For this purpose, a complete set of methods was used to comprehensively analyze mitophagy levels, mitochondrial reactive oxygen species (ROS), mitochondrial membrane potential (MMP) and the mitochondrial mass (MM) of subsets of lymphocytes. It is expected that this will provide a complete set of standards, and drawing the mitochondrial metabolic map of lymphocyte subsets at different stages of differentiation and activation.Mitochondria are mainly involved in ATP production to meet the energy demands of cells. Researchers are increasingly recognizing the important role of mitochondria in the differentiation and activation of hematopoietic cells, but research on how mitochondrial metabolism influence different subsets of lymphocyte at different stages of differentiation and activation are yet to be carried out. In this work, the mitochondrial functions of lymphocytes were compared at different differentiation and activation stages and included CD8+ T cell, a relatively higher level of mitochondrial metabolism was noted for naive CD4+ T cells. Finally, from the CD8+ T cell subsets, CD8+ Tcm had relatively high levels of MM and MMP but relatively low ones for mitophagy, with effector T cells displaying the opposite characteristics. Meanwhile, the autophagy-related genes of lymphoid hematopoietic cells including hematopoietic stem cells, hematopoietic progenitor cells and lymphocyte subsets were analyzed, which preliminarily showed that these cells were heterogeneous in the selection of mitophagy related Pink1/Park2, BNIP3/NIX and FUNDC1 pathways. The results showed that compared with CD4+ T, CD8+ T and NK cells, B cells were more similar to long-term hematopoietic stem cell (LT-HSC) and short-term hematopoietic stem cell (ST-HSC) in terms of their participation in the Pink1/Park2 pathway, as well as the degree to which the characteristics of autophagy pathway were inherited from HSC. Compared with CLP and B cells, HSC are less involved in BNIP3/NIX pathway. Among the B cell subsets, pro-B cells inherited the least characteristics of HSC in participating in Pink1/Park2 pathway compared with pre-B, immature B and immature B cells. Among CD4+ T cell subsets, nTreg cells inherited the least characteristics of HSC in participating in Pink1/Park2 pathway compared with naive CD4+ T and memory CD4+ T cells. Among the CD8+ T cell subsets, compared with CLP and effector CD8+ T cells, CD8+ Tcm inherit the least characteristics of HSC in participating in Pink1/Park2 pathway. Meanwhile, CLP, naive CD4+ T and effector CD8+ T were more involved in BNIP3/NIX pathway than other lymphoid hematopoietic cells.Of all lymphocytes, B cells had a relatively high mitochondrial metabolic activity which was evident from the higher levels of mitophagy, ROS, MMP and MM, and this reflected the highly heterogeneous nature of the mitochondrial metabolism in lymphocytes. Among the B cell subsets, pro-B cells had relatively higher levels of MM and MMP, while the mitochondrial metabolism level of mature B cells was relatively low. Similarly, among the subsets of CD4This study is expected to provide a complete set of methods and basic reference values for future studies on the mitochondrial functions of lymphocyte subsets at different stages of differentiation and activation in physiological state, and also provides a standard and reference for the study of infection and immunity based on mitochondrial metabolism. In this case, the subset of CD8+ T cell include effector CD8+ T, effector memory CD8+ (CD8+ Tem) and central memory CD8+ T (CD8+ Tcm), while the subset for CD4+ T cells include nTreg cells, memory CD4+ and naive CD4+ T cells  mice were maintained in the animal facility of the Institute of Hematology. All experiments involving animals were carried out according to the animal care guidelines with approval of the Institutional Animal Care and Use Committees of the State Key Laboratory of Experimental Hematology.+ T, CD4+ T, B and Natural Killer cells (NK) as well as their subsets  were obtained from the flushed bone marrow of 6-8-week-old mice . For this purpose, cell concentrations were adjusted to 5×10Single-cell transcriptome data for hematopoietic stem cells (HSCs), multipotent progenitor cells (MPPs), common lymphoid progenitor cells (CLPs), and lymphocytes of mouse bone marrow were extracted from the NCBI database (GSE77098). This was followed by an analysis of nine genes related to mitophagy in blood cells to determine their expression levels.For all flow cytometry data, the mean fluorescence intensity and standard deviation (SD) of each channel were determined. For the t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) diagrams, cells for which protein expression was similar are close, while highly interconnected nodes cells represent those having similar phenotypes in order to visualize different subsets of cells. A heat map or a color dimension overlaid on the t-SNE or UMAP diagrams show the final cell classification. In the t-SNE and UMAP diagrams, the proximity of cells reflects their distance in the high-dimensional space.P-values of < 0.05. The GraphPad Prism 6 software were used for all graphical representations.Data processing was carried out with the SPSS 26.0 statistical software package. Normally-distributed data were presented as the mean ± SD, with the results compared using ANOVA. Groups with a uniform variance or an uneven one were compared by applying the LSD method or Tamhane’s T2 method respectively. For non-normally distributed data, the results were expressed as median with the interquartile range. In addition, with the distribution being non-normal in this case, groups were compared using the non-parametric Kruskal-Wallis test. For all statistical tests, significant differences were indicated by + T cells, with the lowest level obtained for CD8+ T. More specifically, compared with CD8+ T cells, CD4+ T cells had significantly higher levels of MM, MMP and ROS. Similarly, B cells had the highest level of MMP (P < 0.001) as well as a significantly higher mitophagy level compared with CD4+ and CD8+ T cells, with NK cells also having a significantly higher mitophagy level than CD8+ T cells . Similarly, a significantly higher expression level was noted for ST-HSC compared with CD8+ T cells (P < 0.001), while in the case of B, Optn expression was significantly higher than for CD4+ T and CD8+ T cells (P < 0.01). The other gene, Tax1bp1, encodes an autophagy receptor that connects ubiquitin to the membrane of an autophagosome membrane during the selective autophagic clearance of damaged mitochondria. In this case, a significantly lower expression level of this gene was noted for CD4+ T compared with LT-HSC, ST-HSC and MPP (P < 0.01). Altogether, the results suggested that out of the four lymphocytes, B cells were more similar to LT-HSC and ST-HSC in their level of involvement in the Pink1/Park2 pathway as well as in terms of their greater similarity to the autophagy pathway characteristics of HSC. In contrast, CD4+ T, CD8+ T and NK cells were less involved in the autophagy pathway and inherited less of the characteristics of HSC. For the BNIP3/NIX pathway, the expression level of Bcl2 was significantly lower in LT-HSC and ST-HSC compared with CLP and B cells (P < 0.05), thus indicating a lower involvement of HSC in this particular pathway. The bioinformatics and statistical analyses of these results showed that transcription was heterogeneous and subgroup-specific in hematopoietic stem progenitor cells and lymphocytes, with the expression of autophagy genes, in particular, being significantly heterogeneous among cell populations.Statistical analysis of the expression levels of autophagy-related genes in lymphoid cells at different stages of differentiation showed that + T and CD8+ T cells, with B cells having the lowest level (P < 0.001). In lymphocytes, the fact that B cells had higher levels of mitochondrial functions but lower SSC levels indicate a significantly lower number of organelles such as ribosome, Golgi apparatus, endoplasmic reticulum and lysosome in B cells.Side scatter characteristics (SSC) was used in order to characterize the number of organelles in lymphocytes as an indicator of the MM of hematopoietic cells. SSC reflects cells’ granularity, that is, the complexity of cell organelles in terms of their types and numbers and the SSC results of lymphocytes and their different subsets are shown in P < 0.001), thus indicating that the organelle content was higher in pro-B. Finally, results of mitophagy showed that, of all B cell subsets, pre-B had the highest mitophagy level while mature B had the lowest one. These results show that, compared with the relatively primitive subpopulation, mitophagy levels were lower in differentiated B cells . As a serine/threonine kinase, Pink1 can specifically locate depolarized mitochondria for activating parkin through ubiquitin phosphorylation. The recruitment of autophagy receptors subsequently induces mitophagy. Pink1 expression was significantly lower in ST-HSC compared with immature B cells (P < 0.05), while that of Tax1bp1 was significantly lower in pro-B in comparison with LT-HSC, ST-HSC, MPP and pre-B (P < 0.01). Thus, it appeared that, among the subsets of B cells, pro-B cells inherited the least characteristics of HSC in terms of their involvement in the Pink1/Park2 pathway. For the BNIP3/NIX pathway, Bcl2 was significantly more expressed in CLP compared with LT-HSC, ST-HSC, pro-B, pre-B and immature B cells (P < 0.01), hence indicating that CLP was strongly involved in this pathway . Therefore, the results reflected the heterogeneity in terms of organelle numbers.UMAP, t-SNE and FlowSOM analyses indicated that phenotypic differences allowed CD4+ T cell at different differentiation and activation stages indicated that Optn was more highly expressed in LT-HSC and ST-HSC compared with nTreg, memory CD4+ T and naive CD4+ T cells (P < 0.05). In addition, nTreg had a significantly lower Tax1bp1 expression level than LT-HSC, ST-HSC and MPP (P < 0.01), although that of ST-HSC was significantly higher compared with naive CD4+ T cells (P < 0.01). These results suggest that, of all subsets of CD4+ T cells, nTreg cells inherited the least characteristics of HSC in terms of their participation in the Pink1/Park2 pathway. Regarding the BNIP3/NIX pathway, Bcl2 expression was significantly higher in naive CD4+ T cells in comparison with LT-HSC and ST-HSC cells (P < 0.01), thus showing that in a similar way to CLP, the former was more involved in the BNIP3/NIX pathway , hence indicating that active cells were of greater complexity and had a higher number of organelles.UMAP, t-SNE and FlowSOM analyses showed that CD8+ T cell at different differentiation and activation stages indicated that Optn was significantly more expressed in LT-HSC and ST-HSC compared with naive CD8+ T and CD8+ Tcm (P < 0.05), with CD8+ Tcm having a significantly lower level of Tax1bp1 expression in comparison with LT-HSC, ST-HSC, MPP, CLP, naive CD8+ T and effector CD8+ T (P < 0.05). These results show that CD8+ Tcm inherited the least characteristics of HSC in terms of their participation in the Pink1/Park2 pathway, especially when compared with CLP and effector CD8+ T cells. For the BNIP3/NIX pathway, Bcl2 was significantly more expressed in naive CD8+ T and effector