Using this method, we further reveal the atomic-scale mechanisms responsible for the highly active perimeter sites and demonstrate that the charge transfer behavior can be readily controlled using post-synthesis treatments. This methodology provides a blueprint for better understanding the role of charge transfer in catalyst stability and performance and facilitates the future development of highly active advanced catalysts.Precise control of charge transfer between catalyst nanoparticles and supports presents a unique opportunity to enhance the stability, activity, and selectivity of heterogeneous catalysts. While charge transfer is tunable using the atomic structure and chemistry of the catalyst-support interface, direct experimental evidence is missing for three-dimensional catalyst nanoparticles, primarily due to the lack of a high-resolution method that can probe and correlate both the charge distribution and atomic structure of catalyst/support interfaces in these structures. We demonstrate a robust scanning transmission electron microscopy (STEM) method that simultaneously visualizes the atomic-scale structure and sub-nanometer-scale charge distribution in heterogeneous catalysts using a model Au-catalyst/SrTiO Precise control of charge transfer between catalyst nanoparticles and supports presents a unique opportunity to enhance catalytic performance. Here the authors demonstrate a scanning transmission electron microscopy method to visualize atomic-scale structure and sub-nanometer-scale charge distribution in heterogeneous catalysts, shedding light on the atomic-scale mechanisms behind their highly active perimeter sites. Many of these interactions, including small-cluster stabilization, support participation in catalysis, and oxide encapsulation of metal nanoparticles12, can be routinely accessed by various high-resolution microscopy techniques15. Directly studying charge transfer is more challenging, however. State-of-the-art theoretical calculations provide a powerful way to predict charge transfer and catalytic reaction mechanisms at the individual particle-level when representative structural models are given, but thus far experimental charge transfer studies have relied mainly on indirect or bulk experimental measurements17. Such methods cannot resolve the charge distribution around individual nanoparticles, and information about the influence of specific particle-support interface atomic configurations on charge redistribution is therefore difficult to obtain12. Scanned probe microscopy techniques have been used to retrieve information about local work function, and thus charge state, at high spatial resolution, but characterization of three-dimensional (3D) particles is challenging for these techniques, especially at particle perimeters, so these studies are often involve individual adatoms or two-dimensional “raft-like” particles on flat substrates22. Our understanding of charge transfer processes in real heterogenous catalysts therefore remains limited by a lack of techniques capable of directly studying these phenomena at their inherent nanometer length scales in individual 3D nanoparticles25.Metal-support interactions significantly affect the reactivity, selectivity, and stability of oxide-supported metal nanocatalysts and therefore represent effective tuning parameters for optimizing catalyst performance30. The exact role charge transfer plays in dictating this behavior, however, such as whether it is involved in the high activity of perimeter sites33, is not well understood. For instance, it has been reported that negatively charged Au nanoparticles, i.e., particles that have gained electrons from the support, promote adsorption of CO molecules and weaken O2 bonds30, resulting in enhanced CO oxidation activity34. Cationic Au species, on the other hand, have been shown to have increased stability, a reduced activation barrier, and increased activity for CO oxidation35. Nevertheless, it is accepted that the structure and chemistry of the particle-support interface plays an important role in dictating transfer of charge39. The ability to provide direct experimental evidence of charge transfer features on the nanometer scale and correlate this with atomic-scale interfacial structure would therefore significantly aid in resolving these ambiguities and enhance our understanding of charge transfer processes, allowing improved catalysts to be designed.For example, heterogeneous catalysts composed of Au nanoparticles on oxide supports possess intriguing catalytic properties  and charge transfer between the Au nanoparticle and oxide support is believed to be critical to the catalytic behavior of these systems3 (STO) support as a model heterogeneous catalyst system, we probe charge redistribution around individual nanoparticles at the nanometer scale for the first time. To accomplish this, we adopt and further develop four-dimensional (4D) scanning transmission electron microscopy (STEM) techniques designed to map features related to projected electric and magnetic fields mainly in thin single crystals51. Using these techniques, we provide direct evidence that charge transfer occurs in the pristine Au-STO system from the support to the Au particle and that the overall direction of charge transfer can be inverted by a simple treatment aimed at modifying the support surface, which leads to altered catalytic activity. In addition, by pairing our experimental results with density functional theory (DFT) calculations, we provide new insights into the mechanisms behind the highly active perimeter sites of heterogeneous catalysts, which involve correlated charge transfer and local structural modifications.Here, using Au nanoparticles on a SrTiO53.Figure 54. The center of mass (CoM) of the electron beam intensity in the detector plane, for example, measures momentum transfer from the specimen to the electron probe, and hence carries information about internal fields46. The same 4D dataset also allows us to reconstruct simultaneously acquired conventional STEM images such as annular dark-field (ADF) and bright-field (BF), which can provide structural and chemical information. Simultaneously acquired ADF- and BF-STEM images and an inverted CoM map taken of a Au nanoparticle on the STO support are shown in Fig. While conventional STEM techniques provide valuable atomic-scale information, they are not typically sensitive to properties related to extended electrostatic fields. We therefore additionally employed 4D-STEM, which can be used to extract information related to internal electric fields and corresponding potentials and charge densities46. This provides the possibility for charge distributions, and thus the charge transfer behavior of metal-oxide supported metal nanoparticle catalysts, to be studied by 4D-STEM. Raw maps of the inverted divergence of the CoM shifts (dCoM) for Au-STO samples are shown in Supplementary Fig. Gauss’s law allows information about the projected charge density in the specimen to be generated from information directly related to projected electric fields48, which was used as a first attempt at extracting information about any nanometer-scale charge distribution present. Figure 49, as discussed in detail in the Supplementary Information. The projected charge density map in Fig. 55. In addition, the charge state near the perimeter region is especially important because it is believed that this is where critical reaction steps take place. In the CO oxidation reaction, for example, it is hypothesized that gold surfaces serve as CO adsorption sites and activation of oxygen molecules occurs at the particle perimeter56. Charge redistribution near the perimeter is therefore expected to influence oxygen activation and charge variation on the catalyst surface likely impacts transport of CO to the perimeter, both of which would affect the rate of oxidation reactions occurring there. In addition to the particle observed, a nearby smaller particle ~2 nm across  STO surface (see Methods section for details). Systems with both SrO- and TiOAs opposed to the net negative charge on the particle, individual Au atoms at the particle-support interface can become positively charged when in close proximity to support O atoms Fig. . This le59. Here, we provide direct evidence that inverting the charge transfer direction is feasible using post-synthesis treatments. As described in the Methods section, the specimen shown in Figs. Precise control over the direction of charge transfer at catalyst-support interfaces is critical for the design and optimization of heterogenous catalysts. Different charge schemes for Au nanoparticles, i.e., positively or negatively charged, are favored for different catalytic reactions55. In addition, the opposite charge states of Au measured in this study further validate the CoM measurements of charge distribution. The potential impact of secondary electron emission and plasmonic excitations is minimal (Supplementary Discussions).Figure 61, the distinctive charge distributions and local perimeter structures introduced by the two treatments likely result in different active sites, altered transport mechanisms of adsorbed molecules, and a modification of the delicate balance between elementary steps in catalytic reactions. It should also be pointed out that these results demonstrate the intricacy of the nano-environment of heterogenous catalyst interfaces. Minute changes to the system, such as particle size, interfacial facets, vacancies/dopants, and impurities are thus expected to modify the charge distribution and lattice strain/defects of a catalyst, and hence its performance. Methods such as those described here are therefore necessary for exploring the consequences of such modifications.DFT calculations emulating the O-treated case provide theoretical support for the positive charge on Au particle as well . Inductively coupled plasma (ICP) spectroscopy was performed by Galbraith Laboratories Inc. The loading of Au in the sample was measured to be 0.15 wt.%. Same treatments as those for the Au/single crystalline STO were performed for the powder samples.To synthesize the samples, single-crystal STO STEM specimens were first prepared by mechanical polishing, followed by ion milling. The thin region of the resulting specimens is ~10 nm thick. Comparison of simulated and experimental data, discussed below, confirms that the STO is on the order of 10 nm thick for the sample in Fig. 66. The Perdew-Burke-Ernzerhof (PBE)67 functional form of generalized-gradient approximation (GGA) was used for electron exchange and correlation energies. The projector-augmented wave method was used to describe the electron-core interaction68. A kinetic energy cutoff of 450 eV was used for the plane waves. The Brillouin zone was sampled at the gamma point only. A vacuum layer of 15 Å was added for the surface slabs along the z-direction. The SrTiO3 slab contains a total of four layers, with the bottom two layers fixed in their bulk-optimized positions from DFT, and with the top two layers and Au atoms allowed to move. The Au cluster in Fig. 69. To emulate the O-treated case, oxygen atoms were added to the interfacial regions of the cluster on the bridging sites between Au and surface Ti and locally optimized with DFT. These interfacial oxygen atoms were placed in the most stable locations according to our own studies, and these are consistent with previous computational work that found the bridging Ti-O-Au to be the most stable for Au cluster–TiO2 interfacial sites70. The data in Fig. The DFT calculations were performed using the Vienna Ab Initio Simulation Package (VASP)Supplementary InformationPeer Review File


