Background: Frozen section and smear preparation are the current standard for intraoperative histopathology during cancer surgery. However, these methods are time-consuming and subject to limited sampling. Multiphoton microscopy (MPM) is a high-resolution non-destructive imaging technique capable of optical sectioning in real time with subcellular resolution. In this report, we systematically investigated the feasibility and translation potential of MPM for rapid histopathological assessment of label- and processing-free surgical specimens.Methods: We employed a customized MPM platform to capture architectural and cytological features of biological tissues based on two-photon excited NADH and FAD autofluorescence and second harmonic generation from collagen. Infiltrating glioma, an aggressive disease that requires subcellular resolution for definitive characterization during surgery, was chosen as an example for this validation study. MPM images were collected from resected brain specimens of 19 patients and correlated with histopathology. Deep learning was introduced to assist with image feature recognition.Results: MPM robustly captures diagnostic features of glioma including increased cellularity, cellular and nuclear pleomorphism, microvascular proliferation, necrosis, and collagen deposition. Preliminary application of deep learning to MPM images achieves high accuracy in distinguishing gray from white matter and cancer from non-cancer. We also demonstrate the ability to obtain such images from intact brain tissue with a multiphoton endomicroscope for intraoperative application.Conclusion: Multiphoton imaging correlates well with histopathology and is a promising tool for characterization of cancer and delineation of infiltration within seconds during brain surgery. Surgical resection is first-line treatment for many cancers. Maximizing cancer resection while sparing adjacent healthy tissue is crucial for optimal treatment outcomes Frozen sections and smears are the most commonly used techniques for intraoperative assessment during cancer surgery. These methods typically require 20-30 minutes to process, in contrast to the standard formalin-fixed, paraffin-embedded (FFPE) histopathology which usually requires >24 hours. However, the freezing process is destructive to tissue and may introduce image artifacts in vivo imaging.To improve intraoperative assessment, various optical techniques have been developed for rapid, high-resolution imaging of fresh human brain tissues, including microscopy with ultraviolet surface excitation (MUSE)  in vivo with subcellular resolution MPM is a non-destructive technique, capable of high-speed imaging of biological tissuesin situ, high-quality TPF imaging of human tissues intraoperatively.This study reports the use of three-channel MPM to evaluate unprocessed and unlabeled human brain tissues from 19 patients. Imaging results were co-registered and compared with clinical standard histopathology. MPM captured several essential diagnostic features and deep learning algorithms applied to MPM images were able to discriminate tissue types. We also demonstrate subcellular resolution label-free imaging of intact brain tissue with a miniature fiber-optic scanning multiphoton endomicroscope that is suitable for Human glioma specimens were obtained from patients undergoing brain surgery at the Johns Hopkins Hospital with patient consent. Normal human brain tissues were obtained from short post-mortem interval autopsies performed on de-identified individuals free of neurologic disease whose next-of-kin consented to research use of tissue. All aspects of the project were performed according to protocols approved by the Institutional Review Board of the Johns Hopkins Hospital.Table S1). Freshly resected specimens were kept in ice-cold phosphate buffered saline solution (PBS) during tissue transportation as well as the entire imaging procedure. The tissue surface was cut flat and covered with a cover glass during imaging. All the measurements were performed in a temperature-controlled (20 °C) dark chamber. After imaging, a subset of specimens were fixed with 10% neutral buffered formalin, and then embedded in paraffin, sectioned at 5 microns, and stained with hematoxylin and eosin.13 fresh non-cancerous specimens from 8 autopsy cases and 25 fresh specimens from 11 neoplastic neurosurgery cases were included in the study  for 20 min or with 1 µM 4',6-diamidino-2-phenylindole (DAPI) for 2 min, rinsed in PBS for 1 min, and then imaged with MPM again to further assess cytoarchitecture co-registered with the label-free images for comparison and confirmation. The detailed procedure for tissue preparation and imaging is shown in Figure S2 shows a schematic of the MPM imaging system. The custom-built three-channel multiphoton microscopy system was based on an Olympus microscope body . A tunable Ti:sapphire laser  was used as the excitation source. The raster-scanned laser beam was focused on the sample by a high numerical aperture water immersion microscope objective . Epi-fluorescence and SHG signals were collected by the same objective lens and separated from the excitation light with a dichroic mirror, and then further filtered for each of the three channels by a 496 nm long-pass optical filter (F1) for FAD, a 447/60 nm band-pass optical filter (F2) for NADH, and a 390/18 nm band-pass optical filter (F3) for SHG signals before finally coupled into a photomultiplier tube (PMT). Gains and thresholds were set identically for all three PMTs. Images were acquired using an excitation wavelength at 780 nm with an average power of ~30 mW. Images of a size 350 μm × 350 μm from the three channels were collected in a raster fashion, and it took about 9.59 s to acquire one frame of 1024 × 1024 pixels with a 350 μm × 350 μm field of view (FOV). Multiple MPM images were acquired sequentially and automatically stitched to create a single mosaic image with a larger FOV. Three dimensional volumetric images were acquired by automatically scanning the objective focus along depth.The design details of the multiphoton endomicroscope can be found elsewhere ®. Quantitative image processing and analyses were performed using ImageJ.Automated stitching was performed using custom code written in MATLABA residual convolutional neural network (ResNet) was used for real-time, automated and robust classification of MPM images of unstained human brain tissues To test the diagnostic accuracy of the ResNet-based method, 35 specimens from 18 cases were selected by a neuropathologist (Nauen) to be included for the training and validation of two ResNets with ResNet 1 for differentiating normal gray matter and white matter and ResNet 2 for differentiating cancerous and non-cancerous tissues. All the training, validation and testing used each individual images of a size of 350 μm × 350 µm (a single unstitched MPM FOV) within a mosaic. Image tiles within a mosaic that did not contain tissue were excluded. ResNet 1 contained 2,389 MPM FOVs classified either as gray matter or white matter. ResNet 2 contained 3,909 MPM FOVs classified either as cancerous or non-cancerous tissues. For ResNet 1, all FOVs  from 7 non-cancerous cases (Nos. 1-7) were used for training and validation, and the FOVs  from case No. 8 served as the test set. For ResNet 2, all FOVs  from 12 cases  were used for training and validation, and the FOVs  from cases Nos. 7-8, 12-13 and 18-19 served as the test set. Specimen classification was performed at the mosaic level and the specimen was classified as cancer when greater than 50 % of the FOVs within the mosaic were predicted as cancer by the trained neural network.in vivo detection of cancer, two 8-week-old immunodeficient male BALB/c nude mice  were stereotactically inoculated with cancer cells as previously described 6 GFP labeled GBM1A cells cultured from a patient-derived primary stem cell line In order to test the capacity of MPM for -1 body weight) and xylazine (10 mg kg-1 body weight) and maintained by continuous inhalation of isoflurane-oxygen mixture (1-2%). GFP imaging was performed to confirm the development of cancer. Two contralateral burr-holes were made using a dental drill to allow for MPM imaging.Four weeks after cancer cell inoculation, the mice underwent MPM imaging. The mice were anesthetized by intraperitoneal injection of ketamine (100 mg kgAn electron-multiplying CCD (EMCCD), equipped with a zoom lens and a long-pass filter (≥496 nm), was used to image the GFP signal from the mouse brain cancer model. A mercury lamp together with a 485/20 nm band-pass filter was employed to provide excitation light.Figure 1). Evaluating two-photon fluorescence (TPF) and second harmonic generation (SHG) images of such tissue collected with the MPM system, we found that cellular and subcellular structures are clearly visible in the FAD and NADH channels , and strong SHG signals from blood vessel walls and collagen deposition  are evident. After acquisition of label-free MPM images, the tissue was labeled with DNA dye DRAQ5 for comparison. The same structural landmarks  are found in the label-free image , the DRAQ5-stained image , and the co-located conventional formalin-fixed, paraffin-embedded (FFPE) hematoxylin and eosin (H&E) image . The dark character of nuclei on MPM was seen in all brain regions examined. Nuclear detail in the NADH channel is seen more clearly at higher magnification , in which the dark nuclei correspond exactly to the red cell nuclei in the overlaid DRAQ5-stained image . The dark character of nuclei on label-free MPM images is presumably due to absence of FAD and NADH in this structure. TPF/SHG mosaic images can be created by automated stitching of individual TPF/SHG tiles to obtain a larger field of view . Features critical for pathologic evaluation such as nuclear size and nuclear morphology are readily appreciated in fresh and unlabeled brain tissue viewed with MPM.For the initial characterization of the ability of our system to resolve subcellular features critical for histopathologic interpretation, we assessed fresh unstained tissue from high-grade glioma  of the cortex with a transition from gray matter (left) to white matter (right). The two regions are readily distinguished by the presence (in gray matter) or absence (in white matter) of larger cells (neurons). The human neocortex is conventionally divided into six layers Figure ; representative higher-magnification images from each layer are shown in Figure S3). Moreover, the areas within the dotted box highlight that microstructural features of each layer in the MPM image are in good agreement with those in the corresponding co-located FFPE H&E micrograph. Each layer consists of a characteristic distribution of neuronal sizes, shapes, and densities. The large nuclei, often surrounded by yellow granules, are identifiable as neurons . The granules in the neuronal somata appear to be similar to lipofuscin, emitting in the NADH and FAD channels and thus appearing yellow Figure , Figure S4). Compared with gray matter, subcortical white matter  reveals distinct histologic features, with dense regions of axon matrix (indicated by pink arrowhead and dotted dashed line) that appear as green, roughly linear structures, and interspersed small yellow lipofuscin-like granules, which may arise from myelin membrane remnants Figure S5). The results show that MPM is able to provide detailed visualization of the microstructure of human brain.To further test the ability of the system to characterize brain structure cell-by-cell, we next assessed freshly excised