CD8+ T cells compared with LT-HSC cells (P < 0.01), thus indicating that, in a similar way to CLP, the former was more involved in the BNIP3/NIX pathway , reflecting the strong mitochondrial functions of CD4+ T cells. This phenomenon may be related to a change in the mitochondrial content of T cells during lineage development. During the process of differentiation, T cells turn into a metabolically active state characterized by “increased nutrient intake, increased glutamine decomposition and increased glycolysis metabolism” to meet the demand for active proliferation. T cells also increase the mitochondrial pool, with the mitochondrial content increasing accordingly. In the study of immune cells, it was found that ROS played a very important role in the process of T cell differentiation. The high concentration of ROS in the environment was conducive to the production of IL-2 and IL-4, promoting Th2 differentiation and prolonging Th2-mediated immune response. The corresponding low concentration of ROS promoted the differentiation of Th1 and Th17. In addition, some studies also showed that in CD8+ T cells, low MPP showed enhanced persistence in vivo compared with high MMP. By activating CD8+ T cells, the proliferation resulting from low membrane potential is less than that induced by CD8+ T with high membrane potential. CD8+ T cells can also enhance autoimmunity and greater anti-tumor effects. The increase of MMP is helpful to promote the secretion and function of effector cytokines in various lymphocyte lineages. For example, in CD8+ T cells, high MPP displayed increased oxidative stress, DNA damage response, cell cycle arrest and T cell failure, which altogether may lead to T cell apoptosis. On the other hand, low MMP is more effective in combating oxidative stress, protecting against DNA damage and resisting apoptosis. Therefore, the differences between CD4+ T cells and CD8+ T cells at MM, MMP and ROS levels may indicate the heterogeneity of lineage development  and central memory T cells (Tcm) not only participate in the maintenance of an immune cell bank, but also play an important role in immune response . Among tStudies have shown that there is a dynamic balance in the MM of cells, with mitochondrial distribution, arrangement, numbers, size and morphology being different in cells which are at different stages of differentiation and activation –36. MMP + T and CD4+ T). In B, CD8+ T and CD4+ T subpopulations, pro-B, nTreg and effector CD8+ T cell populations displayed greater heterogeneity than other cells within the same subpopulation  was stronger than for adaptive immune cells . In the process of immune response, the energy supply pathway of lymphocytes changes, and the morphology as well as dynamics of mitochondria also change  in the bone marrow, while lymph nodes and spleen, which are sites of immune response, have a higher proportion of mature lymphocytes , before being presented on the cell surface in the form of MHC complex and recognized by immunocompetent lymphocytes. After recognition and binding of antigen peptides with BCR, TCR and other lymphocyte surface receptors, a series of signal transduction cascades occur in the lymphocytes, and these ultimately enable lymphocytes to undergo appropriate biological changes for immune response. During the immune response, different lymphocytes play different biological functions, and this requires specific changes in the mitochondrial functions of different types of lymphocytes. T cells differentiate into CD4et cells .+ T helper cells which is mainly regulated by the generation of ROS necessary for NFAT, NF-kB and proximal TCR signal transduction. For example, compared with Th17 cells, the oxidative phosphorylation level of Treg increases and the glycolytic flux decreases. Similar to T cells, B cells also experience a major transformation in their metabolic mode as they switch from their initial resting state to proliferating cells. After binding with antigens, B cells greatly enhance glucose and glutamine metabolism during cloning and amplification. BCR stimulates the release of calcium ions into the cytoplasm, promotes the production of ROS in mitochondria and allows the activation of downstream signal pathways. In this case, the level of ROS production affects the activation of downstream signaling pathways. During antigen presentation, NK cells promote various biological processes at the molecular level by upregulating glycolysis and oxidative phosphorylation. Generally speaking, resting mature NK cells maintain their cell homeostasis mainly through oxidative phosphorylation. When they are affected by proinflammatory cytokines such as IL2 and IL12, they display a strong upregulation of glycolysis and oxidative phosphorylation pathways , granulocyte subsets  and erythroid cell subsets . This will add to the current understanding of the mitochondrial functions of hematopoietic cells.The heterogeneity of mitochondrial functions are important for lymphoid hematopoietic differentiation. In this work, to ensure uniformity, each mitochondrial feature was detected by using the same flow cytometer at the same time. The voltage of the photomultiplier tube of the target fluorescence channel was also consistent in each flow template, with potential interference from other fluoresceins on the target fluorescence channel eliminated by regulating fluorescence compensation regulation. In this way, the mitochondrial functions of 14 main types of lymphocytes were determined at different differentiation and activation stages simultaneously. This study compared the mitochondrial metabolism of different lymphocytes and their subsets to provide a complete set of methods and standards for analyzing the mitochondrial mitophagy, ROS, MMP and MM levels of hematopoietic cells, Furthermore, mitochondrial metabolic maps of lymphocytes were drawn at different stages of their differentiation and activation while single cell sequencing technology allowed the heterogeneity of the mitochondrial autophagy pathway, as inherited from lymphoid hematopoietic cells, to be analyzed. The current results provide a standard and reference for future studies involving mitochondrial metabolism in subsets of myeloid cells, especially since these functions are also closely related to the maintenance of hematopoietic homeostasis. Finally, this study may serve as a reference in the study of tumor and aging-related biomarkers based on mitochondrial metabolism.+ T lymphocytes, CD4+ T lymphocytes, B lymphocytes, NK cells as well as their subsets. A complete set of methods was used to comprehensively analyze mitophagy levels, ROS, MMP and MM of subsets of lymphocytes. Of all lymphocytes, B cells had a relatively high mitochondrial metabolic activity which was evident from the higher levels of mitophagy, ROS, MMP and MM, and this reflected the highly heterogeneous nature of the mitochondrial metabolism in lymphocytes.In this work, the mitochondrial functions of lymphocytes were compared at different differentiation and activation stages and included CD8+ T, CD8+ T and NK cells, B cells were more similar to LT-HSC and ST-HSC in terms of their participation in the Pink1/Park2 pathway, as well as the degree to which the characteristics of autophagy pathway were inherited from HSC.Meanwhile, the autophagy-related genes of lymphoid hematopoietic cells including hematopoietic stem cells, hematopoietic progenitor cells and lymphocyte subsets were analyzed, which preliminarily showed that these cells were heterogeneous in the selection of mitophagy related Pink1/Park2, BNIP3/NIX and FUNDC1 pathways. The results showed that compared with CD4The original contributions presented in the study are included in the article/The animal study was reviewed and approved by the Institutional Animal Care and Use Committees of the State Key Laboratory of Experimental Hematology.HL, WF, and WY contributed equally to this work. YZ, YG, and XK conceived and directed the project; HL and WF performed the experiments; HL, WF, WY, ZC, XK, and EL analyzed the data; HL wrote the manuscript. WF, WY, ZC, XK, EL, FS, YG, and YZ contributed to the discussions and comments on the paper. All authors contributed to the article and approved the submitted version.This work was supported by grants from National Natural Science Foundation of China , Tianjin Science and Technology Planning Project (No. 18ZXXYSY00010) and CAMS Innovation Fund for Medical Sciences (2022-I2M-2-003). This work was supported funded by Tianjin Key Medical Discipline  Construction Project (No. TJYXZDXK-006A).All authors kindly thank the core facilities of State Key Laboratory of Experimental Hematology, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College for the technical assistance.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


After exploration, words were presented while participants performed a deep or shallow encoding task. Incidental memory was quantified in a surprise test. Results showed that participants in the deep encoding condition remembered more words than those in the shallow condition, while novelty did not influence this effect. Interestingly, however, children, adolescents and younger adults benefitted from exploring a novel compared to a familiar environment as evidenced by better word recall, while these effects were absent in older adults. Our findings suggest that the beneficial effects of novelty on memory follow the deterioration of neural pathways involved in novelty-related processes across the lifespan.Exploration of a novel environment has been shown to promote memory formation in healthy adults. Studies in animals have suggested that such novelty-induced memory boosts are mediated by hippocampal dopamine. The dopaminergic system is known to develop and deteriorate over the lifespan, but so far, the effects of novelty on memory across the lifespan have not yet been investigated. In the current study, we had children, adolescents, younger, and older adults ( Also events occurring in the temporal vicinity of novelty exploration are relevant, as these may relate to the requirements or consequences of exploring that environment.Do you remember what you had for breakfast during your holiday abroad last year? And do you remember what you had for breakfast the day after getting back? Chances are that you have recollection of your holiday breakfast, but not of the one you had at home. Although both events are almost equally distant in time, the breakfast you had in a familiar environment was less memorable than the one you had in an unfamiliar holiday location. From an evolutionary perspective it makes sense that learning is promoted around the time that novel environments are explored. When visiting a new place, it is crucial to learn about the circumstances of danger and reward, to optimize chances of avoiding danger and finding rewards in the future4. Animal work has further suggested that the effects are dependent on hippocampal dopamine that can have two potential sources: One being the ventral tegmental area (VTA) and the other being the locus coeruleus  scenes before performing a word learning task 5 min later10. Commensurate with the findings in animals that suggest that novelty can promote memory, it was observed that participants recollected more words on this unrelated task, 24 h