The current gold standard of gait diagnostics is dependent on large, expensive motion-capture laboratories and highly trained clinical and technical staff. Wearable sensor systems combined with machine learning may help to improve the accessibility of objective gait assessments in a broad clinical context. However, current algorithms lack flexibility and require large training datasets with tedious manual labelling of data. The current study tests the validity of a novel machine learning algorithm for automated gait partitioning of laboratory-based and sensor-based gait data. The developed artificial intelligence tool was used in patients with a central neurological lesion and severe gait impairments. To build the novel algorithm, 2% and 3% of the entire dataset  were required for assessments with laboratory equipment and inertial measurement units. The mean errors of machine learning-based gait partitions were 0.021 s for the laboratory-based datasets and 0.034 s for the sensor-based datasets. Combining reinforcement learning with a deep neural network allows significant reduction in the size of the training datasets to <5%. The low number of required training data provides end-users with a high degree of flexibility. Non-experts can easily adjust the developed algorithm and modify the training library depending on the measurement system and clinical population. Walking is the most important form of mobility and allows us to participate in labour, societal and sports-related activities. To regain a healthy, normal walking pattern after injury or disease is, therefore, one of the most important goals in clinical rehabilitation ,2,3. EffAn alternative to laboratory-based 3D CGA are wearable sensor systems coupled with machine learning analytics ,10,11,12The current gold standard for gait partitioning uses laboratory-based force plate data to detect foot-contact and foot-off events . While fWhile machine learning-based sensor systems are promising to improve the accessibility of CGA, they still have some limitations. One main limitation is the lack of technical flexibility  and clinical flexibility . For example, the majority of currently used machine learning-based sensor systems were validated in healthy adults or built for rather narrow groups of patients with similar gait impairments ,11. OnceWe address the current limitations in machine learning-based gait assessment tools by developing a highly flexible machine learning method that requires only a few training datasets and can be easily modified by end-users without the need for laboratory-based ground truth data sources. The proposed solution consists of a novel, reinforced deep neural network and a dynamic, living training library that can change and adapt over time with end-user input . Contrary to previous attempts, the newly designed algorithm recognizes patterns in motion signals  and identifies gait features, such as foot-contact and foot-off events, through reinforcement, rather than statistics alone. We hypothesize that, by giving more autonomy to end-users through reinforcement learning, our proposed approach results in an order of magnitude less training data, as well as orders of magnitude more technical and clinical flexibility in applicable use cases.We will first establish the flexibility and accuracy of the reinforced deep neural network for laboratory-based 3D CGA patient recordings and then in a wearable IMU sensor system. Finally, we present a clinical use case for the AI tool and IMU sensor system by visualizing AI-based partitions of the electromyographic (EMG) signal of the gastrocnemius muscle in patients with a central neurological lesion. Time-normalized visualizations of gastrocnemius muscle activity are a frequently used method to identify abnormalities in calf muscle activity and diagnose spasticity ,5,6,7.To address the main aim of the current study, we used a two-way approach. First, accelerometer data from 3D CGA patient recordings were used to train the AI tool for laboratory-based assessments. In the second step, the AI tool was trained and validated with IMU-based accelerometer data from the Oro Muscles IMU sensor system.Historical data recordings between April 2021 and June 2021 were selected from the database of the motion laboratory of the University Medical Center Groningen, The Netherlands. Datasets were included if patients previously signed informed consent, were diagnosed with a central neurological lesion and full 3D CGA data were acquired. The patient recordings consisted of on average eight-meter walking trials during regular clinical visits at the motion laboratory of the UMCG Groningen, The Netherlands. In total, 60 walking trials from 14 patients were included in the analysis. The right and left legs were treated separately, resulting in a total of 120 datasets.The 3D CGA patient recordings consisted of 3D marker position data of the plug-in gait model (2010) recorded at 100 Hz with 10 optical cameras (Vero) and Vicon motion capture software Nexus 2.12. Two Amti force plates recorded the ground reaction force data at 1000 Hz during gait recordings.The 3D CGA-based identification of foot-contact and foot-off events was based on the in-built Vicon Nexus algorithm using force plate data. Initial foot contact was detected once vertical ground reaction forces exceeded 10 Newton. The moment of foot-off was defined once the vertical ground reaction force decreased below 10 Newton. All gait events were manually checked by an experienced lab technician and corrected if needed. In cases where force plate signals were corrupted because the gait deviated too much, gait events were manually annotated by an experienced lab technician and visually checked by the principal investigator of this study.Step lengths were computed based on the absolute distance between the left and right lateral malleolus markers from the plug-in gait 3D CGA model. The 3D CGA-based foot-contact events were used to define the moment of maximum step length. Gait speed was computed based on the absolute distance (m) travelled by the anterior superior spine marker divided by time (s). All spatio-temporal gait data were averaged across steps within a trial and across trials of the same condition (barefoot and shoes/orthotics) per participant.The total number of steps made within a trial was computed from 3D ankle marker position data. First, the difference between the anterior–posterior left and right lateral malleolus marker positions was computed for each 3D CGA trial. In the next step, the number of peaks in the left–right ankle distance signal was used to count the number of steps per trial. The sum of all steps across trials was used as the total number of steps for each condition and participant. Custom Python scripts (v. 3.8) were used to compute the spatio-temporal parameters and total number of steps. The accuracy of the step detection algorithm was visually checked by the principal investigator and corrected if needed. To build the AI tool, an existing ML algorithm, Saguaro, consisting of a Hidden Markov Model, self-organizing map and a generative module , was comFirst, the recorded EMG and IMU signals were pre-processed with a smoothing algorithm (Fast Fourier Transform (FFT) and Zurbenko–Kolmogorov Filter (ZK)) . The proIn the current study, the AI tool was trained with manually annotated hints between foot-contact and foot-off events from the mtp-2 marker acceleration signal . In a neThe force plate data and manual partitions from the 3D CGA system were used as the ground truth data for assessing the AI tool’s partitioning accuracy. Partitioning accuracy was determined by computing the mean difference between foot-contact and foot-off events from the ground truth with the AI tool’s partitions. If the partitioning error exceeded 0.060 s, the corresponding data set was transitioned into the training set and another hint was created.Custom MATLAB  and Python (v. 3.8) scripts were used for data processing, analysis, feature extraction and computation of spatio-temporal gait variables.The first five consecutive patients visiting the motion laboratory between June 2021 and December 2021 eligible for inclusion were asked to participate in the IMU-based validation study of the AI tool. Next to the plug-in gait marker set, Cometa EMG sensors were placed according to the SENIAM guidelines on all major superficial lower limb muscle groups . EMG data were recorded at 1000 Hz as part of the usual clinical 3D CGA. In addition, two Oro Muscle IMUs and EMG sensors were placed at the shank and foot and gastrocenemius and tibialis anterior muscles, respectively . The Oro3D CGA-based event detection was the same as described in 2.1. Cometa and Oro Muscles EMG data were bandpass-filtered between 20 (high band) and 450 Hz (low band) with a fourth-order Butterworth filter. To create the linear envelope, EMG data were rectified and low-pass-filtered at 10 Hz with a fourth-order Butterworth filter.In total, five steps and six hints from four patients were fed into the AI tool for algorithm training. When compared with the ground truth data, the absolute average difference in foot-off and foot-contact event detection was 0.021 s (±0.021 s). The maximum time difference between laboratory-based and machine learning-based event detection was 0.08 s.In total, five patients participated in the experimental validation study with the wearable sensor system. For the partitioning of the IMU sensor system data, one step from every walking condition and each patient  was used as a hint . Hence, to re-train the AI tool and allow the partitioning of all 368 steps in swing and stance phases, less than 3% of the entire dataset was required for re-training. When compared with laboratory-based 3D CGA partitioning, the average 3D CGA-based AI partitioning error was 0.035 ± 0.028 s and the sensor-based AI partitioning error was 0.032 ± 0.024 s.Combining a Saguaro algorithm with end-user-informed reinforcement learning and deep neural networks allows successful gait partitioning of 3D CGA data recordings as well as wearable, sensor-based IMU recordings. More importantly only a few manually annotated training hints were required to achieve accurate partitions. Only 2% (six hints out of 567 steps) of the entire dataset was required to accurately partition the 3D CGA recordings in severely impaired patients with a range of different gait impairments . For senThere is one main difference in ours as compared with current machine learning approaches for gait partitioning. By incorporating reinforcement learning and a deep neural network, the current AI tool does not try to discern patterns in the signals alone, but is aided by end-users to select patterns of interest. While this reinforcement does require more user input, it reduces the required training data in orders of magnitude and yields a high degree of technical and clinical flexibility. Only a few, manually annotated reinforcement hints are required to adjust the deep neural network and search for new patterns in the signal. These features allow clinicians to easily adjust the AI tool to different measurement systems , analysis of different output signals  or locomotor activities . This clinical and technical flexibility is an important aspect for facilitating the use of CGA in a broad clinical context and making it accessible for more patients and non-specialized clinics or physiotherapy practices.Another important feature of the novel AI tool is that it does not require the exact time points from laboratory-based ground truth data sources  for training. Instead, the AI tool uses manual inputs from the GUI to identify relevant patterns in the signal  as traditional force-plate-based methods (1–2 steps on average) per patient. Including more steps in the diagnostic process improves the diagnostic validity, especially in young children and patients with complex movement disorders. In addition, automating gait partitioning can reduce the time required for data processing during traditional 3D CGA by about 30 min per trial , leadingWhile our results and previous studies showed that machine learning has the potential to replace force-plate-based gait partitioning, their implementation is scarce, and it remains challenging to automate diagnostic steps in the CGA process. We made a first step by visualizing the AI-based partitioned muscle activity of the gastrocnemius muscle . VisualiWe propose that AI-based solutions should not aim to replace laboratory-based 3D CGA systems and biomechanical interpretation steps, but should aim to provide non-specialized clinics with the ability to perform basic assessments or screening of key gait functions. For example, sensor-based gait assessment tools could be used to inform clinicians whether or not abnormalities in muscle activity are present, and further investigation with more advanced systems is required. Other feasible use cases for AI-based sensor solutions can be automating the assessment of abnormal foot positioning during stance, problems in foot clearance or deficiencies in spatio-temporal parameters . Spatio-temporal parameters are especially relevant because they are an important metric of overall mobility and are often used to evaluate the effect of interventions ,2,3.The following aspects warrant consideration when using the AI tool in daily clinical care or for research purposes. When training the AI tool for laboratory-based 3D CGA accelerometer data, one needs to account for the polarity of the acceleration signal with respect to the walking direction. The change in polarity when changing walking direction in the laboratory doubles the number of hints required. Using input data that do not change polarity as a consequence of the walking direction  could, therefore, half the number of required manually annotated hints.Before actual use in clinics, potential end-users may need to re-train the AI tool based on their own patient population, measurement system and primary data source. While all algorithms are implemented in C++ and run on Linux, MacOS and Windows 10, without any dependencies on third-party packages, their actual implementation would require some technical expertise. The GUI for selecting swing intervals is written in Java and accesses the partitioning algorithm via the Java Native Interface (JNI). Finally, before implementation into daily clinical patient care, the user-friendliness of the AI tool should be improved and further validation steps in larger patient populations are required.Combining reinforcement learning with a deep neural network allows significantly smaller training datasets (<5%) with comparable accuracy in gait partitioning for laboratory-based 3D CGA as well as wearable sensor systems. The low number of required training data and ease of training through the GUI provide end-users with the flexibility to use the AI tool in different measurement systems and clinical populations. Future studies will show the potential of the novel AI tool to allow automatic diagnostics of foot contact and spatio-temporal gait parameters, and facilitate the accessibility of CGA in a broad clinical context.


