Biominerals, such as nacreous bivalve shells, are important archives of environmental information. Most marine calcifiers form their shells from amorphous calcium carbonate, hypothesised to occur via particle attachment and stepwise crystallisation of metastable precursor phases. However, the mechanism of this transformation, including the incorporation of trace elements used for environmental reconstructions, are poorly constrained. Here, using shells of the Mediterranean mussel, we explore the formation of nacre from the meso- to the atomic scale. We use a combination of strontium pulse-chase labelling experiments in aquaculture and correlated micro- to sub-nanoscale analysis to show that nacre grows in a dynamic two-step process with extensional and space-filling growth components. Furthermore, we show that nacre crystallizes via localised dissolution and reprecipitation within nanogranules. Our findings elucidate how stepwise crystallization pathways affect trace element incorporation in natural biominerals, while preserving their intricate hierarchical ultrastructure. Biominerals contain trace elements that can give important environmental information, but the mechanism by which these are incorporated into the structure is not well understood. Here, the authors explore the crystallization pathways involved in the formation of nacre, and how these affect the incorporation of trace elements. Observations of ACC in natural bio-carbonate systems such as echinoid spicules3, foraminifera shells4 and mollusc nacre5 were among the main drivers of the paradigm change in crystallisation theory from classical monomer-by-monomer processes towards non-classical crystallisation pathways6. In fact, crystallisation via particle attachment and stepwise transformation of metastable precursor phases are now accepted as crystallisation models for many different systems8.A growing body of evidence indicates that calcifying organisms form their hard parts  from amorphous calcium carbonate (ACC), which later transforms via a stepwise crystallisation of intermediate metastable phases rather than by direct precipitation of aragonite and calcite from seawater11. Presently, these reconstructions are based on the incorrect assumption that bio-calcite and -aragonite form directly via precipitation from seawater, while more realistic modelling of uptake and distribution of elements and isotopes through a stepwise crystallisation pathway via ACC is still lacking.Bio-carbonates are important archives for both environmental reconstructions and forward-modelling of future environmental and climatic conditions, including sea-surface temperatures, ocean pH and salinity12. As a general principle, amorphous materials lack defined partition coefficients and are thus less selective with respect to trace element incorporation compared to their crystalline counterparts. In the case of ACC, stepwise crystallisation occurs either via dissolution and reprecipitation, solid-solid transformation or a combination thereof13. While dissolution and reprecipitation mechanisms are governed by equilibrium partition coefficients15, chemical re-distribution during solid-solid transformation can deviate significantly from equilibrium partitioning and instead preserves the original chemical composition of ACC in the crystalline end-product. Thus, either transformation pathway has a significantly different effect on element partitioning into the final crystalline phase.A critical knowledge gap in working towards a new model for element and isotope partitioning in natural bio-carbonates is the lack of insight into the mechanisms by which the different intermediate calcium carbonate phases control the chemical composition of the final stable phase. Generally, the composition of crystalline phases is governed by their distinct crystal chemistry and can be quantified using equilibrium partition coefficients, defined as the concentration ratio of a specific element between two phases17. This pathway is usually associated with significant morphological changes to the texture of the final crystalline phase18. However, the preservation of intricate hierarchical structural details in natural systems during stepwise crystallisation seems to contradict the findings in the laboratory and instead support either solid-solid transformation, or very localised dissolution-reprecipitation processes.In the laboratory, ACC typically transforms via a dissolution and reprecipitation mechanismMytilus galloprovincialis) and a combination of Sr pulse-chase labelling experiments with correlated micro- to sub-nanometre analysis. M. galloprovincialis shells form via a stepwise crystallisation pathway from ACC to aragonite20. Our pulse-chase labelling aquaculture experiments with living bivalves (see methods) produced shells with well-defined bands of Sr-enriched CaCO3 that are visible under the electron and ion beams and serve as timestamps of shell growth21. Aquaculture-based pulse-chase labelling experiments employing trace elements, such as strontium and magnesium, have significantly furthered our understanding of the growth dynamics in various corals and sea urchins23, yet, similar applications to bivalves are rare21. Correlated analysis using Nanoscale Secondary Ion Mass Spectrometry (NanoSIMS), Atom Probe Tomography (APT) and nanoscale Photo-induced Force Microscopy (PiFM) enabled stepwise spatially downscaled visualisation of the time-stamped nacre portions from the meso- to the atomic scale. We show that nacre forms via a two-stepped process of extensional followed by space-filling growth, a process that has long been suggested26 but is directly observed here via the Sr-labelled growth sequence. Most importantly, we demonstrate that the transformation of ACC to aragonite in natural nacre occurs via dissolution and reprecipitation within individual nanogranules, thus elucidating the mechanism behind the preservation of the hierarchical nanostructures in natural biominerals upon stepwise crystallisation.We aim here to elucidate the transformation mechanisms from ACC to aragonite during bivalve nacre growth using living Mediterranean mussel shells  to explore atomic-scale element distribution patterns in Sr-labelled nacre and subsequently correlate these analyses with Photo-induced Force Microscopy (PiFM). Regions of interest in the Sr-enriched shell portion were prepared using the interlamellar organic sheet as a point of reference for atom probe-tip preparation during BSE imaging and simultaneous Focussed Ion Beam (FIB) cutting . PiFM is a nanoscale AFM-based technique that raster-scans the sample surface at high spatial resolution. It measures the force created in a very small interaction volume between the AFM cantilever tip and the sample surface, while a laser sweeps through the infrared spectrum causing absorption-specific variations in the recorded force−1 is the characteristic main band (asymmetric stretching) of aragonite45 and the band at 1658 cm−1 identifies the C=O stretching vibrations of the amide I functional group46. The organic phase is visible throughout the organic interlamellar sheet and as part of the intracrystalline organic matrix inside the nacre tablet. The weaker absorption band at 1446 cm−1, located adjacent to the aragonite main band, is assigned to strontianite. Notably, this band is only present in spectra from the Sr-labelled portions of nacre  of unlabelled and Sr-labelled nacre  to the raw spectra in the HyPIR map shown in Fig. m−1 Fig. . PiFM rem−1 Fig. . We, theThe resulting component maps Fig.  verify o24: Extensional nacre growth occurs along the local growth direction of the shell normal to the organic interlamellar sheets  and Sr-poor  portions within individual nacre tablets  rather than based on their chemical composition: Nassif et al.19 reported similarly sized, 3–5 nm wide ACC layers coating the nacre tablets in Haliotis laevigata. In the shell of Phorcus turbinatus and at spatial resolution of individual nanogranules, Macias-Sanchez et al.34 observed 5–10 nm wide ACC coatings along the exteriors of crystalline aragonite nanogranules (referred to as nanoglobules). Both studies34 argue that these ACC-rich areas represent vestiges of the non-classical crystallisation pathway of nacre and represent phase separations combined with stabilisation of ACC by trace metal ions and/or organic molecules expelled upon crystallisation of aragonite48. Similarly, we interpret the Sr heterogeneity observed here as a result of phase transformation of ACC confined within nanogranules that are caused by the phase separation and the exclusion of excess Sr upon crystallisation of aragonite.Heterogeneity of similar dimensions, including in nacre nanogranules have been previously reported in the literature49 of the growing shell due to the lack of long-range order of the ACC52. Subsequent crystallisation of ACC in the nanogranules is most likely triggered by dehydration53 aided by the fact that the organic sheath, which delineates the nanogranular biomineralization compartments, is highly permeable for water54. Upon crystallisation in the confinement of nanogranules, phase separation manifests in areas of pure aragonite, separated from areas of strontianite or perhaps aragonite-strontianite solid solutions56 beyond the 5 nm spatial resolution of PiFM. These Sr-rich areas are confined to individual nanogranules rather than straddling their boundaries, as the nanogranules are individually coated by an organic sheath that prevents effective material transport. Hence, each organic-coated nanogranule37 serves as a compartment for the crystallisation of aragonite from ACC in confinement57.During aquaculture, Sr is non-selectively incorporated from the Sr-enriched seawater into the ACC phase58. Dissolution and reprecipitation, on the other hand, involves material transport, thus creating heterogeneity, and leads to the heterogeneous distribution of aragonite and strontianite at the nanoscale. Dissolution and reprecipitation transformation from ACC to aragonite confined to individual nanogranules explain the preservation of the space-filling nanogranular texture of nacre. Spatially coupled dissolution-reprecipitation reactions that preserve the fine structures and overall shape of the replaced mineral, kinetically outcompete solid-solid transformation reactions and are, in fact, very common in mineralised systems59. They are catalysed by a fluid and are usually driven by small free energy differences between the reaction partner phases. Specifically, in interface-coupled systems with an interfacial fluid58, the dissolution rate of one and the activation energy barrier for nucleation of the other reaction partner create local equilibrium conditions, which result in the preservation of very fine structural details after phase transformation61.The systematic presence of Sr-enriched and Sr-poor areas observed within individual nanogranules throughout the nacre tablet is a critical indication that the major transformation mechanism is the dissolution of the ACC to crystallise as aragonite. Upon transformation via a solid-solid mechanism, the chemical composition would remain unchanged and would therefore not be heterogeneous18. These previous experiments thus fail to explain the preservation of the hierarchical ultrastructure observed in natural biominerals and, thus, seem to support solid-solid transformation of ACC to the crystalline calcium carbonate phase. We provide here direct observational evidence in naturally formed nacre that the ACC-to-aragonite transformation proceeds via an intragranular and spatially confined dissolution-reprecipitation mechanism. Our findings resolve the long-standing question around the transformation processes of natural nacre and show that the fine structural details of the material are preserved by a dissolution-reprecipitation mechanism that takes place in confined compartments of organically coated nanogranules.Compared to natural biomineralization systems, a common issue encountered in laboratory dissolution-reprecipitation experiments is the significant morphological change occurring during transformationMytilus galloprovincialis  were collected alive from Twofold Bay, New South Wales, Australia and brought to the Macquarie University Seawater Facility. About 50 juvenile mussels sized 5–30 mm were evenly divided into two 50 L polyethylene tanks that were connected to a recirculating system for sterilised, filtered natural seawater sourced outside the Sydney harbour. The tanks were maintained at local ocean temperature, salinity and pH, while the lighting was adjusted to a