To physically interact with a rich variety of environments and to match situation-dependent requirements, humans adapt both the force and stiffness of their limbs. Reflecting this behavior in prostheses may promote a more natural and intuitive control and, consequently, improve prostheses acceptance in everyday life. This pilot study proposes a method to control a prosthetic robot hand and its impedance, and explores the utility of variable stiffness when performing activities of daily living and physical social interactions. The proposed method is capable of a simultaneous and proportional decoding of position and stiffness intentions from two surface electro-myographic sensors placed over a pair of antagonistic muscles. The feasibility of our approach is validated and compared to existing control modalities in a preliminary study involving one prosthesis user. The algorithm is implemented in a soft under-actuated prosthetic hand (SoftHand Pro). Then, we evaluate the usability of the proposed approach while executing a variety of tasks. Among these tasks, the user interacts with other 12 able-bodied subjects, whose experiences were also assessed. Several statistically significant aspects from the System Usability Scale indicate user's preference of variable stiffness control over low or high constant stiffness due to its reactivity and adaptability. Feedback reported by able-bodied subjects reveal a general tendency to favor soft interaction, i.e., low stiffness, which is perceived more human-like and comfortable. These combined results suggest the use of variable stiffness as a viable compromise between firm control and safe interaction which is worth investigating further. An upper limb amputation leaves a person with limited ability to perform work and daily living activities, but also hinders social interaction and the perception of self-image . Even though our work is inspired by Sensinger et al. , there aAlthough the use of cocontraction to control impedance could compromise the standard adoption of this feature as a switching technique, it is important to stress the existence of other available options in the market for switching, e.g., sequences of time-based contractions, external inputs, etc. Moreover, it is true that not all prosthetic systems need switching to operate. One example of this is the common tridigital myoelectric hand, while another is the soft-underactuated prosthetic hand  from the online manipulation of a pair of sEMG signals, recorded from two antagonistic muscles. Nonetheless, several theories in motor control try to explain the neurophysiological variables and their dynamic relation to define both position and stiffness commands in natural conditions. Feldman  define RC proportional to the integral of the EMG signals difference. Here, users can relax their muscles when the hand is closed and just activate them to move the hand in aa explicit direction (closing or opening). An additional feature is the reduction of involuntary activations due to external perturbations, to which PPC is more sensitive.In conventional systems, the simplest way to control one Degree of Freedom (DoF) prosthesis is by the so-called proportional position control approach (PPC), where the motor voltage is proportional to the difference between the EMG signals amplitude  of the motor controller, can strongly modify the performance of a robotic system , and the stiffness with their sum. When adjusting task-related grasp forces with an impedance controller, lower cocontraction results in higher compliance, allowing gentle grasping of fragile or deformable objects. Instead, higher stiffness values are experienced when grasping heavier or more rigid objects. This feature enables smooth modulation of the hand estimated force, while still allowing for task completion . Is is proportional to the total activation of user's muscles and it is calculated as the weighted average of the level of activation from two antagonistic muscles  to isolate voluntary cocontraction in a binary  detection signal CD. In particular, Ic is defined asTo properly decouple user's stiffness intentions from position commands, we introduce and monitor the cocontraction index , pure cocontraction phenomena, unless perfectly symmetrical and synchronized (which never happens in practice), would be interpreted as either open or close command, depending on which of the two EMG signals is observed overcoming its activation threshold first.The FSM used to discriminate the user's intended actions is introduced in RC, in analogy with typical velocity control frameworks, is updated according to the differential equation,The state transitions regulate FSM operation and, when met, let the system jump from the present state to another. The definition of the hand RC and RS are simultaneous and independent, thus the algorithm keeps generating commands of position and stiffness simultaneously. It is possible to observe that there is some correlation between motion commands and stiffness, since when the user contracts one muscle, e.g., to close the hand, the stiffness command will always be larger than the minimum it has at rest, imitating the natural behavior of muscles, which is a desired and welcome effect.Note that the calculation of In this section, we present an example of the behavior of the proposed algorithm, and compare it to existing methods, highlighting the different interpretation of the user's intended actions. In this case, the EMG data were collected from a healthy subject . Two commercial sEMG sensors  were used to acquire the inputs from the subject. The sensors, commonly used in commercial prostheses, include base signal conditioning to reject electric line noise, amplify, and rectify the signal. The onboard sensing was achieved using a custom electronic board  and Ic (bottom) as extracted from the signals of Is tends to rise both in the case of cocontraction and of pure contraction. This behavior reflects the natural behavior of antagonistic muscles, but complicates the detection of pure cocontraction phenomena, if it was based on the value of Is. This intuition motivates the introduction of the index Ic (bottom panel), which correlates with pure cocontractions more accurately. For this reason, we compare it with a threshold ThCD to reconstruct the binary cocontraction detector CD.RC, applied to the same signals of PPC: Proportional Position Control (top);PVC: Proportional Velocity Control with the use of FSM without explicit coconctraction detection;PVC/CD: Proportional Velocity Control with explicit coconctraction detection CD, as extracted from the bottom panel of CD. This is the same as using the finite state machine shown in CD = 0.Note that method PVC uses a finite state machine with the same states and transition of case PVC/CD, but which does not considers EMG1 = FDS and EMG2 = EDC, has the problem of interpreting cocontraction as if it was a reduction in the level of activation, a behavior which can be in opposition to what is intended by the user. This could result in an opening of the hand when a stiffening or a faster motion in the opposed direction is being intended. In addition, although PPC is more reactive to muscle variations, the subject must keep its muscles active to maintain the hand closed, increasing the risk of fatigue, both physical and mental.PPC  top, beiThe introduction of PVC  middle cCD and the PVC/CD method , a 19 DoF robust and functional prosthetic hand with an underactuated design that allows the actuation along the first grasp postural synergy using a single motor , impedance control was implemented by adjusting online the proportional gain of the controller, called as stiffness reference and defined as inhs and ls the high and low saturations. Is has been previously low-pass filtered. Since the SHP