later after being exposed to novel rather than familiar stimuli. This study observed effects of novelty on consolidation, but also on encoding. Previous neuroimaging work has suggested that co-activation of the hippocampus and dopaminergic midbrain support successful encoding  it is possible that novelty may mediate memory through effects on encoding or consolidation10. The study by Fenker et al.10, however, contrasts with the previous work in animals that investigated effects of novelty on memory, in that it employed images of novel scenes rather than novel environments. More akin to the studies in rodents, one study used 3D immersive novel and familiar environments by employing virtual reality20. In a within-subjects design, participants explored a novel environment on one day and a previously familiarized environment on a different day, before performing a word learning task. It was found that exploration of a novel environment improved recall, but not recognition in a memory test shortly later.Relative to the work in animals, however, research on the effects of novelty on memory is lagging in humans11. Similar beneficial effects of novelty have been found on visual memory in adolescents, suggesting that experiencing novelty can have a generalizable effect on long-term memory21. In line with the work in healthy adults20, one previous study employed spatial novelty, comparing effects in children and adolescents with attention deficit hyperactivity disorder (ADHD) and a typically developing control group22. Findings from this study suggest that exploration of a virtual novel environment improved free recall on a word learning task in children and adolescents with ADHD, but not in typically developing children. The authors suggested that the lack of positive effects in the control group may be explained by novelty only improving weak memory traces, which may have been more prevalent in the children with ADHD due to general learning impairments, but the role of memory strength has not yet been experimentally investigated in humans.Not only novel scenes and spatial novelty have been shown to have benefits on memory. One study in elementary school children found that experiencing a novel but not familiar science or music lesson 1 h before or after reading a story improved memory of the story30, and one previous study found that children respond stronger to stimulus novelty than adults, as evidenced by faster responses to an auditory target when a novel rather than familiar image was shown31. Changes in the response to novelty across the lifespan are supported by structural and neuroimaging studies that have suggested an age-related degeneration of the substantia nigra/ventral tegmental area . In line with this suggestion, a recent study in young adults suggested that active exploration of novel environments may indeed be required, as only active exploration, but not passive novelty exposure enhanced word recall37. Novelty-exposure interventions have been argued to have the potential to counteract or slow-down age-related memory decline32, but as the influence of age remains underinvestigated it is currently unclear whether the beneficial effects of novelty on memory as discussed above are also present in older adults.Notwithstanding these prior indications of differences between children and adults, the effects of spatial novelty on memory across the lifespan has not been investigated systematically, and it thus remains unclear whether age influences these effects. Psychophysiological studies have suggested that the topology and size of the novelty-induced event-related components change with agingn = 439) including children (8–11 years), adolescents (12–17 years), younger adults (18–44 years), and older adults  that they could freely explore. They then explored the same (familiar) or a novel environment, after which they were shown a list of words. One group of participants performed a deep encoding task , while another group of participants performed a shallow encoding task (“is the first letter of the shown word open or closed?”). After a short distraction task, word recall and recognition, and memory for encountered landmarks during exploration was tested. Participants also filled out a novelty seeking (NS) questionnaire40.In the current study we tested the effects of novelty on memory over the lifespan, in a relatively large sample (43). We furthermore expected that these effects would be stronger in adolescents and younger adults as compared to children and older adults, since dopaminergic functioning rises and declines with age38. As novelty has been shown to especially promote encoding of weak memory traces in animals44, we explored whether the boosting of novelty would be stronger for participants who performed the shallow rather than deep encoding task5. We furthermore expected that exploration behavior would be positively linked to subsequent word recall, via putative dopaminergic modulation32.We expected that novelty exploration would promote word recall but not recognition (cf. 25 and28). Forty-five participants were excluded: 17 participants were excluded because of administrative issues , seven due to technical issues , seven because of language issues , six because they worked together or received help from a parent, five participants because they did not finish the tasks in sequence , and two participants because they talked on the phone during the word learning task. As such, 439 participants were included in the main analyses (401 performed the task in Dutch and 38 in English). As the landmark test did not run on all laptops due to technical issues, the number of included participants that completed this task was only 331. Participants were classified as children , adolescents , younger adults  or older adults  based on their age (and presumed associated differences changes in dopaminergic functioning:46). Supplementary Information (SI): Appendix 1 shows demographics and the distribution of participants over age groups and conditions. Participants in the first testing week performed a word learning task with a deep encoding, and participants in the second week performed a shallow encoding task. For participants within each age-group, age distributions were similar across the different novelty and level of processing conditions . Also sex distributions were similar over conditions .A total of 487 visitors of the NEMO Science Center in Amsterdam aged 8 years or older volunteered to participate in this study. Data was collected during a 2-week Science Live exhibition, during which we tested all visitors interested in volunteering during all opening hours of the NEMO Science Center. While this somewhat restricted our control over the age and the total number of participants, it yielded a final sample size that largely exceeded that of prior studies  of Leiden University, the Netherlands. All procedures were in line with the Declaration of Helsinki , and followed relevant COVID-19 guidelines and regulations.Throughout all procedures the experimenters were wearing a mask and gloves as a safety regulation regarding the COVID-19 pandemic. For data collection we used six laptops in two spacious testing rooms that allowed for social distancing (> = 1.5 m). The experimenter stayed in the testing room throughout the entire procedure to start the tasks and to answer questions. The entire experimental procedure took approximately 15–25 min.Data was collected at the NEMO Science Center in Amsterdam. Upon arrival, participants were asked to disinfect their hands as part of the COVID-19 protocol. Before participation, participants or their parents read the information letter and were given the opportunity to ask questions. After giving written informed consent, the participants were seated before they performed a series of tasks on a laptop.47, the landmark task and NS questionnaire were created using E-Prime 3.0 software .The VEs were created using Unity Version 2017.2.21f1 , and were matched in size, path length, and number of intersections. Both VEs consisted of fantasy islands with unusual landmarks (such as a slot machine) at intersections or road endpoints, including land and a body of water  and eleven words referred to a non-living thing . Similarly, four words started with a closed letter  and eleven with an open letter .For the word learning task fifteen Dutch neutral nouns were chosen from the CELEX lexical database and translated to English for non-Dutch speakersParticipants were reminded of the response keys and task during the encoding, recall and recognition phase of the word learning and landmark tasks. The response keys were shown below the word, in the location corresponding to the keyboard, and in the semantic task the response keys were further accompanied by the picture of a cow (to indicate a living thing) and a chair (to indicate a non-living thing). These reminders were included to lift the working memory load, especially because this otherwise could have made the task disproportionally difficult for the younger children.Landmarks were objects from the Unity Asset store, and included a wide range of easily recognizable objects, such as an airplane and desk chair. Pictures of the landmarks presented on a grey background were used in the landmark memory test. During this test also lures were presented, which consisted of objects that were not part of either of the two VEs.familiarization phase, participants explored the VE for 3 min. After exploration, they were asked to indicate their happiness  and arousal  on a visual analogue scale (VAS) with Self-Assessment Manikins49. They could use the number keys to indicate their answers, and completing the ratings took less than 1 min.Participants received scripted verbal instructions regarding how to navigate through the VE. The ‘W’ key  could be used to move forward, and the mouse could be used to look around and determine heading direction. The space bar could be used to jump, although there was no function in jumping, as one could not jump on top of things. Participants were instructed that they could navigate freely but should try to stay on the paths. During the first second exploration phase participants explored either the same  or a new VE for another 3 min . After this exploration, participants were asked to rate their happiness and arousal levels again on the same two VAS as before the first exploration. See Fig. During the word task, instructions were shown on the screen. During the encoding phase, fifteen nouns were shown in a random sequence . In the first week of data collection, word learning involved a deep encoding task in which participants had to judge whether the shown word represented a living  or a non-living  thing. During the second test week, word learning involved a shallow encoding task in which participants had to indicate whether the first letter of the shown word had an open (such as a “W”) or closed (such as an “O”) shape. Each word was presented for a duration of 3000 ms (irrespective of whether a response was given or not). In between words a fixation cross was shown for 500 ms. After the encoding phase, participants performed a series of nine simple math problems  in a distractor task. The solution to all problems varied between 1 and 9. Next, participants were prompted to