circadian day/night cycle. The mussels were fed daily using a commercially available microalgae mix 31. After 3 weeks of acclimatisation, the experimental period consisted of 35–55 days in which bivalves were transferred four times (group 1) and three times (group 2) from ambient seawater  to conditions with elevated Sr concentrations of 120 µg/g (15× mean ocean water). The Sr-enriched seawater was produced by dissolving 0.37 g strontium dichloride hexahydrate  per litre into the tanks. Sr-labelling intervals were maintained for 3 days (group 1) and 6 days (group 2) and Sr-enriched seawater was fully replaced every 48 h. Between the labelling events, mussels were transferred back to ambient conditions for 6 (group 1) and 12 (group 2) days. After the last labelling event, mussels were collected and deep-frozen at −20 °C. After the experiments, soft tissues were removed, shells were rinsed in deionized water and air-dried. Strontium was chosen as an elemental marker for pulse-chase labelling experiments, as Sr/Ca ratios in ACC are linearly dependent to the ratio in seawater49.Juvenile Mediterranean mussels 62. Polished mounts were used for PiFM without any additional preparation steps, while SEM-EDS and NanoSIMS analyses required sputter coating with carbon (20 nm) and gold (10 nm), respectively.Shells were mounted in EpoFix epoxy resin  and left to cure in the fridge at 2 °C. Lapping and polishing consisted of a series of 500–4000 grit diamond lapping discs, followed by 3 and 1 μm diamond suspensions and a diluted suspension of 0.04 μm colloidal silica  concluded the polishing31. In situ liftouts were performed by using an accelerating voltage of 30 KV and a beam current of 1 nA. Annular milling was performed using a Zeiss Auriga FIB-SEM starting at 30 kV and 1 nA and stepping down the voltage and current to 10 kV and 50 pA. As nacre is a highly beam-sensitive material, it was crucial to use suitable FIB parameters and to maintain adequately low  electron-beam conditions for imaging during preparation31.Specimens for APT were prepared using the Xe beam of a ThermoFisher Helios Hydra G4 UXe DualBeam Plasma Focussed Ion Beam-Scanning Electron Microscope (FIB-SEM) at the Australian Centre for Microscopy and Microanalysis (ACMM), University of Sydney. Regions of interest in the shells were BSE imaged to visualise the Sr-labelled nacre layers while accurately depositing the platinum protection strips onto the target areas for liftout  and operating conditions were 20 kV accelerating voltage, 12 mm working distance and 200 pA beam current. The primary electron beam was focused to a spot size of 400 nm that scanned a map area of 80 × 60 µm at a resolution of 1027 × 768 pixels. A ZAF correction was applied automatically by the software and major element concentrations resemble previous wavelength dispersive analysis21. Data processing was also performed using the AZtec 3.1 software.A Zeiss EVO MA15 tungsten SEM equipped with an Oxford 20 mmHigh-resolution backscattered electron (BSE) images of polished cross-sections were taken using a JEOL JSM-7100F field emission gun-scanning electron microscope (FEG-SEM) at Macquarie University. Images were acquired at 15 kV acceleration voltage and 8 nA beam current.88Sr/40Ca isotope abundances were mapped using a new generation CAMECA NanoSIMS 50 L ion probe at the University of Western Australia. Operation conditions followed published procedures21. A Hyperion RF plasma oxygen ion source produced a primary oxygen ion beam that was focused to a spot size of 100 nm to scan 50 × 50 μm map areas at a resolution of 512 × 512 pixels. Both Ca and Sr isotopes were measured on electron multipliers at 5000 mass resolution. Data reduction was performed using the OpenMIMS plugin (Harvard University) for ImageJ.31 and consisted of a pulse energy of 100–200 pJ, a pulse frequency of 160 kHz and a 0.5% detection rate that yielded a data set of 3 million detector hits . The tip shape geometries of all datasets were calibrated by using SEM images, which gives a more accurate result for biominerals than using the voltage evolution curve31. Data reconstruction, 3D visualisation and compositional profiles were obtained using the IVAS software version v3.8.4. All compositional profiles : The dashed line marking the transition from Sr-poor to Sr-rich aragonite areas was defined by a significant increase in Sr, while the dashed line marking the transition from the Sr-rich aragonite to the organic interlamellar sheet was set to the intercept point of Ca and C Fig.  and 9.42. We used a quantum cascade laser (QCL)-module from Block Engineering LLC as excitation source consisting of four serially connected gap-free QCLs that provide access to a wide wavenumber range of 770–1860 cm−1. Measurements were conducted in dynamic AC AFM mode using a NanosensorsTM 300 kHz platinum iridium-coated, non-contact, silicon-based AFM probe . For more details on the instrumentation and methodology see Otter et al.42. All PiFM data were processed in SurfaceWorks 3.0 Release 30. PiFM spectra were normalised to the laser power profile and smoothed with a factor of 17.PiFM analyses were conducted using a VistaOne system at Molecular Vista Inc. San Jose, CA-USA. The method is based on conventional atomic force microscopy (AFM) and utilises the oscillating movements of a piezoelectric metal-coated cantilever while probing the sample surface. A wavelength-tunable IR laser is used to illuminate the sample area below the cantilever tip and the absorption in characteristic FTIR fingerprint regions is recorded by the increased attraction force on the cantilever43. Hence, PiFM can resolve nanoscale phase heterogeneity more appropriately and even separate individual neighbouring peaks that are not spectrally resolved in the broader FTIR absorption band envelopes. For this reason, we include PiFM absorption spectra of geological aragonite  and synthetic strontianite  for comparison (Fig. The absorption bands produced by PiFM correlate with those from traditional FTIR apart from the fact that PiFM bands are narrower, due to the monochromatic excitation source and the significantly smaller sampling areason Fig. . These sPCA/MCR was performed in SurfaceWorks 3.0 Release 30 using the PCA/MCR plugin. All input spectra from the HyPIR map shown in Fig. For a list of samples and experiments see Supplementary Table Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Reporting Summary


Breast carcinoma (BCa) remains the second most common cause of cancer-related death among American women. Whereas estrogen receptor (ER) expression is typically regarded as a favorable prognostic indicator, a significant proportion of ER(+) patients still experience either de novo or acquired endocrine resistance. Previously, we have shown that the loss of orphan nuclear receptor NURR1 expression is associated with neoplastic transformation of the breast epithelium and shorter relapse-free survival (RFS) among systemically treated breast cancer (BCa) patients. Here, we further ascertain the prognostic value of NURR1 in BCa, and its differential expression among Black and White female BCa patients. We assessed the expression of NURR1 mRNA in BCa patients using the Cancer Genome Atlas (TGCA) and compared the occurrence of basal-like cancer and luminal A breast cancer subtypes. Expression levels were further stratified according to racial identity of the patient. We next assessed the correlation of NURR1 expression with Oncotype DX prognostic markers, and the association of NURR1 expression with relapse free survival in patients treated with endocrine therapy. Our study shows that NURR1 mRNA expression is differentially correlated with luminal A vs. basal-like cancer BCa and is predictive of poor relapse-free survival, confirming a similar trend observed in our previous studies using microarray data. NURR1 expression was positively correlated with expression of Oncotype DX biomarkers associated with estrogen responsiveness, while being inversely correlated with biomarkers associated with cell proliferation. Furthermore, we observed that NURR1 expression was positively associated with greater relapse-free survival at 5 years among patients treated with endocrine therapy. Interestingly, we found that among Black women with luminal A BCa, NURR1 expression was repressed in comparison to White women with the same subtype. Breast cancer (BCa) is one of the leading causes of cancer death in women. The majority of breast cancers are estrogen receptor positive ER(+) and initially respond well to endocrine therapy. However, some patients with ER(+) BCa do not respond to endocrine therapy resulting in poor survival outcomes. Analyzing the Cancer Genome Atlas datasets, we found that patients with low expression of NURR1 gene with ER(+) BCa have poor survivorship in response to treatment. This low NURR1 expression is predominantly found in Black patients compared to other population groups leading to the disparity in ER(+) BCa. NURR1 expression can serve as a prognostic biomarker in identifying ER(+) BCa patients that may benefit from early, aggressive treatment strategies. AccordiOur intent is to determine if there exist specific biomarkers that can further stratify patients beyond the current molecular and histological subtypes to better assess the BCa-related mortality risk, and if those markers are relevant to Black patients who have historically been excluded from clinical studies. Currently, the “gold standard” for assessing recurrence risk for patients with an ER(+) and lymph node-negative BCa diagnosis is the Oncotype DX genomic test –12. In tNURR1 (NR4A2) is a member of the NR4A family of orphan nuclear receptors  ,16. NR4ANURR1 appears to play divergent roles in cancer progression . In breaIn this study, we sought to further characterize the prognostic significance of NURR1 expression in BCa, and whether a differential prognostic significance exists based on the population under study. Utilizing TCGA (the Cancer Genome Atlas) PanCancer Atlas data through the KMPlotter and CBioportal webtools, we assessed the expression of NURR1 in luminal A and basal-like cancer BCa, and among Black and White patients stratified by molecular subtype. Additionally, we compared the prognostic significance of NURR1 to that of the individual Oncotype DX RS component genes and assessed the correlation of NURR1 with better 5yr RFS rates among patients taking endocrine therapy. It is our assertion that NURR1 may function as a specific biomarker that may help to identify higher risk Luminal A BCa patients and contribute to reducing the disparity in RFS suffered by Black women with breast cancer.2.2.1.kmplot.org) to generate Kaplan-Meier survival curves for overall survival of BCa patients with high (upper quartile) or low (lower quartile) expression of NURR1 based on mRNA-seq data in the Cancer Genome Atlas (TGCA) PanCancer Atlas . We. Wep valiomarker . The AUC × 10−5) . The AUC4.The underrepresentation of people of color in various clinical trials and the mismatch between clinical trial representation with the real-world population has been documented by various studies . MultiplA recent study conducted on 1332 women (including 666 Black) found that Black women had larger tumor sizes, increased nodal disease, and higher percentages of triple negative subtype with poor disease-free survival and overall survival . The ideIn our previous studies we have shown that the orphan nuclear receptor NURR1 is most highly expressed in normal breast epithelium, is repressed transformed breast epithelium . In BCa,RS is the sum of all these scores multiplied to their coefficients as shown in the equation below.The oncotype DX assay’s recurrence score n levels . These gvels [RS . There aficients  13]. Th. Th(RS) group gene expression results in lower The S values . The RS te risk” . We founCa cases . RegardlCa cases . It is o5.Our studies suggest that NURR1 is differentially expressed at higher levels in less aggressive BCa phenotypes, and that its expression is likely a marker for endocrine sensitivity among patients with luminal A BCa. Additionally, we show that NURR1 is expressed at lower levels among Black women with BCa, and that this may contribute to disparities associated with BCa survivorship. These findings suggest that NURR1 may function as a biomarker for favorable outcome in BCa and may be a feasible pharmacologic target in BCa. Furthermore, this may yield insight into the factors associated with continued racial disparities in breast cancer survival, which persist even among Black patients with so-called favorable BCa phenotypes.