has already a mechanical compliance model, which is explained in detail in Della Santina et al. (KSHP). As KSHP increases with the relative angle between the joints of the fingers, motor stiffness is more relevant in configurations where KSHP is larger, as it occurs when the hand grasp tightens around a target object.being a et al. , the actTo explore the feasibility of using our algorithm for the impedance control of a prosthetic hand, and preliminarily investigate how this could affect the use of the prosthesis during daily life (in section 7), we present a pilot test executed on a single prosthesis user. For the moment, this prevents any possibility of generalizing our results over patient variabilities that can arise due to several factors, the most important of which are the differences in their residual limbs and in their specific muscle conditions. This effort is deferred to future extensions of this study, that will include a larger and statistically significant number of amputees.The subject involved  has a congenital malformation at the trans-radial level of the left arm. She is a customary user of a cosmetic prosthesis, but she is also familiar with myoelectric prostheses. Although she can properly control standard myoelectric hands, with two independent antagonistic EMG signals, she is not used to include the artificial hand in the execution of ADL, or in interactions with other humans. In addition, even though natural coactivation can be found in her EMG recordings, the user has never intentionally used coactivation as a control input to command prostheses, neither for the control of impedance, nor for switching. To account for this, a training phase was performed to let the user learn the voluntary use of coactivation. All procedures (including experiments in section 7) were executed under the approval of the Ethical Committee of the University of Pisa and with informed consent from all participants.This experiment analyses the differences in performance of four control modalities in response to external disturbances:PPC-HS: Proportional Position with High constant Stiffness;PVC-HS: Proportional Velocity with High constant Stiffness;PVC-LS: Proportional Velocity with Low constant Stiffness;PVC-PS: Proportional Velocity with Proportional Stiffness.Following the results of section 4, all modalities with proportional velocity control (PVC) use the proposed PVC/CD method to decode user's intended actions, also in the cases where the stiffness is constant. All control systems were implemented on the same hardware presented in section 5. The implementation of the hand stiffness control, as well as the method used to estimate the grasp force, are analogous to Ajoudani et al. . The firThe user was let to familiarize with cocontraction for 5 min before starting the experiment. She was asked to perform cocontractions of different amplitudes and durations. Visual feedback of the FDS and EDC levels was being provided during the trial and the training, to assist the user in maintaining steady cocontraction levels and properly activate both muscles simultaneously.The user was asked to grasp and hold a plastic bar (2 cm diameter and 32 cm length), in front of her. An experimenter then pulled the bar from both extremities, toward the distal side of the prosthetic hand, as to pull it away from the grasp see . Then, tIn a first condition, the described action was repeated, in each of the four control modalities, with the user being instructed to not oppose to the pulling action. This condition is called “involuntary reaction,” based on the consideration (see the section 6.3 for a discussion) that it is still possible to observe some reactions of the subject-prosthesis ensemble, both at the level of user's muscles , and at the level of hand motors (τ variations due to changes in the hand position and in the stiffness command).Then, the experiment was repeated again, for the four control modalities, in a condition in which the subject was instructed to voluntary apply cocontraction before the external perturbation was applied (condition “voluntary cocontraction”). No intentional closure or aperture of the hand was executed in order to evaluate the reaction of the system with respect to cocontraction modulation only.For each of the eight experimental conditions described, the user executed one repetition, to obtain a representative sample of subject muscle activation and not be affected by fatigue. Afterwards, to evaluate more thoroughly the possibilities offered by the proposed control method (PVC-PS), we repeated the action in the “involuntary reaction” condition for 10 trials and present its results.RC as reconstructed by the different control modes, and the current position (C), measured by a magnetic encoder, which is part of the standard setup of the prosthetic hand. Both quantities are relative to the position of the motor that controls the synergistic closure of the prosthesis. Just in the proposed method (PVC-PS), which is the only one with variable stiffness control, the third panel displays the observed stiffness index and the final reference stiffness commanded to the system. The bottom panel for each condition reports a reconstruction of the torque (τ) that the motor exerts on the hand along its synergistic direction of motion, which is directly proportional to the force applied to the object. This is controlled (by the embedded hand controller) to be proportional to the difference between the reference command (RC) and the measured motor angular position (C), multiplied by the stiffness of the controller (RS), as inBased on a model of the dynamic behavior of the controlled motor, the actual output torque can be reconstructed asKBEF is an experimentally defined correction constant. All variables are normalized and expressed in percentage.where ω is the speed of the hand and C and RC values. In particular, when the RC arrives to the maximum and the difference between C and RC is constant for three samples, this suggests the success of the grasp and marks its beginning. To mark the end of the grasp, we look for when the difference of C and RC changes its sign, indicating that an intended action of opening has initiated.In each of the conditions, we mark the beginning and the end of the grasping action and the interval of grasp. The beginning and the end of the grasping action are extracted with a threshold detection on the correspondent EMG signal . The grasping phase, where the cylinder is already grasped, is extracted from the analysis of From those, it is possible to extract a series of metrics characterizing the various trials, that are reported in Finally, This validation confirmed that the implementation of the different control modalities make the system behave differently, as it is already appreciable in The results from IR condition of the PPC-HS and PVC-HS see , show thRC is very difficult in PPC, as the hand opens because of the excessive increase of EDC , we observe how the involuntary reaction to external perturbations only affects the reference stiffness and, therefore, the grasping force when required. This is visible in Finally, we observe that the use of voluntary cocontraction is minimal (approximately 10 s), as the prolonged contraction of muscles is considered fatiguing by the user. However, for a PVC with variable stiffness control, it proved to be very useful to react to perturbations and adapt to different situations.Kp) in PVC-LS, the difference between RC and C, when the grasp is considered successful, is much larger. Moreover, although proportional position controllers (PPC) are more reactive by definition, the results show longer grasping times than in PVC-HS. This issue could be caused by the difficulties encountered to fine control the hand closure with PPC.To sum up, with