enter as many words as they could remember from the encoding phase. They were instructed to press ENTER, to continue entering words or to press ESC + ENTER to continue if they could not remember any more words. In the following recognition test all 15 words from the encoding phase were randomly shown, interspersed with 10 lures (new words that were not presented during encoding). Participants had to indicate for each word whether it was old (“press X”) or new (“press N”). Each word was shown until a response was given. All phases of the word task were finished in 3–4 min. Recall was quantified by the percentage correctly remembered words, while recognition was quantified by the corrected hit rate . Next, participants performed a visuomotor adaptation task, which was completed in 2–3 min (results published in54).For the landmark test assessed memory for landmarks that participants could have encountered during the second exploration phase. In total 35 landmarks were shown, of which 20 were present in the second VE  and 15 were lures . Participants had to indicate for each landmark whether they saw it before (“press X for old”) or not (“press N for new”). When participants indicated “old” they were further asked to indicate whether they thought the landmark was “sure old” (“press X”), “probably old” (“press N”) or whether they guessed (“press M “). Each landmark was shown until a response was given and the test had a duration of approximately 2–3 min. As an estimate of landmark recollection, the “sure” CHR was calculated .The NS scale of the Tridimensional Personality Questionnaire55, whereas children and adolescents filled out a simplified and abbreviated (20 item) version of the questionnaire. Each question remained on the screen until a response  was given. All questions could be answered in about 2–5 min. Afterwards feedback was shown on basis of the total NS score . These cut-off scores were only used to provide the participants feedback and were not used in any analyses.Finally, participants reported their sex , age in years, and handedness . Adults (> 17) subsequently filled out the 34 items of the 38. In line with our hypothesis that older adults would show diminished effects of novelty, an interaction between novelty and age was followed up with three 2*2*2 ANOVAs with Novelty , Encoding type , and Age  as factors. As the groups between conditions were unequal, we also included Encoding type in this analysis, but the main effect and interactions with this factor are not interpreted. For all analyses, the α-criterion was set at 0.05, and Bonferroni-Holm correction was applied to compensate for multiple testing.Recall and CHR for words were subjected to 2*2*4 ANOVAs with Novelty , Encoding type  and Age group  as between-subject factors. As we expected the effects of age on memory performance to be quadratic, with performance peaking in adolescents or young adults, we followed up a main effect of age group with a quadratic contrastpj was calculated for each of the two VEs, where the likelihood that someone visited each of the XY positions j was calculated, by dividing the total number of visits to that location by the total number of visited locations for all participants. See Fig. Roaming entropy (RE) during the first and second exploration round was defined for each participant. In this analysis the Z-coordinates were omitted, as the VEs consisted of only one location for each of the XY coordinates . As there was a very high number 6.31 million) of possible locations the likelihood that the same coordinates were visited during the 3-min exploration was small, therefore the individual paths were smoothed using a Gaussian filter with a width of 100. Then a likelihood matrix 1 millionREi) was calculated per participant and exploration round by summating over the product between the individual’s path (pij) and the log of the probability that each location was visited (pj) divided by the log of the number of possible locations (k):Roaming entropy  as the sum of Euclidian distances between successive datapoints (2D) and counted the number of landmarks that were encountered in the second exploration round for each participant by defining regions of interest (ROIs) for each of the landmarks for which memory was tested. These ROIs consisted of rectangular bounding boxes around the landmarks. ROIs could overlap in case landmarks were close to each other. For each participant it was determined which ROIs were visited. The total number of ROIs visited provides an additional measure of exploration, as it reflects how many regions were visited by the participant. A GLM including novelty  and encoding type  as categorical predictors, and RE for round 2 and age as continuous predictors of word recall was ran, to investigate whether exploration behavior as quantified by RE could predict later word recall above and beyond the effects of novelty and encoding type. We chose to include only RE and not distance travelled, or landmarks encountered in this model, as these measures were found to be positively correlated (see SI: Appendix 5). RE is the most commonly used measure of exploration and the only of these three measures for which we found a novelty effect. The GLM was ran on centered data to reduce multicollinearity. Multicollinearity was shown to be low, with all variance inflation factor (VIF) values < 1.15. It is of note that we ran our task on different laptops with varying specifications, which resulted in different sampling rates between participants, but as participants were randomly distributed over the laptops, and RE exhibits a similar pattern of results as the other exploration measures  we believe that potential effects of these differences were minimal.https://psyarxiv.com/r2tdn/A previous version of this manuscript was published as a preprint F = 76.72, p < 0.001, ŋ2 = 0.16. Word recall also differed as a function of age group, F = 14.33, p < 0.001, ŋ2 = 0.09. A quadratic relationship of age was observed, Contrast estimate = − 0.65, p < 0.001, with the adolescents and younger adults remembering more words than the children and older adults.SI: Appendix 2 reports analyses of subjective arousal and mood ratings. In SI: Appendix 3 the level-of-processing analyses for performance during encoding are reported. Figure p = 0.115), novelty interacted with age group, F = 3.20, p = 0.023, ŋ2 = 0.02  = 7.85, p = 0.006, ŋ2 = 0.06 (surviving Bonferroni-Holm correction α/3). For younger versus older adults a similar pattern was observed, with younger adults having higher word recall after exploration of a novel compared to familiar environment, and the reverse for older adults, F = 5.97, p = 0.015, ŋ2 = 0.03 (α/[3 − 1]). Finally, children also had higher word recall after exploration of a novel compared to familiar environment, while older adults showed the opposite pattern, F = 4.83, p = 0.029, ŋ2 = 0.02 (α/[3 − 2]). No other interactions were observed in the main ANOVA .Although no main effect of novelty was observed p = 0.11, noveltyAs we did not check whether participants who completed the English version of the task were (near) native speakers, they may not have been sufficiently familiar with the words included in our list. We therefore repeated the main ANOVA without the data from the participants who completed the English version of the task and observed the same pattern of results as reported for the analyses on all subjects. Furthermore, when including language version as a between-subjects factor , no effect of language was found.F = 43.74, p < 0.001, ŋ2 = 0.09. Age also influenced recognition, F = 16.85, p < 0.001, ŋ2 = 0.11. A quadratic relationship of age was observed, Contrast estimate = − 0.93, p < 0.001, with adolescents and younger adults remembering more words than older adults and children. Novelty did not influence CHR (p = 0.259), and no interactions were observed .Figure Figure Fs > 6.06, ps < 0.001, etas > 0.04. Follow-up contrasts revealed quadratic effects for all three measures with higher exploration measures for adolescents and younger adults than for children and older adults , but age and novelty interacted for RE in round 2, F = 2.73, p = 0.044, ŋ2 = 0.02. RE in round 2 was affected by novelty, with a larger RE in the familiar compared to the novel condition, F = 8.49, p = 0.004, ŋ2 = 0.02. For the number of encountered landmarks and distance travelled no effect of novelty was observed (ps > 0.060). There was a statistical trend suggesting that NS scores were higher for younger versus older adults, t(153.74) = 1.950, p = 0.053 .The different exploration measures  were analyzed with univariate ANOVAs with novelty  and age  as factors. A main effect of age group was observed for the number of encountered landmarks, distance travelled, and RE in round 2, all In line with the main ANOVAs a GLM (details in Methods) suggested that word recall was higher in the deep than in the shallow condition, and an effect of age group was found  approach comparing age group does not allow us to infer whether the observed effects were driven by a detriment in performance in older adults or better performance in younger participants. However, crucially, the effects of age and novelty on recall cannot be explained by general arousal or mood reports of participants, as these affective measures did not differ between novelty conditions and did not follow the same pattern over the different age groups as the effects on memory. Irrespective of novelty, arousal and mood peaked in children, with higher ratings for children compared to adolescents. In line with previous work, we observed no novelty-related effects on recognition37. It is possible, however, that our subjective measure of arousal and mood (9-point SAMs) was not sensitive enough to identify fluctuations. We therefore recommend that future studies use more objective or validated measures, such as heart rate (variability), pupil size, or dedicated questionnaires  to estimate awareness.In line with the rise and fall of the dopaminergic system, quadratic effects showed higher memory performance  in adolescents and young adults, compared to children and older adults32. The mesolimbic dopamine system is strongly associated with motivation58, but this system also has been suggested to underlie the effects of novelty on memory60. As such, the effects of novelty through dopaminergic modulation as described above, would likely share neural pathways with potential effects of novelty on motivation. In the current study, however, we did not include a measure of motivation, nor did we include measures of dopaminergic functioning, therefore potentially differential effects of novelty on motivation and dopaminergic pathways cannot be teased apart.A potential explanation for our findings is that novelty influenced motivation differently across age groups (as suggested by the NOvelty-related Motivation of Anticipation and exploration by Dopamine model [NOMAD]n = 64), with some conditions having a low number of participants. Potentially, the lack of a novelty effect in this age group was due to this smaller sample size. Especially, identifying a 3-way interaction may have been hard as a result (observed power was moderate for the 3-way interaction = 0.458). It is also possible that participants in the different age groups experienced