Ultrafast structural probing has greatly enhanced our understanding of the coupling of atomic motion to electronic and phononic degrees-of-freedom in quasi-bulk materials. In bi- and multilayer model systems, additionally, spatially inhomogeneous relaxation channels are accessible, often governed by pronounced interfacial couplings and local excitations in confined geometries. Here, we systematically explore the key dependencies of the low-frequency acoustic phonon spectrum in an elastically mismatched metal/semiconductor bilayer system optically excited by femtosecond laser pulses. We track the spatiotemporal strain wave propagation in the heterostructure employing a discrete numerical linear chain simulation and access acoustic wave reflections and interfacial couplings with a phonon mode description based on a continuum mechanics model. Due to the interplay of elastic properties and mass densities of the two materials, acoustic resonance frequencies of the heterostructure significantly differ from breathing modes in monolayer films. For large acoustic mismatch, the spatial localization of phonon eigenmodes is derived from analytical approximations and can be interpreted as harmonic oscillations in decoupled mechanical resonators. Advanced technological applications ranging from heat management in nanoelectronicsThe complex microscopic mechanisms of pico- and femtosecond phononic processes are being uncovered by high-resolution optical spectroscopy and recently developed ultrafast methodologies. For example, phonon–phonon couplings, modified phonon dispersion relations, and dissipation times in nanoscale systemsHere, we apply an analytical acoustic mode description of ultrafast structural dynamics in a nanoscale bilayer system. Explicit expressions for the resonance frequencies are derived and compared to numerical results. The coupling of individual phononic modes in both layers is analyzed with respect to the acoustic mismatch and the emergence of localized modes is demonstrated.supplementary material S1 for details). The resulting oscillatory change in film thickness occurs with a periodicity given by the strain pulse round trip time.In order to arrive at a resonant acoustic mode description for bilayer films, we start off by considering a simple monolayer, as often investigated in ultrafast diffraction experiments.H, acoustic resonant modes with mode index v is the longitudinal sound velocity of the material. The base frequency f1 corresponds to the inverse round trip time of the strain wave. Mode amplitudes in the superposition depend on the effective time- and length-scale of the sample excitation. Specifically, for a homogenous excitation within the depth of the thin film and for a pump-induced stress with a rise time much larger than the considered resonance frequencies, one obtains nth mode amplitude . As an example, the modulation of the Bragg linewidth in laser-excited thin films was found to occur at twice the frequency of the breathing mode.In ultrafast diffraction experiments, the temporal evolution of the average strain along the probing direction is encoded in a periodic change of reciprocal lattice vectors leading to an angular displacement of the center-of-mass of Bragg scattering conditions. Only uneven higher harmonics of the fundamental breathing mode frequency are contributing to the average angular shift. Modes with even z-direction) using a one-dimensional linear-chain model . Allowed acoustic mode frequencies nω are obtained as the nth order root of the resulting characteristic function,vr are plotted in In the following, an analytical description is presented allowing for a more general discussion of strain propagation in coupled bilayer systems. For strongly mismatched bulk material properties, approximate solutions are found yielding insights into the origin of coupling mechanisms between adjacent layers. The acoustic wave field in the two quasi-isotropic elastic media, platinum and silicon, is described as a linear combination of back and forth propagating plane waves along the ω, solutions asymptotically approach the poles of the tangent functions located at The resonance frequencies in the limit of large ratios . Specifically, for A change in supplementary material S2) yields the corresponding displacement field, with the absolute wave amplitude shown in Solving for the wave amplitudes at a given resonance frequency supplementary material] at the interface (z = 0), which result in a relation between the impedance ratio and the strain in both materials: n)-Pt–Si branches . In contrast, for (n)-Si–Pt branches [e.g., for n = 5, shown in The differences in the exemplary wave structures are caused by the acoustic boundary conditions [see Eq. (6) in the Zr) become also evident from the phase difference of the forward and backward propagating wave components. As shown in t for selected resonance frequencies are shown in The sinus- and cosine-like standing waves in the bilayer .Finally, the overall structure of the frequency maps can be understood by considering the resonances of the individual decoupled layers, corresponding to the horizontal and inclined lines in For macroscopic acoustic resonators, a resonant mode picture is well established. In the case of localized nanoscale acoustic fields, a series of questions arises, for example, regarding the validity of continuum-theory boundary conditions at small length scales, the importance of the material interface for acoustic and electronic coupling or the impact of nanocrystallinity. The mode analysis presented here may serve as a reference model to gauge potential deviations arising from the nanoscale dimensions involved.In conclusion, we determined the acoustic response of a nanoscale metal/semiconductor bilayer system upon femtosecond optical excitation, calculating the strain dynamics from linear-chain simulations and describing the acoustic field in terms of superimposed counter-propagating harmonic waves perpendicular to the sample surface. In the confined heterostructure and due to elastic boundary conditions, quantized phonon eigenmodes arise with frequencies in the gigahertz range, exhibiting strong couplings across the bilayer interface.supplementary material for further details on numerical and analytical models discussed in the main text.See the


Vegetation indices are commonly used techniques for the retrieval of biophysical and chemical attributes of vegetation. This paper presents the potential of an Autoencoders (AEs) and Convolutional Autoencoders (CAEs)-based self-supervised learning approach for the decorrelation and dimensionality reduction of high-dimensional vegetation indices derived from satellite observations. This research was implemented in Mt. Zao and its base in northeast Japan with a cool temperate climate by collecting the ground truth points belonging to 16 vegetation types (including some non-vegetation classes) in 2018. Monthly median composites of 16 vegetation indices were generated by processing all Sentinel-2 scenes available for the study area from 2017 to 2019. The performance of AEs and CAEs-based compressed images for the clustering and visualization of vegetation types was quantitatively assessed by computing the bootstrap resampling-based confidence interval. The AEs and CAEs-based compressed images with three features showed around 4% and 9% improvements in the confidence intervals respectively over the classical method. CAEs using convolutional neural networks showed better feature extraction and dimensionality reduction capacity than the AEs. The class-wise performance analysis also showed the superiority of the CAEs. This research highlights the potential of AEs and CAEs for attaining a fine clustering and visualization of vegetation types. Vegetation is an integral component of life, and identification and classification of vegetation types provides valuable information for understanding the distribution and dynamics of vegetation as for environmental changes. Spectral reflectance measured from remote sensing platforms provides crucial information on identification and discrimination of vegetation types.The reflectance measured from remote sensors vary with specific biophysical and chemical attributes such as plant type, leaf pigments, water content, and morphological characteristics of the plant canopy concerned ,2. VegetMachine learning is a commonly used technique for interpreting remote sensing images into vegetation parameters. There are a number of machine learning algorithms available for dimensionality reductions. The Random Forests (RFs)—an ensemble of decision trees built by splitting the attributes of the data and averaging the output value of all trees—is one of the effective machine learning algorithms for learning non-linear data interactions ,11. The Some other classical techniques of dimensionality reductions are principal component analysis ,23,24, tArtificial neural networks (ANNs) has demonstrated effectiveness in a number of climate change and ecological studies, such as change detection , plant iIn recent years, the use of Autoencoders (AEs) has attracted increasing attention to create low-dimensional projections of high-dimensional data. AEs are artificial neural networks (ANNs) designed for learning self-supervised latent representations of multi-dimensional data ,36,37.ThThe major objective of this paper is to present an Autoencoders (AEs) and Convolutional Autoencoders (CAEs)-based self-supervised learning approach for the decorrelation and dimensionality reduction of high-dimensional vegetation indices derived from satellite observations. The compressed images are utilized for the clustering and visualization of vegetation types, and they were compared over the Random Forests-based important features. The potential of this approach for the classification of vegetation types is also assessed using the Random Forests (RFs) classifier.This research was implemented in Mt. Zao, which is located on the border between Yamagata and Miyagi prefectures in Japan. This region is characterized by a cool temperate climate with snowfall during winter. It represents a typical mountainous ecosystem in northeastern Japan. The location of the study area is shown in The performance of Autoencoders (AEs) and Convolutional Autoencoders (CAEs) for the clustering and classification of vegetation types was assessed with the support of ground truth data. The ground truth data were collected through a field survey, which was conducted in 2018. The field survey was assisted by time-lapse images available in Google Earth. For each vegetation type, 107–300 sample points (longitudes and latitudes), representing a homogenous area of at least 30 × 30 m, were collected. This research dealt with the following list of vegetation types  present Sentinel-2 scenes available for the study area from 2017 to 2019  were processed. All images were processed for cloud removal and atmospherically corrected to obtain top of canopy reflectance using the Sen2Cor software (v2.8). For each Sentinel-2 scene, 16 vegetation indices (as shown in We employed densely connected Autoencoders (AEs) and Convolutional Autoencoders (CAEs) for the decorrelation of high-dimensional vegetation indices. The model architectures utilized in this research are illustrated in The performance of AEs and CAEs-based compressed images for the clustering and visualization was compared to the classical RFs-based retrieval of the important features. The RFs algorithm has been employed as a classical approach for deriving variable importance . The pixFurthermore, performance of the compressed images  in different dimensions  in terms of classification of vegetation types was also assessed quantitatively. For the supervised classification, Random Forests (RFs) classifier was employed on a 75% training set and