The noradrenergic system is implicated to support behavioral flexibility by increasing exploration during periods of uncertainty and by enhancing working memory for goal-relevant stimuli. Possible sources mediating these pro-cognitive effects are α2A adrenoceptors (α2AR) in prefrontal cortex or the anterior cingulate cortex facilitating fronto-striatal learning processes. We tested this hypothesis by selectively stimulating α2ARs using Guanfacine during feature-based attentional set shifting in nonhuman primates. We found that α2A stimulation improved learning from errors and facilitates updating the target feature of an attentional set. Neural recordings in the anterior cingulate cortex (ACC), the dorsolateral prefrontal cortex (dlPFC), and the striatum showed that α2A stimulation selectively enhanced the neural representation of negative reward prediction errors in neurons of the ACC and of positive prediction errors in the striatum, but not in dlPFC. This modulation was accompanied by enhanced encoding of the feature and location of the attended target across the fronto-striatal network. Enhanced learning was paralleled by enhanced encoding of outcomes in putative fast-spiking interneurons in the ACC, dlPFC, and striatum but not in broad spiking cells, pointing to an interneuron mediated mechanism of α2AR action. These results illustrate that α2A receptors causally support the noradrenergic enhancement of updating attention sets through an enhancement of prediction error signaling in the ACC and the striatum. The noradrenergic system supports attention, working memory and learning functions . These hThere are various ways how noradrenergic modulation could support the flexible switching of cognitive states. One possibility is that tonic noradrenergic enhancement modulates arousal , and inci) it is a highly selective α2A receptor agonist with 15–60x higher affinity for the α2A, over the α2B and α2C subtypes (ii) its mechanism enhancing working memory in neurons of the dlPFC is well documented (iii) its possible modulation of flexibility has remained unclear , the dorsolateral prefrontal cortex , and the head of the caudate nucleus (striatum). We investigated these questions by administering the α2A receptor specific drug Guanfacine in NHP performing an attention set shifting task while we recorded single neuron activity in ACC, dlPFC, and striatum. NHP lesion studies have documented these areas are necessary for adaptive learning and each area contains neurons with activity correlating with efficient learning of abstract feature values during set shifting . The tassubtypes , (ii) itcumented , while  and 66  electrophysiological recording sessions respectively. A total of 1157 single units (619 and 538 units from monkey H and K) were collected across the ACC , dlPFC , and in the anterior striatum (n = 291 units) .We quantified the speed of reversal learning on days with vehicle and Guanfacine administration as the first trial in a block at which performance exceeded the learning criterion . Average learning occurred at trial 16 and occurred 3.2 trials earlier with Guanfacine than with vehicle . Later in the block , Guanfacine did not affect performance after error  or correct trials .Faster learning could be achieved by adjusting performance after nonrewarded (error) trials or after rewarded (correct) choices. We tested for changes in performance accuracy post-error and post-correct trials early or later in a block and found a significant main effect of drug condition  = 4.89; p = .028), block timing  = 62.54; p < .001) and post-error vs post-correct trials  = 266.48; p < .001) with a significant interaction between drug condition and timing in the block  = 6.63; p = .010). These results reflect that early in the block , Guanfacine significantly improved post-error performance for 2 trials after an error  , but didWe analyzed the pupil diameter of the monkeys to infer the effect of Guanfacine on noradrenergic neuron activity in the locus coeruleus (LC). During the first three blocks of each session, when Guanfacine concentrations are highest, monkeys had a more constricted pupil diameter compared to vehicle  . The enhThe effects of Guanfacine on outcome encoding and RPE signaling were primarily a modulation of the strength of encoding without altering the overall proportions of neurons encoding outcome variables in the feedback epoch .Previous studies have shown that reversal learning recruits proportionally more narrow spiking (NS) neurons in ACC, dlPFC and striatum , 2021. W2 values and ranking neurons according to the best explaining variables, which showed that in the feedback epoch the best-fit variable rankings for Guanfacine and vehicle were significantly correlated and thus similar during the feedback epoch in the dlPFC , ACC , and striatum  , the chosen location in the striatum (p = .019) and the target location in the ACC (p = .024) in the feedback epoch of the task . These e = .425) .A prior study suggested that Guanfacine can enhance in the dlPFC the neural representations of attended, short-term memorized stimulus locations during a delay period prior to making a choice . In our Here, we reported the behavioral and neural activity signatures of noraderenrgic α2A receptor-specific enhancement of flexible learning. We developed a feature-based attentional set shifting task that required reversing the target color of an attention set through trial-and-error learning. A previous behavioral study suggested that Guanfacine facilitates reversing attentional sets through two mechanisms, enhancing how strong prediction errors are used to update expected values and by reducing the influence of non-attended features . Here, wTaken together, these findings suggest that noradrenergic signaling in all three recorded brain areas, ACC, dlPFC, and striatum, supports cognitive flexibility by enhancing prediction error signaling and improving the representation of the target feature in a top-down attention set. This conclusion is consistent with recent causal manipulation studies in rodent , and calOur findings of enhanced RPE encoding and faster reversal learning support conclusions from studies in mice documenting noradrenergic neurons in the locus coeruleus causally support flexible behavioral switching of stimulus - reward associations . In thesGuanfacine enhanced the correlation of neural firing with task relevant variables without increasing the number of neurons with firing correlations. This pattern of results reflects an enhanced neuronal signal-to-noise ratio for coding task relevant variables, which included better encoding of the color feature of the target stimulus. This conclusion corroborates and extends the seminal NHP study of Guanfacine in dlPFC by Arnsten, Wang and colleagues . In theiOur electrophysiological recordings allowed distinguishing narrow spiking (NS) from broad spiking (BS) neurons , with NSOur study documents that Guanfacine enhances flexible reversal learning of attention sets, which adds clarity to the potential of Guanfacine as a highly selective α2A acting drug to enhance attentional functions . Our resWe found the neural correlates of enhanced set shifting in those neural circuits in the ACC and striatum of NHPs that are known to activate during guided exploratory behavior and information seeking . ActivitPrevious studies with α2A agonists in NHP have overwhelmingly described working memory improvements  age 7 and 9 years old. Both subjects were fluid restricted during the length of the experiment with unrestricted access to chow. All animal care and experimental protocols were approved by the York University Council on Animal Care and were in accordance with the Canadian Council on Animal Care guidelines.Data was recorded from two male rhesus macaques (https://www.brown.edu/Research/monkeylogic/). Eye positions were calibrated and tracked monocularly using a video-based eye tracking system . Eye calibration occurred daily using a 9-point fixation pattern and was monitored throughout each session. Liquid reward, controlled from an air-pressure mechanical valve system  was delivered via a sipper tube.Animals were seated in a custom-made primate chair and placed in a dark, sound attenuated booth such that their eyes were 65 cm away from a 21’ LCD monitor with a 85 Hz refresh rate. Experimental control, including stimulus presentation, eye positioning monitoring and reward delivery was done through MonkeyLogic . The learning trial was then defined as the trial during which the lower 95% confidence bound exceeded chance (p = 0.5) and did not drop back down below chance for the rest of the block.To identify learned blocks and an individual trial where statistically reliable learning could be said to have occurred in each block, we used an ideal observer estimation maximization (EM) algorithm . BrieflyGuanfacine was purchased  and prepared with sterile water vehicle (0.1 mL volume) immediately before blinded IM injections. Subjects received Guanfacine (0.075 mg/kg) or sterile water vehicle injections close to 2 hours before the start of the first trial (mean: 135 ± SE 2 min). Each week contained at most a single Guanfacine administration day which was always either on Thursday or Friday while vehicle data was collected on either Tuesdays or Wednesdays; animals still trained every day. In total, we recorded 17 and 12 Guanfacine days for monkey Ha and monkey Ke respectively. We the selected dose of Guanfacine because it was previously shown that it enhances performance in this task .Single contact tungsten electrodes  were used for extracellular recordings. They were loaded into up to 4 software-controlled precision micro-drives  and lowered into the brain through a 20×25 mm rectangular recording chamber guided by MR images. Single units were recorded in the dlPFC (area 46), the ACC (area 24), and the head of the caudate nucleus  Figure . Data amHighly isolated single units were classified based on the properties of their actin potential waveforms using previously published methods . BrieflySpike trains were transformed into spike-density functions smoothed with a Gaussian kernel with a standard deviation of 50 ms. Only correct (rewarded) and incorrect choice trials were analyzed; incorrect trials were defined as unrewarded trials where either the unrewarded object was chosen or any choice was made during the dimming  of the unrewarded object (either before or after the dimming of the rewarded object). The average trial-wise activity during the epoch of interest (0.05–1s during the feedback epoch and 0.05–0.7s during the attention cue onset epoch) of each neuron was regressed to 18 variables that were classified as either stimulus variables, outcome variables or latent model variables. The 6 binary stimulus variables were the color (color 1 vs color 2), motion (up vs down) and location (left vs right) of the chosen stimulus and the color, motion and location of the rewarded stimulus. The outcome variables were trial outcomes (binary: rewarded or unrewarded), trial outcomes during learning only see  above, tA single neuron may have multiple significant regressions and for each significant regression , a correlation coefficient was computed. These coefficients were then averaged for Guanfacine and non-drug neurons and their difference plotted separated between unsigned, positive and negative correlation coefficients for each brain region and also split by putative cell types. Statistical comparison between Guanfacine and non-drug neurons was done through bootstrapping with shuffled condition labels (5000 permutations). Only comparisons with at least 3 neurons in both Guanfacine and non-drug categories were statistically tested.2) was also identified. Then the variables that best explained activity in each brain region were ranked based on the proportion of neurons that had the highest R2 value per variable (For each neuron, the strongest regression (significant regression with the highest Rvariable . This raWe estimated latent variables underlying learning performance including the reward prediction error and the expected stimulus values using a hybrid Bayesian-reinforcement learning model as validated and described in previous studies . This moSupplement 1