the environments differently in terms of novelty, potentially explaining the observed differences between the age groups. Future studies could include additional subjective measures regarding the experienced novelty of the environments to further address the effects of such differences over the lifespan.One limitation of the current study was that the number of participants per age group varied, as we could not select participants on age in the museum setting . Due to natural variation in the age of the museum visitors, the older adult group was the smallest  over the lifespan69, suggesting that changes in this region develop gradually. Taking into account this work on dopaminergic functioning across the lifespan, it is unlikely that dopamine deterioration occurs abruptly. Despite our sample of older individuals being relatively young, it is likely that some of these changes already started to develop in our sample too, as changes in dopaminergic functioning have already been reported in early adulthood. This point could be further investigated by including a sample of older individuals  or by adopting a longitudinal design in future studies. Also note that our findings of novelty influencing immediate recall (only after a short distraction task) differ from the studies in animals, where typically long-term potentiation or memory are measured after longer delays . Due to this difference and other differences regarding the type of novelty  or memory content , it is difficult to compare the current findings with those in animals. As such it is not possible to make conjectures regarding underlying neural mechanisms on basis of the current study’s results. Future studies in humans could aim to further bridge the gap between the two literatures by using more similar designs as in the animal studies, or to investigate the potential neural mechanisms .One may argue that a limitation regarding our current interpretation in terms of dopaminergic mechanisms is that the mean age of our older adults was ~ 53 years old, while prior indications of age-related deterioration of dopaminergic pathways were based on slightly older participants  encountered more landmarks, had higher RE, and travelled further during the second round of exploration (novel/familiar). Indeed, encountered landmarks, distance travelled, and RE exhibited a positive correlation with later memory success on the landmark task. Interestingly, participants in the familiar condition had higher RE than those in the novel condition. A reason for this may be that we tested memory immediately after a short distractor task. Some animal studies suggest that the interaction of novelty and depth of encoding develops over timeTaken together, our findings suggest that exploring a novel environment has a generalizable memory boosting effect, on both weakly and strongly encoded information, in children, adolescents, and younger adults, but not in older adults. These results imply that the beneficial effects of novelty on memory are limited to younger individuals, and that interventions aimed at counteracting age-related memory impairments may be less effective.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.


Myrj-b-PCL copolymer with various PCL/Myrj ratios were synthesized via ring-opening bulk polymerization of ε-caprolactone using Myrj (Myrj S40 or Myrj S100), as initiators and stannous octoate as a catalyst. The synthesized copolymers were characterized using 1H NMR, GPC, FTIR, XRD, and DSC. The co-solvent evaporation method was used to prepare CyA-loaded Myrj-b-PCL micelles. The prepared micelles were characterized for their size, polydispersity, and CMC using the dynamic light scattering (DLS) technique. The results from the spectroscopic and thermal analyses confirmed the successful synthesis of the copolymers. Transmission electron microscopy (TEM) images of the prepared micelles showed spherical shapes with diameters in the nano range (<200 nm). Ex vivo corneal permeation study showed sustained release of CyA from the developed Myrj S100-b-PCL micelles. In vivo ocular irritation study (Draize test) showed that CyA-loaded Myrj S100-b-PCL88 was well tolerated in the rabbit eye. Our results point to a great potential of Myrj S100-b-PCL as an ocular drug delivery system.Low aqueous solubility and membrane permeability of some drugs are considered major limitations for their use in clinical practice. Polymeric micelles are one of the potential nano-drug delivery systems that were found to ameliorate the low aqueous solubility of hydrophobic drugs. The main objective of this study was to develop and characterize a novel copolymer based on poly (ethylene glycol) stearate (Myrj™)- Ethoxylated fatty acids e.g., PEG stearates (sold under the trademark Myrj™) are non-ionic surfactants widely used in various drug delivery systems . When inThe United States Food and Drug Administration (US FDA) has approved the use of Myrj™ products as safe excipients used in cosmetics, pharmaceutical formulations, and food additives . RecentlPoly (ε-caprolactone) (PCL) is an eco-friendly polyester and has been widely utilized for tissue engineering and controlled drug delivery applications . It allob-PCL significantly improved the water solubility of paclitaxel (from ca. 0.3 µg/mL up to 88.4 µg/mL) and sustained the release of the loaded drug in vitro , stannous octoate (95%), ε-Caprolactone, and HPLC-grade tetrahydrofuran (THF) were purchased from Sigma-Aldrich . Deuterated chloroform  or Myrj S100 (MW ~ 4700 Da) were used as a macroinitiator and stannous octoate was used as the catalyst. Monomer (ε-caprolactone) to catalyst molar ratio was always kept at 1:500. Different ε-caprolactone to Myrj feed ratios were used to synthesize Myrj-b-PCL block copolymers with varying degrees of ε-caprolactone polymerization. Briefly, either Myrj S40 or Myrj S100, ε-caprolactone, and stannous octoate were added to an ampoule that was previously flamed and purged with nitrogen gas, which was then sealed under vacuum. The reaction was conducted at 140 °C for 4 h. Then, it was terminated by removing the reaction vessel (ampoule) from the oven and storing it at room temperature overnight.Ring-opening polymerization of ε-caprolactone was the approach used to synthesize the copolymers ,16. For 1H NMR (Bruker Ultra shield 500.133 MHz spectrometer) in CDCL3.Tetramethylsilane (TMS) was used as an internal standard, and Topsin software was used to process the data and obtain the spectra. The number average molecular weight of all synthesized copolymers was determined from 1H NMR spectra by comparing the peak intensity of  present in the PEO segment of each copolymer to that of PCL . The calculation used the integration area of the peaks of methylene protons of PCL at 4.07 ppm and of PEG at 3.65 ppm, respectively  copolymer-based micelles were used for topical ocular delivery of dexamethasone and no irritation was reported [All the involved animals were active and healthy without any abnormal signs and symptoms of overall toxicity throughout the experiment, except for the observed signs as scored and mentioned in O-b-PCL)  and methO-b-PCL)  micelle reported . All togb-PCL and Myrj S100-b-PCL copolymers were successfully synthesized, but only Myrj S100-b-PCL formed micelles with optimum size, PDI, and no precipitation. The mean diameters of the prepared self-assembled structures were in the nano-range (≤200 nm). Moreover, Myrj S100-b-PCL micelles significantly increased the aqueous solubility of CyA from ca. 23 µg/mL to over 540 µg/mL. The developed micelles showed a transcorneal permeation comparable to Restasis®, the leading commercial CyA ocular formulation. The in vivo ocular irritation study demonstrated that CyA-loaded Myrj S100-b-PCL88 micelles were well tolerated in the rabbit eye. Our results point to a great potential for Myrj-b-PCL micelles to serve as an efficient solubilizing and delivery system for CyA and potentially other hydrophobic drugs.Myrj S40-


Traction force microscopy (TFM) has emerged as a versatile technique for the measurement of single-cell-generated forces. TFM has gained wide use among mechanobiology laboratories, and several variants of the original methodology have been proposed. However, issues related to the experimental setup and, most importantly, data analysis of cell traction datasets may restrain the adoption of TFM by a wider community. In this review, we summarize the state of the art in TFM-related research, with a focus on the analytical methods underlying data analysis. We aim to provide the reader with a friendly compendium underlying the potential of TFM and emphasizing the methodological framework required for a thorough understanding of experimental data. We also compile a list of data analytics tools freely available to the scientific community for the furtherance of knowledge on this powerful technique. The premise of mechanobiology is that the mechanical properties of biological tissues can direct given cellular processes, like proliferation, migration, survival, and differentiation. Therefore, mechanobiology entails the understanding of how forces are generated, maintained, and interpreted by cells which actively respond to biophysical stimuli arising from their milieu .Figure 1The primary sites of cell interaction to any substrate are the multiprotein complexes which connect the extracellular matrix (ECM) to cell cytoskeleton, the focal adhesions (FAs).i.e., their localization or conformation changes following the application of physical and biochemical stimuli generated at the ECM). The cooperative activity of these components makes it difficult to determine the specific mechanosensitivity of single FA members. An established example of an FA mechanosensitive protein is talin, a 270-kDa protein which interacts directly with both β-integrin cytoplasmic domain and F-actin. The protein acts as a force buffer by unfolding the numerous rod domains following mechanical load, thus exposing cryptic hydrophobic binding domains able to interact with vinculin  monolayer cultures routinely used to study cellular mechanisms. However, the predictivity of in vitro monolayers when compared to native tissues is known to get poorer with the increase in the system complexity. Moving to three-dimensional (3D) culture allows cells to undergo indirect mechanical stimulation by controlling the rigidity and stiffness of the ECM in which they are embedded  as engineered tools to measure single-cell adhesion forces , 29, 30.et al. . As a no  or silicon-based gels are common substrates for TFM. Both types of gels exhibit a linear elastic behavior under deformations produced by cell traction, and their stiffness can be varied over a range of several orders of magnitude. Interestingly, mechanical properties of those gels have been proven not to change under the action of biochemical factors that may occur during a TFM measurement, including cell proteases .et al., who designed a polydimethylsiloxane (PDMS) contractile force screening platform featuring 96 monolithic independent wells ; converet al., . It is worth noting that under elongated focal adhesions, upward and downward normal tractions are more likely to appear on distal (toward the cell edge) and proximal (toward the cell body) ends of adhesions. The resulting rotational moments affect