variable stiffness control, the estimated force varies along the grasp action adapting to different conditions, both external (such as disturbances), and internal (such as reflexes and voluntary changes in cocontraction). This results in a larger force and a more rigid grasp only when needed or desired. Therefore, the hand is more responsive to unexpected situations, while remaining adaptable and soft otherwise, promoting thereby human interaction and collaborative tasks. Please refer to the Finally, in These repetitions reinforce the feasibility of the algorithm and the need of a myoelectric algorithm that understands better external situations and user intentions, and adapt the system accordingly, as the one we proposed. Although the present work does not provide evidence on the extendibility of our results to other prosthesis users, the positive outcomes suggest further investigations, especially in subjects with similar muscle conditions. These would be useful toward studying generalization to different patients, effects of fatigue, attentional requirements, and embodiment.The previous protocol helped the user in familiarizing with the capabilities of the various control modalities implemented in the SHP. This section compares different stiffness control modalities to explore the potential of variable stiffness in some Activities of Daily Living, that include self-interaction and social interaction. The compared control modalities are: high constant stiffness, low constant stiffness, and variable stiffness . Since the previous section confirmed the poor performance of PPC, both in terms of risk of fatigue and control finesse, only PVC is used to control joint position in all conditions. Accordingly, the different behaviors experienced during the experiment are mainly related to different stiffness behaviors.The ultimate purpose of this investigation is to evaluate the needs of prosthesis users, in terms of hand stiffness modulation, when performing different types of tasks. Therefore, despite being aware of the limitations of performing this pilot study with just one user, we consider the opinion and experience of a prosthesis user very valuable. Moreover, we analyse the preferences and opinion of able-bodied subjects that interact with the user as secondary subjects. The authors believe that it is also important to know what people expect or want when interacting with robotic hands to improve and normalize their acceptance in society.To account for the variability in human interaction preferences, the experimental protocol is repeated with 12 secondary subjects. These secondary subjects are limb-intact people  with normal motor and cognitive functions, able to understand the experimental procedure. The same prosthesis user presented in section 6 participated in this study. All subjects (1 limb-loss + 12 limb-intact) gave informed consent.Our hypothesis is that a stiffer control may result in a very rigid grasp, which can cause difficulties in bimanual or collaborative tasks. However, the same modality can improve user's reliability when moving heavy objects, where a very strong grasp is needed in order not to lose the item. Likewise, the authors hypothesize that a softer control would be perceived as safer and more comfortable, and increase the overall quality of the social and self-interaction.The prosthesis user is asked to execute a sequence of tasks, designed to require different amount and modulation of grasping force involved. The experimental tasks are divided in two groups. The first group of tasks is performed by the prosthesis user alone see :T1. Lifting a heavy object (full tool case) from the floor to the table;T2. Self-interaction T3. Bimanual manipulation: grasping several objects characterized by different properties  with the prosthetic hand, pass them to the intact hand, and then release them.The second group of tasks foresee physical interaction with the secondary subjects. These tasks allow us to study the perceived effects of the various controllers in physical social interactions between humans, mediated by a robotic prosthesis. They are:T4. Hand-shaking  of 2.4 g,Full plastic bottle (0.5 L) of 0.5 kg,Metallic tool case (395 × 300 × 135 mm) of 4 kg.Two of the three plastic cups were filled with wooden balls  to slightly increase their weight. One of the cups was completely full of balls, while the other one was half-full.For each secondary subject the experimental protocol was repeated with the three different control modalities. Subjects (prosthesis user and secondary subjects) were naive about the modality implemented on the system. The presentation order of the control strategies was randomized by blocks in order not to favor any possible learning. Moreover, this randomization increases the difficulty for the prosthesis user to recognize the control properties over iterations. Inside of each block, the order of the objects presented in T3 and T5 was also randomized for each subject to avoid the learning of the force required to move the objects.As underlined in Biddiss and Chau , standarOnly the prosthesis user is required to compile the System Usability scale (SUS)  criterion, only to the questions that showed an overall statistically significant difference from Friedman ANOVA.Due to the dataset being discrete and not normal (Lilliefors test), we applied Friedman ANOVA test for pairwise non-parametric data. In the case of secondary subjects, the opinion between control modalities was dependent (pairwise), while for the SUS test was also considered dependent, even if all answers came from the same prosthesis user, as we found differences at the SUS data distribution over time. ANOVA test informs whether there is an overall difference between groups , but it does not tell which specific group differed from others—We feature p-values obtained for all SUS questions are reported in The Friedman Please, note that the last raw of p-values from Friedman test are detailed in the caption, while significance between control modalities is presented through asterisk after the post-hoc test, directly on the plots. Questions Q2 and Q4, which refer to “human-likeness” and “comfort” presented significance with favorable results for low stiffness.The same statistical analysis of Friedman + Tukey's was done to the results from secondary subjects, where The fact that we obtained statistical significance, both in primary and secondary questions, presents evidences in favor of the hypothesis that the different strategies implemented influence subjects' perception. Moreover, we can also infer the difficulties on task execution from the differences in performance.Looking at the evolution of the SUS answers, it is possible to appreciate a trend which could suggest the existence of an adaptation process. This could be due to the task learning, or to the fact that the user, over iterations, learned to recognize the controllers and thus adapt faster to them. We observe that the user started preferring both high constant stiffness (HS) and proportional stiffness (PS) due to their reactivity, which feels more natural and personal as the hand responds faster to muscles commands. However, this changed over the course of the experiments when the possibility of causing discomfort to people, due to an excessive squeezing with HS, arose. The user also underlined the lack of confidence and difficulties to command the hand when using the low constant stiffness controller (LS), because of the opposite reason, i.e., lack of reactivity see . FinallyWithout explicit knowledge about the controller used, the user was able to understand the differences in performance and the diverse sensations elicited through the experiment. This perception fits with our hypothesis, validating the proper implementation of variable stiffness