Chirality of magnons is an intrinsic degree of freedom that characterizes the handedness of spin precession around its equilibrium direction. This commentary summarizes recent progress on spin pumping by ferromagnetic resonance in magnetic heterostructures. In particular, the commentary highlights one fundamental issue in spin pumping: the chirality dependence of the spin current. Right-handed spin pumping has been successfully described by a phenomenological spin-damping term that the damped angular momentum of the spin precession converts into a spin current2. Nonetheless, the role of spin-precession chirality in spin pumping remains a fundamental issue. Specifically, it is unclear whether the right-handed and left-handed spin precessions pump the same spin current. Since nature selects only right-handed spin precession in ferromagnets, it is an experimental challenge to address this fundamental issue by investigating spin pumping from right-handed and left-handed spin precessions independently. Specifically, the experiment needs to answer if opposite chiralities of the spin precession should pump opposite spin polarizations of the spin current?Chirality (or handedness) is an important concept that distinguishes a system from its mirror images. Magnons in ferromagnetic materials, the bosonic quasiparticles of collective spin excitations, have the unique character that only right-handed chirality exists in the spin precession around its equilibrium axis. Such right-handed spin precession could pump a pure spin current and create an electric voltage in neighboring layers, thus opening new opportunities for spintronics development5, its time average 1. Since the handedness of the spin procession is lost after time averaging, it is of fundamental interest to ask if a left-handed spin precession should pump the same spin current as a right-handed spin precession.Akin to electric current, which is a flow of charge, spin current is a flow of spin that delivers angular momentum in space. Pure spin current, which consists of only the flow of spin without the flow of charge, mostly comes from the so-called spin pumping where the precession of a magnetic moment pumps a spin current into a neighboring layer due to the extra damping of m1 and m2) in an AFM around their equilibrium directions always have opposite chirality in either of the two degenerate eigenmodes of magnons. For instance, the right-handed precession of m1 around the +z direction is accompanied by the left-handed precession of m2 around the -z direction. Recently, it was proposed that AFMs should be an effective spin current mediator because the spin currents carried by the precessions of two magnetic sublattices should be added together rather than be subtracted from each other6. This result raises the fundamental question of whether opposite chiralities of spin precessions should pump the same or opposite angular momentum of the spin current. In an AFM, it is impossible to separate the spin pumping signals from m1 and m2 precessions because of their coexistence, thus prohibiting the investigation of spin pumping from an isolated left-handed precession. Consequently, theorists have no choice but to accept the hypothesis that the damping term of 6. The angular momentums carried by m1 and m2 precessions are both described by the same damping term for spin current transmission in AFM insulators8. To address this fundamental issue, it is critical to realize an isolated left-handed spin precession and to study its spin pumping in an experiment.In ferromagnets, only right-handed spin precession exists. In antiferromagnets (AFMs), however, the two antiferromagnetically coupled spins should precess around their equilibrium directions with opposite handedness Fig. . As sket9. In an artificial ferrimagnet of Py/Gd/Py/Gd/Py/Pt multilayer in which the Py and Gd are antiferromagnetically coupled, the net magnetization always precesses around a magnetic field with right-handed chirality, the same as the magnetization precession in a ferromagnet. Because the temperature-dependent Gd magnetization (MGd) is stronger than the Py magnetization (MPy), there exists a transition from the Gd-aligned phase (|MPy| < |MGd|) at low temperatures to the Py-aligned phase (|MPy| > |MGd|) at high temperatures. Then the MPy precession should have a right-handed chirality in the Py-aligned phase (Fig. MPy precession does not exist in conventional ferromagnets because it is generated by its antiferromagnetic coupling to the right-handed MGd precession. Spin pumping by the right-handed and left-handed MPy precessions could be realized at the Py/Pt interface and detected by the dc voltages via the ISHE. Therefore, spin pumping by isolated left-handed MPy precession can be explored and compared to the result of right-handed MPy precession without changing other parameters. As the main result of the experiment, Liu et al. demonstrated unambiguously that opposite chiralities pump opposite spin polarizations of the spin current. That is, the right-handed and left-handed MPy precessions around the same axis produce opposite signs of the dc voltage via the ISHE. In addition, two different resonance modes were observed in this artificial ferrimagnet, corresponding to ferromagnetic antiferromagnetic excitations. Their work establishes the relationship between spin precession chirality and the electrical readout of spin pumping, demonstrating chirality as an independent degree of freedom and an information carrier in future spintronic devices.One recent experiment designed a cleaver method in which spin pumping from Py into Pt layers by left-handed and right-handed Py magnetic precessions were realized independentlyase Fig.  and a lease Fig. . The lef


Classification of motor imagery (MI) tasks provides a robust solution for specially-abled people to connect with the milieu for brain-computer interface. Precise selection of uniform tuning parameters of tunable Q wavelet transform (TQWT) for electroencephalography (EEG) signals is arduous. Therefore, this paper proposes robust TQWT for automatically selecting optimum tuning parameters to decompose non-stationary EEG signals accurately. Three evolutionary optimization algorithms are explored for automating the tuning parameters of robust TQWT. The fitness function of the mean square error of decomposition is used. This paper also exploits channel selection using a Laplacian score for dominant channel selection. Important features elicited from sub-bands of robust TQWT are classified using different kernels of the least square support vector machine classifier. The radial basis function kernel has provided the highest accuracy of 99.78%, proving that the proposed method is superior to other state-of-the-art using the same database. The recent increase in Brain-computer interface (BCI) has attracted researchers to develop solutions for computers and other devices with the aid of brain activities. BCI manipulates the brain’s electrical activities to help the specially-abled carry out their routine tasks. The cognitive activities accessed through electroencephalogram (EEG) signals provide an intelligent solution to assist specially-abled individuals to accomplish body movement just by mere imagination without any external support is motor imagery (MI) classification . Non-invSeveral techniques using EEG signals exploring time, frequency and time-frequency (TF) domain computation have been developed to detect MI tasks. Separation of MI tasks by distinction sensitive learning vector quantization based adaptive autoregression model has been proposed in . Welch sExploring evolutionary optimization for adaptive selection of proper basis function;Use of optimum decomposition level to decompose the signal into sub-bands;Exploring the utility of Laplacian score for selecting proper channels to reduce computational complexity.Wavelet transform (WT) and Wilcoxon statistical method with tabu fuzzy standards have been used in . IsolatiThe automated and adaptive TQWT has been used to various physiological conditions  ,45,46 anaa, al, av, aw, ay) sat on comfortable chairs have been recorded. Subjects performed the MI tasks of right foot (RF) (task1) and right hand (RH) (task2). According to the international 10–20 system, one hundred eighteen electrodes are used to acquire the EEG recordings of MI-related tasks. For intimation of MI tasks, subjects are shown with visual cues of 3.5 s before acquiring EEG signals [aa, al, av, aw, ay training set composed of 168, 224, 84, 56 and 28 trials and remaining used for testing. The actual sampling rate in recording EEG signals is 1000 Hz, later downsampling at 100 Hz. The stepwise working of the proposed method is shown in The proposed method uses the IV-a dataset of BCI competition-III . MI-task signals . For eacFor BCI, two types of oscillations play a vital role, Rolandic mu and central beta lying in the frequency range of 7-30 Hz . These oQ), redundancy rate (r) and levels of decomposition (L) as a basis function. Decomposing a signal with L level results in the generation of one lowpass SB (LPS) and L highpass SBs (HPS). TQWT can tune the Q as per the oscillatory behavior of signals. The higher quality factor is recommended for better frequency resolution and a higher redundancy rate for the well-localized time domain. After the L level decomposition of signal, LPS A TQWT is a parametrized discrete-time WT with a tunable quality factor. To decompose the signal into subbands (SBs) using TQWT requires quality factor (ented by (1)V0L of decomposition. To resolve an issue of uniform tuning parameters, robust TQWT is proposed to automate the selection of Q and r using EOAs. The steps for robust TQWT are described in Algorithm 1. The quality factor of TQWT, which must be higher for signals with higher oscillations, is represented byWith the tuning property of Algorithm 1 Robust TQWT1:Q and r initially to 1.Select the 2:Q and r.Calculate 3:Q, r and Decompose EEGs with 4:Q, r and M (No. of time samples).Get the approximated original signal by inverse robust TQWT using 5:Compute the MSE of decomposition error 6:while(do7: if (ew(t)== min) then8:  Optimum tuning parameters  and the Laplacian graph i and j correspond to nodes t is the constant, respectively.The features elicited from the filtered robust TQWT decomposed SBs are computed for 118 channels. To reduce the complexity of the BCI system, instead of exploring all the channels for classification, the adequacy of the single EEG channel is used in this framework. Laplacian score (LS), based on Laplacian Eigenmaps and locality preserving projection, is explored for selecting appropriate channels. The Laplacian score for the fined as .(17)Lk=N points Statistically, significant features are classified using classification techniques. This methodology uses the LS-SVM classifier to discriminate against the RH and RF activities. LS-SVM involves the formulation of inequality constraints that transform non-linear problems into linear equations with a rigid regression cost function. For a training set of data length of assifier  is definlable in . The linThe polynomial kernel can be defined asThe equation of MHW kernel is denoted asl is the degree of polynomial kernel, a are the parameters of MHW and MW kernels.The RBF kernel is defined byQ, r and The selection of fixed basis functions for decomposing non-stationary EEG signals may result in information loss. Setting the tuning parameters of TQWT may not yield the desired results, leading to higher misclassification. The method proposed in this paper uses the automatic selection of tuning parameters to decompose EEG signals using EOA accurately. PSO, ABC, and CS optimizations are used for self-selection of Q and r is used to compute Q, r and The decomposition error obtained for robust TQWT using EOA is shown in Equation  is obtaip < 0.05 are considered to be significant. Features from 118 electrodes are elicited from decomposed SBs. Employing features of 118 electrodes for classifying MI tasks increases the system’s complexity. Therefore, the Laplacian feature score is evaluated to select the substantial channel for performance evaluation. The Laplacian score of the five time-domain features is shown in Five kernels of LS-SVM classifiers are employed in this method to evaluate the classification accuracy of different SBs of channel-1. As the RBF kernel overperforms other kernels, it is used to evaluate the performance parameters of channel-1. The proposed framework is compared with the existing SOTA using the same database for its effectiveness. The performance of the proposed method is compared with 15 SOTA techniques considering the number of channels and features they have used, as shown in The model is robust .The developed model is simple (requiring only a single channel and five features to compute model performance).The model is data-driven (does not require selection of basis).The developed model has following advantages:The model is tested on a single EEG dataset with only five subjects.The model does not provide explainability for the predictions.However, the model suffers some limitations which are as follows:This method explores the utility of automatic selection of optimum tuning parameters of robust TQWT using evolutionary optimization algorithms. The adaptive selection of optimum tuning parameters is accomplished using PSO, ABC and CS algorithms. CS provides the fittest solution for the objective function; hence, the tuning parameters of CS are used to evaluate optimum decomposition levels and decompose the signal with these parameters. This method exploits the LS for selecting a dominant channel for segregating MI tasks using the LS-SVM classifier. The proposed method obtained an ACC of 99.78% which is higher than all other methods using the same database. The method proposed in this paper can be employed in a real-time BCI system to recognise MI tasks with lowered complexity as it uses only a single channel with a lower number of features.