validated on a 25% test set. For the quantitative evaluation, we computed the confidence interval by implementing bootstrap resampling of the dataset at 1000 times. The bootstrap resampling technique involves drawing of sample data repeatedly with replacement from a data source and reduces a biased estimation of the accuracy. The research procedure has been illustrated in The discriminative ability of the lower dimensional features can be visualized by plotting their distribution in a three-dimensional space. A three-dimensional scatter plot of the RFs algorithm-based retrieval of the most important features is shown in An improvement on the clustering of vegetation types by the AEs-based compressed features over the RFs algorithm can be seen with a wider inter-class variation of the clusters in Further improvement by the CAEs-based compressed features can be seen in The RGB color composites of the AEs and CAEs-based three-dimensional compressed images in We employed the bootstrap resampling method to report the confidence interval of the CAEs-based classification approach. The bootstrap resampling was done for 1000 times with 75% training and 25% testing data. The accuracy obtained with the test data was collected for each bootstrap resampling, and the frequency of models yielding the test accuracies has been plotted in The distribution of feature importance obtained from bootstrap resampling of the CAEs-based three features has been shown in Similarly, we calculated the test accuracy using ten features obtained from the CAEs, and the frequency of models yielding the test accuracies has been plotted in Furthermore, we summarized the significance of the Autoencoders (AEs) and Convolutional Autoencoders (CAEs) over the Random Forests (RFs) by employing bootstrap resampling at 1000 times with 75% training and 25% testing data. The test accuracies obtained from the bootstrap resampling also showed a higher performance of the Autoencoders (AEs) and Convolutional Autoencoders (CAEs) over the Random Forests (RFs). Interestingly, it should be noted that difference between them (RFs versus AEs or CAEs) started to decrease when number of input features increased. However, the main objective of this research was to compress the high-dimensional dataset into least dimension so as to visualize the inter-class variability of the vegetation types. Therefore, self-supervised learning with the Autoencoders (AEs) and Convolutional Autoencoders (CAEs) has met our objective of showing the inter-class variability of vegetation types at lower dimension. The collection and preparation of ground truth data is very time-consuming and expensive for the vegetation mapping projects. The ability of such self-supervised learning and visualization of the satellite images should contribute to the better interpretation and discrimination of vegetation types (such as collection of ground truth data) as well as subsequent supervised classification for the operational mapping of vegetation types at a broad scale.We implemented the Autoencoders (AEs) and Convolutional Autoencoders (CAEs)-based self-supervised learning approach for the decorrelation and dimensionality reduction of high-dimensional satellite-based features. Deep learning is a versatile technology specialized for big datasets. Once the high-dimensional features were compressed into lower ones, we employed Random Forests (RFs) classifier for the classification of vegetation types.A significant processing challenge exists with an ever-increasing collection of huge volumes of remote sensing data with enhanced spatial and spectral resolution. To address this issue, dimensionality reduction techniques have been recommended for reducing the complexity of the data while retaining the relevant information for the analysis ,57. TherSpectral vegetation indices have been used by many researchers for the clustering and classification of vegetation types. For example, Villoslada et al.  highlighPrevious studies have also attempted dimensionality reduction of remote sensing data for the classification and mapping of vegetation types. However, most of these researchers have employed classical dimensionality reduction techniques. For example, Alaibakhsh et al.  used PriIn this research, we showed Autoencoders (AEs)-based self-supervised learning as a potential approach for the decorrelation and compression of high-dimensional vegetation indices in a cool temperate mountainous ecosystem in Japan. Compared to the classical Random Forests (RFs)-based dimensionality reduction method, the Autoencoders (AEs) and Convolutional Autoencoders (CAEs) showed superior performance on the clustering and classification of vegetation types. While the purpose of dimensionality reduction approaches is to represent the relevant information into the least amount of dimensions, the three-dimensional compression of vegetation indices using the CAEs method showed around a 9% increase in the confidence interval over the RFs. The RFs extracts the most important features out of given features, whereas the AEs and CAEs generate compressed features through self-supervised learning approach. Therefore, this research highlights the application of the CAEs method for the clustering and visualization of vegetation types. In the future, we will assess the efficiency of CAEs in other regions.


The survival probability of early human conceptions is very low. At least 73% of natural single conceptions have no real chance of surviving six weeks of gestation . After sVery little information is available on rates and common causes of spontaneous second- or mid-trimester miscarriage , possibly due to the global lack of reporting systems. The National Vital Statistics System in the United States reports fetal mortality from 20 week’s gestation . In the In the UK, 12–24 weeks gestational age is defined as a late miscarriage ,12 with The first publications on the possible causes of second-trimester miscarriage emphasised the role of placental inflammation. A retrospective study by Russel , examiniA study of 360 spontaneous abortions showed placental inflammatory lesions in a third of cases of early fetal death at 13–18 weeks gestation but in 60% when the fetal death was at 18–24 weeks . AnotherThe placenta plays a key role in implantation and development of the fetus. Soluble Fms-like kinase and placental growth factor are both involved in placental vascularization. Andersen et al.  examinedFactor V and the prothrombin mutations have been associated with an approximate tripling of the risk for late miscarriages . The autDefective haemochorial placentation as a cause of miscarriage was first reported in 1987 . None ofIn a study on spiral artery transformation and trophoblast invasion, 96 spiral arteries in 26 pregnancies at 13 weeks or later were compared to 236 spiral arteries in 74 normal pregnancies matched for gestational age . CompareValuable information on possible causes of late miscarriage came from the Safe Passage Study, a prospective investigation on the effects of alcohol exposure during pregnancy on stillbirths and sudden infant deaths . When a From the abovementioned studies, it is clear that placental pathology plays a major role in the etiology of spontaneous second-trimester miscarriages. Causes of fetal demise at the end of the second-trimester differ little from that of stillbirths. Therefore, placental histology in second-trimester miscarriages may be of great help to identify risks in future pregnancies as the same complications tend to repeat. Interestingly, placental disease was also the leading cause of antepartum stillbirths (26%) in the 633 stillbirths examined by the Stillbirth Network. However, they did not differentiate between the different placental conditions such as MVM or acute chorioamnionitis . In the As some of the causes of second-trimester miscarriages and early stillbirths are similar, information on the causes and rates of miscarriage may provide valuable information for efforts to reduce stillbirths. It is necessary to analyse stillbirth and perinatal mortality rates regularly to project whether the millennium goals for 2030 will be reached . AlthougIt is important to keep in mind that there are several predisposing conditions to miscarriages including genetic, anatomical, endocrine, immunological, infective, and environmental.As stated earlier, worldwide reform is needed in the care of women after they have had a miscarriage . Part of


Additionally, the interplay between cardiac MMPs and their endogenous tissue inhibitors of MMPs, is thought to be critical in atrial ECM metabolism and fibrosis. We also review recent evidence about the role of changes in the miRNAs expression in AF pathophysiology and their potential as therapeutic targets. Furthermore, keeping the balance between miRNA molecules exerting anti-/profibrotic effects is of key importance for the control of atrial fibrosis in AF.The cellular and molecular mechanism involved in the pathogenesis of atrial fibrosis are highly complex. We have reviewed the literature that covers the effectors, signal transduction and physiopathogenesis concerning extracellular matrix (ECM) dysregulation and atrial fibrosis in atrial fibrillation (AF). At the molecular level: angiotensin II, transforming growth factor-β1, inflammation, and oxidative stress are particularly important for ECM dysregulation and atrial fibrotic remodelling in AF. We conclude that the Ang-II-MAPK and TGF-β1-Smad signalling pathways play a major, central role in regulating atrial fibrotic remodelling in AF. The above signalling pathways induce the expression of genes encoding profibrotic molecules . An important mechanism is also the generation of reactive oxygen species. This pathway induced by the interaction of Ang II with the AT Myocardial fibrosis, causing atrial fibrillation (AF), is one of the main factors leading to heart remodelling. It should be noted, however, that the process of fibrosis causes significant changes both in the ventricles and in the atria of the heart. Ventricular fibrosis leads to the development of heart failure, while atrial fibrosis leads to the generation of atrial fibrillation episodes. Pathological phenotypes in atrial and ventricular fibrosis are different. Ventricular fibrosis is primarily induces pumping dysfunction (systolic dysfunction and diastolic dysfunction) whereas atrial fibrosis is responsible for cardiac conduction abnormalities. The process of atrial fibrosis includes various individual and multifactorial processes with underlying complicated interactions between cellular and neurohormonal mediators . Myocard2+ current passage . I. I124]. Another important pathway involved in the process of atrial fibrosis is the CTGF-dependent pathway, while the expression of CTGF signalling molecule is regulated again by TGF-β and endothelin. In the effect of CTGF action, collagen synthesis is increased. In the regulation of CTGF expression four miRNA molecules are involved: miR-30a, miR-133, miR-26a, miR-132  117,126126,129. 2+-permeable transient receptor potential canonical-3 (TRPC3) protein. The increased TRPC3 protein level was associated with intense activation, proliferation and differentiation of atrial fibroblasts . I. I129]. roblasts .The studies by Qiao et al.  also preAnother molecule regulating the expression of genes encoding proteins participating in collagen biosynthesis and demonstrating an antifibrotic effect is miR-29b . The tarThe knowledge of the functions fulfilled by individual miRNA molecules in the process of atrial fibrosis enables a deeper insight into the molecular background of AF. miRNA molecules can play the function of both activators and inhibitors of the secreted profibrotic factors. Keeping the balance between miRNA molecules demonstrating anti- and profibrotic effects is of key importance for controlling the atrial fibrosis process.The presented miRNA molecules , showingAtrial fibrosis should be regarded as a potential key factor and biomarker of AF pathogenesis. Fibrotic tissue formation is a complex multifactorial process involving many interactions of neurohumoral and cellular factors. The studies presented in the paper seem to clearly suggest that the Ang II-MAPK and TGF-β-Smad signalling pathways and Rac1-dependent CTGF activation play an important, even crucial role in the direct or indirect regulation of atrial remodelling and fibrosis in AF. An extremely important role in the regulation of the fibrotic process and ECM remodelling is also played by miRNA molecules. The miRNA molecules exert both pro- and antifibrotic effects. They participate in the regulation of the expression of genes encoding the most important proteins of the signalling pathways involved in fibrosis. Keeping of the balance between miRNA molecules exerting anti- and profibrotic effects is of the key importance for the control of atrial fibrosis in AF .Inflammatory status and oxidative stress are important elements contributing to changes in the ECM. The ECM metabolism is a process regulated in a strict and dynamic way in the cardiac tissues by the balance of the degrading enzymes and their endogenous inhibitors. The co-operation between MMPs and TIMPs is regulated by growth factors, inflammatory cytokines and ROS. An understanding of the molecular mechanisms mediating the MMP/TIMP balance may contribute to a new look at remodelling of the heart atria and to development of effective drugs which could prevent AF or reverse its pathogenesis.The cellular and molecular control of atrial fibrosis is very complex . The rec