unstained human non-cancerous frontal cortex from autopsy. Figure 3 shows an example of unfixed, unlabeled tissue TPF/SHG images and co-located H&E histology obtained from a high-grade glioma. MPM images clearly demonstrate the increased cellularity, showing densely packed individual cancer cells. Cells with an enlarged or irregular nucleus can be identified as cancer cells . The zoomed-in view  highlights pleomorphism in the form of irregular, enlarged nuclei. The ability to assess the morphology of individual cells is critical for histology-caliber assessment of the presence or absence of infiltrating glioma in a given region.For brain cancers, the World Health Organization (WHO) classification scheme is most commonly used Figure S6). Moreover, compared with non-cancerous tissues , far fewer yellow lipofuscin-like granules are observed in the cancerous tissue, which may reflect less accumulation of lipofuscin in the newly grown brain cancer cells. This distinction is less readily seen in conventional FFPE H&E micrographs and could provide additional diagnostic information for visual assessment by expert histopathologists.In additional to auto-fluorescent NADH and FAD, aged brain tissues contain the 'aging pigment' lipofuscin Figure 4 details TPF/SHG images of the appearance of vascularization along with necrosis and collagen deposition in freshly excised unstained high-grade glioma tissue. In the necrotic area , cell outlines are still visible ('coagulative necrosis'), and nuclei appear smaller or absent, similar to their appearance on H&E. Collagen in the adventitia of larger blood vessels in the high-grade glioma is well visualized . Figure  and 4E highlight collagen deposition in the extracellular matrix, which show dense and clustered blue SHG signals over a larger area. By highlighting collagen either from the basement membrane of blood vessels or from direct deposition, and demonstrating changes in necrotic cells, MPM is well suited for revealing diagnostic features of glioblastoma. Table S2 comparatively summarizes the key diagnostic histologic features of non-cancerous and cancerous brain tissues in the MPM and H&E images.Additional hallmarks of glioblastoma are the presence of tortuous and disorganized blood vessels (termed microvascular proliferation) Ex vivo this would obviate the need for tissue flatness during imaging of fresh, fixed, or fixed/embedded tissues, and in vivo it would permit assessment of multiple depths without moving the probe. The penetration depth with a given wavelength and incident power is highly dependent on the type of tissue, and it was found that a deeper MPM imaging depth could be achieved in non-cancerous gray matter and high-grade glioma tissues than in non-cancerous white matter . This result is consistent with our previous finding that glioma tissue has significantly lower optical attenuation when compared with non-cancerous white matter Moreover, MPM can acquire images at various depths, which is analogous to traditional serial sectioning from a paraffin block.  Figure S. This reInterpretation of histopathological images require a highly trained pathologist and is often time-intensive, and subject to inter-observer variability. Recently, machine-learning based methods for diagnostic classification have been increasingly applied to microscopy images 2, the size of a single unstitched MPM FOV) within a mosaic. This network makes predictions on an individual MPM FOV level. Our result shows that the trained network could predict gray versus white matter at the MPM FOV level with a 94% accuracy. Figure  shows the mosaic TPF/SHG image of a fresh non-cancerous human cortical specimen including gray matter and white matter. The gray matter, gray-white junction, and white matter can be clearly identified based on the probability heatmap  generated by ResNet 1. The second ResNet (ResNet 2) was trained to distinguish cancerous versus non-cancerous brain tissues. Our result shows that the trained ResNet 2 could make this distinction with a 92% accuracy at the individual MPM FOV level. At the mosaic level of each specimen, classification can be achieved based on the assessment of individual FOVs within the given mosaic. An individual FOV is categorized as cancer when the probability predicted by the trained ResNet 2 is more than 50%. At the mosaic/specimen level, the entire specimen is classified as cancer when greater than 50% of the FOVs within the mosaic are classed as cancer. As an example, ResNet 2 correctly assessed 154 out of 163 MPM FOVs from specimen #19-1 as cancer, and the remaining 9 FOVs as normal, so the specimen is classified as cancer. By using this approach, classification of MPM mosaic images at the specimen level as cancerous or non-cancerous achieved 100% accuracy .We proposed and trained two ResNet models. The first one (ResNet 1) was trained to distinguish gray matter and white matter. The corresponding H&E histology served as the ground truth. Training, validation, and testing used each individual image  with dark nuclei and angular cell bodies containing lipofuscin-like granules in non-cancerous gray matter . White matter axons appear as green nearly linear structures (indicated by pink arrowhead and dashed line) and smaller fluorescent deposits are found in the non-cancerous white matter . Figure  shows a clear border between white and gray matter (indicated by the dashed line). Large blood vessels (red arrowheads) and cancer cells (yellow arrowheads) with dark nuclei and fewer yellow lipofuscin-like granules can be found in high-grade glioma tissue . Cell outlines are still visible, and nuclei appear absent in the necrotic area of high-grade glioma . Although the images presented in Figure 6 are averaged over twenty frames, the corresponding single-frame images  capture similar structural details, demonstrating the excellent detection sensitivity of the multiphoton endomicroscope. Use of ex vivo samples is critical for development of the system. For a proof-of-concept demonstration, we conducted in vivo MPM imaging on a mouse model implanted with GFP-labeled cells from GBM1A, a patient-derived cell line Figure , MPM permits in vivo identification of glioma cells with enlarged nuclei , which were confirmed by GFP fluorescence  to be cancerous.The results described above demonstrate that MPM can be used for label-free, non-destructive and rapid imaging of human brain tissues with subcellular histological detail. The approach is thus suitable to guide the neurosurgeon intraoperatively and in real time by providing neuropathological information on the surgical 'margin' to safely maximize glioma resection while sparing adjacent heathy brain tissue. Our group previously reported an ultracompact, fiber-optic nonlinear endomicroscope for label-free functional histological imaging in vivo imaging can be possible without need for tissue removal, sectioning or processing. Currently, the frame rate of the endomicroscope is ~2 frames/sec, which continues to improve, permitting rapid assessment The most commonly used method to generate diagnostic quality tissue sections is fixation in formalin, followed by paraffin infiltration, sectioning, and staining. Since this tissue preparation process requires at a minimum many hours and often in practice several days, alternative histology techniques including frozen sectioning and smear preparations are used when intraoperative assessment is required. These methods are far faster, requiring only a few tens of minutes from the time of tissue removal to viewability on the microscope. However a) the fastest turnaround time for a tissue sample to be taken from the operating room to the histology laboratory for freezing, cutting, staining and assessment is approximately 10 minutes under optimal conditions, which is a lengthy delay for clinical decision making during a surgical procedure, b) the freezing process may introduce geometric distortion, causing significant image artifacts Figure 3) and our clear identification of necrosis  will enable the pathologist using MPM to visualize the tissue to effectively distinguish active tumor from treatment effect. Such ability could in principle be used for identification other types of lesions  or indeed of any microscopic tissue pattern. Although we are optimistic that our resolution  will permit identification of mitotic figures, further testing is needed to confirm. Furthermore, with MPM, the operator can view in real time tissue microarchitecture over different regions of interest in three dimensions simply by panning and adjusting the imaging beam focus, which will likely further improve the diagnostic efficiency, sensitivity and accuracy.Our study demonstrates that MPM is able to capture essential diagnostic hallmarks for brain cancer identification and classification. Previous studies have demonstrated that that multiphoton excitation of autofluorescence hold the potential to distinguish tumor tissue and normal brain based on the intensity and lifetime of fluorescence in vivo) NADH and FAD are often sequentially excited at 700-750 nm and 850-920 nm, respectively, in order to obtain cleaner (or less mixed) fluorescence signals. This sequential excitation at different wavelengths, however, would lead to a lower imaging frame rate, and more importantly, it would become more difficult in ensuring pixel-level registration between the NADH and FAD channels in the case of dynamic samples  level. We hypothesize that the diagnostic accuracy would be improved by increasing the sample size.Machine learning-based diagnosis may be able to ultimately reduce inter-observer variability and support real-time standardized intraoperative pathology. We trained and implemented a ResNet model for rapid, automated intraoperative classification of MPM images of fresh and unstained brain tissues. Our preliminary results demonstrated that MPM-based machine-learning methods can be used for discrimination of non-cancerous and cancerous tissues. However, because of the restricted sample size, some MPM FOVs may have unique numbers, sizes, distributions, and morphologies of cell bodies, nuclei, and blood vessels that are beyond the general features included in the training set, and thus the diagnostic accuracy was only 92% at the FOV  or a dedicated laser operating an efficient ablation wavelength  in vivo to reveal cellular metabolic/redox status given by the ratio of FAD and NADH fluorescence of biological tissue Several compact MPM platforms have been recently developed to facilitate the translation of MPM to in vivo optical histologic imaging of brain cancer. The current FOV diameter is roughly 140 microns and the imaging depth is about 200 microns. As a result, it is not possible to scan a large tissue area/volume with one FOV. For future clinical use, multiphoton endomicroscopy can be robotically co-registered with a surgical microscope or integrated with other wide-field imaging technologies for complementary image guidance over a large area of the surgical cavity. The imaging speed and FOV of the endomicroscopy technology are under active investigation and expected to be improved significantly in the near future to meet needs for performing real-time intra-operative optical histology in vivo. Use during surgery in the fashion we envision would permit diagnosis to be integrated more closely with treatment than generally possible. When ultimately combined with MRI-based techniques for localization Multiphoton endomicroscopy represents a promising pathway for Supplementary figures and tables.Click here for additional data file.