Primordial germ cells differentiate into gametes through complex processes over a long period of time. Along the way, environmental signals are integrated into the chromatin state and epigenome, leading to molecular and cellular phenotypes. As a result, a diverse set of genomic and epigenomic information is passed on to the next generation. Despite a common principle of sexual dimorphism in which two types of gametes are produced and passed on to the next generation, the repertoire of genes involved and their functions are extremely diverse among species.Daphnia. These article Research Topic should facilitate a better understanding of the molecular pathways associated with gametogenesis.This article Research Topic covers papers on sexual reproduction in mammals as well as non-mammalian model organisms, such as medaka and Ishihara et al. identified novel paternally imprinted genes by re-analyzing public sequence data sets of sperm and early embryos published in previous mouse studies. They found that these novel paternally-expressed genes in zygotes are associated with H3K4me3 in the paternal genome in sperm and zygotes at the pronuclear stage 3 (PN3), thus identifying an epigenetic inheritance mechanism that is distinct from DNA methylation- and H3K27me3-based imprinting  . In miceShima provides a mini-review on the latest knowledge related to the role of mini-puberty in spermatogonial stem cell (SSC) formation. This phenomenon is known as temporal activation of the hypothalamic-pituitary-gonadal axis during the neonatal period , substantial progress has been made in understanding the mechanisms underpinning gene regulation during gametogenesis. Further technical innovation would shed light on hitherto unknown mechanisms of gene expression, chromatin structure, and nuclear dynamics in gametogenesis of diverse organisms.


The interaction between macromolecular proteins and small molecule ligands is an essential component of cellular function. Such ligands may include enzyme substrates, molecules involved in cellular signalling or pharmaceutical drugs. Together with biophysical techniques used to assess the thermodynamic and kinetic properties of ligand binding to proteins, methodology to determine high-resolution structures that enable atomic level interactions between protein and ligand(s) to be directly visualised is required. Whilst such structural approaches are well established with high throughput X-ray crystallography routinely used in the pharmaceutical sector, they provide only a static view of the complex. Recent advances in X-ray structural biology methods offer several new possibilities that can examine protein-ligand complexes at ambient temperature rather than under cryogenic conditions, enable transient binding sites and interactions to be characterised using time-resolved approaches and combine spectroscopic measurements from the same crystal that the structures themselves are determined. This Perspective reviews several recent developments in these areas and discusses new possibilities for applications of these advanced methodologies to transform our understanding of protein-ligand interactions. Often the life-time of the protein-ligand complex is tuned to dictate its function. In this respect, protein ligand interactions can display life-times ranging from microseconds to days. Complex life-times are determined by the ligand off-rate, with a high off-rate commonly associated with transient complexes and resulting in a dissociation equilibrium constant (KD) in the milli to micromolar range, whereas static complexes have a significantly lower off-rate and subsequently KDs into the nanomolar range and beyond. Obtaining high-resolution structural information for protein-ligand complexes provides direct information on the mode of interaction and is particularly powerful when combined with suitable biophysical methods, such as calorimetry or surface plasmon resonance that enable thermodynamic and kinetic parameters of the binding interaction to be quantified. Tremendous effort has been invested into developing methods to obtain structures of protein-ligand complexes, with orders of magnitude improvements in sample throughput and data analysis being achieved, particularly for the application of early fragment-based drug discovery  that are standard in X-ray crystallography may result in binding modes or interactions that are not fully consistent with those occurring under physiological conditions . A fascidentical . In thisAdditionally, the X-rays used to determine structures can themselves alter the structure of the crystalline protein through radiation damage , which iIn this Perspective, we review recent methodological advances relevant to structure determination of validated, high-resolution protein-ligand complexes and provide several examples of how these approaches have the potential to elevate our understanding of ligand binding.Early X-ray crystal structures were almost exclusively obtained at room temperature with crystals typically mounted in capillaries. Radiation damage concerns and increasingly brilliant X-ray synchrotron beamlines led to the development of highly effective cryo cooling methods with almost all structures subsequently determined at 100 K. Such cryogenic structures have led to tremendous insights into protein-ligand binding over many decades. However, the question of physiological relevance on a crystal complex determined at 100 K arises , and thuin situ (VMXi) beamline at Diamond Light Source  of microcrystals  are used for X-ray diffraction in sequence to assemble a complete dataset . The cruWe have shown the utility of serial femtosecond crystallography (SFX) at the SACLA XFEL in Japan to determine high-quality structures of protein-ligand complexes of iron and copper-containing proteins . LigandsUsing SFX to obtain structures of enzyme-substrate or enzyme-product complexes provides the essential starting point to determine time-resolved structures of transient states or enzyme intermediates. Several different methods have been developed to initiate reactivity within microcrystals. The most intuitive approach is to rapidly mix microcrystals with a suitable reagent solution at a defined point prior to X-ray exposure, in a manner analogous to stopped-flow enzyme kinetics. While conceptually simple, there are many technical challenges related to mixing rates and optimal homogeneous reaction initiation. Simple mixing of a protein and ligand can be achieved using a mix-and-inject system . Alternavia a pulse of light of the appropriate wavelength, typically delivered using a laser pulse  simulations of copper nitrite reductase clarified the protonation states of a catalytically important aspartate residue together with that of the substrate, intermediates and products . HoweverContext for the above is provided by further development of ultrahigh throughput structure determination of protein-ligand complexes at 100 K. This field has been pioneered by the XCHEM platform at Diamond Light Source  with a fIn conclusion, recently developed methods tremendously enhance our ability to understand the interactions between proteins and their ligands. Synergies between these methods and envisaged future developments suggest a bright future for time-resolved, ambient conditions structural biology of protein-ligand complexes.