Rehabilitation specialists have shown considerable interest for the development of models, based on clinical data, to predict the response to rehabilitation interventions in stroke and traumatic brain injury survivors. However, accurate predictions are difficult to obtain due to the variability in patients’ response to rehabilitation interventions. This study aimed to investigate the use of wearable technology in combination with clinical data to predict and monitor the recovery process and assess the responsiveness to treatment on an individual basis.Gaussian Process Regression-based algorithms were developed to estimate rehabilitation outcomes  using either clinical or wearable sensor data or a combination of the two.The algorithm based on clinical data predicted rehabilitation outcomes with a Pearson’s correlation of 0.79 compared to actual clinical scores provided by clinicians but failed to model the variability in responsiveness to the intervention observed across individuals. In contrast, the algorithm based on wearable sensor data generated rehabilitation outcome estimates with a Pearson’s correlation of 0.91 and modeled the individual responses to rehabilitation more accurately. Furthermore, we developed a novel approach to combine estimates derived from the clinical data and the sensor data using a constrained linear model. This approach resulted in a Pearson’s correlation of 0.94 between estimated and clinician-provided scores.Significance: This is important in the context of developing precision rehabilitation interventions.This algorithm could enable the design of patient-specific interventions based on predictions of rehabilitation outcomes relying on clinical and wearable sensor data.  I.STROKE and traumatic brain injury (TBI) are major causes of long-term disability , 2]. Th. Th2]. TWhereas the availability of many rehabilitation approaches provides the opportunity to design patient-specific interventions and thus to achieve optimal clinical outcomes, the criteria that should be used to select the most suitable intervention given the individual patient’s characteristics are still debated. Among others, Winstein and Varghese proposed investigating mechanistic approaches to the design of rehabilitation interventions . These aIdeally, the design of rehabilitation interventions would rely on predicting and longitudinally monitoring clinical outcomes, which in turn would allow clinicians to select the intervention associated with optimal outcomes on a patient-by-patient basis. In this context, clinicians and researchers have directed their attention to the use of wearable sensors as a tool to assess the effects of rehabilitation interventions , 24]. I. I24]. IUsing data collected by means of wearable sensors to estimate the motor recovery trajectory of stroke and TBI survivors is meaningful only if the technology provides researchers and clinicians with predictions of rehabilitation outcomes that are more accurate than the ones clinicians can derive based on information that is routinely available in the clinic . It is worth emphasizing that clinical evaluations are regularly performed prior to starting rehabilitation interventions. Hence, information about the patients’ status and the intervention characteristics are known to the clinical team. Would this clinical information be sufficient to accurately predict rehabilitation outcomes in response to the intervention? Would it be necessary to use wearable sensor data to obtain accurate predictions of the rehabilitation outcomes? Would combining clinical data-based estimates and wearable sensor data-based estimates lead to improvements in the accuracy of the predictions of rehabilitation outcomes?In this study, we addressed the above-stated questions by collecting longitudinal data from a cohort of stroke and TBI survivors with a broad spectrum of baseline clinical characteristics and by developing algorithms  suitableII.A.A total of 44 subjects with upper-limb hemiparesis were enrolled in the study. Of these subjects, 22 were stroke survivors , and 22 were TBI survivors . Subjects were considered eligible to participate in the study if they were 1) 18–80 years old, 2) beginning to undergo an inpatient or outpatient rehabilitation intervention involving upper-limb therapy at the time of the baseline visit, and 3) affected by upper-limb impairments as determined using the FMA-UE scale . All the subjects participated in a first study visit and 38 of them also participated in a second study visit after undergoing a rehabilitation intervention. Six subjects were unable to return to the laboratory for the second visit. Of the subjects who participated in the second study visit, 17 were stroke survivors  and 21 were TBI survivors . Eight of the 17 stroke survivors and 20 of the 21 TBI survivors who completed both study visits were rehabilitation inpatients at the start of the study. All the other subjects were outpatients.During the study visits, wearable accelerometer units  were secured using bi-adhesive tape and/or Velcro straps to the sternum as well as the arm, wrist, thumb, and index finger of the hemiparetic upper-limb. After donning the sensor units, subjects were instructed to perform a series of motor tasks to assess the quality of upper-limb movements using the FAS . The FASReaching Tasks, whereas the remaining tasks are referred to as Manipulation Tasks . F. F43]. FReaching Tasks, a total of 357 data features were extracted using data segments corresponding to the performance of the entire task. For the Manipulation Tasks, a total of 1,035 data features were extracted from each of the data segments corresponding to the performance of the above-mentioned movement components  minimum, maximum, and mean values, 2) root mean square value, 3) ratio of the magnitude of the dominant frequency and total signal energy, 4) skewness, 5) kurtosis, 6) signal entropy, 7) Spearman correlation coefficients derived from the time-series computed for different axes, and 8) duration of the data segments associated with the performance of each movement component. The skewness and kurtosis represent the symmetricity and peakedness of the distribution of the time-series data, respectively. The entropy captures the regularity of the fluctuations observed in the time-series. The Spearman correlation coefficients of the acceleration magnitude time-series of all pair combinations of the sensor data  were computed. These correlation coefficients were meant to capture the characteristics of relative movements of different body segments, including compensatory movements such as leaning forward with the trunk when subjects reached for an object in front of them , 43]. F. F43]. Fents see .A correlation-based data feature selection algorithm  was empl3)a posteriori estimates to produce the conditional distribution of the latent variable, because this method performs well for training sets of small size  and and7] anKey variables to determine how to combine clinical data-based estimates and sensor-data based estimates were shown to be the number of treatment sessions, the chronicity of the neurological injury, and the FAS and FMA-UE scores at baseline. This result is of great interest because it is consistent with previous reports indicating that large motor gains can be achieved with high-dosage interventions , 11] bu bu11] buWhereas the objective of this study was to develop a framework to generate FAS score estimates by combining clinical data-based estimates and sensor data-based estimates, future work should be devoted to leveraging the proposed framework to generate more accurate estimates of rehabilitation outcomes by improving both the algorithm to derive estimates using solely sensor data and the predictions derived using solely clinical data. Because, in the context of a clinical application of the proposed approach, sensor data would be collected longitudinally, then techniques to model the time-course of the FAS scores could be utilized to improve the accuracy of sensor data-based estimates. These include GPR models suitable to predict datapoints of a time-series . In addiIt is worth emphasizing that the results presented in this manuscript support a clinical scenario in which stroke and TBI survivors’ recovery trajectories are longitudinally monitored to develop patient-specific rehabilitation interventions. Clinical data collected at baseline could be utilized to compute the expected clinical outcomes of the intervention (assuming responsiveness to the prescribed treatment). Sensor data collected longitudinally in the clinic or in the home and community settings during the performance of functional motor tasks  and evaluated the trained models based on data collected during the post-treatment visits from a total of 38 subjects (17 stroke and 21 TBI survivors). However, despite the relatively small data samples, the evaluation of the machine learning models was performed using the LOSOCV technique, which minimized the chances of overfitting the training model to patient-specific movement patterns. Secondly, the proposed approach is based on collecting sensor data longitudinally, during the intervention period. Sensor data could be collected in the clinic as part of the outpatient visits scheduled for treatment or in the home and community settings. In the former case, therapists would assist patients in donning/doffing the sensors. In the latter case, either patients would have adequate motor and cognitive abilities to don/doff the sensors on their own or a caregiver would provide assistance. In all these scenarios, minimizing the number of sensors would be highly desirable, which we did not pursue in this study. Future work should identify the minimum set of wearable sensors and optimal body locations that can provide adequate tracking of the recovery trajectory . Lastly,V.r = 0.94). These estimates were marked by an error  that compared favorably with available inter-rater reliability data for the FAS. The algorithms developed in this study can be used to predict and monitor rehabilitation outcomes and enable the development of patient-specific rehabilitation interventions based on the responsiveness of each individual to different treatment strategies.The study showed that a GPR model based on clinical data collected at baseline can predict rehabilitation outcomes  in stroke and TBI survivors better than traditional models, but still fails to account for the variability in the level of responsiveness to treatment across individuals. A GPR model was also used to estimate rehabilitation outcomes based on data collected using wearable sensors with results superior to those obtained using clinical data. Using constrained linear modeling and quadratic programming, we developed an algorithm to combine the clinical data-based estimates and the sensor data-based estimates. The algorithm accounted for the clinical characteristics of each subject at baseline. The FAS score estimates derived using the proposed algorithm showed a high level of correlation with FAS scores provided by clinicians (