Quantifying mineral block supplement intake by individual beef cattle is a challenging task but may enable improved efficiency of supplement use particularly in a grazed system. Estimating time spent licking when cattle access the mineral block supplement can be useful for predicting intake on an individual basis. The advancement of sensor technology has facilitated collection of individual data associated with ingestive behaviours such as feeding and licking duration. This experiment was intended to investigate the effectiveness of wearable tri-axial accelerometers fitted on both neck-collar and ear-tag to identify the licking behaviour of beef cattle by distinguishing it from eating, standing and lying behaviours. The capability of tri-axial accelerometers to classify licking behaviour in beef cattle revealed in this study would offer the possibility of measuring time spent licking and further developing a practical method of estimating mineral block supplement intake by individual grazing cattle.k-nearest neighbour [kNN]) were employed to develop behaviour classification models using three different ethograms: (1) licking vs. eating vs. standing vs. lying; (2) licking vs. eating vs. inactive; and (3) licking vs. non-licking. Activities were video-recorded from 1000 to 1600 h daily when access to supplement was provided. The RF algorithm exhibited a superior performance in all ethograms across the two deployment modes with an overall accuracy ranging from 88% to 98%. The neck-collar accelerometers had a better performance than the ear-tag accelerometers across all ethograms with sensitivity and positive predictive value (PPV) ranging from 95% to 99% and 91% to 96%, respectively. Overall, the tri-axial accelerometer was capable of identifying licking behaviour of beef cattle in a controlled environment. Further research is required to test the model under actual grazing conditions.Identifying the licking behaviour in beef cattle may provide a means to measure time spent licking for estimating individual block supplement intake. This study aimed to determine the effectiveness of tri-axial accelerometers deployed in a neck-collar and an ear-tag, to characterise the licking behaviour of beef cattle in individual pens. Four, 2-year-old Angus steers weighing 368 ± 9.3 kg (mean ± SD) were used in a 14-day study. Four machine learning (ML) algorithms (decision trees [DT], random forest [RF], support vector machine [SVM] and  The smartphones were placed on tripods and positioned 75 cm above the floor in front of the block supplements outside the pens. Video resolution for all phones was set at 1080 p (1920 × 1080 pixels) quality. Each smartphone was equipped with a 32 GB microSD card (SanDiskLicking vs. eating vs. standing vs. lying.Licking vs. eating vs. inactive (standing + lying).Licking vs. non-licking (eating + standing + lying).Each video file was observed and annotated using Sheep Movement Classification Interface software  to generate annotated daily files for each steer in a .csv file format. Discrete events of individual behaviours were annotated to reflect the mutually exclusive behaviours of licking, eating, standing and lying . The sofAccelerometer data were collected continuously for seven days and processed using the R statistics environment . The aveX-, Y-, and Z-axes values and behaviour annotations were further discretised into a 10 s-time interval or windows size (epoch). Thus, there were 250 records required to create one row  in each new dataset [X,Y,Z), maximum , average , and standard deviation  values of X-, Y-, and Z-axis, magnitude (MAG), movement variation (MVA), signal magnitude area (SMA), entropy (ENT), energy (ENG), pitch (PIT), roll (ROL) and inclination (INC). Mathematical formulas for these features are shown in The two datasets that contained  dataset . The 10- dataset  who indiEach behaviour dataset for licking, eating, standing, and lying from all cattle was proportionally split into 70% (training) and 30% (testing) in the R statistic environment ,36 usingk-nearest neighbour (kNN); and (4) support vector machine (SVM). The DT algorithm constructs a group of binary trees based on the values of selected variables. It recursively splits the dataset into subsets with consistent values of the predictor variables [Four machine learning (ML) algorithms were employed to develop behaviour classification models: (1) decision trees (DT); (2) random forest (RF); (3) ariables . The RF ariables . The kNNariables . The SVMariables . These aariables ,42,44,45mtry) was set at 5  and the number of trees (ntree) was set at 500. In RF and SVM algorithms, all features were used as prediction variables for developing the model while only the top three important features were selected for DT and kNN algorithms, respectively. Both DT and kNN are simple algorithms and only require a small number (3–5) of the top important features for model development based on their mean Gini values. Use of the top important features in the DT algorithm reduces the redundancies of the model development [The “randomForest” and “varImpPlot” function of the “randomForest” package  were useelopment . For theelopment . Previouelopment , Alvarenelopment , and Sheelopment . Analysielopment  within tThe behaviour classification models developed using the training dataset for each ML algorithm across the three ethograms in both deployment modes were independently applied to the testing dataset for validating their performance. The confusion matrix for each ML model prediction was computed using the “caret” package . To detehaviours . PerformThe inter-rated reliability test using Cohen’s kappa coefficients was likewise applied to select the best deployment for capturing values of the feature’s relative importance. The kappa statistic signifies the extent to which collection of the data represent the variables measured . This woX-, Y-, and Z-axes sampled over a 60 s of observation from the neck-collar and ear-tag accelerometers for licking, eating, standing, and lying behaviours are depicted in n = 538), 26.2% (n = 618), 25.9%  and 25.1% (n = 594) for neck-collar and 26.2% (n = 594), 26.4% (n = 600), 25.5% (n = 580), and 21.9% (n = 497) for ear-tag deployment modes. The failure of the sensors to capture the acceleration signals has contributed to the unequal number of datapoints (samples) between neck-collar and ear-tag accelerometers.No aberrant behaviours resulting from accelerometer deployments were observed in any cattle throughout the experiment. The acceleration signals of the According to the mean Gini values, MVA and SDx were the first and second most important features for distinguishing licking from other observed behaviours across the three ethograms within both neck-collar and ear-tag deployment modes except for ethogram 3 of the neck-collar deployment . The disThe overall performance of ML algorithms in predicting behaviours of beef cattle using the testing dataset across the three different ethograms within the neck-collar and ear-tag accelerometers is presented in The performances of the RF algorithm model in classifying licking behaviour of beef cattle are described in Dependency upon integration of radio frequency identification (RFID) and automatic feeding systems to remotely monitor supplement intake of beef cattle has prompted the use of more efficient and accurate technologies for the collection of individual information in larger herds without disrupting their daily routines and natural behaviours. Tri-axial accelerometers have the capability of accurately differentiating mutually-exclusive behaviours of grazing ruminants , and thiX were the top two features used to classify the licking behaviours of beef cattle by the ML algorithms employed on the tri-axial accelerometer data. This trend was consistent across five out of six ethograms (3 for each deployment mode). Gao et al. [X-, Y- and Z-axes values while SDX represents distribution of the signal within the X-axis values. Hence, the differentiation of X-axis values was evidence of apparent dorso-ventral moving direction recorded by neck-collar and ear-tag accelerometers when the event changed from licking to other behaviours. A recent study using an ear-tag accelerometer configured at 12.5 Hz with a 10 s time interval reported MVA and SDX as the two most important features to classify grazing, lying, standing and walking events of sheep [X in our study indicated that the ML algorithms discriminated the behaviours based on the difference of movement patterns between behaviours.In this present study, MVA and SDo et al.  explaineof sheep . The preZ was the first important feature in ethogram 3 followed by SMA and MAXZ and is the most consistent feature within the top three features in all ethograms. González et al. [Z-axis values in the present study signified that the neck-collar accelerometers captured the distinction of longitudinal (anterior-posterior) movements of the head when the cattle were licking. During licking the head is lowered and as the tongue protrudes, the head moves back and forth in the longitudinal plane. This might relate to the high accuracy of the neck-collar accelerometer in a situation where similar head orientation was captured from licking and biting behaviours. Also, SMA is a suitable measure to differentiate static and dynamic activities from the accelerometer signals [For the neck-collar deployment, AVGz et al.  found th signals ,19,54. HBy using random forest ML algorithm, two deployment modes (neck-collar and ear-tag) of tri-axial accelerometers were capable of classifying licking by contrast with eating, standing, and lying behaviours with high accuracy >90%; . The behThe lower performance of the DT algorithm in this present study might be because of over-fitting the model and the hierarchical partitioning of each tree that reduces (1) the ability to categorise relationship between variables and (2) the effective sample sizes causing a difficulty in identifying rules and trends in each subsample . It shouIn this current study, the behaviour classification model for the neck-collar tri-axial accelerometer was more accurate than the ear-tag tri-axial accelerometer, with Cohen’s Kappa coefficient for the neck-collar deployment model being also superior to the ear-tag deployment. The substantial agreement between actual and model-predicted behaviour was higher in the present study than studies with dairy cows by Bikker et al.  and dairApart from the lower performance of ear-tag based accelerometers compared to the neck-collar accelerometers, the practicalities of adoption in commercial contexts favour ear-attached sensors. The smaller size makes it less invasive to the cattle and costs less to implement per individual. Therefore, classification algorithms must be capable of dealing with interdependent dynamic accelerations. The potential of an ear-tag based sensor to accurately discriminate licking would be an improvement enabling measuring mineral block supplement intake based on time spent licking by individual cattle. It also offers versatility and is an efficient way to monitor and harness individual information particularly in an extensive environment. Advancements in remote monitoring systems using internet technology are required to remotely transmit the data from the ear-tag sensor to a central database system for improving production efficiency by reducing time of mustering for individual data collection. However, in commercial systems where cattle are already fitted with neck-collars for other purposes, measuring licking with neck-collar accelerometers would be ideal due to the greater accuracy with this deployment.The behaviour classification model developed by random forest ML algorithm for both deployment modes performed well  compared to SVM, kNN and DT algorithms, with the neck-collar deployment mode performing slightly better in classifying licking behaviour within three different ethograms than the ear-tag deployment mode. This is partly because of the firm attachment of the sensor to the collar generating consistent orientation and acceleration signals. Movement of the ear independently from the body might also be responsible for lowering sensitivity and PPV of the model. For commercial use in large herds for grazing systems, however, the ear-tag deployment mode is more feasible and likely to be more cost efficient than the neck-collar deployment as current advancement in electronic ear tags for cattle allows attachment of automatic devices. This current study confirms that the accelerometer is a promising technology to differentiate between licking and other behaviours and provides important research evidence to continue applying this methodology to a paddock environment and to test the model performance in a commercial situation.