Administration of levodopa for Parkinson’s disease (PD) has remained the most effective therapy for symptom management despite being in use for over 50 years. Advancing disease and age, changing tolerability and gastrointestinal (GI) dysfunction may result in change in dietary habits and body weight, as well as unpredictable motor fluctuations and dyskinesias. Dietary proteins which convert into amino acids after digestion are implicated as major factors that inhibit levodopa absorption. For people living with PD (PwP) who experience motor fluctuations, low protein diets (LPD) and protein redistribution diets (PRD) may be effective and are often recommended as a non-pharmacologic approach for improving levodopa bioavailability. However, there is a lack of consensus on a standard definition of these diets and appropriate treatment algorithms for usage. This may be due to the paucity of high-level evidence of LPD and PRD in PwP and whether all or specific subgroups of patients would benefit from these strategies. Managing diet and protein intake with proper education and monitoring may reduce complications associated with these diets such as dyskinesias and unintentional weight loss. Additionally, alterations to medications and GI function may alter levodopa pharmacokinetics. In this narrative review we focus on 1) mechanisms of dietary protein and levodopa absorption in the intestine and blood brain barrier, 2) dietetic approaches to manage protein and levodopa interactions and 3) practical issues for treating PwP as well as future directions to be considered. While levodopa has been investigated in human studies as early as the 1960s4, optimization of delivery and absorption remain critical issues – particularly in people living with PD (PwP) who experience suboptimal improvements in motor symptoms and advanced disease. Levodopa  is transported via the gastrointestinal (GI) tract, enters systemic circulation and is eventually transported across the blood-brain-barrier (BBB) where it is later converted to dopamine for utilization. To improve absorption and prevent early  conversion to dopamine, levodopa is usually co-administered with carbidopa or benserazide5. Furthermore, levodopa is catabolized by the enzyme catecholamine-O-methyltransferase (COMT) to form 3-O-methyldopa (3-OMD) which may inhibit levodopa metabolism to form dopamine. An increase in plasma levodopa levels has been documented with matched motor response in PwP7 and remains a useful tool for studying levodopa pharmacokinetics. Other factors that have been associated with levodopa bioavailability include age, sex, race, and low body mass index (BMI), which highlights the importance of dose customization11.Often utilized early and throughout the course of Parkinson’s disease (PD), orally administered levodopa  is a precursor for dopamine and considered to be the standard pharmacologic treatment for management of PD symptoms12. Levodopa-induced dyskinesias may appear as early as within the first 6 years from PD diagnosis14. These dyskinesias and motor fluctuations can also be accompanied by a host of issues including hypermetabolism, fatigue, dysphagia, low appetite and BMI, and decreased quality of life15. Disease progression may also contribute to the need for increased amounts and frequency of levodopa doses due to an elevated “threshold” for therapeutic response after chronic usage and a decrease in the amount of functional dopaminergic neurons16. Chronic levodopa absorption is hindered by complex interactions between drug kinetics (including patient-specific parameters), PD pathophysiology (disease progression and GI dysfunction) and food intake  which can prove challenging for management5. Dietary approaches such as low protein (LPD) and protein redistribution diets (PRD) have been proposed over the years to improve levodopa response. Efficacy of LPD and PRD diets have been systematically reviewed within the last decade18 but questions remain regarding appropriate treatment algorithms and customization of care to identify those PwP who would benefit the most from these diets. The purpose of this narrative review is to discuss 1) current literature on levodopa and dietary protein pharmacokinetics and interactions, 2) efficacy of LPD and PRD and 3) challenges and limitations for managing these interactions.Adverse effects of chronic levodopa usage and disease progression include dyskinesias and increased motor fluctuations which can be defined as unpredictable changes from optimal motor control (“ON” period) to decreased motor control in which symptoms reappear (“OFF” periods)5. When administered, levodopa is considered to be a large neutral amino acid and structurally similar to other aromatic amino acids such as phenylalanine, tyrosine, and tryptophan, and its absorption primarily occurs in the proximal intestine20.In the peripheral tissues , there is increased metabolism of levodopa to dopamine by the vitamin B6-dependent enzyme, aromatic L-amino acid decarboxylase (AADC). To prevent early conversion to dopamine in the peripheral tissues by AADC, AADC inhibitors  are co-administered with levodopa to improve bioavailability, thus decreasing the cumulative therapeutic dose and subsequent degree of peripheral side effects21. While fasting levodopa time to peak absorption (tmax) is rapid ranging from 15 to 60 min23, delayed gastric emptying and constipation can significantly increase the tmax and decrease the maximum peak concentration (Cmax) of the drug5. This reduction in Cmax is possibly due to increased pre-systemic decarboxylation of levodopa by AADC, reducing bioavailability and absorption. While PwP are predominately male24, pharmacokinetic studies have shown that women have a higher area under the curve (AUC) and Cmax even after adjusting for body weight25. It is posited from these studies that differences may be due to variations in hormones , body weight/BMI and composition, and COMT activity. Subsequently, dyskinesias are more prevalent in women likely due to higher levodopa bioavailability28.The rate of gastric transit and sex differences can pose significant challenges to levodopa delivery. GI dysfunction is a common non-motor symptom in PD and highly prevalent in up to 80% of PwP. Constipation and gastroparesis (delayed gastric emptying) are among the more common GI symptoms in PwP29. These series of reactions yield mainly di- and tripeptides that can transport via intestinal peptide transporter 1 (PEPT1) on the apical membrane where they are further broken down in the enterocyte into free amino acids by cytosolic peptidases30. Free amino acids circulating in the lumen can enter the enterocyte at the apical membrane and exit on the basolateral side through these amino acid transport systems31. Amino acid transport systems are highly specific depending on affinity, and competition can arise during absorption. These transport systems are the primary target for levodopa absorption across the intestine and through the BBB.Unlike levodopa, dietary forms of protein must undergo enzymatic digestion in the stomach and proximal intestine to unfold quaternary, tertiary and secondary structures prior to absorption in the proximal intestine32. Using in vitro and in vivo models, Camrago et al. demonstrated levodopa can be transported by enterocytes across the apical membrane through the b0,+AT-rBAT (SLC7A9-SLC3A1) and exits the basolateral side primarily by TAT1 (SLC16A10) and LAT2-4F2hc (SLC7A8-SLC3A2) to a lesser extent32. b0,+AT-rBAT is an antiporter exchanging large neutral amino acids on the luminal side, while TAT1 is an aromatic amino acid uniporter and LAT2-4F2hc is antiporter on the basolateral side. In these models, levodopa is competitively inhibited by neutral and cationic amino acids such as leucine and arginine for uptake by b0,+AT-rBAT  or COMT inhibitors (i.e. entacapone) does not seem to inhibit levodopa transport across b0,+AT-rBAT despite having a similar structure to levodopa. In the postprandial phase, increased amino acid accumulation in the portal vein may trans-stimulate increased efflux from LAT2-4F2hc on the basolateral membrane, suggesting a potential target for improving levodopa absorption with meals.In practice it has been thought that levodopa is absorbed by the same transporters as free, large neutral amino acids; however, current evidence remains limited on the intestinal transporters involved in this mechanism. To date, only one study published in 2014 has identified the transporters involved38. The results of these studies further prompted investigations of protein-restricted diets in PwP (described later) in order to possibly limit competition of amino acid transport systems. Protein intake in both people with- and without PD has failed to show reduced tmax and Cmax in previous studies40, which suggests that intestinal absorption of levodopa may be more affected by GI dysfunction (discussed in later sections) and fluctuations in plasma LNAA levels for transport across the BBB.The effects of meals and dietary protein on levodopa absorption has been described as early as 1973 in PwP who experience motor fluctuations5. Circulating amino acids (both endogenous and exogenous) can be transported across the BBB by a variety of amino acid transport systems41. Similar to intestinal absorption, levodopa has been shown to cross the BBB via the sodium-dependent antiporter, LAT1-4F2hc (SLC7A5-SLC3A2) expressed on endothelial cells43  as it displays even greater affinity for amino acids such as phenylalanine, tryptophan and leucine. These amino acids are found commonly in protein-containing foods and supplements which may drive further competition for levodopa absorption when administered with meals45.The bioavailability of levodopa within systemic circulation prior to crossing the BBB is considered one of the main determinants of levodopa pharmacokinetics49. Using MPTP-induced parkinsonian monkeys, Alexander et al. investigated the effect of levodopa and LNAA influx comparing striatal extracellular fluid (ECF) as a ratio to plasma levodopa46. As expected, co-infusion of LNAA and an oral high protein meal (given prior to infusion) inhibited uptake of levodopa by 54–75% and 17–56%, respectively. Differences were not seen between control and MPTP-induced monkeys suggesting the transport rate may not always be disease-specific. Two studies have measured levodopa and amino acid competition using positron emission tomography (PET) and demonstrated co-administration of amino acids led to a reduction of levodopa uptake compared to fasting in humans and plasma LNAA concentrations were