There are limited reports on the use of tolvaptan for syndrome of inappropriate antidiuretic hormone secretion (SIADH) in children. Managing serum sodium levels in SIADH patients during chemotherapy is often difficult because of the need for massive fluid infusions. We report the course of the use of tolvaptan for the treatment of hyponatremia during chemotherapy in a four-year-old girl with a suprasellar germ cell tumor. The patient was a Japanese girl who presented with left ptosis with a mass in the pituitary gland and cavernous sinus. She was diagnosed with an intermediate-grade germ cell tumor and was treated with carboplatin and etoposide combination chemotherapy. She developed hyponatremia due to SIADH caused by intravenous infusion therapy before chemotherapy. Subsequently, tolvaptan  was administered orally to control serum sodium levels. After 4 h of administration, a marked increase in urine volume of up to 15 mL/kg/h was observed, and serum sodium level increased from 126 to 138 mEq/L after 10 h of tolvaptan administration, followed by a decrease in urine volume. The use of tolvaptan in pediatric patients with SIADH who require intravenous hydration during chemotherapy can be useful for the management of serum sodium balance. Syndrome of inappropriate antidiuretic hormone secretion (SIADH) is a condition in which, despite low osmotic pressure, arginine vasopressin (AVP) secretion is not suppressed, AVP is continuously secreted, and excess body fluid accumulates because of the promotion of water reabsorption within the renal collecting tubule, resulting in diluted hyponatremia ,2. SIADHThe vasopressin type-2 receptor antagonist tolvaptan can be used to treat hyponatremia. Tolvaptan selectively and competitively binds to and blocks the V2 receptor located in the walls of the vasculature and luminal membranes of renal collecting ducts, thereby preventing the binding of vasopressin to the V2 receptor ,2. This Herein, we report the course of the use of tolvaptan for the treatment of hyponatremia during chemotherapy in a four-year-old girl with a suprasellar germ cell tumor presenting with SIADH.The patient was the first child of Japanese non-consanguineous parents. She was born at full-term via normal delivery, and her birth weight was 3482 g. Neonatal screening tests were within the normal range. She was a healthy girl until four years of age. She visited our department presenting with left ptosis, left eye abduction failure, and left low vision. Contrast-enhanced T1-weighted imaging revealed a mass with inhomogeneous enhancement in the pituitary region, cavernous sinus, and enlargement of the pituitary stalk. Based on the biopsy results, she was diagnosed with an intermediate-grade germ cell tumor and was treated with carboplatin and etoposide combination chemotherapy (CARE therapy). Serum Na levels at admission and after biopsy were 137 and 132 mEq/L, respectively, ranging from normal to mildly low. Following hydration therapy before chemotherapy, she presented with neck pain and a decrease in serum sodium levels due to SIADH . Her carThe course of the first cycle of CARE chemotherapy is shown in This was a retrospective analysis of the clinical course of a patient examined and treated at the Niigata University Medical and Dental Hospital in Japan. The use of tolvaptan in this case was approved by the Clinical Ethics Review Committee of Niigata University Medical and Dental Hospital. Written informed consent was obtained from the mother.The upper panel shows the changes in serum sodium levels and urine-specific gravity. The lower panel shows the sodium content of intravenous infusion. The color intensity of the square is proportional to the concentration of Na.The cornerstone of SIADH treatment is water restriction, but fluid balance can be difficult to manage when fluids are needed, such as during chemotherapy. We report a pediatric case of hyponatremia due to hydration during chemotherapy in a four-year-old girl with a suprasellar germ cell tumor.Reports of tolvaptan use for SIADH in children are limited ,9,10,11.Management of sodium balance for SIADH during chemotherapy with massive infusion is difficult. Willemsen et al. reported the use of tolvaptan for hyponatremia associated with massive infusion during methotrexate therapy for intracranial B-cell lymphoma . TolvaptThe onset and duration of action of tolvaptan in pediatric patients with SIADH are unknown. In the US Guidelines for hyponatremia, it is essential that the serum sodium concentration is measured frequently during the active phase of correction of hyponatremia at a minimum of every 6 to 8 h during the use of tolvaptan in adult patients with SIADH, particularly in patients with risk factors for osmotic demyelination . In thisThe use of tolvaptan in pediatric patients with SIADH who require intravenous hydration during chemotherapy can be useful for the management of serum sodium balance.


The use of pre-hospital blood transfusion by air ambulance crews is increasing. Blood transfusion is traditionally ‘authorised’ by doctors, not prescribed. However, there is an increasing interest in extending the capability of authorisation to other practitioners – that is, non-medical authorisation (NMA). A UK framework for nurses and midwives has existed since 2007, but training for critical care paramedics (CCPs) has been limited.The Resuscitation with Pre-Hospital Blood Products (RePHILL) trial was launched in 2016, requiring pre-hospital administration of red cells and LyoPlas. Authorisation was initially restricted to doctors, leading to missed recruitment by paramedic-only crews. The trial protocol was amended in 2019 to permit NMA following suitable training and stakeholder consultation. We present a targeted training programme designed to support paramedic-led transfusion within the framework of the pre-hospital trial.We considered the knowledge and skills required for NMA and compared this with baseline knowledge from paramedic training to identify the training gap. We examined examples of existing military and civilian NMA training to develop a targeted programme for a single air ambulance. The four elements of our training programme were pre-course online training, previous trial participation, face-to-face training and competency assessment.Training was delivered to three CCPs, who cascaded the training to 14 colleagues. The training time was one morning, including a face-to-face session and assessment. Novel topics included physiological triggers for transfusion and transfusion risks in the pre-hospital environment. Paramedics were encouraged to recognise and report new patterns of adverse events. Reflective feedback suggests the programme provided CCPs the knowledge to autonomously recruit trial patients and authorise transfusion. The use of pre-hospital blood transfusion by air ambulance crews is increasing in England and Europe . Blood iThe Resuscitation with Pre-Hospital Blood Products (RePHILL) trial was launched in 2016. The trial compared standard saline resuscitation in major traumatic haemorrhage with red cells and freeze-dried plasma . The triWe considered the NMA knowledge and skills required for the pre-hospital trial against the baseline knowledge from CCP and trial training to identify the transfusion training gap. We then examined examples of military and civilian NMA training to develop a targeted programme sponsored by the PHEM clinical lead for The Air Ambulance Service (TAAS).Paramedic study includes the physiology and management of shock together with the basics of haematology. Some courses include transfusion competency arranged with a local hospital trust, using standards defined by the 2006 Patient Safety Notice . TAAS CCAll our trial CCPs had already undertaken good clinical practice (GCP) and trial-specific training for RePHILL. GCP ensures that ‘everyone involved in research is trained or appropriately experienced to perform the specific tasks they are being asked to undertake’ . Trial-sCivilian courses reviewed included the well-established NHS Blood and Transplant (NHSBT) course  and a hoWe designed a classroom-based session and assessment to address the role requirements and complement earlier training. The programme included:an introduction to the background of NMA and the use of LyoPlas;the RePHILL trial, physiology of shock and decision to transfuse; andrecognising, managing and reporting pre-hospital hazards of transfusion.TAAS requested cascade training starting with a face-to-face session for three CCPs at a local hospital with a history of teaching NMA. The training team consisted of a consultant anaesthetist with specialist interest in transfusion, a transfusion practitioner and the RePHILL research paramedic. All three were involved in designing the programme, together with a consultant in transfusion medicine with experience in military and civilian NMA. The four elements of our training programme are shown in Students were invited to supply immediate feedback via email at the end of the session. Following notification via the trial database of a patient recruited by a CCP, the member of staff was invited to reflect on their experience. Both of these were in the form of unstructured feedback in order to allow for as much freedom of expression as possible.Face-to-face training of three CCPs took place in December 2019. Post-course feedback was positive and reflected the importance of all elements of the package.Initially participants confessed to feeling a little unsure before attending:Prior to the session I had completed the online transfusion training , howeverPrior to attending the session I was concerned that the level of knowledge I had regarding the management of any transfusion-related complications was insufficient and/or that my general knowledge about the more theoretical aspects of blood transfusion would be insufficient. (CCP2)We were pleased to hear that we had allayed these fears and provided them with an improved level of confidence:The unique environment critical care paramedics work in creates challenges in identifying adverse transfusion reactions, but the session covered them, with practical advice and solutions. Areas such as ABO blood types were also discussed but reassurances given that . . . limited exposure to blood products meant concerns were alleviated. (CCP1)I had convinced myself that spotting these reactions was somewhat of a dark art, they were things that I must by hypervigilant for. The reassurance that any reaction was likely to look like a normal anaphylaxis and that the treatment was the same has allowed me to relax a little. (CCP2)In addition, participants were keen to pass on this knowledge and enthusiasm and subsequently trained all 14 of their CCP colleagues within three months. There were surprises in the feedback, too. CCP2 stated:Going forward I see no reason