The microenvironments formed by cortical (c) and medullary (m) thymic epithelial cells (TECs) play a non-redundant role in the generation of functionally diverse and self-tolerant T cells. The role of TECs during the first weeks of the murine postnatal life is particularly challenging due to the significant augment in T cell production. Here, we critically review recent studies centered on the timely coordination between the expansion and maturation of TECs during this period and their specialized role in T cell development and selection. We further discuss how aging impacts on the pool of TEC progenitors and maintenance of functionally thymic epithelial microenvironments, and the implications of these chances in the capacity of the thymus to sustain regular thymopoiesis throughout life. The current pandemic caused by the SARS-CoV-2 virus underscores the importance of maintaining a pool of immunologically competent T cells, which are capable of responding to virtually any new foreign threats while tolerant to the host own tissues. The establishment of a diverse T cell receptor (TCR) repertoire arises from the random recombination of V(D)J gene segments during T cell development in the thymus. Yet, the arbitrariness underlying this process can also produce autoreactive T lymphocytes. The thymus has developed several control mechanisms to simultaneously establish T cell immunity against non-self elements and impose self-tolerance. Particularly important in the choreography of T cell selection are thymic epithelial cells (TECs), which represent a key component of the thymic stromal microenvironment. TECs are typically subdivided into functionally distinct cortical (cTEC) and medullary (mTEC) lineages . While cThe initiation of TEC development coincides with the onset of thymus organogenesis, which starts around day 9-10 of the murine embryonic gestation (E9-10) . The expvia transgenic expression of Foxn1 or Cyclin D1, increases T cell generation , including mTEC-restricted SSEA-1+ and podoplanin+ (PDPN) mTEPs , 18. Fatt thymus . Given tt thymus , we infe−MHIIloSca-1+  analysis have also contributed to our understanding of the heterogeneity and dynamic of TEC progenitors. This approach has emerged as a new unbiased method to identify novel subsets, providing a valuable platform to analyze their developmental trajectories and determine their relationships with progenitor subsets identified by conventional methodologies. In this regard, new clusters termed “pre-Aire mTEC 1 and 2”  appear tloSca-1+  and MHCI1+Plet1+  TECs. Sial stage , 20. TogThe aforementioned studies underscore that the period between birth and early adulthood is a time of intense alterations in TEC microenvironments, which prepares them to the highly demand role of choreographing the selection of growing number of T cell precursors. In this sense, it is remarkable to appreciate the synchronous coordination between TEC differentiation and the requisites imposed by T cell development. Yet, the erosion of the pool of TEC progenitors seem to accompany the generation of specialized subsets with key roles in tolerance induction. We reason that an in-depth molecular analysis of TEC differentiation during early postnatal may provide insights on how TEC niches are maintained, and can be repaired in the aged thymus. Despite recent advances, it remains unclear how changes in the bioavailability of TEPs impact on the maintenance of TEC microenvironment across life, and ultimately on thymic output. Another unexplored area pertains to the physiological causes underlying the presumed age-dependent decrease and/or senescence of TEPs. Knowledge in these areas will not only permit to comprehend the basic principles that governs thymic function, but also target pathways for the treatment of disorders coupled to dysfunctional thymic/T cell responses.NA and RP wrote the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by a starting grant from the European Research Council (ERC) under the project 637843 and by FEDER - Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 - Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT - Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project POCI-01-0145-FEDER-029129 (PTDC/MED-IMU/29129/2017) and PTDC/MED-IMU/1416/2020. NA is supported by the FCT program “Scientific Employment Stimulus” and RP by a FCT PhD fellowship.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Polymers have always played a critical role in the development of novel drug delivery systems by providing the sustained, controlled and targeted release of both hydrophobic and hydrophilic drugs. Among the different polymers, polyamides or poly(amino acid)s exhibit distinct features such as good biocompatibility, slow degradability and flexible physicochemical modification. The degradation rates of poly(amino acid)s are influenced by the hydrophilicity of the amino acids that make up the polymer. Poly(amino acid)s are extensively used in the formulation of chemotherapeutics to achieve selective delivery for an appropriate duration of time in order to lessen the drug-related side effects and increase the anti-tumor efficacy. This review highlights various poly(amino acid) polymers used in drug delivery along with new developments in their utility. A thorough discussion on anticancer agents incorporated into poly(amino acid) micellar systems that are under clinical evaluation is included. Novel polymer-based drug delivery systems are being designed in order to alter the physicochemical and pharmacokinetic properties of drug molecules and to deliver them effectively in a controlled manner. Polymers have garnered attention in the evolution of drug delivery technologies for both water-soluble and hydrophobic drug molecules . The altIn the past, active ingredients were identified and extracted from plant material for the treatment of diseases. However, with the advancements in synthetic chemistry, new drugs for treatment of a particular disease are being introduced through high-throughput screening (HTS). Using this technique, it is possible to test huge libraries of chemicals for their ability to treat the disease. Nonetheless, the full potential of drug molecules can only be accomplished with well-designed delivery systems. The chief hurdle confronting the drug delivery scientists is the design of novel ways to deliver active pharmaceutical ingredients to the target site. Developments in polymer chemistry created new opportunities to deliver drugs near to the target region in a required fashion. At the beginning of 1970s, polymers composed of lactic acid were first employed for drug delivery. The release of the drug from polymers occurs in a cyclic fashion and the release can be further triggered by ambient conditions near the target site. Polymers utilized in drug delivery should bioresorbable, biocompatible and degrade in the body . NeverthPolyamide is a polymer with repeating units linked by amide bonds, while a group of small polyamides containing multiple amino acids of the same types linked through amide bonds is often referred to as poly(amino acid)s. Polyamide occurs naturally or can be made synthetically  4]. Nat. Nat4]. Polymers based on amino acid monomers have gained significant attention in drug delivery. Natural amide-based polymers such as gelatin and albumin are widely used in the preparation of biodegradable microcapsules and microspheres . Synthetg < 100 °C) with a very low water solubility, and hydrolysis of the polymer results in tyrosine and diols with excellent tissue compatibility , is an important member of platinum-containing anticancer drugs and is used in treating various cancers, including malignancies of lungs, GIT and genitourinary tracts ,106,107.