focal adhesions by either protruding or retracting peripheral regions. To measure this, Legant et al.  developea priori assumption of stress state or ECM geometry. Interestingly, in this case we are not bound to infinite substrate requirements typical of the Boussinesq theory (BOX 1E and the Poisson’s ratio ν (The math underneath the reconstruction of traction forces in TFM relies on the theory of linear elasticity . Substra ratio ν .direct TFM) by calculating the strain field ε from the measured displacement field u, according to the linearized expression, which holds for small strains:c is the stiffness tensor, which describes the substrate properties (can be expressed in terms of E and v).TFM problems can be solved directly  of the system to a point load. The integral in Equation u located at t acting in i.e., the assumption of infinite thickness) can be applied.In typical TFM settings, where cell-induced displacements are ca. two orders of magnitude smaller than the substrate thickness , the Boussinesq approximation of an infinite half-space (ν ≅ 0.5), decoupling occurs between in-plane tractions and out-of-plane displacements . Additionally, in most practical cases, displacement vectors are experimentally measured on the x-y plane only, which further reduces the problem to a 2D one, characterized by the following Green’s function :x or y directions separately induce displacements in both x and y directions  or, more commonly, in the spatial frequency domain (Fourier space). All these methods have important methodological considerations, which have been exhaustively addressed in the primary literature and carefully reviewed by Schwarz and Soiné , although other studies tune the regularization parameter for each single dataset to account for biological and experimental variability. Undoubtedly, such arbitrariness may introduce systematic errors and makes it hard to compare results in the literature. via FTTC.From a practical point of view, no consensus has been reached on the application of regularization strategies to experimental data. Many authors recommend a single regularization parameter to be chosen for a given TFM experiment  is a numerical technique used to produce approximate solutions to partial differential equations, as well as integral equations. The goal is to reduce the complexity of the problem to a system of ordinary differential equations that are solved by numerical integration inside a problem-defined domain. The space of the problem is then discretized and subdivided into a finite number of regions (elements) where equations are solved locally . FEM haset al. , who comBOX 2Over the years, several software packages have been released to calculate traction forces and other features of mechanobiological relevance. Here, we present a selection of free tools that could be helpful to the reader.https://github.com/qztseng/imagej_plugins,  .Template matching: performs alignment between the reference and the “stressed” images compensating for experimental errors  using particle image velocimetry with a user-defined searching window ;3.FTTC: calculates the traction map starting from the displacement field, given the substrate-constitutive parameters, the image spatial calibration (pixel/μm), and the regularization parameter λ.A tool for referenced TFM is freely accessible as a set of plugins for ImageJ , downloa1, 2022) . The too   . The sofn et al. .https://www.mathworks.com/matlabcentral/fileexchange/52-regtools, . Detailed explanation is provided in the book by the same author  e author . The pachttps://github.com/FranckLab/LD-3D-TFM, . The package includes both the FIDVC algorithm, which is used to calculate 3D deformation fields from micrographs, and the solver to reconstruct force fields from 3D deformations, according to the method published by the same authors (A MATLAB package for computing 3D TFM in the case of large deformations (LD-3D-TFM) has been developed by the group of Prof. Franck at the University of Wisconsin-Madison and distributed through GitHub repository  authors .et al. . The tool integrates all the computational steps to calculate active cellular forces from confocal microscopy images, including image processing, cell segmentation, image alignment, matrix displacement measurement and force recovery.More recently, a comprehensive tool for 4D  TFM (TFMLAB) based on an FEM engine has been developed as a MATLAB package by Barrasa-Fano et al.  and madeSarcTrack is a MATLAB software program designed by Toepfer et al. . The tool determines sarcomere count and any changes in sarcomere length. In return, the algorithm computes sarcomere percent contraction. Cell contraction is obtained from the imaging of labelled z-disc or m-line pairs inside individual sarcomeres.r et al.  and avaiet al.  technique, developed by Kronenberg et al. . ERISM het al.  of silicone rubber is used to fabricate a microchamber to be filled with culture media. The optical cavity is sandwiched between two semitransparent layers coated in gold. Cellular forces cause wrinkles on the surface of the substrate which are observed at selected wavelengths using an optical microscope endowed with a tunable monochromatic light source (monochromator). Dark fringes are detected at positions where the actual thickness of the cavity fulfills a resonance condition, and the resulting reflectance at that position is hence attenuated. Analysis of the fringe pattern gives a readout of cell-induced deformation field, with an estimated lateral resolution of ca. 1.6 μm. A detailed discussion on ERISM working principle has been provided by Liehm et al. .et al.  displacement, which is detected by collecting a 3D z-stack of the quantum dot array and performing fluorescence intensity profiling along the normal axis.Another approach which has been proposed to bypass the acquisition of a reference image is the one of Bergert et al. . The metet al.  set of case studies demonstrating the versatility of TFM for characterizing cell-generated forces in diverse biological scenarios. Paradigmatic examples are summarized in via the deposition of a scar-like ECM, in a phenomenon dubbed as tissue remodeling   .Moving over to the pure quantification of the single-cell response, Pasqualini et al. investigated the relationship between contractile proficiency and metabolism in neonatal rat ventricular myocyte cells, calculating the ratio between the contractile work done by the cells and the metabolic energy provided by the mitochondria. To do so, cells were cultured on gels with stiffness mimicking soft/immature (1 kPa), physiological (13 kPa), and stiff/pathological (90 kPa) cardiac microenvironments, while measuring the strain energy of substrates following cell contraction and ATP production . Only onThe cells responsible for ECM remodeling in the heart are cardiac fibroblasts, which undergo profound phenotypic alterations in the failing heart . Human cValve cells are also exposed to a high degree of mechanical stress. In order to understand the response of a cell to traction, valve interstitial cells were challenged with long-term uniaxial or biaxial stretching conditions, and their ability to develop traction force was studied as a form of adaptation . The resThe motility of eukaryotic cells is needed for many biological processes, such as embryonic development or tissue repair, as well as for the function of the immune system . Many paThe generation of mechanical forces is central for regulating the attachment of cells to a substrate, for cell spreading and migration. Thus, the analysis of cell migration requires understanding the spatial and temporal pattern of cell–cell and cell–substrate mechanical interactions .The first attempt at investigating the contribution of cell-generated stresses to migration was described in mouse NIH3T3 fibroblasts and entailed the acquisition of time-lapse images and shear fields of traction stress at a high spatial and temporal resolution . These fThese pioneering studies were the first to demonstrate the existence of a frontal towing mechanism for cell migration in two dimensions, where dynamic traction forces at the leading edge actively pull the cell body forward. This theory was recently questioned by studies adopting nanopillars and displaying enhanced spatial resolution to indicate that the highest displacements are produced by the motile cell in correspondence of the perinuclear regions, rather than on the edges .The ability of the cell to exert force on the ECM during migration has been associated with the formation of the FA complexes. However, recent evidence demonstrated the size and overall FA distribution only partially overlaps with the distribution of traction stress. More importantly, at the leading edge, small dynamic adhesions were shown to transmit strong propulsive tractions, whereas stable mature focal adhesions exerted weaker forces . TractioDictyostelium discoideum crawling on soft hydrogels , and their maximum traction decreased to nearly 50 pN/μm2. The authors also investigated cell migration velocity, which was larger on less rigid gels. During cell migration on planar 2D matrices, cells move due to a cyclic process of polarization, protrusion formation, traction generation, and retraction at their rear end. In this condition, inertial and viscous drag forces are negligible. However, cell migrating in a 3D ECM are required to overcome the steric hindrance of the surrounding environment. For this reason, Koch et al.  can be utilized to predict their motility in substrates with low stiffness (elastic modulus ca. 10 kPa). Consistently, the invasiveness was found to correlate with the interplay between the focal adhesions and the cytoskeleton .Another interesting method was designed to quantify traction forces of cancer cells in highly nonlinear 3D hydrogel networks. The technique exploited a finite-element approach based on a constitutive equation which models the complex mechanical behavior of ECM-like hydrogels . InvestiThese results highlight the necessity to extend the evaluation of traction forces outside the limits of the cell adhesion plane to understand the overall complexity of cell behavior.The ability of living cells to efficiently generate and transfer intracellular forces to the surrounding milieu is crucial for cell adhesion, migration, and maturation. Also, the occurrence of aberrant mechanical signals from the ECM and defects in its perception at the cellular level are now considered of physiological and pathological relevance. Although TFM setup has been standardized and its principles are thoroughly detailed in numerous studies and protocols, the processing of data and the extraction of information from TFM measurements remains somehow operator dependent. The intrinsic ill-posed nature of the mathematical problem and nonuniqueness of its solution mandates for numeric approaches which show some margins of arbitrariness. Nonetheless, thanks to the work of some leading research groups, software tools have been made available, which constitute a solid framework for consistent and reproducible data analysis. This effort is expected to contribute to a wider diffusion of TFM for complementing mechanobiology studies at the single-cell scale.The authors declare that they have no conflicts of interest with the contents of this article.