negatively correlated (r2 = 0.51) with BBB influx rates in monkeys48. It should be noted that timing of dietary protein interventions in all studies was either via co-infusion or before levodopa administration. Because half-life of levodopa in both plasma and striatal ECF were noted to be approximately 30 min, future studies should aim to investigate carry over effects of dietary protein interactions when levodopa is administrated in a fasted state.The effect of plasma amino acid concentration  and inhibition of levodopa at the BBB has been described in 4 studies using both animal models and clinical studies in PwP5 51 and correlated with a higher daily levodopa dose53. For PwP who experience significant motor fluctuations, the American Academy of Neurology (AAN) and European Society for Clinical Nutrition and Metabolism (ESPEN) have included LPD and PRD as potential complementary therapeutic diets for PD management in their guidelines56.Levodopa is often recommended to be taken on an empty stomach 20–30 min before or 1–2 h after meals to improve bioavailability51. With the exception of 2 studies57, the use of LPD has not been thoroughly investigated. Both trials were single arm, controlled feeding studies consisting of multi-phase interventions including low protein (10 g/day or 0.5 g/kg body weight), normal protein (1.0 g/kg body weight) or high protein (2.0 g/kg body weight). In the study by Gillespie et al. the multi-phase interventions were implemented with either levodopa alone or levodopa combined with an unspecified peripheral inhibitor37. Timing of levodopa with meals was not reported. The authors noted body weight did not significantly differ during the interventions (data unreported). Participants (n = 8) reported discomfort consuming 10 g/day and 2.0 g/kg body weight while other diet phases including 0.5 g/kg/day were acceptable. Authors concluded the LPD tended to “potentiate and stabilize the therapeutic effect of levodopa” but no motor disability scales or scores were reported. In general, prolonged protein intake of 10 g/day is not recommended due to inability to satisfy whole body protein turnover and increase risk of deficiency51.There is no standard definition adopted for LPD but is generally accepted as limiting protein consumption below the RDA for adults ( <0.8 g/kg of body weight per day)57. When compared to the run-in phase (1.0 g/kg body weight), both protein intakes of 10 g/day and 0.5 g/kg/body weight resulted in reduction of New York University Scale scores of approximately 8 and 3 points, respectively. Of the participants followed for 2 months (n = 4) to 1 year (n = 3), consuming protein intakes of 0.5 g/kg/body weight resulted in 70% of participants reported satisfaction with diet and 30% reporting no improvement. Limitations of these studies also include small sample sizes, missing data, lack of randomization and variability in response amongst participants. Conflicting consensus exists between the AAN and ESPEN guidelines with ESPEN not supporting use of LPD in the absence of high-quality trials56.Mena et al. whom further reported on protein intakes of 10 g/day and 0.5 g/kg body weight in 7 participants18. Similar to LPD, there is no consensus for recommended amounts of protein in PRD, but redistribution is defined as limiting protein intake at breakfast and lunch with no quantitative restrictions of protein content at dinner. Early work by Pincus et al. described one of the first PRD protocols which aimed to characterize the effect of a low protein phase (7 g) during the daytime (8:00 am–4:00 pm) on levodopa pharmacokinetics when compared to a high protein phase (160 g) in 15 participants58. Food intake in the evening was not specifically reported. During the daytime, plasma LNAA were significantly lower in the low protein phase as well as increased sensitivity to levodopa and improvements in disability scores were observed.PRD diets have been more extensively investigated in the literature than LPD66. Seven studies66 implemented interventions with total protein intake between 30 and 80 g/day. Only 3 studies60 implemented interventions with protein intake based on body weight between 0.8 and 1.0 g/kg/day. Redistribution in all studies was typically defined as protein intake between 0 and 10 g during the day (including breakfast and lunch) and the remaining amount of protein consumed at dinner. Control diets were absent in 6 studies65 and outcomes were compared to participants baseline values. The remaining studies66 with control diet phases included either normal and/or high protein diets with even distribution between meals. Duration of interventions was typically short ( <1 month) with one study investigating feasibility of PRD after 2 years62.Further, PRD diets on levodopa response in PwP have been documented in 10 studies64. Barichella et al. reported significant differences between PRD and balanced protein diets on postprandial ON and OFF periods 59. Lowers disability scores with PRD were also reported in 3 studies66. Plasma concentrations of levodopa and LNAA after a PRD were also reported66. Higher concentrations of LNAA were significant in the high protein vs PRD groups66. However, there is conflicting evidence whether PRD improves plasma levodopa concentrations as studies reported either no difference between groups38 or higher concentrations with high protein diets66. In a separated study by Simon et al. levodopa pharmacokinetics were compared between a low protein breakfast (mean intake of 7.6 g) with a high protein lunch (mean intake of 38.7 g)40. No differences in tmax or Cmax were observed between groups and significantly higher AUC for the high protein lunch was noted. Post hoc analyses by the authors revealed this effect may be mediated by levodopa dosage and carry over effects of the low protein breakfast as the high protein lunch was correlated with higher trough concentrations. Therefore, it is hypothesized the benefit of PRD may be a result of improved competition at the BBB vs peripherally and should be confirmed in future studies.Lower and/or improvements in motor symptoms  in PwP following a PRD ranged from 32 to 79% depending on the scale used64. Motor fluctuations are associated with younger age of onset, sex and advanced stages of disease (Hoehn & Yahr [H&Y] stage ≥3)69. Interestingly, an in silico GI computational model of levodopa pharmacokinetics demonstrated H&Y stage 3 and 4 may benefit the most from modifications in protein intake (LPD or PRD)34. LPD did not show any benefit for the predicted AUC, while PRD was predicted to increase AUC compared to fasted and LPD.Further, a limited number of studies have attempted to identify characteristics of PwP who may benefit the most from modifications in protein intake (diet responders). Usual protein intake prior to implementation of LPD or PRD may influence responsiveness to the intervention (higher vs. lower baseline protein intake) and should be considered. Some studies have reported the most robust benefits of modifying protein intake in PwP who have experienced either shorter duration of motor fluctuations or treatment66 and weight loss64 which may or may not be desired. Therefore, implementation of PRD should be closely monitored with careful consideration of levodopa dosage, body weight, BMI and total energy and protein intake to reduce unwanted side effects. While benefits were reported for PRD in all studies, data should be interpreted with caution as only 2 out of 10 studies were randomized controlled trials59. Generalizability to the larger population of PwP is unknown at this time due to heterogeneous study designs and small sample sizes (n < 20). Therefore, benefits of this diet should be confirmed in larger, randomized controlled studies.Long term adherence of PRD assessed by Karstaedt et al. appears feasible with 30 out of 43 participants (70%) reporting compliance to diet recommendations after 1–2 years. Adverse effects of PRD were increased prevalence of dyskinesia (requiring reduction of levodopa dosage)71. Discontinuation of PRD due to weight loss was described in 2 studies62. However, Barichella et al. reported a PRD is safe when estimated energy requirements are met (−1.8% within 6 months), suggesting monitoring nutritional status may minimize unintentional weight loss of PRD59. Malnutrition may be present in up to 24% of PwP72 and correlated with markers of PD severity73 and quality of life74. PwP are at risk of weight loss and malnutrition due increased symptom-associated hypermetabolism  and decreased caloric intake 72.Unintentional weight loss and loss of lean body mass should be a consideration for long-term utilization of LPD and PRD in PwP. Low body weight and weight loss have been associated with higher levodopa dose per kilogram of body weight (increasing risks for dyskinesias) and faster decline in motor function, respectively75. This is consistent with previous guidelines that suggest older adults may require protein intake as high as 1.5 g/kg/day to achieve nitrogen balance and promote adequate muscle protein synthesis76. However, these guidelines may not always be appropriate for PwP when considering medication pharmacokinetics and expert consensus is needed to determine appropriate protein intake in this population. Factors  should be taken into consideration when determining appropriateness of diet modification. PRD would be ideally initiated when motor fluctuations first occur, prior to increasing levodopa dosages to reduce dyskinesia risks.Nitrogen balance studies can assess whole-body catabolism vs. anabolism status using the ratio of estimated nitrogen intake and 24 h urinary nitrogen loss, but this has not been adequately investigated in PwP. One small pilot study reported an average protein intake of 1.1 g/kg/day resulted in net nitrogen loss in PwP compared to healthy controls, indicating increased risk for muscle tissue breakdownBox 1 Considerations for managing diet, medications and gastrointestinal issues in PwPDietary AssessmentTake levodopa on an empty stomach 30 min before or 2 h after a meal.Assess possible food-drug interactions, by recording at least a 1-day dietary recall that includes amount/type of foods and drinks consumed, timing of meals, medications, and motor fluctuations.If motor fluctuations present, consider appropriateness of PRD with protein intake at least 0.8 g/kg/body weight. Monitor body weight and dyskinesias.Avoid use of low-protein diets ( < 0.8 g/kg/day) to prevent loss of lean body mass.Administer levodopa with a small carbohydrate snack  to reduce nausea after administration.High fiber diet and adequate hydration for constipation management to improve levodopa bioavailability.Low-fat diet for gastroparesis management to improve levodopa bioavailability.Consider dietitian referral for diet assessment and education for PwP.Medication Dosing and TimingEducate PwP/care partners on indication, dose, frequency, administration times, what to do if missed dose, food and drug interactions, and potential adverse effects.Consider other formulations of levodopa delivery such as half tablets, extended-release orally disintegrating, transdermal or enterally administered to improve levodopa bioavailability.To prevent nausea, carbidopa may reduce side effects if available. A minimum daily dose of 75 mg is required to prevent peripheral conversion. Domperidone or trimethobenzamide can also be considered.Monitor and