− to -COO− in the side chain of P(Glu) is the key driving force in the formation of the cisplatin polymeric micellar complex. The polymeric micellar complex has a particle size of 30 nm. The complex was non-dissociating upon dilution and the critical micellar concentration value was found to be 5 × 10−7 [The micellar formulation of NC-6004 is made up of polyethylene glycol (PEG) in the corona (outer shell) of micelles and the inner core comprises of a coordinate complex of poly(glutamic acid) (P(Glu)) and cisplatin D. The li5 × 10−7 . The dru5 × 10−7 . Further5 × 10−7 . The com5 × 10−7 ,47.max and AUC0–t values were found to be higher for NC-6004 than cisplatin alone. The results of the pharmacokinetic studies are shown in the max 2.5 folds higher for NC-6004 compared to cisplatin.The pharmacokinetic evaluation of NC-6004 in animals showed that NC-6004 was retained in the blood for a long duration as compared to cisplatin . The Cma50 were about 6–15 fold higher than those for cisplatin. The decreased cytotoxicity of the micellar complex was predominately due to the sustained release of cisplatin from the complex [The anti-tumor activity studies performed in BALB/c nude mice implanted with MKN-45 cell line indicated that the rate of tumor growth was decreased for both cisplatin and NC-6004. The NC-6004 administration equivalent to cisplatin had no significant difference in the rate of tumor growth. The time course of rate of change in body weight for NC-6004 showed no change, while cisplatin showed a significant decrease in body weight, which indicated the superiority of NC-6004 in treating tumors. The in vitro cytotoxicity studies of NC-6004 performed on human tumor cells form bladder, colon, lung, gastric and breast cancer tissues, suggested that the IC complex .max were 65 and 8 fold higher than that of cisplatin. The disposition studies revealed a higher distribution in the liver and spleen (RES system) and were found to be eliminated via kidneys. Improved therapeutic attributes in terms of better tissue distribution and accumulation at target tissues, and reduced toxicity profiles all resulted in an increased interest to develop into a clinically viable formulation, thus facilitating the compound to enter clinical studies.The administration of cisplatin at 10 mg/kg levels in rats resulted in deaths of about 25% of animals. However, no deaths occurred in the case of cisplatin polymeric micelle, NC-6004. The administration of NC-6004 showed no histopathological change on the tubular epithelium cell-lining of kidneys upon light microscopy studies, whereas cisplatin showed tubular dilation with flattening of tubular epithelium cell-lining of the kidney. The neurotoxicity assessment studies of NC-6004 showed no delay in sensory conduction velocities (SNCV) as compared with cisplatin. The pharmacokinetic studies of NC-6004 compared to cisplatin showed that the NC-6004 micellar complex was circulating in the plasma for a prolonged period of time ,93, with2) showed that the treatment is well-tolerated with minimum nephrotoxicity. However, NC-6004 showed frequent hypersensitivity reactions than cisplatin at all dose levels. From these studies the maximum-tolerated dose and recommended dose for phase II trials were fixed to 120 mg/m2 and 90 mg/m2, respectively. The PK studies showed a longer circulation time in the blood for NC-6004 with a linear pharmacokinetic profile. This shows an inferior cisplatin-related toxicity and superior anti-tumor activity of NC-6004 compared to cisplatin [2 for over 1 h on day 1. Pembrolizumab (200 mg) was administered intravenously over 30 min on day 1 every 3 weeks. The maximum-tolerated dose and recommended phase 2 dose was reported to be 135 mg/m2, which is more than the regular cisplatin doses in the head and neck squamous cell carcinoma treatment. The neurotoxicity or nephrotoxicity of NC-6004 was significantly lower than the conventional cisplatin regimen with a decent safety profile [Phase I clinical trials of NC-6004 involving intravenous administration of the drug within one hour every 3 weeks (dose range: 10–120 mg/misplatin . Recentl profile .w/w). In the aqueous medium, NC-4016 is assembled as a result of the complex formation between -COOH groups in P(Glu) and platinum in oxaliplatin. In 2017, a dose-escalation phase I of NC-4016 in 34 patients suffering from advanced solid tumors or lymphoma was completed. Varying doses of 15–80 mg/m2 every 3 weeks were administered; however, no results have been disclosed so far [2. The phase II study of NC-6300 is underway to assess its tolerability and anti-tumor activity in soft tissue sarcoma patients.NC-4016 is oxaliplatin-loaded in PEG-b-poly(l-glutamic acid) micelles with a diameter of 40 nm and drug of 32%  in the polymer backbone [The contributions of polymer science to the evolving field of drug delivery have been very significant, and there are many examinations underway. Poly(amino acid) polymers have been around for quite some time in drug delivery due to their similarity to proteins and highly biocompatible degradation products. Though poly(amino acid) polymers are hydrophilic, they are easy to alter by linking different functionalities -poly(benzyl aspartate-69) block copolymer micelles [The major hurdle that delays the clinical translation of polymeric micelles is their inability to retain integrity in the blood following intravenous injection. Polymeric micelles within the blood tend to remain either in the assembled state or as mesostructures comprising of macromolecule unimers . The pH micelles . Studiesmicelles .Despite the attractive properties of polymeric micelles in drug delivery, drug entrapment via simple physical entrapment may not result in sufficient stability of drug-loaded micelles in vivo. The presence of multiple interactions such as the hydrophobic/electrostatic interaction may provide better in vivo stability to drug-loaded micelles. Various other strategies such as covalent cross-linking of the micellar core and coating of drug-loaded micelles have been reported in the literature to overcome challenges faced by polymeric micelles. Covalent core cross-linking of the micelles’ core has garnered considerable attention in the production of stable polymeric micelles for drug delivery applications. In a study, the ionic cores of phenylalanine-linked poly(ethylene glycol)-b-poly(L-glutamic acid) in the presence of calcium ions were chemically cross-linked with cystamine. This study demonstrated that hydrophobic moieties in the ionic cross-linked cores of nanogels greatly affected the release of doxorubicin at simulated lysosomal acidic pH and showed an improved anti-tumor activity in an ovarian tumor xenograft mouse model . The othDrugs are normally administrated orally, as tablets, capsules, powders or liquid forms. As time has advanced the need for having delivery systems that could sustain the drug release at the target site has become apparent. During the last couple of decades, polymer science has played a vital role in the design of novel drug delivery systems. Most polymers do not have the natural ability to function optimally as drug delivery devices and this can be achieved by innovative modifications of their physicochemical and physicomechanical properties during synthesis. From the above discussion it is quite obvious that polyamides or poly(amino acids) play a prominent role in the delivery of drugs. Poly(amino acids) are simple and highly adaptable polymers with protein-like properties. They are ideal for drug/nucleic acid delivery and provide suitable drug targeting, release characteristics and bypass multidrug resistance (MDR) factors upon chemical modifications. Several polyamide-based delivery systems were designed to augment the therapeutic properties of drugs and make them more safe and effective in disease treatment. The flexible nature of poly(amino acids) helps modify micellar structures readily to incorporate new features based on the information revealed from clinical trials. Such modifications would result in the design of novel formulations with better performance. Since the last two decades, polyamides have been widely investigated for the delivery of bioactive agents; however, their extensive use is limited by poor control over the release rate of the drug, antigenic potentials and the requirement of enzymes for degradation in the body. With several poly(amino acid)-based micelles in clinical trials, it is very likely that poly(amino acid)s will play a growing role as high performance materials in the medical field.