control. The user reported the following comments:HS: “The grasp is very rigid.” “The grasping force could be dangerous when interacting.” “I am scared of hurting people, I do not like this control. I feel like it is my fault and I need to learn how to measure the force executed.” “I do not feel very confident when interacting with people.”;LS: “It has a smooth grasp. When holding something, the fingers are not rigid.” “The motion is very slow. The hand does not close enough.” “The grasp feels inconsistent, unreliable and uncomfortable.” “I need to use a lot of muscle force to activate it, but the result is always imprecise. I do not like it and it is fatiguing.”;PS: “The grasp was firm but adaptable/flexible while keeping the object grasped.” “I prefer this control, even if I grasp with a lot of force, I feel safe and secure  as the hand is adaptable when I am relaxed.” “I feel confident, even if the hand is closed, if someone or something forces it to open, it opens a bit.” “It allows human-like interaction.”Finally, variable stiffness SUS score obtained a higher acceptability and usability over both constant stiffness control modalities. Moreover, As observed in the seminal work by Hogan , and proAbout the opinion and perception of the secondary subjects, we found statistical significance looking at “human-likeness” and “comfort” aspects see . There, Analysing the video footage of the 36 experiments, it is possible to observe that, when holding the tool case with a low stiffness control, the user encounters difficulty because of the loose grasp. On the contrary, when interacting with another subject using the high stiffness control, the user presents more problems to maintain a conversation due to the cognitive effort used to control the hand so not to exert excessive forces on the other subject. Both these issues were absent in the case of the variable stiffness control, where the user is able to move the tool case with ease and interact while seamlessly having a conversation, suggesting a good control and a low cognitive load. Interestingly, this effect is also visible in bimanual manipulation, where the prosthetic hand adapts better to external conditions when using variable stiffness, allowing the user to move the objects faster while having a more fluent conversation.Furthermore, The number of healthy subjects involved in the interaction experiments and the number of repetitions performed allow us to confidently affirm that, for this user, the method is certainly feasible and indeed, very appreciated. Nevertheless, given the involvement of only one prosthesis user in the study, it is not possible to generalize our results.In order to achieve different desired behaviors in upper limb prosthetics for Activities of Daily Living and for social interaction, an alternative solution to the classical sEMG based control is explored. The proposed method includes stiffness modulation of the hand, proportional to muscle coactivation, with a proportional velocity control of hand position that includes a finite state machine. The feasibility of the algorithm is preliminarily validated with a prosthesis user, comparing its performance with other conventional control modalities implemented in the SHP. Eventually, this concept could be implemented in other rigid prosthetic hands, where differences between modalities could be even more visible/useful, as their only compliance can be given by the motor impedance. Moreover, an important limitation during the ADL experiments was that no form of feedback was given to the prosthesis user during tasks execution. Even though impedance control is a method to manage human interaction without relying excessively on sensory feedback Hogan, , resultsEncouraging results suggest the feasibility of the proposed approach and a good adaptive capacity, which will be investigated more in depth in the future, with different applications and more participants. Although there is room for improvement, the authors believe in the potential of variable stiffness control implementation for prosthetic devices. Finally, as we obtain an extra available signal , it could be potentially used to explore the stiffness control of additional joints, e.g., a wrist, and thereby, increase the dexterity of a prosthesis.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by Institutional Review Board of University of Pisa. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.PC-M, MC, and GG designed the proposed control method and conceived the study. All of the author contributed to the experimental design. PC-M and CP performed the experiments. PC-M executed literature research and performed statistical analysis of the database. PC-M and GG wrote all sections of the manuscript. AB contributed expertise and advice. All authors contributed to manuscript revision, read, and approved the submitted version.The impaired subject, who is not an author of this paper, is employed in the lab's institution as administrative support with the task of managing project dissemination and studying the impact of prostheses on subjects and the Society. She is not involved in the development of the prosthesis functions and control. 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.


Despite the good mechanical properties of natural fibre composites, their use in load-bearing components is still limited, which may be due to lack of knowledge and confidence in calculating the performance of the composites by mechanical models. The present study is providing an experimental evaluation of stiffness predictions of multiaxial flax fibre composite by classical laminate theory (CLT). The experimental base is (i) multiaxial flax fibre composites fabricated with two types of biaxial non-crimp fabrics, having a nominal yarn orientation of ±45°, and (ii) uniaxial flax fibre composites fabricated with the same flax yarn as used in the fabrics. The fabricated composites are characterised by volumetric composition, yarn orientation and tensile properties. A fast and easy operational Fast Fibre Orientation (FFO) method is developed to determine the actual yarn orientation in fabrics and composites. It is demonstrated that the FFO method is a robust method, giving repeatable results for yarn orientations, and it can be used both on fabrics and composites. CLT predictions of stiffness of the multiaxial flax fibre composites are shown to be in good agreement with the measured stiffnesses of the composites in three testing directions . The use of the actual yarn orientations measured by the FFO method, instead of the nominal yarn orientations of ±45°, is shown to result in improved CLT predictions of stiffness with a mean deviation between predictions and measurements on 0.2 GPa. Altogether, it is demonstrated that stiffness of multiaxial flax fibre composites can be accurately predicted by CLT, without any fitting constants, based on independently determined stiffness parameters of the related uniaxial flax fibre composite, and based on measured yarn orientations in the flax fibre fabric. Composite materials is an established class of materials widely used in industry for structural applications, such as wind turbine blades and automobile parts, requiring high stiffness and strength, coupled to low weight. Natural fibre composites, e.g. based on flax fibres, are emerging types of composites that are gaining increased interest in industry due to their good mechanical properties, and with lower weight than conventional composites –5. The pThe current industrial use of natural fibre composites is mostly limited to components with little load-bearing requirements, such as the body panels in automobiles . One reaRecently, tailor made flax fibre fabrics for composites are produced by a number of companies in Europe. The fabrics are so-called