adjust levodopa dosage when implementing interventions that improve bioavailability to reduce dyskinesias.Consider pharmacist referral for medication therapy management and education.Gastrointestinal FunctionConditions such as gastroparesis, SIBO and/or constipation may impair levodopa absorption.Change in diet habits due to poor oral health (masticatory difficulties), anosmia, ageusia, and dysphagia may challenge dietary interventions and increase risk for weight loss.Stool softeners, bulk-producing and osmotic laxatives and suppositories should be used as needed for constipation management to improve levodopa bioavailabilty.Consider speech language pathologist and/or gastroenterology referral(s).PwP people living with Parkinson’s, milligrams, g grams, kg kilograms, SIBO small intestine bacterial overgrowth.There are additional factors at play which affect the levodopa response of PwP that should be addressed in addition to dietary protein interactions Box . These i36. The amount of amino acid competition that occurs at the BBB with subcutaneous or inhaled levodopa has not been well established. The lack of competition with protein at the intestine and BBB may be a theoretical advantage for the choice of dopamine agonists in various formulations ranging from oral to patch to infusion  over levodopa preparations and needs to be further investigated.In addition to addressing dietary protein interactions with levodopa, optimization of medication therapy through effective medication education of PwP and their care partners, consistent medication adherence, and proper administration of medications may mitigate symptom fluctuations and improve quality of life in PwP. Helping with aids for compliance and working with a pharmacist with instructions tailored to cognitive and cultural context is key. When motor response to orally administered levodopa is suboptimal, alternative formulations (immediate vs. continuous vs. extended) and routes of administration  may be considered. These alternatives may compete differently with dietary proteins at both the intestine and BBB77. Some report difficulties with timing medication away from meals especially when levodopa dose frequency exceeds 3–4 times per day78. Exogenous factors that may influence gastric rate and levodopa bioavailability include pH-lowering medications 79 and gut microbial interactions such as Helicobacter pylori infections and small intestinal bacterial overgrowth80. Host-microbiome interactions are a growing area of research, including the responsiveness and delivery of levodopa medications in the GI tract. Certain species of gut bacteria  express tyrosine decarboxylase which can convert levodopa to dopamine peripherally and may contribute to heterogenous responses and side effects of levodopa administration82. Interestingly, investigations of genetically-engineered probiotic bacteria is an emerging area of research for improving levodopa delivery83. Nutrition interventions that aim to improve GI dysfunction such as constipation (high fiber diet and adequate fluids) and/or gastroparesis (low fat diet) may improve levodopa bioavailability84. Other GI symptoms such as anosmia, ageusia and dysphagia in PwP can complicate implementation of dietary interventions due to decreased appetite and reduced food and fluid intake15.Beyond the current guidelines of taking levodopa on an empty stomach, PwP may still choose to take the drug with food to avoid GI side effects such as nausea and lightheadedness0,+AT-rBAT, TAT1 and LAT2-4F2hc) has been recently elucidated in vitro and in vivo. Future studies should confirm these findings with in vivo models and elucidate strategies for increasing trans-stimulation of levodopa by the transporter LAT2-4F2hc. While addressing dietary protein interactions with levodopa may aide in medication bioavailability, larger randomized, controlled clinical trials are warranted to clarify efficacy of PRD in subpopulations of different disease severity, ages, sex, ethnic, GI and genetic influences. Other dietary interventions such as plant-based diets (vegan or vegetarian) may also be a key area of investigation given plant-based proteins are lower in essential amino acids 29 that could compete with levodopa absorption. Future development of biomarkers or machine learning algorithms that can predict responsiveness of dietary protein modifications on levodopa pharmacokinetics could be helpful. Currently, dietary interventions for optimizing levodopa response in PwP are implemented only as a “rescue” therapy instead of utilizing a more holistic, proactive, and preventative therapeutic approach. Increased collaboration with allied health professionals and creation of dietary guidelines to manage diet in PwP among national organizations should be prioritized.More investigations to support the customization of dietary protein in the management of PwP is of utmost importance. Levodopa absorption within the intestine facilitated by saturable transporters  may be an effective treatment approach for managing dietary protein interactions. Daily protein intake of 0.8 g/kg/body weight is adequate and routine assessment of motor symptoms and nutritional status could reduce complications of PRD. However, limitations exist within available evidence including absence of control groups, short trial durations and heterogenous study designs. Given these limitations, high-quality randomized, controlled trials are still warranted for PRD. Factors that should be considered in future research include disease stage and progression, dietary habits, body weight, duration of motor fluctuations, as well as the interactions of sex, race and genetic influences, co-medications & comorbidities. Medication management (including education) and GI dysfunction should also be addressed to improve levodopa pharmacokinetics, if warranted. This paper highlights the need to investigate and better understand the many underlying nutritional and pharmacokinetic factors before increasing levodopa dosing for PwP who experience motor fluctuations. Based on the current review, there are many gaps in knowledge that warrant timely attention until conclusive recommendations on dietary protein and PRD can be made for PwP.Further information on research design is available in the NR Reporting Summary Checklist


Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 ‘4D Flow CMR Consensus Statement’. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards. This is an update to the 4D Flow CMR Consensus Statement published in 2015 [Hemodynamics evaluation is crucial for the assessment of cardiovascular diseases, and is essential for understanding pathophysiology and explaining clinical manifestations. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) uniquely provides comprehensive, in vivo characterization of cardiovascular blood flow. With this approach, the blood flow velocity is measured through motion encoding in all three spatial directions and resolved relative to all three dimensions of space and to the dimension of time along the cardiac cycle (3D + time = 4D).4D Flow CMR is an extension of 2D Flow CMR  which isSeveral review papers are now available on 4D Flow CMR –12, detaThe previously published consensus statement  covers bSince the publication of the original consensus statement, the field of 4D Flow CMR and the size of its user base has grown, supported by advances in CMR scanner hardware and coils, data acquisition and reconstruction strategies, vendor support, and availability of commercial post-processing solutions. Key advances in the last five years include further acceleration and diversification in acquisition methods. However, the most important development has been that 4D Flow CMR is now clinically available and supported by the major vendors of CMR scanners. Additionally, post-processing tools are commercially available, United States Food and Drug Administration (FDA) approved, European (CE-) marked for clinical use and in some countries, approved for reimbursement. These developments have enlarged the user base and paved the way for the more widespread clinical application of 4D Flow CMR, which is now used in the clinical routine at multiple centers worldwide. This is prompting large cohort, longitudinal and multi-center clinical studies. As the variety of acquisition and analysis platforms grows, standardized imaging acquisition, analysis, and publication approaches will simplify pooling data for meta-analysis studies and increase the validity of study results.It is important to note that clinical and research 4D Flow CMR applications have differing priorities. Clinical acquisitions need to be fast with reliable flow and velocity quantification. In research, scan duration is less important whereas comprehensiveness of data is prioritized. Conversely, validation is more complex in the research setting as there often is no predefined gold standard for comparison for advanced measures beyond velocity and flow.Recommended acquisition parameters for clinical use—with a growing number of clinical centers starting out in 4D Flow CMR we have summarized updated clinical parameter recommendations based on consensus from centers clinically using 4D Flow CMR.Clinical post-processing workflow—this section describes key elements to consider and follow when choosing a clinical post-processing platform and setting up a clinical workflow.Quality assurance and validation advice—with a growing number of different sequences and post-processing platforms commercially available, we have further extended the advice for clinical quality assurance and validation when starting out with 4D Flow CMR. Furthermore, we address the challenges faced in quality assurance and validation in the research setting.Integration into clinical practice—this section covers a selection of advice from centers that have integrated 4D Flow CMR into the clinical workflow.Recommended publication standards—this section provides a checklist specific for 4D Flow CMR.Overcoming limitations and future considerations—focusing on what is on the horizon for 4D Flow CMR.Appendix: 4D Flow CMR sequence options—since the last consensus statement, the options of available 4D Flow CMR sequences have considerably increased. This appendix, therefore, summarizes some aspects to consider when choosing a sequence prior to setting up a research study or clinical service.This update statement builds on the previously published consensus statement  and focuThis consensus update is based on published data, where available, and consensus experience. It aims to cover a large audience, including clinicians and scientists interested in starting out in 4D Flow CMR as well as bringing together established groups in the area.The choice of 4D Flow CMR acquisition parameters requires careful consideration of a balance between accuracy and scan time. For clinical use, it is advisable to keep the 4D Flow CMR acquisition to 5–10 min. Thereby it can easily be added to a clinical workflow, such as in the waiting period between gadolinium administration late enhancement enhancement (LGE) imaging, without interfering with or extensively prolonging the established protocols in the institution.The improved signal to noise ratio (SNR) at higher field strength such as 3T can be beneficial in the younger pediatric setting given the higher spatial resolution needed due to the small body size anatomy but is less important