Fault signals in high-voltage (HV) power plant assets are captured using the electromagnetic interference (EMI) technique. The extracted EMI signals are taken under different conditions, introducing varying noise levels to the signals. The aim of this work is to address the varying noise levels found in captured EMI fault signals, using a deep-residual-shrinkage-network (DRSN) that implements shrinkage methods with learned thresholds to carry out de-noising for classification, along with a time-frequency signal decomposition method for feature engineering of raw time-series signals. The approach will be to train and validate several alternative DRSN architectures with previously expertly labeled EMI fault signals, with architectures then being tested on previously unseen data, the signals used will firstly be de-noised and a controlled amount of noise will be added to the signals at various levels. DRSN architectures are assessed based on their testing accuracy in the varying controlled noise levels. Results show DRSN architectures using the newly proposed residual-shrinkage-building-unit-2 (RSBU-2) to outperform the residual-shrinkage-building-unit-1 (RSBU-1) architectures in low signal-to-noise ratios. The findings show that implementing thresholding methods in noise environments provides attractive results and their methods prove to work well with real-world EMI fault signals, proving them to be sufficient for real-world EMI fault classification and condition monitoring. Power generation equipment and assets used in high-voltage (HV) power production plants are prone to developing faults; if these faults are undetected they can lead to breakdowns, in turn causing health and safety hazards, legal issues and incurring major losses such as fines and large-scale power outages . ConditiThe work in this study proposes an automated classification system to classify several EMI fault signals in various noise levels. The produced ML system will classify EMI fault signals by using data in the form of Stockwell (S) transform time-frequency (TF) decomposition matrices, introduced by , as inpuThe following sections of this paper will outline the methods used in this study and will be structured as follows; The feature engineering method used in this study is the S transform, introduced by ; this TFThis study uses the S transform to create TF decompositions of raw time-series EMI signals. The produced TF decomposition retains frequency dependant resolution from the original time-series signals. The retention of this frequency resolution proves to be highly desirable in regards to EMI fault signals from real-world assets due to their non-stationary characteristics. The S transform is selected due to its ability to detect low frequency components of a signal while also providing the ability to detect short lived high frequency components of the signal under analysis, a quality that is not prevalent in the STFT.As the signals used throughout this study are of discrete time nature, the derived TF transform must cohere to this. The discrete time S transform for these signals can be found by performing operations on the Fourier transform, the discrete Fourier transform Equation .(1)X[k]The S transform can then be found by carrying out operations on the Fourier transform from Equation . This isHowever, Equation  does notEquation  is used.The produced S transform then undergoes further processing to convert the imaginary product of Equation  to a modThresholding or shrinkage functions are primarily used for de-noising as observed in ,12. The The work carried out in this study will observe several thresholding methods; soft thresholding and hard thresholding , firm thThe soft thresholding method sets values within the given threshold ranges to zero and values outwith these ranges retain their original values minus the threshold parameter value. This relationship is shown in Equation , where γHard thresholding sets values within threshold ranges to zero and while values outwith the threshold ranges retain their original values; this relationship is shown in Equation .(5)δ(w)Originally introduced to overcome downfalls found in the soft and hard thresholding methods, it has a non-linear approach to values outwith its single thresholding parameter range. Values within the thresholding range are set to zero while values outwith this range are altered non-linearly, as shown in Equation .(6)δ(w)Firm thresholding consists of two thresholding parameters; this leads to the alteration of values in three ranges. Values within zero and the lower thresholding parameter are set to zero, values within the lower and upper threshold parameters are altered accordingly, and values above the upper threshold limit retain their original values. These relationships are outlined in Equation , where γH-trim thresholding is a method introduced to outperform soft thresholding, prior to the introduction of H-trim, firm thresholding was seen to outperform soft thresholding in electrocardiogram (ECG) signal denoising although firm thresholding had two thresholding parameters compared to H-trims single thresholding parameter. Equation  outlinesa, b, and c.QCT is a method introduced to overcome the weaknesses found in soft and hard thresholding. Overcoming the Gibbs phenomenon, outlined in , caused sholding . QCT conValues within the lower threshold range are set to zero, values within the lower and upper threshold range are assigned a quadratic curve value and finally values greater than the upper threshold range retain their original values. Given that Equation  can be fb and c with respect to the thresholding ranges, this is shown in Equations b and c wThe studies throughout this work implemented two neural-network architectures based upon the DRSN proposed in . ArchiteThis study builds upon the work in  by impleThe overall DRSN architecture used in this study can be found in cth neuron and it is scaled to the range cth neuron; this relationship is shown as the Sigmoid layer in Designed to learn a single thresholding parameter, the RSBU-1 architecture can be found in Equation , where zcth channel of the feature map h, w and c show the indexes of the height, width and channels of the feature map w.The discovered scaling parameter Equation , where hThe RSBU-1 architecture was used to find the single thresholding parameters for soft, hard, Garrote, and H-trim thresholding.The RSBU-2 architecture, found in w undergoes absolute GAP, the resultant one-dimensional vector is propagated to a two-layer FC network and the produced output of the FC network cth channel First, the feature map Equation  producinw shown as Equation .(16)λ 16 standard from , and impThe signals in the original dataset then underwent further pre-processing to produce 11 datasets with known noise levels, this was carried out by denoising the original signals using a symlet4 wavelet with a posterior median threshold rule from  implemenPrior to model ingestion, the signals in the dataset underwent feature engineering to become two-dimensional real-valued TF mappings, this decomposition was performed using the S transform outlined in The studies required the training of six different learned thresholding architectures and two conventional ML methods, a 50-layer ResNet model (ResNet50) and a 16-layer Visual Geometry Group (VGG16) model proposed in , along wained in , the L2 The mean test accuracies over the ten runs are provided by testing the thresholding architectures against corresponding known noise level data and the results can be found in The work in this study produced several thresholding methods to tackle the noisy environments in which HV condition monitoring, through EMI signal analysis, incurs. Providing methods that automate the denoising and classification process of EMI signals, the results of the work found the benefits of exploring novel thresholding methods in the field, how these thresholding methods can be used with ML to produce a non-expert dependant system to carry out denoising prior to classification, and the work produced an architecture to allow for the learning of several thresholding parameters when required for thresholding methods which require more than one learned parameter. The architecture proposed in this work showed significant improvements in current conventional ML classification methods.The systems produced in this work can be used to develop an adaptable condition monitoring software to reduce dependence on both HV condition monitoring experts and signal processing experts. Creating an adaptable and robust fault classification system will benefit users and producers of electricity by ensuring the prevention of devastating losses. The work from the study can be built upon by observing further thresholding methods and exposing these methods to assets in real-world settings.


Too little or too much sleep is associated with accelerated cognitive decline in older adults. However, sleep duration does not capture other sleep problems prevalent in older adults, such as difficulties with falling or staying asleep. Less is known about the impact of sleep quality on cognitive ageing, and if this relationship differs between England and China. Therefore, the aim of this study is to examine the relationship of self-reported sleep quality with cognitive performance and rate of change over 6-7 years follow-up in two nationally-representative samples of English and Chinese older adults. The primary outcome was a memory score (range 0-20), which was assessed using immediate and delayed 10-word recall tests in both cohorts. The results of bivariate descriptive analyses at baseline suggest there may be an inverted U-shaped association between sleep quality and memory in English older adults, and a positive dose-response association in Chinese older adults.


This approach allows to investigate wide range of interfacial properties, including surface morphology, internal cracks, mechanical properties, electronic/ionic conductivity and surface potential, with nanoscale resolution in-operando during the battery cycles as well as post-mortem.•PVD and novel BEXP methods were introduced to prepare battery powder materials as perfect specimens for nanoscale SPM characterization.•Various physical/chemical properties of battery materials can be probed on the as-prepared specimens under liquid electrolyte using in situ/operando SPM techniques.•Ex situ/post-mortem analyses based on the controlled environment multifunction SPM characterizations can be achieved in the BEXP polished degradation battery electrodes.The cathode/anode-electrolyte interfaces in lithium/sodium ion batteries act as the “gate” for the ion exchange between the solid electrode and liquid electrolyte. Understanding the interfacial properties of these solid-liquid interfaces is essential for better design high-performance lithium/sodium ion batteries. Here, we provide a novel method for studying solid-liquid interfacial properties of battery materials through combining physical vapor deposition (PVD) and beam-exit cross-sectional polishing (BEXP) followed by controlled environment multifunctional Scanning Probe Microscope (SPM). In this method, commercial battery materials can be either directly grown on the current collector substrates, or polished by obliqued Ar-ion beams to get a nanoscale flat surface which allows the multifunctional SPM to study sample directly in the liquid electrolyte or in protective oxygen/H  Specifications tablein situ SPM techniques have been used as a powerful tool for battery interfacial property characterization for many years, most previous researches merely employed electrochemical Atomic Force Microscope (EC-AFM) for operando nano-morphology observation in situ SPM for the correlation of the battery performance with its interfacial properties. To date, a range of advanced SPM techniques have been developed to operate in the liquid environment, which simultaneously enable the morphology, nanomechanical and nanoelectrical characterizations Although While such model SPM specimens can dramatically increase the characterization efficiency and image quality, improve test stability and reproducibility, the real battery electrode materials generally present more complex micro/nano particle morphology. As a result, it is difficult to obtain high resolution SPM images on micro/nano-size particles, especially in the liquid environment. In many cases, the interaction force of SPM tip and/or surface tension of liquid electrolyte could cause the detachment of particles from substrates. Many solutions, including substrate embedded single-particle (SEP) method 4Ti5O1222PVD method, including pulsed laser deposition (PLD), thermal/E beam evaporation and sputtering, are suitable for the deposition of metal oxide, such as Li+, minimally affecting physical and chemical properties of the material section. It should be noted that composite battery electrodes prepared by BEXP are not only suitable for ex-situ/post-mortem SPM characterization, but also suitable for detecting the actual failure sites in composite electrodes through in situ/operando measurements. With minimal topographic contrast of the section, it is essential that complementary material sensitive contrast could be used for mapping the evolutions of local nanomechanical properties operando and post-mortem conditions.The post-mortem SPM conducted in a controlled environment is also becoming a powerful technique for battery degradation research in situ EC-cell and demonstrations of different SPM measurements were provided in this paper.Here, we introduce the complementary methods, PVD and BEXP, combining with multifunctional SPM to study physio-chemical properties on the battery electrode-electrolyte interface. The preparation of SPM specimens, assibilation/structures of 2 cathode , Dielectric Electrostatic Force Microscopy (D-EFM) and Scanning Spreading Resistance Microscopy (SSRM), can be also performed in the Ar atmosphere in this system. In a nutshell, both the in situ (in the liquid electrolyte) and post-mortem (in Ar atmosphere) SPM measurements can be realized in such controlled-environment multifunctional SPM. The in situ SPM measurement can be carried out in the special designed EC-cell with a temperature controller from Bruker Company. in situ EC-cell. The materials and functions of each part are listed below:(1)Base: The nickel-plated tungsten alloy. Four flat-head screws to secure the base to the ring (body).