Opportunities for developing innovative and intelligent drug delivery technologies by targeting the endocannabinoid system are becoming more apparent. This review provides an overview of strategies to develop targeted drug delivery using the endocannabinoid system (ECS). Recent advances in endocannabinoid system targeting showcase enhanced pharmaceutical therapy specificity while minimizing undesirable side effects and overcoming formulation challenges associated with cannabinoids. This review identifies advances in targeted drug delivery technologies that may permit access to the full pharmacotherapeutic potential of the ECS. The design of optimized nanocarriers that target specific tissues can be improved by understanding the nature of the signaling pathways, distribution in the mammalian body, receptor structure, and enzymatic degradation of the ECS. A closer look at ligand-receptor complexes, endocannabinoid tone, tissue distribution, and G-protein activity leads to a better understanding of the potential of the ECS toolkit for therapeutics. The signal transduction pathways examine the modulation of downstream effector proteins, desensitization, signaling cascades, and biased signaling. An in-depth and overall view of the targeted system is achieved through homology modeling where mutagenesis and ligand binding examine the binding site and allow sequence analysis and the formation of libraries for molecular docking and molecular dynamic simulations. Internalization routes exploring receptor-mediated endocytosis and lipid rafts are also considered for explicit signaling. Furthermore, the review highlights nanotechnology and surface modification aspects as a possible future approach for specific targeting. Cannabis sativa, observation of endogenous ligand binding, the genetic and physical mapping of the human cannabinoid receptor gene, and identification of enzymes that synthesize and degrade endocannabinoids and has resulted in increased interest and global acceptance of the use of Cannabis sativa [The discovery of the endocannabinoid system (ECS) began with the isolation of the active ingredient in an extract of s sativa . The gros sativa  [NO_PRINs sativa ,4,5,6,7.s sativa ,12,13,14Cannabis sativa is not without controversy; and the legality and stigma associated with the plant slowed the transition of use into the pharmaceutical industry [The global trend of decriminalizing industry . Challenindustry . Direct industry . CB1-R aindustry . While tindustry ,20,21. Iindustry .The most promising receptors and molecular targets in the endocannabinoid system have been identified which suggests strategic targeting approaches may improve drug delivery . The litCnrs) from several species have been cloned. In this review, we describe the use of different canonical and non-canonical receptors, phytocannabinoids, natural and synthetic endocannabinoids used to achieve specific drug delivery targeting.The strategies used to target sites where the endocannabinoid system is already active by enhancing endogenous cannabinoid tone appear to be more selective with minimal side effects and directly activate cannabinoid receptors ,43. HoweCannabis sativa is the most widely used illicit recreational and medicinal drug, in modern Western Society. Cannabis also has the most extended history of human use recorded compared to any other illicit drugs. The popularity of use of the plant lies in an ability to alter sensory perception and cause elation and euphoria [euphoria . The Freeuphoria .Cannabis sativa has been used as a fibre plant, a grain crop, and a medicinal plant in China since 4000 BC [Cannabis sativa plant used as a medicine by the ancient Chinese civilization was reported in the oldest known Chinese pharmacopoeia, the Shen-Nung Pen-ts’ao Ching, which lists 366 herbs and 1000 herbal formulations [ 4000 BC . The fib 4000 BC . Accordi 4000 BC . The eff 4000 BC . The Canulations ,55. Shenulations . In thesulations .Cannabis indica is mentioned in many ancient sacred Indian scriptures and folklore. The Indian Hemp Drugs Commission of 1893–1894, following testimony from hundreds of native and Western doctors about the therapeutic uses of cannabis [Cannabis indica is one of the most important drugs of Indian material medica [Many prescriptions were filled for the analgesic effect, especially for severe pain due to broken bones. Cannabis seeds are still prescribed as a laxative by Chinese physicians today . The morcannabis  concludel medica .Cannabis sativa, although limited by the high concentration of Δ9-THC compounds which dominates the present-day Cannabis sativa plant due to the changes in cannabis potency over the last few decades [Cannabis as a psychoactive substance reached Europe and America through trade with the Arab community in the 19th century to 1937, when it was banned in the United States of America . The iso decades . The las decades .i/o-coupled receptors [The ECS is a neuromodulatory system found throughout the human body . In 1992eceptors ., which follows a transduced functional response which is biological or physiological following the commencement of binding. Typically, a receptor has two main domains, a ligand-binding, and an effector domain. Receptor overexpression, unique binding motifs, and receptor patterning on the cell surface must be considered when selecting a receptor for receptor-mediated drug delivery technologies [Any biological macromolecule that may bind a drug and generate a measurable response, is considered a receptor. Two important properties of receptors are binding according to the laws of thermodynamics which is typically stereo-selective, saturable, and reversible in nature or signal transductionnologies .The isolation and sequencing of the superfamily, seven-transmembrane (7TM) G-coupled protein receptors commenced with the successful cloning of the receptor . This direceptor . The sixreceptor .Endocannabinoid receptors that were initially cloned are now well-established target sites and the identity of the cDNA sequence was confirmed when a rat cerebral cortex library revealed the identity of the CB1-R . StudiesThe CB1-R integral membrane protein with seven membrane-spanning helices coupled to heterotrimeric G-proteins on the intracellular side is depicted in In addition to CB1-R and CB2-R, receptors and ion channels may also interact with the ECS and GPCRs such as GPR55, GPR18, GPR119, peroxisome proliferator-activated receptors (PPAR), transient receptor potential (TRP) channels such as the vanilloid receptor TRPV1, GABA receptors, calcium, potassium, and sodium channels. While the GPCR regulate diverse physiological responses, they share common signaling mechanisms. Extracellular stimuli induce conformational changes in GPCR that activate heterotrimeric G-proteins and other intracellular effectors . The coni are compared, the active CB1-R-Gi and CB2-R-Gi are similar and the agonist-binding pockets are almost identical  to investigate binding potency and identify hotspot residues for CB1-R and CB2-R revealed that the hotspot residues for CB1-R and CB2-R are similar in both the active and inactive states whereas the hotspot residues of the different active states are diverse  suggestis and Gi proteins [s to Gi, and when mutated to Ile or Val a switch to a balanced coupling with Gs and Gi.Recent studies have revealed a highly conserved DRY(X)5PL motif, in which the residue Leu-222 resides and is located in intracellular loop 2 of CB1-R and CB2-R, and plays a vital role in mediating selective coupling to Gproteins ,94. Figuproteins . MutatioThe expression of CB receptors in the human and rodent brains diminishes according to the natural ageing process  and the CNR1 [CNR1 have been associated with cannabis dependence [CB1 receptors are most abundant in the brain and primarily located in the neurons . CB1-R aCNR1 . CB1-R pCNR1 . Variatipendence ,111,112.pendence .The gene encoding the human CB2 receptor was cloned in 1993 and the location on chromosome 1p36 identified . The sitEndocannabinoids play an important role as powerful regulators of synaptic function in the central nervous system where they regulate neural functions and behaviors . As fundio/ proteins [Stimulation of the CB1 receptor transduces stimulation of mitogen active phosphorylase kinase (MAP) and adenylyl cyclase inhibition, which decreases cyclic AMP production. CB1 receptors are coupled to ion channels through Gproteins . They coproteins .The CB2 receptor inhibits adenylyl cyclase in human lymphocytes and spleen cells in the mouse that express CB2 receptors . The actiα proteins regulate adenylyl cyclase. The inhibition of cyclic AMP production was noted when cell lines expressing CB1 or CB2 receptors were stimulated [γ mediates the regulation of ion channels, mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-kinase (PI3K). The two most studied endocannabinoid receptors CB1-R and CB2-R are separated primarily by differences in their amino acid sequence signaling mechanisms and tissue distribution.G-coupled proteins are secondary messengers that convey information to one or more effector proteins following receptor binding  and moduimulated . The freα and DAG-β with an arachidonic acid moiety at position 2 [α and DAG-β are produced from either the phospholipase-C-catalyzed hydrolysis of phosphatidylethanolamine or from the hydrolysis of phosphatidic acid [The first two endocannabinoids to be discovered were N-arachidonoylethanolamine (anandamide) and 2-arachidonoylglycerol (2-AG) which are both synthesized on demand in response to elevated intracellular calcium levels . While esition 2 . The predic acid . Anandamdic acid . Severaldic acid ,140.Cannabis sativa, they are also naturally produced in the mammalian body as endocannabinoids in a characteristic on-demand biosynthetic pathway. Endocannabinoids are similar to prostanoids in that they are not stored but are rather generated upon demand in response to a depolarization-induced rise in intracellular calcium levels or following activation of different metabotropic receptors [i/Go-coupled protein cannabinoid receptors or by exhibiting structural similarities with cannabinoids [Cannabis sativa L. is a dioecious plant belonging to the Cannabaceae family. Cannabinoids, flavones, and terpenes are the main phytochemicals found in this plant. Due to synergistic activity some biological activities of cannabinoids are known to be enhanced due to the presence of terpenes and flavonoids in the extracts [Cannabis sativa such as alkaloids, terpenes, terpenoids, polyphenols and derivatives of fatty acids, present in plants not belonging to the cannabis genus. The most potent psychoactive constituent of Cannabis sativa is Δ9-THC, first isolated in 1964 [A 2008 review described cannabinoids as the terpenophenolic constituents of the hemp plant . The caneceptors . Phytocaabinoids . Cannabiextracts . Phytoca in 1964 . The Δ9- in 1964 .As research into the ECS demonstrated cannabinoid receptors as viable targeting sites, more and more natural products are emerging as potential therapeutic prospects. Novel cannabinoids from diverse natural sources and species, including animal venom which contain toxins that modulate CB1-R and CB2-R with high affinity and selectivity .The components of the endocannabinoid system, including cannabinoids and related lipid mediators, make up the endocannabinoidome we have come to know today. There is an ever-growing list of cannabinoids, including phytocannabinoids from the cannabis plant, endogenous compounds, synthetic analogues, phytogenic and synthetic cannabimimetics that have been studied in recent years . PhytocaCannabinoid receptors are important for regulating a variety of physiological and pathological activities and potential ligands for the receptors hold promise as drug candidates for the treatment of different diseases. Ligands have been developed with functional and subtype receptor selectivity with the help of structural studies of cannabinoid receptors that