in older children and adults where body size is sufficient for good SNR at lower field strengths.Coil selection largely depends on local protocol and availability. The routine number of coil elements used in standard cardiac imaging is sufficient for good quality 4D Flow CMR acquisition. The number of coil elements needs to be balanced against the ability of the scanner to reconstruct the data in a timely manner.Volume coverage ideally includes at least the valves and aortic and pulmonary sinuses (even if focusing on intra-cardiac anatomy) for data quality assurance purposes  , 36. HenIt is important to note here the difference between acquired resolution, based on the field-of-view and k-space matrix size, and the reconstructed resolution, which is often higher than the acquired due to the use of spatial interpolation during image reconstruction. This is an important distinction, since sequence performance is primarily defined by the acquired rather than the reconstructed resolution. For completeness and easier comparison, both acquired and reconstructed resolutions should be stated in scientific publications.4D Flow CMR requires the selection of an upper velocity encoding limit (VENC) during scan prescription to avoid velocity aliasing. This setting will adjust the motion encoding gradients accordingly to the desired motion sensitivity. In non-contrast acquisitions, the VENC should be as low as possible to keep adequate VNR and improve accuracy while avoiding aliasing .Large vessels (pulmonary artery and aorta): 150 cm/s Dissection false lumen: 50–150 cm/sVenous blood flow (including extracardiac conduit and pulmonary arteries in Fontan patients): 50–80 cm/sIntra-cardiac: 100–150 cm/sChoice of VENC should be close to the maximum velocity (< 25% above)  and can Electrocardiographic (ECG) gating should be retrospective whenever possible to capture hemodynamics throughout the complete cardiac cycle –42. OperRespiratory motion suppression can improve image quality , 45 and Advised scan parameters are summarized in Table As many acquisition parameters are likely to influence 4D Flow CMR acquisition, it is important to have consistent protocols which have undergone local quality assurance testing.The spoiled gradient-echo sequence with short repetition time (TR) generates phase-contrast angiograms without the need for contrast agents , 47. SNRThe standard flip angle for non-contrast 4D Flow CMR acquisition should be set around the Ernst angle which equates to a flip angle of around 7° for non-contrast 4D Flow CMR with repetition time and echo time chosen as short as possible. After contrast administration a higher flip angle is often beneficial, but this depends on contrast agent used and time past since administration. Several clinical centres use the following guidance: If acquiring 4D Flow CMR directly after gadolinium administration, it is advisable to increase the flip angle to 15–25° 1.5T and 12° at 3T. , 49, 53.Data pre-processing steps are described in detail by the previous 4D Flow CMR consensus statement and this remains valid . Key elePost-processing of 4D Flow CMR data includes the following steps: 1) background phase offset correction, (2) anti-aliasing if required, (3) segmentation, (4) visualization , and (5) quantification including an internal consistency check , flow components as well as relative pressure distribution for research purposes. Many software packages now also include valve tracking, circumventing the issue of through-plane motion and permitting valve motion to be factored in when computing flow, which improves accuracy especially in mitral and tricuspid valve assessment .For accurate flow measurements, 4D Flow CMR requires correction for phase offset errors associated with eddy currents and concomitant gradient fields if not corrected during image reconstruction. While offset errors can be corrected by repeating the exam with a stationary phantom and subtracting the flow measurements of the static tissue from the patient’s data , this isIn cases where maximum blood flow velocity surpasses the chosen VENC, velocity aliasing can result in corrupted velocity measurements. In these cases, phase unwrapping can improve the accuracy of the flow and velocity measurements –65. MostDepending on the software solution, evaluation of flow data starts either with 3D segmentation of the vessel or direct placement of regions of interest in the imaging volume delineating the vessel contour in 2D cross-sectional planes. Appropriate regions of interest selection, orientation, and segmentation are important parts of the flow and velocity quantification process . Care muUsing retrospective valve tracking, a dynamic reformatted 2D plane of through-plane velocity is created from the time-resolved 3D velocity data , instantaneous streamlines, and time-resolved pathlines. The differences between streamlines and pathlines are described in detail in the first 4D Flow CMR Consensus Statement . We emphGuided by the visualization of anatomy and blood flow, 2D planes can be placed to measure flow parameters at anatomical landmarks or in areas of pathological flow. The most relevant clinical 4D Flow CMR-derived parameters are flow volumes and flow velocities that should be provided in the clinical report. Quantitative data should always be validated for internal consistency  determined by LV cine short-axis volumetric assessment. Valve tracking has led to the improved indirect method involving subtraction of aortic net flow from the mitral forward flow. In cases where there are multiple jets with different directions or the regurgitation jet has uncorrectable aliasing, we recommend using the indirect method with valve tracking through the mitral and aortic valves as this has been shown to be more accurate in these cases [The standard CMR method for mitral regurgitation quantification, here called se cases , 75.While using any 4D Flow CMR method for assessment of valvular regurgitation, it is recommended to cross-check the quantification against standard methods. If there is a significant discrepancy in the quantification of regurgitation volume between methods (> 15 ml or > 10%), it is recommended to revisit the analysis and investigate the cause of the discrepancy using the conservation of mass principle . The following equations can be used to check the consistency of flow data:LV stroke volume (short-axis cine segmentation) = mitral forward flow + aortic backward flow = aortic forward flow + mitral backward flow.Retrospective valve tracking can be applied in patients with atrial fibrillation . HoweverBoth initial validation and ongoing quality assurance are important aspects of clinical 4D Flow CMR . This seFor incorporation into standard clinical practice, 4D Flow CMR acquisitions must meet quality thresholds that provide the interpreting clinician with confidence in both the qualitative and quantitative accuracy of the data. Accuracy in 4D Flow CMR can be influenced by the choice of vendor sequences , acquisiInitial validation is advised to be undertaken when using a new sequence, updating a sequence (such as a significant sequence change with system updates), gradient servicing, applying significant changes in acquisition parameters or using a new post-processing platform:We advise acquiring 10 datasets  with both the institution’s standard 2D Flow and 4D Flow CMR including at least: ascending aorta, pulmonary trunk, left branch pulmonary artery, right branch pulmonary artery, superior vena cava, descending aorta and pulmonary veins. If possible we also advise to rescan the volunteers/patients ideally after exiting and then re-entering the scanner either on the same day or a defined short recall period (< 1 month).Initial visual assessment of the velocity and magnitude images should include assessment of motion artefacts, wrap around artefacts and any aliasing in systole.We advise to include 3 steps in the quantitative assessment: (1) comparison to 2D Flow CMR, (2) within dataset validation, (3) inter- and intra-reader comparison (when changing/updating post-processing platform). Ideally, differences in flow assessment should be ≤ 5%. Scan-rescan differences up to 10% are acceptable due to minor physiological differences between scans.Comparison to 2D Flow CMR: We suggest comparing forward flow and peak velocity for at least ascending aorta, pulmonary trunk, left branch pulmonary artery, right branch pulmonary artery, superior vena cava and descending aorta between 2D Flow and 4D Flow CMR in the 10 validation datasets. This captures arterial and venous flow with different flow velocities as well as a variety of vessel diameters see Fig. . Fig. 3IAortic flow (add 5% for coronary flow if measuring above sinuses) = pulmonary flowRight + left pulmonary artery flow = main pulmonary artery flowBranch pulmonary artery flow = pulmonary vein flow Superior vena cava + descending aortic flow = ascending aortic flowWithin dataset validation: This makes use of the conservation of mass principle. Mass is neither created nor destroyed and so flow volumes should stay equal. Therefore, the following forward flow comparisons can be made in all 10 datasets and should show equal flow:This allows the assessment of measurement planes in a variety of directions within the 4D Flow CMR dataset.Furthermore, we advise placing 2–4 measurement planes in the ascending aorta between the sinuses of Valsalva and the 1st branching vessel. Again, using the conservation of mass principle, the flow volume should match in all planes (< 5% difference).Inter- and intra-reader comparison: We advise each reader involved in the clinical service to complete the above flow validations in all 10 datasets twice at least 1 week apart to evaluate any inter or intra-reader bias. Differences in flow assessment should be ≤ 5%.Everyday quality assurance in every dataset acquired should at least include:Initial visual assessment of the phase contrast and magnitude datasets should include assessment of motion artefacts, wrap around artefacts and any aliasing during systole.Quantitative assessment using within dataset validation using the conservation of mass principle. At least one of the above ‘within dataset’ forward flow comparisons can be completed. The choice of these depends on the underlying anatomy and physiology and is determined by the reading physician.When embarking on integrating 4D Flow CMR into the clinical workflow, several considerations are important. Initial validation of the chosen 4D Flow sequence on the local CMR scanner is paramount  then 4D Flow CMR may take higher priority and be acquired earlier in the imaging protocol, especially if 4D Flow CMR is used in place of standard 2D Flow imaging.In pathologies where 4D Flow CMR plays an adjunctive role , ensuring that all diagnostic sequences are completed before the acquisition of 4D Flow CMR is a common approachHistorically, 4D Flow CMR has been considered a research technique and thus placed at the end of clinical exams after diagnostic sequences; however, with the emergence of clinically validated applications and postprocessing software, some centers are now adding 4D Flow CMR to routine clinical CMR protocols –82. WhenQuantitative analysis of flow volumes and peak velocity can easily be integrated into standard CMR reporting templates. We advise reporting both 2D and 4D Flow CMR concomitantly until both imaging and clinical cardiology teams feel confident