non-crimp fabrics, and typically with a biaxial nominal ± 45° fibre orientation. The laying up of these fabrics on top of each other is the basis for fabrication of multiaxial flax fibre composite laminates. In this context, the actual fibre orientation in the fabrics  is of central importance for the resulting mechanical properties of the composites.The present study aims to evaluate the use of CLT to predict stiffness of multiaxial flax fibre composites. Stiffness is a fundamental mechanical property for most structural applications. The evaluation of the CLT predictions will be based on experiments where two types of non-crimp biaxial flax fibre fabrics are used to fabricate multiaxial composites. In addition, uniaxial flax fibre composites are fabricated to provide input parameters for the CLT predictions. A fast and easy operational method is developed to determine the actual yarn orientation in fabrics and composites. The measured stiffness of the multiaxial composites, in three testing directions, is compared with the stiffness predicted by CLT.3, 3.0 GPa and 0.35, respectively.Two types of commercial non-crimp biaxial flax fibre fabrics (AmpliTex 5008), purchased from Bcomp Ltd., Switzerland, are used. Specifications of the two fabrics and their photographs are shown in A fast and easy operational method was developed to accurately determine the orientation of yarns in fabrics and composites. The developed Fast Fibre Orientation (FFO) method is illustrated in As shown in If the yarn orientation of the biaxial fabric is exactly ± 45°, then layup A gives a so-called symmetric laminate where the yarn angles around the centre thickness line of the laminate are symmetric to each other. This is a typical applied requirement for composite laminates to avoid that a fabricated laminate gets distorted, by balancing the internal stresses. Layup B gives a non-symmetric laminate. Furthermore, if the yarn orientation of the biaxial fabric is exactly ± 45°, the yarn orientation in the laminates made with layup A and B will be the same, and equal to ± 45°.In contrast, if the yarn orientation of the biaxial fabric deviates from the nominal ± 45°, then both layup A and B give non-symmetric laminates. Furthermore, the yarn orientation in the laminates with layup A and B will be different from each other, and the yarn orientation will not be biaxial, but instead it will be multiaxial. This is illustrated in Vacuum infusion was performed to impregnate the layups of fabric with epoxy resin, followed by curing (5 hours at 50°C), and then de-moulding of the composite laminates and post-curing (4.5 hours at 80°C). The dimensions of the fabricated laminates were 300 x 300 x 2.9 mm.-1(1 mm/2 x 470 mm), and will be neglected. The number of winding layers was set to be 14 in order to obtain composite laminates with a thickness of 3.0 mm, i.e. the same thickness as the multiaxial laminates. After filament winding, the yarns on the aluminium plate were enveloped in a vacuum bag, and infused with epoxy resin and cured, resulting in two laminates per fabrication. The applied curing conditions were the same as the ones used for the multiaxial composite laminates.Fabrication of uniaxial composite laminates was performed by filament winding followed by vacuum infusion. The flax yarn was wound on an aluminium plate of 470 x 400 mm, and with a lateral movement per rotation of 1 mm. The resulting misalignment of the wound yarns is about 0.1° (= tanVf), matrix (Vm), and porosity (Vp) in composites can be calculated as follows:ρf, ρm and ρc are the density of fibres, matrix and composite, respectively, and Wf is the fibre weight fraction. Thus, in addition to the density of fibres and matrix, measurements are required of the fibre weight fraction and the density of the composites. In the present study, to perform these measurements, 6 specimens with planar dimensions 25 x 25 mm were cut from the composite laminates. The edges of the specimens were polished to remove any loose fragments, and their in-plane dimensions (length and width) were measured with an accuracy of 0.01 mm. After drying under vacuum overnight, the weight of the specimens (mc) was obtained. By knowing the area of the specimens (Ac) (= length x width), the weight of the fibres (mf) in the specimens was calculated from the area weight of the fabric, in the case of the multiaxial composites , the specimens were weighed submerged in water, and the density was determined by utilizing the Archimedes principle. In a previous study by Madsen et al. [ρf for flax fibres was determined to be 1.540 g/cm3.The volume fractions of fibres  were cut in three directions of the laminates: 0° , 45° and 90°, as shown in Before tensile testing of the multiaxial composites, the yarn orientation in the tensile specimens was determined by the developed FFO method. The specimens were scanned by the flat head scanner using a transmitted illumination mode. Tensile tests of the specimens were performed using a displacement rate of 2 mm/min on a hydraulic testing machine  with a 100 kN load cell. For the multiaxial composites, 3 specimens were tested for each testing direction, and for the uniaxial composites, 5 specimens were tested. The lower number of tested specimens for the multiaxial composites was due to the limiting area of the laminates. Strain was measured by two extensometers with 50 mm gauge length attached to each side of the specimens. Stiffness was determined as the slope of the initial linear part of the measured stress-strain curves in the strain interval 0.01–0.15%.Preliminary, the stiffness of the multiaxial composite laminates was predicted by three methods: 1) by using the rule of mixtures model with the Krenchel fibre orientation factor , 13 to cQ matrix). Then, the Q matrices of the plies are integrated by the three coupling matrices . In order to calculate the stiffness of a composite laminate with a given layup of plies, CLT requires knowledge of the following four stiffness parameters of the uniaxial ply: longitudinal stiffness (Ec1), transverse stiffness (Ec2), shear modulus (Gc12) and Poisson’s ratio (νc12).A complete description of classical laminate theory (CLT) is found in , 11. CLTEc1 was determined from the measured stiffness of the uniaxial laminate. The parameter Ec2 was calculated by the inverse rule of mixtures model  and Ef2 were found to be 39.4 and 5.5 GPa, respectively. A similar ratio between these two stiffness parameters is assumed in the present study. i.e. Ef2 was estimated as equal to 5.5/39.4 × Ef1. This ratio of 1/7 is supported by an almost identical ratio found by Baley et al. [Gc12 was calculated by the Halpin-Tsai equation [ξ is a fibre shape factor which was set to be 2 with the assumption that fibres have circular cross sections. The parameters Gf and Gm are the shear modulus of the fibres and the matrix, respectively. The matrix is assumed to be isotropic, and Gm can therefore be estimated as equal to Em/{2(1+νm)}, where νm is the Poisson’s ratio of the matrix. In the above-mentioned study of jute/epoxy composites [Gf was found to be 3.5 GPa. A similar ratio between the two stiffness parameters Gf and Ef was assumed in the present study, and Gf was accordingly estimated as equal to 3.5/39.4 × Ef1.In the present study, Thomason  values fy et al. . The parequation  (Eq 7).mposites , the valνc12 was estimated based on the findings in Cichocki and Thomason [νc12 was determined to be about 0.05 to 0.10 below νm. Therefore, since νm in the present study was measured to be 0.35 for the epoxy resin, νc12 for the composites was estimated to be 0.30.Finally, the parameter Thomason  where νcIn some cases, CLT calculations can be simplified under the assumptions of symmetry and balance of the plies in the composite. In the present study, however, such