provided insight into ligand-receptor interaction, activation and/or signaling of cannabinoid receptors. Structural information relating to cannabinoid receptors has permitted researchers to design specific ligands for the precise modulation of the endocannabinoid system . A studyThe most commonly studied cannabinoid ligands activate or inhibit cannabinoid receptor signalling by binding at the orthosteric sites of cannabinoid receptors . The ortAllosteric modulators bind to spatially distinct binding sites at the CB1 and CB2 receptors . AllosteAllosteric modulators do not activate the receptor directly but interact with topographically specific sites from the orthosteric ligand-binding pocket which modify the structural conformation of the respective receptor protein . Modern An approach to improving the safety profile of direct orthosteric activation is the pharmacological modification of receptor activation using PAM to enhance the activity while maintaining spatial and temporal control of the receptor. The enhanced signalling action of PAM may be through an increase in receptor-orthosteric ligand affinity or less efficient dissociation of orthosteric ligand and receptor .Pamplona et al.  reportedA study investigating the effects of positive allosteric ligands of cannabinoid receptors using a potent dual orthosteric agonist revealed that when used to treat neurodegenerative disorders, a combination of the orthosteric agonist and positive allosteric modulator was a promising therapeutic approach . GAT229,NAM have been shown to weaken the impact of orthosteric ligands and Shao et al.  revealedBiased agonists produce different degrees of activation along different pathways. Following activation, a biased agonist can selectively activate either the G protein or β-arrestin pathway . CannabiAn attempt to bypass the side effect profile of direct CB1-R activation led to the development and clinical investigation of the peripherally restricted CB1-R and CB2-R agonist, AZD1940 . AZD1940The activation of peripheral CB1-R has been proposed to exhibit analgesic activity for which the analgesic properties of AZ11713908, a peripherally restricted CB1-R agonist was evaluated following by systemic administration of AZ11713908 in CB1-R and CB2-R knock-out mice  which prThe complexity of cannabinoids demands a deep understanding of molecular pharmacology to facilitate fine-tuning of potential cannabinoid treatments. Understanding the endocannabinoid system also permits identification of new potential leads for drug development . An arseBy regulating two elementary signaling molecules viz., neurotransmitters from neurons and cytokines from immune cells, the endocannabinoid system is believed to play a pro-homeostatic function in pathology ,182,183.The anti-proliferative properties of cannabinoids in which inhibition of adenocarcinoma cell growth after oral administration of Δ9-THC in mice has been reported . The endWhile enhanced endocannabinoid tone may result in cessation of disease, there are cases in which up-regulation of the system is involved in pathogenesis  of obesiThe ECS is known to impact the female reproductive system where it has an effect on oocyte maturation, folliculogenesis, and ovarian endocrine secretion . A complWhile some cannabinoid receptor ligands such as allosteric modulating agents and biased agonists act directly), other treatment options indirectly target the enzymes responsible for synthesis and catabolism . In manyPharmacological strategies for enhancing endocannabinoid tone include additional targets outside the endocannabinoid system, specifically cyclooxygenase-2 (COX), cholinesterase (ChE), prostaglandin F2α receptor (PGF2α-EA) in addition to commercially available medicines and plant material which exhibit cannabimimetic properties that enhance endocannabinoid levels . StandarThe inhibition of endocannabinoid metabolism focusses on two enzymes viz., fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL) . The maiA strategic approach to potentiating endocannabinoid signaling is the prevention of endocannabinoid inactivation by intracellular enzymes through inhibition of extracellular uptake of endocannabinoids. Compounds which inhibit the cellular uptake of anandamide include AM404, VDM11, UCM707, OMDM1, OMDM2, and LY2183240 . RetrogrPiper nigrum and demonstrated cannabimimetic effects in mice, proving it is a highly potent inhibitor of anandamide and 2-AG. Naturally occurring fatty acid amides in Echinacea puprurea exhibited anti-inflammatory, analgesic, and anxiolytic properties in mice and WOBE437 and RX055 are synthetic derivatives of these fatty acid amides [Several endocannabinoid membrane transporter (EMT) inhibitors have been tested in preclinical studies. While most EMT inhibitors were thought to be specific for EMT, they have been shown to interact with other components of the ECS and inhibit FAAH, MAGL, COX-1, 2, and FABP5. Some highly potent EMT inhibitors with good selectivity include Guineensine, BSL34, WOBE437, and RX055. Guineensine is extracted from the medicinal plant d amides . There ad amides .Another approach to enhance endocannabinoid tone, is to block the intracellular proteins involved in endocannabinoid transport. ARN272 competes with AEA for FLAT binding, thereby reducing the internalization of AEA  and SBF1It has been shown that the saturable, temperature-dependent substrate selective properties of lipophilic endocannabinoids make the uptake of endocannabinoids possible through facilitation by proteins ,210. CelCNR1, the gene encoding CB1-R and FAAH, the hydrolyzing enzyme with subsequent alteration of endocannabinoid signalling or tone [While cannabinoid receptors are distributed widely throughout the body of vertebrates, there are differences in anatomical distribution . In most or tone ,214,215. or tone ,217,218. or tone ,221,222.The homology of CB1-R between mice, rats, and monkeys is identical to human CB1-R (97–100%) and lower homology occurs for CB2-R with only 81% similarity between the rat and human receptors. The action of different cannabinoids differs with cellular context and species differences . Human CIn the same pathophysiological state, it has been shown that the concentration of endocannabinoids differs depending on species, stage of disease and tissue involved . In a trA potential strategy to target the ECS specifically is the use of FABP since they display specificity in tissues at selected sites in the body ,228. Celi proteins, CB1-R also couples with Gs or Gq proteins [i and βγ subunit proteins coimmunoprecipitate with the CB1-R revealed that WIN 55,212-2 behaves as an agonist for all three Gi subtypes. In addition, ligand-selective G protein responses were identified, and multiple receptor conformations may result in individual G protein activity [s or Gi –coupled pathways, Bonhaues et al. [i and inhibited cAMP production, CB1-R coupled to both Gs-mediated cAMP production and Gi-induced activation of ERK1/2 and Ca2+ transportation [Each guanine protein interacting with cannabinoid receptors is coupled to effector proteins or subunits that mediate cellular signals. The heterotrimeric subunits and classes of G-proteins are depicted in proteins . In a stactivity . To tests et al.  investigortation .Ligand-receptor complex activation leads to conformational changes in the receptor which permits binding and activation of heterotrimeric G-proteins. G-protein-coupled receptor kinases recognize the structural conformation of cannabinoid receptors and undergo differential phosphorylation to generate specific patterns or barcodes depending on the ligand ,235. Theβ-arrestins act as scaffold proteins for endocytic machinery and signaling molecules including mitogen-activated protein kinases (MAPK). The ligand-induced receptor internalization role of β-arrestins occurs as the β-arrestin C terminus binds directly to clathrin, thereby producing a scaffold for endocytic machinery. In this way, desensitized receptors are internalized from the cell surface via clathrin- or caveolae- mediated endocytosis.kiss1 neurons in female mice [In a study involving the frog Pelophylax esculentus, the endocannabinoid AEA was found to modulate the GnRH system in vitro and downregulate steroidogenic enzymes in vivo . Anotherale mice , currentale mice . Apart fale mice .Cannabis sativa is finding suitable models to test the therapeutic efficacy since few animals exhibit the same endocannabinoid system biodistribution and activity as humans [The increasing acceptance of phytocannabinoids across the globe has resulted in a need to identify their role in the management of disease. Precise mapping and localization at the cellular, tissue and regional levels of distribution of cannabinoid receptors is critical to determining their role accurately . The chas humans .Mapping the genome and elucidating the structure of cannabinoid receptors with the aid of modelling software may facilitate an understanding of how ligand-receptor complexes engage in modulating downstream signaling of the ECS. Consequently, the elucidation of cannabinoid receptors and other GPCR structures is an attractive area of research . BreakthThe major challenge inhibiting the progression of clinical use of cannabinoids is the challenge of formulation design of pharmaceutical dosage forms to incorporate the cannabinoids which exhibit low aqueous solubility, low bioavailability, are oily and resin in nature which are unstable. The untapped potential of the endocannabinoid system is often restricted by unspecific site targeting. Attempts to develop peripheral or CB2-R selective agonists to minimize centrally occurring psychoactive effects have not yet been successful. Clinical studies revealed a loss in translation between the reality of clinical studies and the preclinical promise of CB2-R agonists in experimental models ,209. NanPharmaceutically, nanotechnology is a popular alternative to traditional approaches of medicine delivery due to an ability to engineer the technology for improved efficacy . CommonlThe ideal drug delivery vehicle (DDV) platform may be strategically engineered to pass biological barriers and facilitate specific intracellular localization by modulating drug release mechanism, mode of delivery and transport into the body, and target cells . PhysicaWhen designing a GPCR-mediated targeted drug delivery system, entry into the cell across biological barriers is an essential consideration . Cell trReceptor-mediated drug delivery systems (DDS) are well-established approaches used to improve specific targeting and enhance cellular uptake of therapeutic compounds . The impNanoengineered drug delivery vehicles (DDV) are designed to transport encapsulated cargo containing therapeutically active ingredients  to the sThe benefits of nanotechnology are derived from the impact of size on biodistribution, cellular uptake and kinetics of release . The maiWhen evaluating nanoparticles designed for the selective delivery of a drug, the effects of particle size and surface charge on murine macrophage uptake and in vivo biodistribution demonstrated that particle size and surface charge were critical parameters. The size of nanoparticles plays a role in the manner they interact with biological systems such as the immune system for example. An investigation into the interdependent effects of physicochemical properties on cellular uptake and biodistribution showed that even relatively small physicochemical differences such as a 10-mV difference in potential changed phagocytic cell uptake. The negatively and positively charged fluorescence-labelled chitosan derivative nanoparticles evaluated displayed cell-line and energy-dependent endocytosis. The high cationic surface charge and large particle size of >100 nm resulted in higher serum protein adsorption and non-specific uptake by most cell lines when compared to that observed for neutral or anionic particles .Receptor-mediated endocytosis of nanocarriers is affected by shape . A stratParticle