Habitat loss, urbanisation and climate change may cause stress in koalas. Non-invasive monitoring of faecal cortisol metabolites (FCMs) can be utilised to evaluate the impact of stress. The effectiveness of two enzyme immunoassays (EIAs), 50c and cortisol, in measuring FCM values in wild, stressed koalas was tested. Faecal samples of 234 diseased, injured and control koalas in Queensland, Australia were analysed. Diseased and injured koalas had significantly higher FCM values than clinically healthy control animals as measured by the 50c EIA. Only the 50c EIA detected higher absolute values in males, and also found that females showed a more elevated response to stress manifested by injury and disease. The cortisol EIA was also found unreliable in detecting stress in rehabilitated koalas treated with synthetic glucocorticoids as it cross-reacts with these chemicals.Loss of habitat, urbanisation, climate change and its consequences are anthropogenic pressures that may cause stress in koalas. Non-invasive monitoring of faecal cortisol metabolites (FCMs) can be utilised to evaluate the impact of stressors. The aim was to determine if the tetrahydrocorticosterone (50c) and cortisol enzyme immunoassays (EIAs) could be effective in measuring FCM values in wild, stressed koalas. This research included 146 koalas from the Australia Zoo Wildlife Hospital (AZWH) and 88 from a study conducted by Endeavour Veterinary Ecology (EVE), Queensland, Australia. Faecal samples of diseased, injured and control koalas were analysed. The effect of hospitalisation on FCM values was also investigated. Diseased and injured koalas had significantly higher FCM values than clinically healthy control animals as measured by the 50c EIA. FCM values with the cortisol EIA differed significantly between control and diseased koalas, but not between control and injured ones. Moreover, only the 50c EIA detected higher absolute values in males compared to females, and also found that females showed a more elevated response to stress manifested by injury and disease compared to males. The 50c EIA detected stress during hospitalisation better than the cortisol EIA. The cortisol EIA was also found unreliable in detecting stress in rehabilitated koalas treated with synthetic glucocorticoids as it cross-reacts with these steroids providing artificially high values. The hypothalamic-pituitary-adrenal (HPA) axis is one of the systems responding to an organism’s internal and external changes to maintain homeostasis. It regulates metabolic and physiological processes by stimulating the release of glucocorticoids (GCs), such as cortisol and corticosterone, produced by the adrenal cortex ,2. DurinDuring stressful situations, its function is to maintain homeostasis and ensure the individual’s survival by increasing the output of glucose for muscular and brain function and decreasing the activity of peripheral organs, hence preparing the organism’s response to cope with the situation. Anti-inflammatory responses and immune suppression are also exacerbated by cortisol release in response to stress ,8,9.The secretion of cortisol is naturally limited by a negative feedback loop caused by its own secretion , and desPhascolarctos cinereus) were listed as endangered in Queensland, New South Wales (NSW) and the Australian Capital Territory under the Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) [In February 2022, koalas (PBC Act) . The conPBC Act) .Chlamydia pecorum is one of the bacteria causing devastating diseases in koalas, affecting the urogenital system with cystitis, endometritis, pyelonephritis and prostatitis, as well as causing blindness and impacting the respiratory tract [In South East Queensland (SEQ), in particular, there is significant loss of koala habitat for housing developments and for the expansion of the road and rail networks. The increased traffic volume and larger distances between areas of koala habitat are causing koalas to travel long distances and to cross roads, with a high chance of being attacked by dogs or hit by vehicles ,17,18,19ry tract ,22. Conversely, there are ample examples showing that the effect of pain caused by illness and injuries in animals can increase stress hormone and, as a consequence, faecal cortisol metabolite (FCM) concentration ,25,26,27The effect of stressors on koalas, at an individual and population level, can be evaluated using a non-invasive method that measures the levels of FCMs. Accounting for the lag time due to the transition in the intestinal tract, metabolites of cortisol are directly related to adrenocortical activity during stressful events ,27,28.Previous studies, which explored the relationship between stress (investigated by FCMs) and injuries or illness in domestic species and wildlife, including koalas, yielded mixed results with metabolite values increasing above or decreasing below the baseline ,29,30,31Our recent research, conducted with captive koalas in wildlife parks, identified tetrahydrocortisol to be the main FCM in koalas . ValidatHowever, those studies did not investigate the suitability of both EIAs in identifying naturally occurring stressors in this species. A clear need was expressed for more studies to validate the EIA using biological parameters  such as The study started in February 2021 and was completed in March 2022. Two groups of wild koalas were part of this study: a group of 146 koalas admitted to the Australia Zoo Wildlife Hospital (AZWH) (code: AZ), Beerwah, Queensland, and one group of 88 from a study conducted by Endeavour Veterinary Ecology (EVE) at The Mill (code: ML), a locality at Moreton Bay, Queensland. Details of the makeup of these groups are shown in The 36 koalas that were neither diseased nor injured and taken to AZ by concerned citizens were considered as the AZ control. During the rehabilitation, ill and injured koalas were treated with a variety of systemic and local (ocular) medications. Systemic treatment included oral synthetic GC, prednisolone , antimicrobial sub-cutaneous injections of doxycycline  and chloramphenicol  and enrofloxacin antibiotic  used as nebulizer. Local treatment included eye ointments with chloramphenicol and GC (Chloroptsone)  and antibiotic chloramphenicol . Wherever possible, information was obtained on clinical activities performed during the collection of scats for the longitudinal study. Chlamydial infection was determined using loop-mediated isothermal amplification (LAMP) [In total, 346 faecal samples were obtained for this study from the AZ koalas. Only intact fresh pellets were collected on admission and in the morning from the ground of the enclosure where the koalas were housed individually. Despite the likely need for an increased collection effort, the use of fresh pellets is recommended to avoid the possible effect of environmental conditions on the structure of the samples [A first sample from each koala was collected on arrival at the hospital before any intervention was undertaken by the veterinarians. Due to the lag time that occurs between a stressful event and the increase in FCM values , the anaA second sample from 53 of the 146 koalas was collected again between 10 and 15 days after admission to detect if changes in FCM values occurred during hospitalisation . Serial faecal pellets from 20 of the 146 admitted koalas  were also collected for a period between 7 and 10 days from admission .The 88 koalas from ML were part of The Mill Koala Tagging and Monitoring Program, carried out by EVE on behalf of Moreton Bay Regional Council. The program aimed to ensure the welfare of koalas during vegetation clearing operations for site remediation and construction works as the site transitioned from industrial use to a mixed-use precinct with a university campus, community infrastructure and future commercial development precincts. Koalas were fitted with collar-mounted K-Tracker biotelemetry tags weighing 70 g , a very high frequency (VHF) transmitter  and lead weight in housing for a total collar weight of 190 g, with a customised weak link based on the weight of the animal. When a koala was located, it was caught by a tree climber using ropes and harness. Koalas were immediately placed in a transport cage (dimensions: 520 mm H × 580 mm L × 350 mm W) with fresh eucalypt browse and transported to the EVE facility for a veterinary examination.Koalas remained in the transport cage until the veterinary examination was conducted. While undergoing veterinary assessment, any fresh and intact faecal pellets voided were collected. If pellets were not produced during the 20 to 45 min veterinary examination, the cage was checked to determine if any suitable fresh pellets could be collected.A sample of at least four intact faecal pellets was collected if fresh pellets were observed. Data relating to each individual’s history and chlamydial status were provided to this project. None of these koalas were either injured or diseased at the time of the faeces collection, hence this was considered as an external control.All the samples provided for this study were immediately placed in a −20 °C freezer, and remained at this temperature until the samples were collected and transported with a −20 °C portable freezer to a −80 °C freezer before processing.Latitudinal and longitudinal coordinates for the 146 koalas prior to admission at AZ were derived from the precise locations provided by the rescuers. The coordinates of the ML koalas were provided by the EVE researchers. A map of the locations of all koalas involved in the study  was geneg for 15 min. Completely dried-down aliquots (0.25 mL) of the extracts in 1 mL Eppendorf tubes, sealed with paraffin film, were shipped to the University of Veterinary Medicine (Austria), where dried sample extracts were resolubilised in 80% methanol and further diluted with assay buffer (1 + 9). Aliquots were analysed in duplicate with cortisol  and tetrahydrocorticosterone (50c) enzyme immunoassays (EIAs). The EIAs were selected based on the findings of Santamaria et al. [The extraction procedure and analysis are described in Santamaria et al. . In briea et al.  and useda et al. ,37.The normality of FCM values was assessed by visually examining the histograms  and by uDescriptive statistics of FCM values were presented for all subgroups of animals, including 95% confidence intervals for medians .For control animals, the non-parametric Mann–Whitney