that CCP-led administration within the RePHILL trial will be in any way different to enrolments made when a doctor is on board. Indeed, I feel it may be slightly more straightforward as we are perhaps more used to following the protocol and completing the required documentation.These comments support the authors’ argument that paramedics are already ideally placed to confirm eligibility for a trial. Firstly, trial inclusion and exclusion criteria mirror the structure of drug indications and contra-indications within the Joint Royal Colleges Ambulance Liaison Committee (JRCALC) guidelines  which paDuring the first ‘live’ case, a RePHILL doctor was present but left the actual enrolment to CCP3. This allowed the CCP to autonomously undertake the enrolment but with the RePHILL trained doctor available on scene for support should he have needed it. The CCP’s feedback showed how the training had boosted confidence:The training I received led to a slick and proficient RePHILL recruitment, and I was left feeling the patient had received the best possible care. Furthermore, had there been any adverse incidents I felt I would have had the knowledge to manage them appropriately. (CCP3)The second paramedic-led recruitment supports the reason for NMA training. The PHEM doctor had not yet completed trial training; therefore the opportunity to recruit this patient would have been missed. Once again feedback from the CCP involved supported the value of his NMA training:I won’t deny that I was probably a little rusty with it being the first enrolment I’d done post-pandemic, but I still felt fairly confident in carrying out the process, which is testament to the previous training provided. (CCP4)He also highlighted the importance of continued learning following the initial training:Moreover, as full-time CCPs, it has become apparent that our continued exposure and experience of enrolling patients to the trial has been beneficial to many of our doctor colleagues who do far fewer PHEM shifts and are less familiar with the logistics and processes involved. (CCP4)This comment highlighted something we had not considered when developing the training package. Having all clinical members of staff on scene trained in NMA ensures that mutual support can be provided. Sometimes it is not clinical grade or level of knowledge that is important; exposure and experience are equally valid.The growing appreciation of early transfusion-based resuscitation has led to a considerable interest in pre-hospital transfusion. The UK paramedic community are well placed to support both trials and transfusion . HoweverThe civilian paramedic literature suggests their role in pre-hospital transfusion is rarely formally published. However, the increasing interest in early blood-based resuscitation is stimulating an expanding scope of practice in both civilian and military practice. And there is a growing body of evidence to show that it is both safe and effective. For example, in a retrospective analysis of 136 trauma patient records between 2011 and 2015, an Australian study investigated paramedic blood authorisation and found that, in cases reviewed by a doctor, 90% of all decisions made by paramedics to give blood were appropriate .Established military programmes include pre-hospital plasma-only resuscitation using LyoPlas successfully introduced in 2011 by the Israeli Defence Force  and moreDuring the RePHILL trial there was no UK commercially available NMA course suitable for our paramedics. We therefore devised our short course primarily using material from the military-civilian THOR network which promotes pre-hospital transfusion. Their Blood Far Forward programme is designed primarily for the Austere Medical Environment . THOR fiAs the paramedic scope of practice continues to develop, they are increasingly involved in trials. Paramedics are uniquely placed to contribute to both the evidence base and practice development in pre-hospital transfusion. The pre-hospital environment is challenging both clinically and logistically and presents novel risks in transfusion practice. Consequently, we propose that new patterns of adverse events should be identified by all members of the pre-hospital team and reported to the national haemovigilance scheme, Serious Hazards of Transfusion (SHOT), to inform future policy and practice.Our training programme was developed for a specific trial and should not be currently used outside of that framework. However, the programme and experience serve to inform development of NMA courses for the wider pre-hospital community.We present the first structured course of its type aimed specifically at the paramedic profession in the context of a trial. The feedback suggests the programme provided CCPs the knowledge to autonomously recruit trial patients and authorise transfusion. Pre-hospital transfusion continues to develop, and we propose that paramedics have an important role in this. In addition, NMA courses should recognise the unique challenges of the pre-hospital environment.We are indebted to Dr Caroline Leech and The Air Ambulance Service team for spear-heading NMA within the RePHILL trial. We thank Dr Falguni Chocksey, Consultant Anaesthetist and Sarah Aston, Transfusion Practitioner from University Hospitals Coventry and Warwickshire NHS Trust for providing bespoke face-to-face training and for their support to the CCPs and the project.HS and HD designed the training concept and drafted the manuscript. All students cited have provided permission to directly quote from their reflective notes. HS acts as the guarantor for this article.None declared.HS is funded by the NIHR EME programme. EudraCT No.: 2015-001401-13. This report presents independent research funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.


Identification of indigenous medicinal plants, including the gathering of information regarding the uses of these plants can help find out their traditional pharmacological activities and their benefits for the community’s healthcare system. In this study, an ethnobotanical investigation was conducted in Shahrekord city, southwest of Iran to indicate the ethnobotanical knowledge about analgesic medicinal plants in the region and the methods of using them.  To this end, plant antioxidants and analgesic medicinal plants were identified. For this purpose, a questionnaire was used to obtain indigenous knowledge from traditional therapists in Shahrekord regarding pain relief using medicinal plants. This ethnobotanical study was conducted in 2018 with the participation of 29 traditional therapists of the region under purpose. Finally, the data drawn from the questionnaires were analyzed using the Excel software. The frequency of plants use was also calculated. Eugenia caryophylata (44%), followed by Alhagi maurorum (31%), Tribulus terrestris (27%), and angustifolia (24%). The Laminaceae family (7 species) was the most frequently used plant family for pain relief. The most frequently used plant organ to relieve the pain was flower (25%), followed by the stem (22%) and leaves (19%).Our study showed that in Shahrekord, 23 species of medicinal plants are used to relieve pain. The highest frequency of use was obtained for  Given the high importance of medicinal plants in Shahrekord, the results of this study and additional scientific investigations can help produce more effective and less harmful drugs from medicinal plants. Pain is one of the main causes of disability, anxiety, and job loss . Pain reShahrekord city is the capital of Chaharmahal and Bakhtiari province with an area of around 2006 km2, accounting for 12% of the total area of the province. According to the 2011 Iranian Population and Housing Census report, the township of Shahrekord has 283210 inhabitants, of whom 253629 people live in urban areas, and 29581 ones live in rural areas. Three dialects are spoken in the city, i.e., Persian, Lori Bakhtiari, and Turkish. The main occupations of the people of this region are agriculture and animal husbandry. Shahrekord’s map is shown in In this ethnobotanical study, traditional knowledge of the participants was collected using a questionnaire in 2018. To this end, the local knowledge of 29 traditional therapists in Shahrekord about the analgesic effects of medicinal plants was drawn with face-to-face interviews and a questionnaire. The questionnaire that had already been prepared was administered to the traditional therapists by the interviewers. The questionnaire included information about the location and demographic characteristics of the respondent and the local name(s) of the plant(s) and the organ(s) used. The interviewers personally referred to the respondents to elicit and record their beliefs about herbal medicine. Among the 29 traditional therapists, eight individuals were female, and 21 ones were male. The education level of the respondents was from high school diploma to master’s degree. The data drawn from the questionnaires were carefully tabulated. Data analysis was performed by the Excel software. In this study, the frequency of plant use was calculated by the equation below:Frequency of used= × 100Eugenia caryophylata (44%), followed by Alhagimaurorum (31%), Tribulus terrestris (27%), and ngustifolia (24%). Other information is presented in The results showed that in Shahrekord, 23 species of medicinal plants are used to relieve pain. As shown in Lavandula officinalis induces analgesia by affecting inflammatory processes [Melissa officinalis has a central analgesic mechanism [Origanum vulgare L. shows analgesic effect due to its antioxidant compounds. This plant produces analgesic effect through inflammatory processes and opioid receptors [Satureja bachtiarica Bung. exerts its analgesic effect through central mechanisms and inflammatory processes [Mentha piperita produces analgesic effect through both central and peripheral effects [Tanacetum parthenium exhibits analgesic effect through inflammatory processes [Hyoscyamus niger produces analgesic effect through cholinergic and opioid mechanisms [Cinnamomum verum exerts analgesic effect through prostaglandins and stimulation of opioid receptors [Zingiber officinale produces an analgesic effect by inhibiting the release of peripheral mediators and cytokines [Anthemis hyalinaDC. also produces analgesic effect through inflammatory processes [Plants have always played a substantial role in the health and well-being of human societies. The beneficial effects of the plants, reported in our study, on various diseases have been confirmed by numerous trials -32. Lavarocesses . Melissaechanism . Origanueceptors . Saturejrocesses . Mentha  effects . Tanacetrocesses . Hyoscyachanisms . Cinnamoeceptors . Zingibeytokines . Anthemirocesses . Each plrocesses -45. TherBased on the ethnobotanical knowledge in Shahrekord, several medicinal plants can be used as pain relievers due to certain pharmacological action mechanisms. The sedative and analgesic effects of some of these plants have already been reported. Regarding the difference in the ethnobotany of medicinal plants between the people of Shahrekord and those of other regions across Iran and different uses of different medicinal plants, as well as the availability of certain medicinal plants in the studied area, our findings on the knowledge of the indigenous people in Shahrekord about the use of medicinal plants may be useful. Besides, some medicinal plants used to relieve pain have not yet been adequately studied for this pharmacological activity. Therefore, if this therapeutic approach is chosen, the side effects of the plant(s) must be taken into account because medicinal plants are not completely harmless and their efficacy has not yet been definitely approved. Therefore, they should be investigated in well-designed clinical trials.The authors declare no conflict of interest.