elasticity is thought to alter the cellular uptake of nanoparticles through cell surface receptor binding and an ability to squeeze through pores in addition to changes in blood circulation time . The intInvestigation of the elasticity of nanoparticles and influence thereof on blood circulation time, phagocytosis, endocytosis and targeting properties revealed that soft particles demonstrated an enhanced circulation and enhanced targeting when compared to harder nanoparticles. In vitro experiments also revealed that soft nanoparticles demonstrated a reduced cellular uptake in immune, endothelial and cancer cells which increased persistence of soft nanoparticles in the circulatory system . Sun et The properties of the drug to be delivered are usually the starting point when selecting materials to build a drug delivery vehicle. Biomimetic nanoparticles based on the size, hydrophobicity, and ideal drug release profile are considered vital when mimicking nature for the design of drug delivery technologies . FormulaLipid-based drug delivery systems are a diverse formulation strategy for the incorporation, dissolving or suspension of active pharmaceutical ingredients in lipidic excipients. Lipids are esters of fatty acids such as glycerides and PEG esters comprised of hydrophobic hydrocarbon chains linked to hydrophilic, electrostatically charged head groups such as glycerides, polyglycerol, or polyalcohol esters. Classes of lipids include fatty acids, long-chain triglycerides, medium-chain triglycerides, propylene glycol esters and mono- or di-glycerides . These cLiposomes are composed primarily of lipids with diacyl chains and can be functionalized by conjugating targeting ligands to chemically reactive lipids. The mechanical properties of liposomes were recently investigated to determine the differences in the endocytic pathway of liposome uptake with different values for Young’s modulus . LiposomBiodegradable polymeric materials have been used to manufacture nanoparticles that cross biological barriers for the purposes of active cancer-targeting . PolymerMicelles are formed by amphiphilic macromolecule copolymers, orientated with single acyl chains facing inward, forming an inner core and their hydrophilic headgroups facing outwardly . Nano-miDe La Ossa et al.  investigSurface modification of nanocarriers has been used to optimize the effectiveness of targeting, improving ligand binding, and enhancing cellular uptake of the drug delivery system. The most influential factors of functionalizing the surface(s) of nanocarriers include spacing, density and orientation of ligands. It has been shown that enhanced cellular uptake and reduced nonspecific uptake in healthy tissues are attributed to the spatially distinct orientation of ligands on the surfaces of nanocarriers.Lipid bilayers of cell membranes have been shown to form compartmentalized domains called lipid rafts or caveolae pits which exhibit different biophysical properties. The raft domain is an essential feature for membrane proteins such as G-protein coupled receptors since they provide a platform for the assembly of signaling complexes and prevent crosstalk between pathways . CaveolaWhile the process of GPCR endocytosis for receptor-mediated drug delivery has been attempted , evidencStudies have revealed that ligand density affects cell internalization of targeted nanoparticles and influences the pathway of nanoparticle internalization by the cells. A ligand presented in a clustered as opposed to dispersed arrangement affects and generally increases the level of cellular uptake in an in vitro epithelial model . An apprLigand-specific endocytic dwell times of CB1-R are able to be used to control the functional selectivity of the receptor. The amount of time during which CB1-Rs are clustered into clathrin-pits with β-arrestins prior to endocytosis was found to be the mechanism by which β-arrestin signaling was controlled . AgonistA multitude of ligands can be conjugated with the surface of nanovehicles and may perform multiple roles including targeting receptor-mediated cellular uptake of CB1-R or CB2-R agonists or antagonists, natural macromolecules, and cell-penetrating peptides. When ligands attached to the surface of nanoparticles in a traditional manner the surface pattern is random across the nanoparticle surface. It was demonstrated  in a stuCannabis Sativa [Subsequent to the discovery of endocannabinoid receptors, the complex endocannabinoid system consists of bioactive lipidic endocannabinoids, their synthesizing and degrading enzymes, the endocannabinoid membrane transporter and the endocannabinoid receptors, research has revealed that the ECS regulates neurotransmitter release, brain development, tissue and organ homeostasis, synaptic plasticity and cytokine release and it follows that the dysregulation of the ECS can be observed in multiple pathophysiological disorders . Decadess Sativa . The sids Sativa . The sers Sativa . A myriaSpecific targeting of the endocannabinoid system seems to be a good starting point towards developing a sophisticated cannabinoid drug design void of undesirable side effects but the future of commercialized ECS products calls for exploration from a broader perspective. Further study into the complexity of the expanded endocannabinoidome is required to consider the dynamics and interconnections it has with other regulatory systems. As the ECS is interconnected with other lipid-based signaling systems and cannabinomimetic compounds have been identified in a variety of foods, research into the link between diet and the synthesis and release of endocannabinoids and related mediators will do well to guide a better understanding of the endocannabinoidome and epigenetics of the ECS .Box 1Novel strategies for targeting the endocannabinoid systemThe full characterization of signaling pathways is essential when considering candidates for targeting the ECS.Approaches to activate either G-protein signaling or β-arrestin signaling, include the use of endocytic lipid rafts, binding at specific extracellular loop motifs and plasticity of the receptor.Methods for using routes of biased signaling, include designing ligands as structural tools including allosteric modulators or ligands that exploit the plasticity of the receptor as G-protein biased ligands or β-arrestin biased ligands.High-resolution crvstal structures of cannabinoid receptors and molecular simulations effectively guide cannabinoid drug design.Nanoparticles can be engineered to provide site-specific delivery of cannabinoid ligands.Altering the density and surface pattern of ligands through clustering and patterns is a strategy to promote the use of one route of endocytosis over another.Overexpression of receptors in different pathological states can be used as potential targets for treatment of specific disorders.Receptor-mediated endocytosis can also be used to facilitate entry into specific sites through cannabinoid receptors.Molecular simulations can be used to predict the motion of every atom in a receptor and those in the molecules with which the receptor interacts.This box summarizes the key points contained in the article.


Here, we demonstratethat reversible on and off switchingof the PL in the NIR region can be achieved in a bicomponent systemcomprised of PbS semiconducting nanocrystals (NCs) and diarylethene(DAE) photoswitches. Photoisomerization of DAE to the ring-closedform upon UV light irradiation causes substantial quenching of theNIR PL of PbS NCs due to efficient triplet energy transfer. The NIRPL fully recovers to an on state upon reversing thephotoisomerization of DAE to the ring-open form with green light irradiation.Importantly, fully reversible switching occurs without obvious fatigue,and the high PL on/off ratio (>100)outperforms all previously reported assemblies of NCs and photoswitches.Precisely modulated photoluminescence (PL) with externalcontrolis highly demanded in material and biological sciences. However, itis challenging to switch the PL  A simple way to implementan optically switchable PL system (OSPLS) is to combine a highly emissivematerial with a photochromic molecular switch,8 generally referredto as photoswitch. Colloidal semiconducting nanocrystals (NCs),10 often referred to as quantum dots, with outstanding performancessuch as bright PL and size-tunable emission wavelengths are idealPL materials for constructing OSPLS. Photoswitches, whose two isomerscan interconvert upon irradiation at different wavelengths, can beused in combination with NCs.13 The photoswitches are typicallybound to the surface of NCs to construct OSPLS in which only one isomercan quench the PL of the NCs, hence the conversion between the isomersupon light irradiation results in the modulation of the PL intensity.Modulating photoluminescence(PL) between a “dark” 20 and photoinduced electron transfer (PET).23 Thus far, OSPLSshave displayed modulated emission only in the visible region and comparablylow PL on/off ratios. Here, we presenta highly efficient OSPLS comprised of PbS NCs and diarylethene (DAE)photoswitches, where the NIR PL of PbS NCs can be reversibly switched on and off when the DAE-open and DAE-closedisomers interconvert upon light irradiation. The intensity of theNIR PL in the “dark” off state is lowenough to yield an on/off ratiolarger than 100, while the emission of the PbS NCs is essentiallyunaffected in the on state. The key to achievingthe optically switchable NIR PL of our design is the large differencebetween the excited triplet-state energies of DAE-open and DAE-closed.The triplet energy transfer (TET) that induces NIR PL quenching exclusivelyoccurs from PbS NCs to DAE-closed, as the triplet excited state ofDAE-open is much too high to allow this process.The mechanisms of reported OSPLSs that use NCs and photoswitcheshave been based on Förster resonance energy transfer (FRET)25SI). Upon the subsequent irradiationof the solution at PSS with green light, the spectrum fully recoversto the initial state. DAE shows some photochromic fatigue over theswitching cycles upon UV and green irradiation . It should be noted that neither DAE-open nor DAE-closedemits light in the NIR region.The PbS NCsand DAE were synthesized according to previous reports.SI. After mixing with DAE, the NIR PL of PbSNCs can be switched on and off uponalternating exposure to UV and visible light, as shown in on/off ratio is >100for 1.5 μM PbS NCs with 67 equiv of DAE. Such a large degreeof modulation is much higher than those for previously reported systemscomprised of NCs and photoswitches. For instance, CdSe/ZnS NCs surface-boundwith 90–100 equiv of spiropyran photoswitches showed a PL on/off ratio of ca. 10 via FRET control,14 and the assembly of CdSe NCs with 600 equivof furyfulgide photoswitches had a maximum PL on/off ratio of 25 via PET control.23 The PL lifetimes of PbS NCs were also examined using time-resolvedPL measurements . PbS NCsshow a PL lifetime of about 2.8 μs, which decreases slightlyto 2.7 μs after the NCs are mixed with DAE-open. Upon isomerizationto DAE-closed, the PL lifetime of PbS NCs dramatically decreases belowthe resolution of our instrument response function (0.7 μs)in the NIR region, which is consistent with the substantial quenchingobserved in the steady-state measurements.The photochromic properties of DAE were retainedafter it was mixedwith PbS NCs. SI). Under the same illuminationconditions , 50% of the DAE molecules convert to theclosed form in the mixture compared to 90% conversion for a solutioncontaining DAE alone. It should be noted that 50% conversion of DAEis enough to efficiently quench the NIR PL of PbS NCs. As a controlmeasurement, a sample prepared with PbS NCs alone did not show anylight-induced modulation of the PL intensity  and is likely the excited state of PbS NCs, which decays onthe microsecond time scale (vide supra).28 fsTA spectra and the corresponding spectral components of PbS NCsmixed with DAE-open are essentially identical to those of PbS