U (Wilcoxon rank sum) test was used to compare FCM values between the locations  and between breeding and non-breeding season for samples obtained on the first collection day.The non-parametric Kruskal–Wallis test was applied to compare FCM values between koala’s conditions  for samples obtained on the first collection day. Nonparametric pairwise comparisons were then conducted using Dunn’s test with the Bonferroni adjustment . The ManPoisson regression was utilised in a multivariate model to evaluate the association between FCM values and koala condition, sex and the interaction between sex and condition for samples obtained on the first collection day . Robust The Mann–Whitney U test for matched data (Wilcoxon rank sign) was applied to compare EIA values for AZ koalas between the first sampling and the subsequent sampling 10–15 days later.The correlation between 50c and cortisol was explored in a scatter plot and the Pearson correlation coefficient was used for quantification.Microsoft Excel (Version 2208 Build 16.0.15601.20204) was used for descriptive statistics and bar and line graphs. Data analysis was performed in STATA 16.1 .A total of 234 koalas from the AZ and ML were considered for the analysis, of which 36 from AZ and 88 from ML were neither diseased nor injured and were considered controls. Of the AZ koalas, 76 were diseased and 30 were injured. Four were diseased and injured, but were excluded from further analyses.The distribution of FCM concentrations measured with both EIAs for the AZ and ML control are shown in The median values (ng/g) (95% CI) detected by the 50c EIA and cortisol EIA in koalas at AZ (N = 36) on the first collection day were 22.4  and 6.8 , respectively. The median values (ng/g) (95% CI) in koalas at ML (N = 88) on the first collection day were 18.8  (50c EIA) and 6.4  (cortisol EIA), respectively. Mean, minimum, maximum FCM values for control koalas from AZ and ML are presented in p = 0.1379) and the cortisol (p = 0.5858) EIAs between the AZ and the ML control, highlighting that healthy koalas have similar FCM values in different geographical locations and confirming that both could be used as a combined control in the analysis.There was no significant difference in FCM values measured by the 50c (p = 0.1469 and p = 0.5415) between the breeding and non-breeding season  are shown in Scatterplots were used to display the bivariate correlations between the two EIAs for the control (N = 124), diseased (N = 76) and injured (N = 30) in day 1 samples . The datp < 0.001), for the diseased was 0.4479 (p < 0.001) and for the injured was 0.4310 (p < 0.0174).The correlation coefficient for the control was 0.4120  (95% CI) detected with the 50c EIA and cortisol EIA for the combined control koalas from AZ and ML (N = 124) were 20.0  and 6.5 , respectively. The median FCM values (ng/g) (95% CI) detected with the 50c EIA for the diseased koalas from AZ (N = 76) were 36.1  and 11.4  with cortisol EIA. The median FCM values (ng/g) (95% CI) of the injured koalas (N = 30) as measured with the 50c EIA were 34.9  and with the cortisol EIA 8.9 .Mean, minimum and maximum FCM values for these three groups of koalas with different conditions are presented in p < 0.001). In the pairwise comparison, diseased and injured koalas had significantly higher FCM values measured by the 50c EIA compared to the control , but FCM values did not differ between diseased and injured koalas (p = 1.000). FCM values measured by the cortisol EIA only differed significantly between control and diseased koalas (p < 0.0001), but not between control and injured (p = 0.1016) or between diseased and injured koalas (p = 0.1246).FCM values measured by both EIAs differed significantly between control, diseased and injured koalas  (95% CI) measured by the 50c and the cortisol EIA of females and males in the control, diseased and injured groups are shown in p < 0.001) and diseased (p = 0.0210) animals, but did not differ between injured females and males (p = 0.2725). FCM values measured with the cortisol EIA were not significantly different between sexes for the three conditions, control (p = 0.2997), diseased (p = 0.9833) and injured koalas (p = 0.2042). Thus, in contrast to 50c EIA, cortisol EIA was not able to detect the difference in FCM values between males and females for control and diseased animals.FCM values measured with the 50c EIA were significantly higher for the males in the control (p < 0.001) and higher in diseased and injured koalas compared to controls (p < 0.001), a significant interaction was also found between the conditions and the sex of the animals (p = 0.0307). Thus, the IRR of FCM values measured with 50c EIA were significantly lower for injured males relative to injured females when compared to the controls. Similarly, IRR of FCM values measured with 50c EIA were marginally lower for diseased males relative to diseased females when compared to the controls (p = 0.074).The results of the multivariate analysis are presented in p = 0.4221).In contrast, in the multivariate analysis for cortisol EIA, the interaction between the conditions and the sex of the animals could not be detected   of stresIn contrast to our previous study , which dA strong artificial increase in FCM values measured by the cortisol EIA was directly associated with the therapeutic systemic administration of prednisolone (Redipred) in koalas whose scats were collected during the therapy. These results can be explained by the antibody of the cortisol EIA cross-reacting with cortisone, prednisolone and prednisone ,51,52 , the main FCM in koalas . MoreoveHigh endogenous GC levels trigger a negative feedback that decreases the secretion of the ACTH, consequently decreasing the release of endogenous GCs . This reAs expected, on day 1, high FCM values were found in diseased and injured koalas. There is an abundance of literature on stress, including anthropogenic stress, causing illness and disease in wildlife, though there are no articles on the effect of disease on stress in wildlife. However, critical and acute illness, generally associated with serious inflammations and infections , had a strong impact on stress in children, causing a significant and sustained increase in plasma cortisol, which was, however, not significant in those with non-critical illnesses . Hence, In fact, injuries are well known to cause pain and increase stress in humans and animals (domestic and wildlife). Pain in horses, resulting from colic, has shown to dramatically increase FCM values , and in The 50c EIA detected that FCM values of males were significantly higher than those of females (except for the injured), but no difference between sexes could be detected with cortisol EIA. Furthermore, through the interaction term between condition and sex in the multivariate analysis, it was identified that 50c EIA values were proportionally higher in females than males for individual conditions. This indicates that females, relative to males, respond to stressful situations derived from disease and injury with proportionally larger elevation of FCM values when measured with 50c EIA. In contrast, when measuring stress levels with cortisol EIA, a difference between sex and the interaction between the sexes and the three conditions could not be detected . Thus, the cortisol EIA is less suited to detecting subtle differences between physiological changes due to pain.Therefore, in koalas, the cortisol EIA had a lesser discriminatory power than the 50c EIA, which reiterates what was already demonstrated in our previous work . HoweverThis study was designed to assess the stress caused by injuries and disease and the effect of hospitalisation on wild koalas. While this study successfully achieved its aim, there were some limitations worth mentioning here.Due to the real-life nature of this study, some elements could not be standardised. As these were wild koalas, their age was not known and, hence, the FCM values between age groups could not be established. However, our previous investigation on captive koalas of known age , showed Koalas were admitted to hospital at different times, but this would not alter the FCM values of day 1 samples as these reflected stress events occurred many hours earlier and further samples in the hospital were collected freshly defecated each morning. Nevertheless, our previous study  showed dThis study has clearly demonstrated that pain causes an increase in stress in koalas, which is known to impact the immune system. Stressed koalas have an increased likelihood of being further affected by illnesses, hindering their natural recovery and wellbeing.While we have established a link between stress and diseases and injuries, anthropogenic activities, some also causing climate change, are also considered stressors increasingly impacting on the survival of koalas. Using a species-specific EIA for measuring FCM values, as an indicator of stress, is of utmost importance.Here, it has been demonstrated that stress can be reliably measured with the 50c EIA. It has been confirmed that the baseline FCM values measured in our previous paper can be used to assess stress in koalas. It has been shown that, before admission to hospital, the diseased and injured koalas were stressed.More importantly, this study has clearly demonstrated the unsuitability of the cortisol EIA to determine stress in most rehabilitated animals and in those treated with synthetic GCs, as the values detected reflect administered exogenous GCs rather than the endogenous cortisol metabolites. Hence, future studies on stress of rehabilitated animals medicated with GCs need to take into consideration the cross-reaction of the EIA with any exogenous GCs. These findings will be applied to a wider study on wild koalas where the relationship between health and stress will be further investigated.


In this commentary, we explore the pioneering implementation of 3D-printed thin liquid sheet devices for advanced X-ray scattering and spectroscopy experiments at high-repetition rate XFELs. This has enabled the development of novel methods, such as serial femtosecond crystallography (SFX), fluctuation X-ray scattering (FXS), and several X-ray spectroscopies, which have transformed atomic resolution molecular imaging and ultrafast materials characterization  is predominantly utilized for liquid sample injection in XFELs  X-ray spectroscopies (Ekimova