Achalasia represents a chronic motility disorder of the esophagus featuring an impaired lower esophageal sphincter relaxation and loss of esophageal peristalsis. By causing dysphagia, regurgitation, aspiration and chest pain, achalasia might tremendously affect life quality of patients. However, the impact of achalasia on the development of mood disorders including depression has largely remained unclear. The aim of this study was to evaluate the incidence of depression in achalasia patients.We analyzed a large primary care cohort database in Germany capturing data from 7.49 million patients.A total of n = 1,057 patients with achalasia diagnosed between January 2005 and December 2018 were matched to a cohort of n = 3,171 patients without achalasia controlling for age, sex, physician, index year, and the Charlson comorbidity index. Interestingly, while the frequency of depression prior to the diagnosis of achalasia was comparable in both groups, new diagnoses of depression were significantly higher within one year after the diagnosis of achalasia compared to the control group, suggesting a direct and previously unrecognized association between achalasia and depression.Our data suggest that the clinical management of patients with achalasia should include a careful and structured work-up for mood disorders in order to improve long-term quality of life in these patients. The first description of achalasia goes back to Sir Thomas Willis in 1674. Today, achalasia is defined as a chronic disorder of esophageal motility characterized by an impaired lower esophageal sphincter (LES) relaxation and the loss of esophageal peristalsis , 3. OnlyAchalasia is characterized by a lack of relaxation of the lower esophageal sphincter. There is often also a disturbance in the peristaltic contractions of the esophageal muscles. In approximately 50% of cases, there is a fixed hypertensive contraction of the lower esophageal sphincter. All of these pathologies lead to the pathognomonic functional obstruction at the gastroesophageal junction. The specific pathophysiology of achalasia is only poorly understood. Different studies suggested that achalasia might occur due to a degeneration of the myenteric plexus and vagus nerve fibers of the lower esophageal sphincter , 5. ThisThe goal of achalasia treatment is to relieve the symptoms caused by the disorder. Both, surgical ) as well as non-surgical procedures are available –9. Howevth revision (ICD-10), while prescription data are coded using the European Pharmaceutical Marketing Research Association (EphMRA) Anatomical Therapeutic Chemical (ATC) classification system. The quality of the data is assessed regularly by IQVIA based on a number of criteria . The database includes only anonymized data in compliance with the regulations of the applicable data protection laws. It has previously been found that the panel of practices included in the Disease Analyzer database is representative of general and specialized practices in Germany ).Achalasia represent a very rare disease with a prevalence of about 10 cases per 100,000 inhabitants . To examAchalasia most probably results from a loss of the myenteric plexus and vagus nerve fibers of the lower esophageal sphincter . It has Our study has several limitations: Despite the German Disease Analyzer database used here has been validated in several medical studies , the conIn summary, our study is the first using a primary care provider database to demonstrate that achalasia is associated with an increased incidence of depression irrespective of other comorbidities or patients’ characteristics. Our data suggest that the clinical management of patients with achalasia should include a careful and structured work-up for mood disorders in order to improve long-term quality of life for these patients.


Cell-based therapy is the fastest growing segment of regenerativemedicine, a field that promises to cure diseases not treated by other smallmolecules or biological drugs. The use of living cells as the active medicinalingredient present great opportunities to deliver treatment that can trigger thebody’s own capacity to regenerate damaged or diseased tissue. Some of the challengesin controlling the quality of the finished cell-therapy product relate to the use ofa variety of raw materials including excipients, process aids, and growth promotionfactors. The quality of these materials is critical for ensuring the safety andquality of the finished therapeutic products. This review will discuss some of thechallenges and opportunities associated with the qualification of excipients as wellas that of the ancillary materials used in manufacturing. Cell-therapy products offer new solutions to treat unmet medical needsby providing therapeutic products based on living cells that can promote the body’sown regenerative capacity. The cell-therapy market is one of the most diversifiedsegments of the biotech industry; it includes human somatic and embryonic cells. Apatient’s own (autologous) cells as well as donated  cells or tissues canbe used to manufacture cell-therapy products. In both cases, the development andmanufacture of the finished product can require either minimal manipulation orextensive processing that can expose the cells to additional components. Majorchallenges in cell-therapy formulations are potential interactions between thecomponents used in manufacturing and formulation, and the living cells. As withother biologics, cell-based therapy formulations include a variety of excipients that are added to stabilizethe cells or to provide physiological osmolality. The manufacture of cell-basedtherapies often requires multiple steps where the cells are exposed to a variety ofcell culture supplements not intended for inclusion in the final product. These cellculture supplements are referred to as process aids, ancillary reagents, orancillary materials ; the finb)). The qualificationof intended excipients present in the finished therapeutic product is required per21 CFR 211.84(a). The United States Pharmacopeia’s book of public standards(referred to as a “compendia”), U.S. Pharmacopeia–NationalFormulary (USP-NF), definesexcipients under General Chapter <1078> as follows: “Any substances, otherthan the active drug or product, that have been appropriately evaluated for safetyand are included in a drug delivery system to either aid the processing of thedrug delivery system during its manufacture, protect, support or enhancestability, bioavailability, or patient acceptability, assist in productidentification, or enhance any other attribute of the overall safety andeffectiveness of the drug delivery system during storage or use.” While excipientsthat are intended to be used in cell-therapy formulations that meet the definitionwill be qualified and tested against compendial monographs when they exist, someof the materials used in manufacturing other than the excipients may end up in thefinished products. These ancillary materials are used as process aids for themanufacture of the cell-based therapies and for which removal from finishedproducts may not be consistently effective. Sakamoto etal.  Guidance onContent and Review of Chemistry, Manufacturing, and Control (CMC) Information forHuman Somatic Cell Therapy Investigational New Drug Applications (INDs) states to etal.  reportedviceversa) needs to be evaluated.The excipients and other materials intended for use in cell-basedformulations may have been qualified for use in other drug and biologicformulations. Table The use of established excipients is the preferred formulationapproach. However, this is not always an option and developers of cell-therapyproducts will often use non-pharmaceutical grade materials. In these situations,strategies need to be in place to control the safety and quality of all rawmaterials used in manufacturing. Risk assessment must address the complexity andmulticomponent nature of the raw materials. Animal-derived materials areconsidered to be a higher risk because of the potential of contamination withadventitious agents, and justification is needed for the use of such materials, aswell as testing to confirm absence of adventitious agents. Additionally,information on the country of origin is required per Good Manufacturing Practices(GMPs) regulations when using materials that carry the risk of transmissiblespongiform encephalopathy. The use of human-derived materials in cell-basedtherapies carries the risk of transmission of communicable diseases. In line withthe quality risk management described in ICH Q9, a risk mitigation strategy shouldinclude having controls in place to assess the impact of using animal- orhuman-derived excipients. While pharmaceutical-grade excipients are considered lowrisk because of their established safety profile, it is important to note thatsuitability of the excipient and its impact on the therapeutic effect of the cellsneed to be established. A strong qualification program is required to ensure thequality of excipients and other components used in the manufacture of cell-therapyformulations. Proper specifications are required to determine the suitability ofthese components during manufacture and in the final formulation. Themanufacturing history of these components as well as the vendor (preferably themanufacturer) needs to be documented. The relationship between the cell densityand the final concentration of the excipient needs to support the intended use ofthe excipient. The stability of the excipients should be assessed in the presenceand absence of the actual cell-therapy product given that the establishedstability profile of the excipient by itself may not be relevant once it is addedto the formulation. It is also critical to determine if potential degradation ofthe excipient might have deleterious effects on the finished product. Overall, thestability and viability the cells and expression of therapeutic entity needs to beestablished. While the intent is to remove the non-cellular components fromfinished cell-therapy products, residual levels of ancillary materials may remaindue to ineffective washing steps or because of uptake or binding to the cellularcomponents. The development of robust assays to measure levels of ancillarymaterials in the final formulation is critical to show the effectiveness of theirremoval. If residual amounts of the ancillary materials are present in thefinished product, they should be qualified including toxicity assessment in animalmodels or other systems.Cell-therapy products prepared for specific patients  can be maintained in liquid suspensions orformulations until administration. For other cell-therapy applications, the timingbetween cell collection/processing and administration to the patient may requirean additional hold time. In these situations, cryopreservation may be a suitableapproach to maintain product stability during storage and shipping steps. CryopreAmong biologic drugs, cell and tissue therapies are unique in thesense that their “active ingredients” may be living cells capable of continuousgrowth and they can secrete metabolites, cytokines, and other growth factors inthe media. This may increase the possibility for excipients to interact with mediacomponents, and cells and their functions may be impacted because of theseinteractions. It is therefore critical that a risk assessment strategy for thequalification of excipients used in cell-based therapies encompass elements beyondstandard approaches for excipients used in drugs and other biologics. Cell-therapymanufacturers need to address the functionality and stability of the excipientsused in these applications. The functionality of an excipient established within aformulation for another drug or biologic may or may not be extrapolated to acell-therapy formulation and may require testing of multiple batches of theexcipient in multiple batches of the cell-therapy product. Another challenge ismultisource suppliers of the same grade of excipient which can lead tobatch-to-batch or supplier-supplier variability and, potentially, inequivalentperformance of the excipient. The successful manufacture of a robust productrequires the use of well-defined excipients and processes that together yield aconsistent product (USP <1078> (viceversa) and that this impact may be further amplified by thebatch-to-batch or supplier-supplier variability. The introduction of novelexcipients or other elements in the formulation of cell-therapy products must takeinto account and address the possible impact on the quality of the finishedproducts. Cryopreservation media components must be evaluated in order to maximizethe therapeutic efficacy of the cells. Components of formulations used in celltherapies must be of the highest quality to ensure consistency in manufacturing andquality and safety of finished medicinal products. Quality of these components maybe achieved by testing against established public standards such as USP standardsfor excipients and ancillary materials.As cell-therapy applications are increasingly introduced to themarket, qualification of ancillary materials used in manufacturing should beaddressed as well as excipients because of the potential for residual ancillarymaterial in the finished products. Regardless of whether the material is anexcipient or an ancillary material, the functionality of the material needs to beaddressed in the context of the formulation as these materials may interact with theliving cells impacting their function (and


