salinity in natural environments [Traits relevant to competitive ability, such as cell size, are known to change as a result of phenotypic plasticity and evolutionary adaptation . We haveronments . This meronments .Our results are directly relevant to understanding eco-evolutionary feedbacks in competitively structured communities. Theory predicts that species converge in their resource-use traits when competing for essential resources ,16. ThisUnderstanding patterns of biodiversity and coexistence requires accounting for past and current evolutionary changes in species’ competitive traits. While macroevolutionary patterns show trade-offs in species' resource-use traits, we found that positively correlated adaptive trait changes drive within-species responses to resource limitation, altering the expected outcome of competition. Such microevolutionary changes in species’ competitive abilities should be considered if we are to improve our predictions of competitive interactions and community dynamics in a changing world.