(2)Ring (body): A 2205 Stainless Steel alloy.(3)Insert: Teflon® (PTFE). An insulating insert is used to electrically and chemically isolate the electrolyte from the EC cell body.(4)Bottom and top O-ring: Kalrez®. Used to provide a seal during the electrolyte injection.(5)“Glass” cover: A laser-cut fused silica cover. It is used to control electrolyte evaporation during the measurements.(6)PVDF insulator: Used to insulate the electrodes from the conductive body.(7)Gold-plated pogo pins: Used to connect the top of the sample to the cell base.(8)Electrodes: Working electrode (WE), reference electrode , counter electrode .The controlled environment SPM measurements are carried based on the Bruker Icon system in Ar environment protected glove box, as shown in In situ electrochemical cell is assembled in a glove box with the contents of moisture and oxygen less than 0.1 ppm:(1)Firstly, place the WE under investigation on the top of the nickel-plated tungsten cell base with electric contacted and fix it between the base and ring by four flat-head screws;(2)Then, insert the PVDF insulator inside the cell body, and put CE/RE strips on the top of the insulator without contacting with WE and cell body (as shown in (3)After the “glass” cover is fixed on the top of the cell through the retaining screws, the EC-cell assembly is completed;(4)At last, a suitable amount of electrolyte is added through the hole of the top glass cover to ensure the WE, RE and CE are completely saturated with the electrolyte, so that cell is fully prepared for the measurements.in situ/operando SPM is the only technique that can directly observe the SEI formation and mechanical properties in liquid electrolyte inside the functioning battery. However, it should be noted that the study of the SEI formation is usually hindered by the roughness of the sample surface and complex decomposition components of battery electrodes and electrolyte. As a result, most previous studies merely carried out the SEI measurements on the HOPG surface which has atomically flat surface forming the known organic/inorganic decomposition The solid-electrolyte interphase layer, which governs key battery electrochemical processes, has always been the most elusive component in lithium/sodium ion batteries. So far, the in situ observations in real space with nanoscale spatial resolution. As shown in the example in 2CO2) in sodium ion battery cathode in situ EC-UFM. Overall, combination of PVD and BEXP show a promising application ability for advanced SPM based nano-mechanical measurements.It should be pointed out that the PF-QNM measurement requires that the tip is mechanically stiff enough to generate the sample surface deformation. Thus, PF-QNM is well suitable for detecting the soft organic components (topmost SEI layer and adsorption molecules) formed on the surface of battery materials, but it is not appropriate for the studying of surface components which have high Young's module values, such as the inorganic oxidation products  vertical  homogeneity of the specimen; 2) stray current of the tip. The vertical homogeneity of specimen relates to the uniformity of specimens. The specimen prepared by PVD on the current collector surface shows uniform specimen thickness and pure sample composite, which is vital for the comparison of current signal difference derived from the material intrinsic transportation properties. As for the stray capacitance of the tip and stray current associated with electrochemical reactions from chemical impurities, these can be significantly reduced by using Bruker SECM tip 2 cathode are presented in Understanding the electronic/ionic transportation properties in battery materials is vitally important for improving battery high-rate performance. AFM based conductivity measurements are powerful techniques for nanometer-scale electrical characterization on a wide range of battery materials. Traditionally, these measurements have been categorized into two classes: Conductive AFM (CAFM), which covers the higher current range (sub-nA up to μA), and Tunneling AFM (TUNA), which covers the lower current range (sub-pA up to nA). As shown in 2 flow glove box, the change in potential distribution arising from battery charging was directly observed in the polished cross-section Controlled environment KPFM, together with conductive AFM, has been recognized as the two most widely used complementary nanoscale electrical characterization tools for battery researches. As shown in in situ/operando and ex situ SPM measurements in these model electrodes.To sum up, the PVD and BEXP methods can prepare model electrode with an atomic-flat surface without contaminations. The as-prepared model electrode can be directly used as the specimen for multifunctional SPM measurements, to perform mechanical, electrical conductivity and other interfacial property characterizations which require sample tip contact interactions during the measurements. Moreover, by performing the multifunctional SPM under a controlled environment, the initial electrochemical process of the electrode-electrolyte interface can be well detected both through The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Previous deep learning methods have not captured graph or network representations of brain structural or functional connectome data. To address this, we developed the BrainNet-Global Covariance Pooling-Attention Convolutional Neural Network (BrainNet-GA CNN) by incorporating BrainNetCNN and global covariance pooling into the self-attention mechanism. Resting-state functional magnetic resonance imaging data were obtained from 171 patients with schizophrenia spectrum disorders (SSDs) and 161 healthy controls (HCs). We conducted an ablation analysis of the proposed BrainNet-GA CNN and quantitative performance comparisons with competing methods using the nested tenfold cross validation strategy. The performance of our model was compared with competing methods. Discriminative connections were visualized using the gradient-based explanation method and compared with the results obtained using functional connectivity analysis. The BrainNet-GA CNN showed an accuracy of 83.13%, outperforming other competing methods. Among the top 10 discriminative connections, some were associated with the default mode network and auditory network. Interestingly, these regions were also significant in the functional connectivity analysis. Our findings suggest that the proposed BrainNet-GA CNN can classify patients with SSDs and HCs with higher accuracy than other models. Visualization of salient regions provides important clinical information. These results highlight the potential use of the BrainNet-GA CNN in the diagnosis of schizophrenia.The online version contains supplementary material available at 10.1186/s12868-021-00682-9. Convolutional neural networks (CNNs) are extremely efficient architectures in image and audio recognition tasks. CNNs performed better than other DNNs in the classification of Alzheimer’s disease versus mild cognitive impairment or normal controls , 2. We aThe BrainNetCNN, a type of CNN, is composed of novel edge-to-edge (E2E), edge-to-node (E2N), and node-to-graph (N2G) convolutional filters that leverage the topological locality of brain network data. With structural connectome data, the BrainNetCNN framework outperformed a variety of other methods in predicting neurodevelopment . AnotherThe diagnoses of patients were SZ n = 128), schizophreniform disorder (n = 40), and schizoaffective disorder (n = 3). There were no significant differences in age and sex between the SSD and HC groups. However, education was lower in the SSD group compared to the HC group  in the network with the Net-GA block compared to the network without the Net-GA block Table . UnexpecThe proposed BrainNet-GA CNN showed the best accuracy 83.13%) and area under the curve (89.42%). Its permutation test  was significant (p < 0.001). The next best model was SENet  methods not capturing graph or network representations of connectome data, we developed the BrainNet-GA CNN by incorporating BrainNetCNN and global covariance pooling into the self-attention mechanism. Advancement of scientific knowledge is described below in terms of methodological and clinical aspects.In the ablation study, favorable performance was reported in the network architecture composed of only two convolutional layers with Net-GA blocks. Relevant studies , 9 have i-th row can be interpreted to indicate statistical dependency between the i-th brain region and all other brain regions. We believe that this technique is a proper approach for neuroimaging data in which correlations or network features between brain regions are crucial. This may be partially supported by the finding that performance dropped a little when second-order pooling was not used in our model. Second, adopting the self-attention mechanism may enhance classification performance by effectively learning graph-wise high-order representations at every convolutional layer and recalibrating filter responses. Because the self-attention mechanism allows covariance pooling to be conveniently plugged into any location of the convolutional layers, it helps build deep CNNs. Unlike the BrainNetCNN, our model is flexible and has a deep structure. This may have contributed to the capture of richer statistics of deep features and improvement of the representation and generalization abilities of deep CNNs. Although implementation of a typical convolutional layer before the Net-GA block was necessary to apply the self-attention mechanism, it may be criticized that features extracted from this convolutional layer may not contain graph or network representations of our connectome data. However, we regarded this convolutional layer as a local sparse feature extractor since a typical convolution operation with small kernels does not significantly distort the topological characteristic of the correlation matrix.The best accuracy was obtained with the BrainNet-GA CNN, compared with other competing methods. Two characteristics of our model may have contributed to this superiority. First, because second-order pooling in the E2N layer captures higher order representations, this may lead to more discriminative features. The covariance matrix produced by second-order pooling is known to improve representation power by quadratic modeling. The Using multivariate DL techniques, neuroimaging-based single-subject prediction of psychiatric disorders has gained increasing attention in recent years. Several studies have employed DL methods to classify SZ and HCs. Using sMRI data, two studies applied a DBN to the original pre-processed images and obtained accuracy rates of 91% and 73.6%, respectively , 11. AppUsing the gradient-based explanation method, we identified discriminative functional connections between the brain regions contributing significantly to the recognition of SSDs. Among the top 10 discriminative connections, some regions (posterior cingulate gyrus and angular gyrus) were related to the DMN and others to the auditory network  and thalamus network. The DMN is involved in complex self-referential stimuli, such as mental time travel, perspective taking, and theory of mind . AccumulOverall pattern of the FC analysis was a more widespread occurrence of increased connectivities in patients with SZ compared with HCs. This seems in contrast with the results of previous studies that global/average connectivity strength was significantly reduced in SZ compared to controls , 24. HowThis study has several limitations. First, because the number of subjects used for the training and test phases was small, it is unclear how well these findings will generalize to different samples. Validation experiments will also be necessary if the transfer classification model is applied to a clinical population at a new imaging site. Second, although the proportion of patients with an antipsychotic naïve or free state was approximately 33%, most of the patients were on medication at the time of scanning. Antipsychotics are known to affect FC [All participating patients (n = 171) met DSM-IV-TR criteria for schizophrenia spectrum disorders (SSDs) according to the Structured Clinical Interview for DSM-IV (SCID) , 35. Ind7. The PANSS and CDSS were administered by trained psychiatrists.The severity of symptoms was evaluated within a week of fMRI scanning using the positive and negative syndrome scale  and, theResting-state functional and structural MRI (rsfMRI and sMRI) data were obtained at the Jeonbuk National University Hospital on a 3 T Verio scanner  using a 12-channel standard quadrature head coil. We collected a 5-min resting-state scan consisting of 150 contiguous echo-planar imaging functional images  atlas. The FC matrix was computed by correlating time series data between every pair in the AAL atlas using the CONN toolbox. Group comparison was performed using ANCOVA with education as covariate. For the contrast map, we applied the cluster-level extent threshold of p < 0.01, which was corrected for multiple comparisons using the false discovery rate  , and BraTo discover discriminative functional connections between the brain regions that make significant contributions to the recognition of SDDs, we used the gradient-based explanation method . To obtaAdditional file 1. Implementation of competing methods.Additional file 2. Contrast maps.