Endoscopic ultrasound (EBUS) strain elastography can diagnose intrathoracic benign and malignant lymph nodes (LNs) by reflecting the relative stiffness of tissues. Due to strong subjectivity, it is difficult to give full play to the diagnostic efficiency of strain elastography. This study aims to use machine learning to automatically select high-quality and stable representative images from EBUS strain elastography videos.LNs with qualified strain elastography videos from June 2019 to November 2019 were enrolled in the training and validation sets randomly at a quantity ratio of 3:1 to train an automatic image selection model using machine learning algorithm. The strain elastography videos in December 2019 were used as the test set, from which three representative images were selected for each LN by the model. Meanwhile, three experts and three trainees selected one representative image severally for each LN on the test set. Qualitative grading score and four quantitative methods were used to evaluate images above to assess the performance of the automatic image selection model.A total of 415 LNs were included in the training and validation sets and 91 LNs in the test set. Result of the qualitative grading score showed that there was no statistical difference between the three images selected by the machine learning model. Coefficient of variation (CV) values of the four quantitative methods in the machine learning group were all lower than the corresponding CV values in the expert and trainee groups, which demonstrated great stability of the machine learning model. Diagnostic performance analysis on the four quantitative methods showed that the diagnostic accuracies were range from 70.33% to 73.63% in the trainee group, 78.02% to 83.52% in the machine learning group, and 80.22% to 82.42% in the expert group. Moreover, there were no statistical differences in corresponding mean values of the four quantitative methods between the machine learning and expert groups (p >0.05).The automatic image selection model established in this study can help select stable and high-quality representative images from EBUS strain elastography videos, which has great potential in the diagnosis of intrathoracic LNs. The differential diagnosis of malignant and benign intrathoracic lymph nodes (LNs) is an important medical problem related to the diagnosis and prognosis of intrathoracic diseases. Compared with surgical examination, needle techniques are recommended as the first choice to obtain tissues , 2. EndoPrevious literature mentioned that ultrasonographic features were suggested to be used for predicting benign and malignant diagnosis of patients undergoing EBUS-TBNA . EBUS imWith respect to qualitative analysis of strain elastography image, the five-score grading method had specific classification and when score 1–3 was defined as benign and score 4–5 as malignant, the diagnostic accuracy in predicting malignant LNs can reach 83.32% –23. QualIn recent years, with the development of machine learning algorithm, machine learning has shown an important role in the field of medical imaging with favorable performance, such as skin cancer, retinal fundus photographs, gastrointestinal endoscopy, chest CT and other aspects –27. By e18F-FDG uptake detected  by positron emission tomography (2); Pathological confirmation was clinically required and EBUS-TBNA examination was feasible (3); Patients who did not have contraindications to EBUS-TBNA and signed informed consent. LNs with qualified strain elastography videos were analyzed in the study. LNs in December were used as the test set to assess the automatic representative images selection model and the remained were used as the training set and validation set. This study was approved by the local Ethics Committee of Shanghai Chest Hospital (No. KS1947) and registered at ClinicalTrials.gov PRS (NCT04328792).Patients who met the following criteria and underwent EBUS-TBNA examination in Shanghai Chest Hospital from June to December 2019 were enrolled in this study (1): At least one enlarged intrathoracic LNs (short axis >1 cm) based on computed tomography (CT), or at least one positive LNs were examined by the ultrasound bronchoscopy  and EBUS strain elastography videos were recorded by the ultrasound processor . The operator detected the location of the target LN and measured the EBUS size at the maximal cross-section of grayscale mode. After observing the grayscale and blood flow Doppler modes, the operator switches to the strain elastography mode and elastography imaging was formed through the patient’s respiration, cardiac impulse and blood vessel pulse generally. In the case of unsatisfactory imaging, the operator shall exert appropriate pressure to the target LN by pressing the up-down angle lever of bronchoscope at a frequency of three to five times per second to obtain better imaging. The maximal cross-section of the LN was recorded and two 20-second videos were saved . SubsequThe training set and validation set were randomly divided at a quantity ratio of 3:1 to train the model with optimal hyper-parameters. The same proportion of benign and malignant LNs was maintained in the two datasets. We developed models with various values of hyper-parameters on the training set and assessed these models on the validation set to determine the hyper-parameter according to the performance. Once the hyper-parameter was determined, we used both the training set and validation set to train the model for prediction and evaluation on the test set. In this paper, the hyper-parameters included the number of representation patterns and whether adopting the update-and-predict strategy or not. The candidate numbers of representation patterns included 32, 64, and 128. Blind to the final diagnosis of LNs, two experts with experience of EBUS images observation >500 LNs assessed the image quality of the validation sets together as following: score 1 , score 2 , score 3 , score 4 , score 5 . Scores 1–3 are classified as benign and 4–5 as malignant 2. When In real-world applications, however, it is hard to collect a training set that has sufficient examples to cover all possible situations and guarantee the generalization ability of the trained model. Consequently, a limited training set usually leads to a performance gap, when applied to the real data. To narrow this gap, in the phase of prediction, we proposed an update-and-predict strategy that ran the trained model twice on the test set. The first run produced the initial predictions of test videos which were used for updating the cluster centers in the model. Subsequently, the updated model was used to obtain the final predictions on the test set. Note that the K-means clustering is an unsupervised learning algorithm that does not require manual annotation or ground truth. Therefore, we leveraged K-means clustering in this paper to update our model using only the predictions of test videos rather than accessing their labels. The label information was not leaked in the phase of prediction. As a result, we can narrow the gap between the training set and test set and do not cause the leakage of label (supervision) information by using the update-and-predict strategy.For the three images selected by the automatic image selection model on the test set, the same two experts evaluated grading score together. Expert group and trainee group (experience of CP-EBUS image observation less than 30 LNs) were employed to select representative images which were used for comparison with that of machine learning. The three experts reviewed two elastography videos of each LN and selected one representative image for qualitative evaluation, respectively. Qualified images shall cover the maximal cross-section of the target LN and have good repeatability . Three tFor qualitative score, the Friedman test was used for the differences among the three images selected by the automatic image selection model and experts, and the Wilcoxon signed-rank test was used for the pair comparison. For quantitative variables, receiver operating characteristic (ROC) curve was used to obtain the area under the curve (AUC) and the cut-off value with the best diagnostic performance. The paired t-test was used for quantitative mean values comparison between images of the machine learning model and experts. The stability of the quantitative results within the three groups was evaluated using the coefficient of variation (CV), and the comparison of the CV among the three groups was further analyzed by the paired t-test. The p value <0.05 was considered statistically significant for above statistical analyses. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for differentiating benign and malignant LNs were calculated by the corresponding formulas. All statistical analyses were performed by SPSS version 25.0 .A total of 415 LNs from 351 patients  were analyzed in the training and validation sets, and 91 LNs from 73 patients  were used as the test set Table 1.To evaluate the stability of machine learning selected images, we analyzed the differences between the three pictures of machine learning, expert and trainee groups, respectively. Results demonstrated that there was a statistical difference in the expert group, while the images of machine learning and trainee groups were relatively stable Table 2.In order to assess machine learning selected images more objectively, paired t-test was conducted on quantitative results of machine learning and expert groups. No statistical difference between the two groups was found which demonstrated that images selected by machine learning can reach the expert level Table 4.The ROC curves were performed on quantitative results of the three groups and cut-off values with the best diagnostic performances were drawn Figure 4Lung cancer is the leading cause of cancer associated morbidity and mortality around the world . PulmonaTraditional qualitative methods are convenient for clinical application, but subjectivity and the difference in experience between different doctors can affect the accurate diagnosis. Images used for quantitative analysis are still manually selected which cannot avoid subjectivity. The CV values in This study still had some limitations. Since there was no restriction on the type of disease included, the machine learning model was only suitable for the diagnosis of intrathoracic LNs enlargement, and further studies were need to determine whether or not this technique is valid to the stage of lung cancer. Besides, although high-quality images were selected from elastography videos, no diagnosis was made by the model for these images, and EBUS modes of grayscale and blood flow Doppler were not applied. The automatic EBUS multimodal image selection and diagnosis may be more convenient for clinical application. Moreover, this was a single-center retrospective study with limited number of LNs and some diseases accounted for limited proportions. Prospective studies and more LNs to train, validate and test the model may acquire more stable models and more convincing results. Thus, it was worthwhile to carry out multi-center studies to improve the outcome of the model .In conclusion, through the application of machine learning algorithm to EBUS strain elastography, we realized the automatic selection of high-quality and stable images from strain elastography videos. The automatic image selection model needs further prospective clinical validation and has potential value in guiding the diagnosis of intrathoracic LNs.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Ethics Committee of Shanghai Chest Hospital. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. Written informed consent was not obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.XZ collected videos, selected representative images, conducted qualitative and quantitative analysis of LNs, and performed statistical analysis. JL designed the machine learning model for automatic selection of representative images. JC and XZ evaluated images selected by machine learning. FX, LW, and JS selected representative images and scored them qualitatively as the expert group. JS and WD designed the study and reviewed the manuscript. JS and HX supported this study. All authors contributed to the article and approved the submitted version.This work was supported by National Natural Science Foundation of China , Shanghai Municipal Health and Medical Talents Training Program (grant number 2018BR09), Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (grant number 20181815), and the Program of Shanghai Academic Research Leader (grant 17XD1401900).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.The reviewer MC declared a shared affiliation with the authors to the handling editor at time of review.