in basing clinical decisions on 4D Flow CMR results alone.More advanced parameters can be derived from 4D Flow CMR velocity maps using dedicated software, but these may not be formally approved yet for clinical use.To take full advantage of the comprehensive nature of 4D Flow CMR, users should interact with the 4D Flow CMR datasets that can be reformatted into any plane to derive the optimum qualitative patient data for display. This is not possible on standard viewing and analysis platforms accessible to clinicians using images for decision making. We, therefore, recommend developing a workflow to save useful 4D Flow CMR images/videos in DICOM format which can then be loaded onto standard viewing platforms. This makes 4D Flow CMR more accessible to clinicians and can be used at multi-disciplinary team meetings even without a 4D Flow CMR specialist present. Especially in congenital heart disease qualitative analysis can be useful in delineating stenosed vessels in more detail, providing information on the exact position and length of flow acceleration. It also easily identifies any flow reversal.Several useful options exist for the validation of different aspects of 4D Flow CMR, such as sequence development, reconstruction algorithms and post-processing workflows. These options can broadly be categorized into (1) in vivo studies, 2) phantom studies, and (3) computer simulations  and clinical studies . High-quality and standardized publications will enable easier replication of proposed sequence protocols for clinical use and facilitate easier and higher quality meta-analysis to move the field forward.Where possible, sharing of published datasets, code and materials to replicate, verify and extend the research presented in the manuscript is encouraged.Below are 4D flow CMR specific considerations:For studies based on a priori stated hypotheses, all hypotheses should be clearly stated when describing the aim(s) of the study.All data processing methods that can affect the quality of the 4D flow CMR data should be described, including correction methods for eddy currents, distortions resulting from gradient field non-uniformity, intravoxel dephasing and concomitant gradient fields, velocity aliasing, as well as noise filtering . Many parameters, including hardware specifics, acquisition parameters, and post-processing software, affect the image quality and properties of 4D Flow CMR data and should be reported as such. The essential and recommended standards are listed in Table Data processing can be performed by several commercial CE- and FDA approved software packages, while in-house developed tools enable techniques for research. Open-source software solutions facilitate reproducible research, and the availability of such tools should be clarified in publications. For commercially available as well as open-source software, the software release version should be detailed.After processing the data, hemodynamic parameters can be extracted from the velocity fields. A range of metrics can be derived, each with relevance depending on the specific application. Thus, a detailed description of the analysis methodology should be provided so that a similar analysis could be performed at other centers.Clinical diagnosis and/or outcome studies need to be designed with an adequate sample size resulting from a power analysis. The methods section should contain a statistics paragraph describing all used statistical methods appropriate for the study size.The results section should include the number of included and excluded subjects, as well as the reason for exclusion, the results of the data quality assurance assessment, at least including a within-dataset validation .If acquisition settings are significantly different from these and previous recommendations  or vary References to methods and techniques should reference the original work.These recommendation standards will contribute to consistently high-quality publications, will improve the review process, and allow for easier comparison of different publications. We would therefore like to stress the importance of following these standards.4D Flow CMR is becoming more widely used in medical centers with the technical and clinical capabilities to incorporate its use into standard-of-care protocols for heart valve, aortic, pulmonary, and congenital heart disease. However, several challenges remain to achieve widespread adoption and application of 4D Flow CMR remain. This includes limited velocity dynamic range due to a single user-selected VENC, long and unpredictable scan times, data storage of large datasets especially in clinical work flows as well as manual and time-consuming data processing (which can affect user confidence). Below we discuss several promising new developments which are ongoing to overcome these limitations.Acceleration techniques enable reductions in acquisition time , 96–109 4D Flow CMR techniques are also being developed that permit respiratory and cardiac self-gating and thereby simplify and streamline acquisition for optimized clinical workflows. Respiratory self-gating eliminates the need for respiratory navigators and can be achieved by repeatedly acquiring a central k-space line that corresponds to a projection of the image volume in the feet-to-head direction . This haCurrent 4D Flow CMR data analysis workflows are often non-standardized and time-consuming, thus limiting reproducibility and clinical translation. Addressing these limitations will require the development of efficient image analysis strategies with minimal user dependence. This is becoming feasible with advances in image processing techniques. For example, automated segmentation of the aorta and pulmonary artery has been demonstrated with atlas-based as well as deep learning-based methods –129. In 4D Flow CMR has moved from “pretty pictures” to providing robust flow quantification in clinical practice. 4D Flow CMR has greatly benefitted from the advances in CMR acceleration making it feasible for clinical use. The worldwide 4D Flow CMR community has grown exponentially since the last consensus statement. 4D Flow CMR is no longer just a tool for researchers but for clinicians. This consensus statement aims to help clinicians initiate a 4D Flow CMR program in their institutions. Furthermore, it aims to set standards for both clinical and research settings to assure consistent high-quality 4D Flow CMR output.


Nanoparticles (NPs) are commonly used in healthcare and nanotherapy, but their toxicity at high concentrations is well-known. Recent research has shown that NPs can also cause toxicity at low concentrations, disrupting various cellular functions and leading to altered mechanobiological behavior. While researchers have used different methods to investigate the effects of NPs on cells, including gene expression and cell adhesion assays, the use of mechanobiological tools in this context has been underutilized. This review emphasizes the importance of further exploring the mechanobiological effects of NPs, which could reveal valuable insights into the mechanisms behind NP toxicity. To investigate these effects, different methods, including the use of polydimethylsiloxane (PDMS) pillars to study cell motility, traction force production, and rigidity sensing contractions, have been employed. Understanding how NPs affect cell cytoskeletal functions through mechanobiology could have significant implications, such as developing innovative drug delivery systems and tissue engineering techniques, and could improve the safety of NPs for biomedical applications. In summary, this review highlights the significance of incorporating mechanobiology into the study of NP toxicity and demonstrates the potential of this interdisciplinary field to advance our knowledge and practical use of NPs. I. I85]. I2(RITC) can alter cellular traction force production in a cell-type-dependent manner. For example, human bone-marrow-derived mesenchymal stem cells (hBM-MSCs) exhibited a significant decrease in traction force production at a concentration of 1.0 μg/μL upon MNPs@SiO2(RITC) treatment, while no differences were observed in the traction force production of untreated and 0.1 μg/μL treated hBM-MSC cells [2(RITC) in another study [2(RITC) were mainly due to alterations in the cell area and decreased intracellular ATP production, which could ultimately affect cell attachment and spread.Recent studies have shown that MNPs@SiOSC cells . Similarer study . ChangesOne way to measure the ability of a cell to recognize the stiffness of ECM is by observing the morphological and cytoskeletal responses of cells cultured on ECM with varying stiffness ,86. The γ) was calculated as the sum of the force vectors of the adjacent two pillars  divided by the sum of their magnitudes. The directionality parameter (γ)  F can be 2(RITC) on HEK 293 cells rigidity sensing at low concentration (0.1 µg/µL) [2(RITC) cannot distinguish soft surfaces from rigid surfaces. The actin structure was also disrupted when MNPs@SiO2(RITC) enters the cell at 1 and 0.1 µg/µL on both soft and rigid surfaces. The current state of the rigidity sensing analysis method that uses submicrometer PDMS pillars showed that MNPs@SiO2(RITC)-treated cells cannot perform rigidity sensing contractions that occur during the initial contact of the cell substrate, indicating the loss of cell ability to sense the rigidity of the pillars. The loss of rigidity sensing is caused when MNPs@SiO2(RITC) damages the actin structure and cytoskeletal components, especially FSCN1 and PXN, even at 0.1 µg/µL.The rigidity sensing method was recently used to show the toxicity of MNPs@SiO1 µg/µL) . In thisThis article highlights the impact of NPs on the cell cytoskeleton and mechanobiology, and the methods used to study nanotoxicity in relation to NP concentration. At lower concentrations (0.1 µg/mL), NPs generate ROS that inhibit the cell cytoskeleton, the production of traction force, and cells’ ability to sense rigidity. Changes in traction force production, rigidity sensing, and cytoskeletal components such as FSCN1 and PXN were observed after NP treatment, indicating possible cell transformation as all transformed cells display defects in their cytoskeletal components. However, no study has yet been conducted on the transformation of cells due to NPs. To further understand the effects of NPs, future research should focus on studying several types of NP based on concentration incorporated with modern microfluidic systems that mimic real organs. These studies will provide a standard for determining the toxicity of NPs.2(RITC), it is crucial to perform further studies and deep analysis since the interaction of NPs with the cell could be different due to their surface coating, size, concentrations, and chemical compositions. Incorporating rigidity sensing and traction force measurements in such studies would provide a more holistic understanding of the toxicity of NPs and aid in the development of safer NPs for various biomedical applications.The effects of NPs on cell cytoskeleton and mechanobiology have been comprehensively reviewed in this article. The toxic effects of NPs on the cytoskeletal components of cells alter the mechanobiological response of the cell, which in turn affects essential cellular functions such as cell migration, division, and proliferation. While the detailed mechanobiological studies were performed only on MNPs@SiO