With the recent advances in cancer immunotherapy, great expectations have been raised for the successful implementation of these novel treatment concepts for patients with B-cell malignancies. The malignant cells in these cancer entities are in constant interaction with non-malignant immune cells and stromal cells in primary and secondary lymphatic tissues, and many B-cell malignancies are associated with immune defects. Even though treatment with immune checkpoint inhibitors or CAR T-cell therapies showed efficacy in some patients, the majority did not respond, for so far unclear reasons. To improve response rates, a better understanding of the cross-talk between the cancer cells and their microenvironment, and of immune escape and treatment resistance mechanisms are urgently needed. The collection of reviews, opinion, method, and original research articles in this Research Topic focuses on the complexity of the tumor microenvironment (TME) in B-cell malignancies and on novel concepts of immunotherapy for patients with these deadly diseases.Apollonio et al. summarize current knowledge on tumor intrinsic and extrinsic mechanisms critical to anti-tumor immune responses, as well as sensitivity to immunotherapies in B-cell lymphomas. They discuss the current understanding concerning the role of T cells and inflammatory signaling in these processes. The article further focuses on co-evolving stromal cells and their regulation of immune responses within the TME.In a detailed and timely review, Delahaye et al. discuss in a mini review article the current knowledge about protective niches in B-cell acute lymphoblastic leukemia (B-ALL) and the development of therapies targeting the crosstalk between leukemic cells and their microenvironment.Similarly, Griggio et al. focus in their informative review on the main immune defects affecting patients with CLL, also describing the complex networks leading to immune evasion and tumor progression. They further summarize the evolution of immune-based therapeutic approaches, including immunomodulatory drugs, monoclonal antibodies, and immunotherapeutic strategies aiming at activating or administering leukemia-reactive immune effector cells.To improve immunotherapy approaches for patients with chronic lymphocytic leukemia (CLL), a better understanding of their defective immune system is required. Vlachonikola et al. focuses on the binary, contradicting role of T lymphocytes in CLL. They describe the imbalanced composition of the T-cell compartment in CLL and how it is driven by antigen selection. Further, they focus on T-cell defects and perspectives of novel immunotherapy approaches to overcome them.Considering the recent advances in our understanding of T-cell activity and defects in CLL, a timely review by Wurzer et al. analysed immune synapse formation between CLL and NK cells and suggest a novel immune escape mechanism in CLL. They show that fast actin remodeling in CLL cells upon contact with NK cells prevents their effective NK-cell-mediated killing. These results highlight the critical role of the actin cytoskeleton in CLL cells in driving resistance against NK cell cytotoxicity and provide a new potential therapeutic point of intervention to target CLL immune escape.One of the main immune defects described for patients with CLL, is the failure to develop proper immune synapses between malignant B cells and effector T cells which was linked to altered cytoskeleton properties. In an original research article, Gonder et al., the use of mass cytometry for a better characterization of cells in the TME of CLL is described. This includes a protocol for antibody panel design and validation, sample preparation and acquisition, machine set-up, quality control, and analysis of cells. Additionally, advantages and pitfalls of this technique are discussed.Due to the increasing interest in the TME, extensive analyses revealed a tremendous complexity and heterogeneity of the cellular microenvironment in cancer. The development of novel technologies for single-cell analysis, like mass cytometry, enhances the number of cellular features that can be surveyed simultaneously and allows for resolving complex cellular systems. In a detailed method article by Augé et al. provide an extensive overview of genomic aberrations associated with RS. The article further focuses on the role of the PD-1/PD-L1 immune checkpoint axis in RS and discusses the potential of targeting this checkpoint as novel therapeutic option for patients with this aggressive disease.Richter Syndrome (RS) is a highly aggressive B-cell malignancy that arises due to the transformation of CLL, and the development of effective treatment options for RS patients is an urgent clinical need. In a very informative review article, Verma discusses in an interesting opinion article the potential mode-of-action underlying this observation.Multiple myeloma (MM) is an aggressive malignancy of plasma cells associated with pathological changes in the bone marrow microenvironment. Due to these, the majority of patients with MM develop anemia. Immunomodulatory agents like pomalidomide or lenalidomide are used for the treatment of MM and associated with the recovery from anemia. Aydin et al. address this important issue in their detailed review article. They summarize published data that show an impact of PI3K inhibition on the TME with a specific focus on CLL, and discuss how a better understanding of these effects of PI3K inhibitor-based therapies can serve as a rationale for the development of improved drugs or of novel combinatory treatment strategies in CLL.Inhibitors of phosphoinositide 3-kinase (PI3K) are approved for the treatment of CLL and other B-cell lymphoma. But the PI3K signaling pathway is not only limited to cancer cells but also crucial for many components of the TME which has to be considered when treating patients with PI3K inhibitors. Albakova et al. explore in their interesting review article the involvement of heat shock proteins (HSPs). As HSPs are highly expressed in lymphoma cells and are known to modulate immune responses and inhibit apoptosis, a better understanding of their role in anti-tumor responses may help in the development of more effective immunotherapy in B-cell lymphoma.Novel immunotherapies, like immune checkpoint blockade or CAR T-cell therapy showed efficacy in some patients with B-cell lymphoma, but for the majority of cases, this treatment approach failed. As a potential resistance mechanisms in Hodgkin and Non-Hodgkin lymphoma, via synthetic agonists is an immunomodulatory approach currently tested in several clinical trials for cancer. In an original research article, Lu et al. show that treatment of established A20 B-cell lymphoma in mice with a synthetic TLR4 agonist controlled tumor development. This effect was associated with T-cell inflammation and dependent on CD8+ T cells. Interestingly, the treatment response depended on TLR4 expression in B-cell lymphoma cells. TLR4 agonist treatment of lymphoma cells led to their enhanced antigen-presentation and increased their apoptosis. It was further sufficient to induce protective CD8+ T-cell responses. Therefore, the therapeutic potential of TLR4 activation in B-cell lymphoma should be further explored.Activation of Toll-like receptor (TLR) signaling Bewarder et al. They generated a full-length IgG1 or Fab antibody format containing the PCNSL-reactive epitope of SAMD14/neurabin-I and showed specific binding of these constructs to lymphoma cells as well as their effective killing in coculture with PBMC.A novel interesting treatment approach for primary central nervous system lymphomas (PCNSL) harboring B-cell receptors that recognize the common auto-antigens neurabin-I and SAMD14 is presented in the original research article by Altogether, the collection of articles in this Research Topic provides a comprehensive overview of the immune microenvironment in B-cell malignancies and the potential of new immunotherapy approaches for these diseases, thereby supporting the development of improved treatment regimens for the patients.All authors edited the Research Topic. MS wrote the editorial. All authors contributed to the article and approved the submitted version.This work was supported by grants from the Fonds National de la Recherche Luxembourg to JP and EM (C20/BM/14592342 and C20/BM/14582635).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.