simplifications could not be done. The actual yarn orientation in the multiaxial composites, as measured by the FFO method, was used. The yarns in the composites were interpreted as being the “fibres” in the above presented description of the CLT calculations.balanced configuration of a fabric where the yarn orientation in the two plies are having equal + and–angles. It can be seen that for fabric I, all data points are above the line. The yarn angles for fabric I in the upper and lower ply are +50.0° ± 1.2° and -52.0° ± 1.4° (mean ± stdv.), respectively. Thus, fabric I is deviating from being balanced, and the yarn orientation can be given as +50°/-52°. For fabric II, the data points are distributed around the line. The yarn angles for fabric II in the upper and lower ply are +47.6° ± 0.9° and -47.2° ± 0.9° (mean ± stdv.), respectively. Thus, fabric II is almost balanced, and the yarn orientation can be given as +48°/-47°. The yarn angles in both fabrics, however, are larger than the nominal ones of +45° and -45°. Vf = 31% and Vm = 69% will be used. Vf = 41% is larger than for the multiaxial laminates. This difference in fibre volume content can be explained by a difference in fibre packing ability of the two types of yarn assemblies [semblies , 17. It measured yarn angles in the tensile specimens compare well with the angles calculated from the fabric. The difference between the mean values is in the range 0–3 degrees, and in most cases the measured yarn angles in tensile specimens and the ones calculated from the fabric overlap each other within the range of standard deviations. Thus, altogether, it is demonstrated that the FFO method is a robust method, giving repeatable results, and it can be used both on fabrics and on composites.The measured yarn orientation in the tensile specimens of the multiaxial composites is presented in The measured stress-strain curves of the uniaxial composites are shown in Vf is not equal in the uniaxial and the multiaxial composites , the stiffness of the uniaxial composites needs to be corrected to account for this. By using the rule of mixtures model, a stiffness on 19.8 GPa is calculated for the uniaxial composites with Vf = 31%.In the CLT model predictions, the stiffness of the uniaxial composites is used as input data to predict the stiffness of the multiaxial composites. However, since The measured stress-strain curves of the multiaxial composites are shown in With respect to the shape of the stress-strain curves for the multiaxial composites shown in The present study will focus on the stiffness of the multiaxial composites, i.e. the slope of the first linear part of the stress-strain curves. Other characteristics of the stress-strain curves, e.g. the transition point, the strength, and the failure strain will not be analysed further. In a recent study by Koh and Madsen , the strEc1), transverse stiffness (Ec2), shear modulus (Gc12) and Poisson’s ratio (νc12). In the present case of the uniaxial flax fibre composite, the longitudinal stiffness is calculated to be 19.8 GPa, by correcting the measured stiffness on 25.0 GPa to a Vf on 31%. The transverse stiffness is calculated to be 3.7 GPa, by using In order to predict the stiffness of a multiaxial composite with a given layup of plies, CLT requires knowledge of four stiffness parameters of the uniaxial ply: longitudinal stiffness , and the other curve is using the nominal yarn orientation of ± 45°. The nominal curve is the same in the four diagrams. Although the actual and nominal curves are close to each other, it can be observed that in general, the actual curves are in better agreement with the measured stiffness of the composites than the nominal curves. The mean deviation between the predicted and measured stiffness is 0.2 GPa for the actual curves (corresponding to 3% relative deviation), and 0.5 GPa for the nominal curves (corresponding to 8% relative deviation). The deviations show also some larger extremes for the nominal curves than for the actual curves, e.g. for layup B and fabric I, the deviations for the nominal curves are 0.9 and 1.4 GPa for the testing directions 0° and 90°, respectively (corresponding to about 20% relative deviation). In general, it can be seen that the nominal curves deviate more from the actual curves for fabric I than for fabric II, and for layup B than for layup A.Altogether, it is demonstrated that measurements of actual yarn orientations lead to better predictions of stiffness of multiaxial composites, and the significance is larger for fabrics which deviate more from the nominal yarn orientations (fabric I), and for layups which potentially are leading to large deviations in yarn orientations (layup B). In a practical context, the benefit of the Fast Fibre Orientation method must be considered with respect to the involved effort for performing the measurements, and the assurance for getting accurate predictions for all fabrics and layups.The present study is addressing prediction of stiffness of multiaxial flax fibre composite laminates by classical laminate theory (CLT). Multiaxial flax fibre composites are fabricated with two types of biaxial non-crimp fabrics, having a nominal yarn orientation of ±45°. Uniaxial flax fibre composites are fabricated to provide input parameters for the CLT predictions of stiffness of the multiaxial composites. The fabricated composites are characterised by volumetric composition, yarn orientation and tensile properties.A fast and easy operational Fast Fibre Orientation (FFO) method is developed to determine the actual yarn orientation in fabrics and composites. The method is based on a standard flat head scanner and utilises 2D Fast Fourier Transformation theory. The yarn orientation in the two biaxial fabrics is measured to be +50/-52° and +48/-47°. The yarn orientation in the later fabric is closer to the nominal ± 45°, more balanced, and more uniform. The measured yarn angles in the composites are found to compare well with the angles determined from the fabrics, with a difference in the range 0–3 degrees. Altogether, it is demonstrated that the FFO method is a robust method, giving repeatable results, and it can be used both on fabrics and composites.Stiffness of the uniaxial flax fibre composites with a fibre content of 41% is measured to be 25.0 GPa. The effective stiffness of the flax yarn is back-calculated to be 57 GPa. The determined values of the required four input parameters for the CLT predictions are 19.8 GPa for longitudinal stiffness, by correcting the measured stiffness on 25.0 GPa to a fibre content on 31%, 3.7 GPa for transverse stiffness, 5.0 GPa for shear stiffness, and 0.30 for Poisson’s ratio.Stiffness of the multiaxial flax fibre composites is measured in the three testing directions of 0°, 45° and 90°. As expected from the biaxial yarn orientation in the composites, testing in the 45° direction gives the largest stiffness of the composites, with values in the range 11.6–12.5 GPa. In the 0° and 90° directions, stiffness is almost halved with values in the range 4.6–6.9 GPa.CLT predictions are shown to be in good agreement with the measured stiffness of the multiaxial flax fibre composites at the three testing directions. The use of the actual yarn orientations measured by the FFO method, instead of the nominal yarn orientations of ±45°, is shown to result in improved CLT predictions of stiffness with a mean deviation between predictions and measurements on 0.2 GPa. Altogether, it is demonstrated that stiffness of multiaxial flax fibre composites can be accurately predicted by CLT, without any fitting constants, based on independently determined stiffness parameters of the related uniaxial flax fibre composite, and based on measured yarn orientations in the flax fabric.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.