NCsalone. This indicates that neither energy transfer nor electron transferoccurs from PbS NCs to DAE-open, which corresponds well with the unquenchedemission of PbS NCs. However, when PbS NCs are mixed with DAE-closed,the spectral evolution changes drastically. The short-lived componentshows a lifetime similar to that of PbS NCs alone, while the lifetimeof the broad and long-lived PbS NCs excited state absorption decreasesto 2.7 ns, showing that the excited state of PbS NCs is strongly quenched.As the excited state of PbS NCs decays, a new species with two distinctabsorption bands centered at 488 and 560 nm forms. The new speciescorresponds to the acceptor state of DAE-closed, which we assign tothe triplet excited state (section 9 of the SI).Femtosecond transient absorption (fsTA) spectroscopy was performedto gain further insight into the mechanism of the PL quenching see 3. The moSI) calculation, the lowest triplet excited state (T1) energies of DAE-open and DAE-closed are 2.65 and 0.89 eV, respectively.NCs exhibit a strong spin–orbit coupling with substantial mixingof the singlet and triplet states,32 and both thebright and dark exciton states can contribute to TET.34 The excited state of the synthesized PbS NCs can be estimated tobe 1.65 eV from the peak of the first excitonic transition. As such,the T1 state of DAE-open is much higher in energy thanthe PbS NCs. Conversely, the T1 state of DAE-closed is740 meV lower than that of PbS NCs; thus, TET can only occurfrom PbS NCs to DAE-closed and not DAE-open. The large TET drivingforce between PbS NCs and DAE-closed is the key to achieving the highPL on/off ratio of our system.The suggested quenching mechanism and triplet energylevels aresummarized in SI. Briefly, there is only a small driving force for PET from PbS NCsto DAE-closed, which is unlikely to cause such highly efficient PLquenching. Additionally, component C in Figure S9). Wetherefore conclude that TET rather than PET is the main mechanismresponsible for the efficient PL quenching observed herein.FRET quenching can be excluded in our design, asthere is no overlapbetween the PL spectrum of PbS NCs and the absorption spectra of eitherform of DAE. The final quenching mechanism to consider is PET, whichis discussed in detail in section 8 of the on and off by illuminatingthe mixture with distinct wavelengths. The high PL on/off ratio (>100) significantly outperforms allpreviously reported assemblies of NCs and photoswitches. The switchingcapability in the NIR region is primarily attributed to the mechanismof triplet energy transfer, which is only energetically possible fromPbS NCs to the triplet excited state of DAE-closed, not DAE-open.The large difference between the excited triplet state energies ofthe DAE derivatives in the open form and the closed form can in principlebe fine-tuned over a wide spectral window. By choosing appropriateNCs in combination with visible or NIR triggered DAE photoswitches,37 it should be possible to observe efficient NIR PL switching thatis activated without using UV light. Our approach will enable furtheroptimization in optically switchable electronic devices and opticalmemory and could offer precise control in super-resolution imagingtoward biological applications.In summary, we have designed an OSPLS comprised of PbS NCs andDAE photoswitches in which the NIR PL can be efficiently and reversiblyswitched


The longevity of a lithium-ion battery is limited by cathode degradation. Combining atom probe tomography and scanning transmission electron microscopy reveals that the degradation results from atomic-scale irreversible structural changes once lithium leaves the cathode during charging, thereby inhibiting lithium intercalation back into the cathode as the battery discharges. This information unveils possible routes for improving the lifetime of lithium-ion batteries. Understanding capacity degradation mechanisms is necessary to rationally design new materials or implement operational protocols to enhance durability, but degradation mechanisms are complex and typically occur across multiple length scales, some of which are not readily accessible without using high spatial resolution characterization techniques.Lithium-ion batteries have received great attention due to their widespread use for applications ranging from small electronic devices, for instance mobile phones, to high-capacity energy storage, such as in electric vehicles and grid energy. A major limiting factor in renewable energy grid integration is the ability to reliably store and access electricity at a low cost. For example, solar panels are economically competitive with fossil fuels; however, solar energy is produced at nature’s will and must be stored for future distribution in the event of solar power surpluses. Li-ion batteries are among the best commercially viable energy storage technologies, but unfortunately, capacity degradation limits their lifetime and battery replacement is expensive. Engineering Li-ion batteries to extend their operational lifetime will decrease cost and limit the environmental footprint associated with renewable energy compared to other energy sources, facilitating widespread usage3. High-energy density Li-ion batteries require high-voltage cathodes that are typically an oxide compound containing Li and at least one transition metal 4. In fact, the discovery of Co-based oxides for use as Li-ion battery cathodes led to the Nobel Prize in Chemistry in 2019 to early pioneers Goodenough, Whittingham, and Yoshino5.Li-ion batteries consist of a cathode/electrolyte/anode heterostructure, as shown in Fig. 8. Correlating the Li distribution and atomic structure at the relevant length scales over the lifetime of a battery is crucial to unlocking the degradation processes and provide the insight needed to limit or avoid it.Li-ion battery capacity degradation originates from structural defects that are created by compositional instabilities in the high-voltage cathode. Lithium removal from metal oxides at high voltage causes structural changes, which can result in defect formation including anti-site defects. Successive charge-discharge cycles lead to defect accumulation that embrittles the cathode and drives capacity loss9. However, Li-containing materials are typically unstable under electron beam irradiation, and the detectability and quantification of light elements is challenging. APT is a time-of-flight mass spectrometer combined with a three-dimensional projection microscope having sub-nm spatial resolution. Aberrations in the projected ion trajectories limit the ability of APT to extract structure or elemental site occupancy, but its compositional sensitivity, in the tens of parts-per-million, extends to light elements, including Li, albeit not without challenges12. Fortunately, the shortcomings of either technique are complemented by the strengths of the other technique13 and therefore, a combined APT and STEM experiment can enable the correlation of atomic structure with nanoscale Li concentrations.(Scanning) transmission electron microscopy ((S)TEM) techniques and atom probe tomography (APT), separately or in combination, are commonly used to characterize the structure and chemistry of materials. STEM provides a two-dimensional, projected image of the material and can attain sub-Å spatial resolution, revealing the structural organization of the atoms, which can also be chemically identified using spectroscopy techniques such as X-ray energy dispersive spectroscopy (EDS) or electron energy loss spectroscopy (EELS). Additionally, electron diffraction can identify the crystallographic phases at the nanoscale0.80Co0.15Mn0.05)O2 (NCM)-based cathode14. The cathode is an agglomeration of approx. 10 µm “powder grains” that each contain several 100 nm-sized particles sintered together, such that only the surface of the 10 µm particles contact the electrolyte. Inductively coupled plasma-atomic emission spectroscopy (ICP-AES), a bulk composition measurement technique, confirms the loss of Li within the cathode over the course of multiple cycles, but the spatial resolution of this method is simply insufficient to determine the origin of the Li loss.To better understand the creation of the observed Li-ion concentration gradients and track the chemical evolution during electrochemical cycling, Chae et al. combined the strengths of STEM and APT to probe the chemical and compositional changes of a LiTEM techniques are better suited for nano- to atomic-scale structural and local valence state identification. The combination of these techniques reveals a direct correlation of the Li loss in NCM cathodes to local structural disorder and phase transformations that limit the capacity of Li-ion batteries. What’s next? These insights demonstrate possible routes for improving the lifetime of batteries via two possible ideas: (i) adjust the material’s composition to limit the migration of TMs into anti-sites, which is related to the energetics of site-occupancy and hence may be calculable by ab initio techniques; (ii) the cores of the cathode particles remain unchanged, meaning that the Li therein is ‘lost’ or rather unexploited, and as such, designing the grain architecture may help use these unused ions. We hope battery experts seize on these results and integrate them into the design of next generation batteries.


Cellular and/or Tissue Product made of stratified keratinocyte-containing epidermis and fibroblast-embedded collagen dermis, has been shown to promote healing in patients with deep partial- thickness burns. The biological mechanisms behind these effects are poorly understood. Macrophages, the primary cell type of the innate immune system, are major regulators of all stages of tissue repair. They accomplish these diverse functions by shifting phenotype throughout the healing process from a pro- inflammatory population to a diverse population of phenotypes that orchestrate resolution of inflammation and healing. In burn injuries this transition is impaired. We hypothesized that skin substitutes promote this healthy transition in macrophage phenotype. The aim of this study was to analyze the crosstalk between skin substitutes and macrophages and to determine the influence of direct contact, secreted factors, and the substrate used in fabrication of the skin substitutes.Primary human macrophages (N=4 donors) were co-cultured either directly or indirectly with a skin substitute via separation by transwell inserts. Macrophages were also cultured directly on the collagen scaffolds used in the skin substitute fabrication process or on low-activation plastic as an unactivated control. After 1 and 3 days, the macrophages were stained with a 10-marker flow cytometry panel to characterize macrophage phenotype: general marker (CD45), M1-related markers  and M2-related markers . For a more thorough evaluation, multidimensional analysis was used to identify unique populations of macrophages. Large-scale Dimensionality reduction using triplets and clustering analysis with using FlowSOM algorithms were performed. Statistical analysis of individual marker expression or cell composition within clusters was performed with one-way ANOVA.In response to both direct and indirect interaction with skin substitutes, macrophages generally decreased M1 marker expression after 1 day in culture and increased M2 marker expression after 3 days. The suppression of M1 markers occurred when macrophages were co-cultured with skin substitutes, and in response to acellular collagen. The upregulation of M2 markers occurred only in response to direct or indirect interaction with cellular skin substitutes. Furthermore, multidimensional single cell analysis showed that contact with the skin substitutes also promoted unique populations of phenotypes that do not fit into the classical M1/M2 paradigm.These results suggest that a potential mechanism by which skin substitutes promote healing is by promoting a transition of macrophages towards pro-reparative phenotypes.