The aim of the investigation was to study the integration between native human dental tissue and new-generation biomimetic materials replicating the mineral-organic complex of dentin and enamel using IR microspectroscopy for multidimensional visualization and analysis.The conditions for stable integration at the interface between biomimetic material and natural hard tissue were identified using a biocomposite buffer system of nanocrystalline carbonate-substituted calcium hydroxyapatite corresponding in its total characteristics to human dentin-enamel apatite and a number of amino acids present in the organic matrix of dentin and enamel: L-histidine, L-lysine hydrochloride, L-arginine hydrochloride, and hyaluronic acid. The finished samples were studied using IR microspectroscopy on IRM channel equipment .The characteristic features of the biomimetic buffer layer at the interface between the enamel and dental material were revealed and visualized based on IR mapping of absorption intensity for particular functional molecular groups with the use of synchrotron radiation, location of the functional groups involved in the processes of biomimetic composite integration was identified. Despite the recent advances in dental materials science, the cements and filling materials employed to restore the anatomic bases of human teeth or their parts have low affinity for the teeth enamel and dentin , 2. As aAt the same time, numerous studies focus on the interaction of synthetic material with dental tissues as well as formation of a biomimetic buffer layer at the interface between the natural hard dental tissue and the dental composite –5 supposGiven that dentin and enamel are structurally organized biological nanocrystalline composites with meso- and nanoporous structure, with anisotropy of mechanical, optical, and trophic properties , developIt is important to note, there have been repeated attempts to use the biomimetic principle for reproducing the organic-mineral complex of teeth and achieving enamel- and dentin-like structures in composites , 18–21. One of the methods that have proven effective in the study of biological objects is infrared (IR) Fourier-transform microspectroscopy –32. The Application of synchrotron IR microspectroscopy has already enabled us to achieve the necessary spectral resolution and reliably identify changes that occur in the molecular composition of samples in case of caries , 36.The aim of the investigation was to study molecular and chemical properties of the layer formed at the interface between the dental material, the biomimetic composite and the hard dental tissue using multidimensional visualization of synchrotron IR microspectroscopy data.Buffer layers of biocomposite materials were studied and conditions for achieving stable functional bonds at the interface between the biomimetic material and the natural hard tissue were identified using the specimens of teeth extracted from patients aged 18–45 years for orthodontic indications. To avoid long-term calcification processes, teeth specimens with initial fissure caries were prepared immediately in accordance with the diagnosed pathology and approved standards.In all specimens, a cavity was formed in the enamel preserving the untreated dentin, using a water-cooling system to avoid overheating of the dental matrix. The surface of the obtained cavity was covered with a biocomposite buffer system containing nanocrystalline carbonate-substituted calcium hydroxyapatite (CHA) developed by us and corresponding in the main characteristics to human dentin-enamel apatite , 38 and –1 at a spectral resolution of 4 cm–1.The resulting slices were studied by IR microspectroscopy using optical channel equipment for IR microspectroscopy  coupled with Vertex 80v IR spectrometer and Hyperion 3000 IR microscope with a detector cooled by liquid nitrogen  . The selThe Australian source of synchrotron radiation with the macro ATR-FTIR attachment was used to study the sections of the interface between the dental material, the biomimetic composite, and the enamel. There were constructed IR maps of IR luminescence intensity for a particular functional molecular group in the area of dental material and tooth enamel integration using the algorithms presented in paper .3) present in the dental material composition based on Bis-GMA (1725 cm–1) [2–CH3 (1457 cm–1), and amide bands at 1650 cm–1 (Amid I), 1550 cm–1 (Amid II), 1240 cm–1 (Amid III), present in both biomimetic composite and native tissue, they also belong to the inorganic components of enamel apatite and biocomposite (PO4 group at 1100–900 cm–1).Studies of the interfacial boundary between the light-cured dental material, the biomimetic composite, and the enamel made it possible to determine a set of basic vibrational modes in the IR spectrum that can act as spectroscopic signatures of molecular groups corresponding to the materials present in the integration area. 25 cm–1) , moleculThere is no morphological/molecular information on the presented IR map of complete absorption spectrum of the interfacial area between the dental material, biomimetic composite and the enamel of the sample. This IR map displays color-coding only for the main band intensities in the absorption spectra from various points on the sample surface, where certain chemical components are present.The characteristic IR spectra obtained using synchrotron IR microspectroscopy from each of the studied areas in the interface between the dental material, the biomimetic composite and the enamel –5 contai–1) contain information on the spatial distribution of the dental material, the organic and mineral (apatite) components across the studied sample section at the interfacial boundary of three media. Blue color encodes the lowest absorption intensity of a particular molecular group, while red indicates the highest one.The presented one-dimensional images (IR maps) produced based on color-coded intensities of three main spectral bands  made it possible to detect visually the interfacial boundary between the enamel and the dental material. Information analysis shows that dental material area does not contain phosphate groups. The entire region adjacent to the enamel with active spectrum vibrations of nonzero intensity in the range 1104–988 cm–1 has dimensions of ~14 μm and is indicated in  apatite , 35, 36.4 group vibrations from 1.5 to 6.5 relative units is of particular interest , correlating with molecular groups characteristic of the organic enamel component and present in the biomimetic buffer layer . It is important to emphasize that this vibration does not overlap with other bands and, therefore, makes one-dimensional IR absorption analysis based on this parameter more reliable and informative as to the spatial distribution of dental material in the studied area.However, one more absorption band located at 1725 cmarea see . As show3) is similar to the location of the material observed in the optical image (see It can be seen in mage see . Particumage see .–1 revealed that the interaction between the dental material and the enamel occurred through a buffer layer. It is necessary to underline that simultaneous analysis of several IR maps based on the analysis of selected and even single bands does not always allow visualization of changes in the heterophase boundary between structurally similar materials. This is associated with the limitations of one-dimensional approach to detecting spectral changes. The above problems can be solved by using multidimensional clustering methods offering the possibility to classify vast arrays of component spectra efficiently. Using this approach, we managed to analyze the features of the complex interface between the dental material, the biomimetic composite, and the tooth enamel. Simultaneous analysis carried out with regard to all the features in the spectral ranges of 1760–1690 and 1520–1360 cmIt is schematically shown in the area marked with a broken line in We have demonstrated the possibility of using molecular multidimensional IR imaging to study the integration between new-generation biomimetic materials replicating the mineral-organic complex of the enamel and native hard tissues of the human tooth.Based on IR maps of intensity for particular functional molecular groups obtained using synchrotron radiation, we have revealed the differences between the healthy tissue, dental material and the biomimetic buffer layer at the interfacial areas and identified location and concentration of functional groups involved in the processes of biomimetic composite integration with native hard tissues of the human tooth.The obtained microspectroscopy data reliably confirm the chemical differentiation of the materials and the presence of organic and mineral interaction at the interface between the biomimetic system and natural hard tissues of the human tooth.