The current work presents a study on hollow cylinder composite beams, since hollow cylinder cross-sections are one of the principal geometry in many engineering fields. In particular, the present study considers the use of these profiles for scaffold design in offshore engineering. Composite beams cannot be treated as isotropic ones due to couplings mainly present among traction, torsion, bending and shear coefficients. This research aims to present a simple approach to study composite beams as they behave like isotropic ones by removing most complexities related to composite material design . The work aims to obtain the stiffness matrix of the equivalent beam through an analytical approach which is valid for most of the laminated composite configurations present in engineering applications. The 3D Euler–Bernoulli beam theory is considered for obtaining the correspondent isotropic elastic coefficients. The outcomes show that negligible errors occur for some equivalent composite configurations by allowing designers to continue using commercial finite element codes that implement the classical isotropic beam model. Hollow cylinders are one of the most common elements in offshore engineering, e.g., risers, pipes and generally used for scaffolding systems. Among vast materials to produce these kinds of elements, all of them have one mutual defect which is an important factor in an offshore environment; that is corrosion. The most common material used in offshore structures is steel, which although it is stiff and light (compared to reinforced concrete) but it can be easily corroded, which makes maintenance activities very expensive. On the other hand, plastics, a non-environmentally friendly material, can be in this context environmental-friendly. This is due to the fact that fewer materials are involved due to less frequent maintenance, thus, less resources. Steel structural elements should be changed frequently in an offshore environment to maintain offshore structural integrity. Steel is used also in onshore civil applications when being lightweight is an important prerequisite at the design phase. One of the plastics’ problem is the low stiffness and strength compared to steel. To overcome this problem fibers can be added in order to make the so-called Fiber Reinforced Plastics (FRPs). FRPs can be produced by different methods which leads to different stiffness and strength. However, composite materials do not behave like well-known isotropic ones. Therefore over the years, several methodologies have been utilized to analyze composite materials and structures simply and accurately.Regarding hollow circular cross-sections, the stress distribution of anisotropic configurations has been led by Lekhnitskii  which waHomogenization is a method to investigate the macroscopic behavior of a material by considering a replacement of that material to an equivalent homogeneous one ,45,46. TLately, Babamohammadi et al.  presenteThe mechanical behavior of isotropic beams is well-known in engineering practices and it is used for designing any kind of frame structure. However, if the beam is made up of fiber-reinforced composites its behavior cannot be attributed to one of the isotropic materials.Stiffness matrices of hollow cylindrical composite structures can be determined by employing a finite element program. In this work, ABAQUS software  has beenThe stiffness matrix of a two-node Euler–Bernoulli isotropic beam with compact cross-section, in the 3D space, has six degrees of freedom per node as Equation . It is cAs far as structures made of composite materials are concerned, there are still no relations available that define the stiffness matrix within a specific theoretical framework. However, it can be demonstrated that orthotropic beams  have the same nonzero elements in the stiffness matrix as the equivalent isotropic one. Thus, if homogenized mechanical properties can be carried out for composites hollow beams the approach for isotropic beams can be transferred to composite configurations. In this regard, a study was carried out by Reddy  wherein The latter has been generalized to hollow circular beams in order to see if such asymptotic behavior could be used to simply model these beams as equivalent isotropic or orthotropic ones.Taking the studies of Reddy  on laminThe stiffness matrix of the composite beam has been computed using ABAQUS as described in  using a n et al.  is also A typical circular hollow profile with cross-ply configuration is depicted in Clearly, the global trend of all stiffness constants deviates from the initial orthotropic behavior and becomes stable when 3 or 4 layers are considered. Thus, it can be established that the study of Reddy  for crosThe validity of the finite element model is tested by comparing it with the results of the analytical approach by Sun et al.  which prn et al.  method dn et al. . TherefoA and L) the results presented below are not affected . Thus, Angle-ply lamination By examining the graphs obtained  it is poAnalogously to the previous section a comparison between ABAQUS and an analytical formulation  is perfoIn conclusion, the present ABAQUS model is able to approximate accurately the homogenized normal As aforementioned, shear and bending stiffness depend on beam slenderness and they are not predicted accurately by Sun et al.  method. Results obtained are depicted in n et al.  formulatIt should be remarked that the calculation of the stiffness matrix by using classical formulas varies with beam slenderness. This error leads to lower stiffness and consequently, it should be considered in the design phase by the introduction of a correction factor. For symmetric lamination schemes and with slenderness values For the angle-ply configurations  and the coupling stiffnesses based on their relevance with respect to the correspondent main stiffness on the main diagonal of the stiffness matrix.All the stiffnesses tends to have a constant value by increasing beam slenderness.The orthotropic scheme (0) is very efficient if subjected to shear, axial and bending actions, but not for torsional ones. However, it has a significant variation while increasing slenderness. Furthermore, it suffers from delamination, because the fibers being all parallel, tend to form a preferential fracture plane.The angle-ply scheme n et al.  formulaeThe angle-ply scheme The quasi-isotropic laminate  however such selection has very small torsional stiffness and low durability and reliability. Therefore, quasi-isotropic and In the previous section, the most common composite materials such as fiberglass/epoxy or graphite/epoxy have been considered. Such composites have a stiffness ratio 2≈13 see . HoweverThis high stiffness ratio allows having a laminate with a high positive or negative engineering Poisson ratio of  by Peel , unbalanThe stiffness coefficients are carried out below for the materials listed in In the following, four configurations investigated numerically and experimentally by Peel  are usedThe laminate A further comparison can be made with the previous lamination scheme The laminate cross-ply laminates, except laminate (90) have lower values, approximately 10% for unbalanced laminates with a fiber pitch angle of After investigating several lamination schemes with standard and high stiffness ratios .Subsequently, an analytical method is proposed for the calculation of the stiffness matrix components On the contrary, the condition A balanced bio-inspired Bouligand-type laminate has been observed to be a good candidate for the present approach because other than being completely defined by the present analytical procedure such scheme demonstrated to have high ductility, dissipated energy, and high load-carrying capability.The present method is valid also for investigating hollow beams with orthotropic materials with high stiffness ratio


Immunomodulation is a technique for the modulation of immune responses against graft material to improve surgical success rates. The main target cell for the immunomodulation is a macrophage because it is the reaction site of the graft and controls the healing process. Macrophages can be classified into M1 and M2 types. Most immunomodulation techniques focus on the rapid differentiation of M2-type macrophage. An M2 inducer, 4-hexylresorcinol, has been recently identified and is used for bone grafts and dental implant coatings. The maxillofacial area is composed of several different tissues, including the skin, mucosa, bone, skeletal muscle, and salivary glands. Accordingly, different kinds of graft materials are required for maxillofacial reconstructive surgery. Autogenous graft materials have been considered the optimal choice due to the lack of immunological complications ; howeverMost types of grafts are successful in otherwise healthy patients. However, the success rate is lower when patients have pre-existing conditions of systemic diseases, such as diabetes mellitus or osteoporosis . RepreseA recent review summarized the current understanding of immunomodulation in bone grafts or osteoimmunomodulation . Most stThese efforts have dramatically improved the effectiveness of immunomodulation and the design of the drug carriers. However, the fundamental mechanism between biomaterial and host response is not well understood. Particularly, the wound healing mechanism is largely unknown. The response to stress-mediated mitochondria may be a key element for understanding these mechanisms. The purpose of this review was to summarize the current level of understanding of macrophages in immunomodulation. Therefore, the application of 4-hexylresorcinol (4HR) in immunomodulation was reviewed in detail.When a graft is implanted into the body, cells attach to the graft surface. Cell response to surface roughness Fig.  has beenBone grafts are designed to imitate the surface roughness of the natural bone with 32 nm grain sizes . Many teIt is unclear whether hydrophobic or hydrophilic surfaces are better for surface wettability. Hydrophobic surfaces show more intense monocyte-derived immune reactions than hydrophilic surfaces . Also, hThe porosity of the graft is closely associated with oxygen concentration and nutrient supply . Also, hThe addition of minerals has been used for the development of bone grafts. The bone is mainly composed of hydroxyapatite; therefore, hydroxyapatite-based grafts or coatings have been used for orthopedics and dental implants , 23. CalMany types of trace elements have been used as ingredients for bone grafts. Silicon-based grafts show osteoblast activation , and higAppropriately, timed angiogenesis is essential for normal wound healing, Fig. . Some coM1-type macrophages are predominant in the inflammatory phase and secrete pro-inflammatory cytokines . The rolMacrophage phenotypes, such as M1, M2, or multinucleated giant cells, may be the consequence of survival strategies in response to environmental changes Fig. . ForeignM1 inducers, such as interferon-γ (IFNγ), lipopolysaccharide (LPS), and TNF-α , may be Following a tissue injury, the epidermis can regenerate, but scar-free healing is still unattainable for skin wounds. Systemic diseases associated with the host immune system and aging may result in impaired wound healing , 55, whiThere have been several hypotheses for macrophage differentiation. Resident macrophages in most organs are the first line of defense against foreign bodies . Some ti4HR is an emerging material for use in immunomodulation Fig. . 4HR admHowever, function-based discrimination among M2 subtypes is difficult. The spectrum of expressed markers overlaps. Any inducer of M2-type macrophages is considered to be beneficial for graft success . 4HR inh. In the diabetic animal model, 4HR ointment showed a substantial increase in capillary regeneration as compared to the untreated control (data submitted for publication).4HR can increase TGF-β1 expression in human umbilical vein endothelial cells (HUVEC) (data submitted for publication) and can also increase VEGFs mediated by TGF-β1 (data submitted for publication). TGF-β1 is an important cytokine in wound healing . Though Controlled release is ideal for optimizing drug effects and minimizing potential side effects. Smart material is designed for controlled release . One exaThe modification of physical properties is valid only in the early stage of grafting. After initial contact with host cells, the effects on wound healing are limited. However, when active components are released early enough, their effect is observed throughout all healing stages Fig. . Many tyNatural macromolecules can be substitutes for synthetic polymers. The collagen-based matrix has been widely tested and used. Collagen is the main component of the extracellular matrix. Scaffold mimics may have an advantage in the transition of macrophage type . Silk fiWound healing is influenced by the general health of the patient. To maximize graft success rates, immunomodulation is essential. Many kinds of immunomodulation have been used and studied in maxillofacial reconstructive surgery. 4HR is a new M2 inducing material that can be applied in various fields of tissue engineering.


Despite custodial grandparents’ significant contributions to their grandchildren’s healthy development, unique needs of older adults often remain unmet with a limited cultural understanding of intergenerational caregiving. Using a phenomenological approach, interviews and focus groups were conducted with 75 custodial grandparents in Malawi (n=29), South Korea (n=23), and the U.S. (n=23). Malawian grandparents presented financial and physical hardships; however, they experienced strong support from community. Korean grandparents reported similar needs as Malawian grandparents while additionally experiencing cultural biases toward grandparent-headed families . The U.S. grandparents disclosed increased needs for social support as well as family trauma with intergenerational impacts. The increase in custodial grandparent population across the world and findings from this comparative transnational research highlight the need for development of a model for culturally responsive practice with grandparent-headed families in a global context. Part of a symposium sponsored by the Grandparents as Caregivers Interest Group.


Identifying immunogens that induce HIV-1-specific immune responses is a lengthy process that can benefit from computational methods, which predict T-cell epitopes for various HLA types.We tested the performance of the NetMHCpan4.0 computational neural network in re-identifying 93 T-cell epitopes that had been previously independently mapped using the whole proteome IFN-γ ELISPOT assays in 6 HLA class I typed Ugandan individuals infected with HIV-1 subtypes A1 and D. To provide a benchmark we compared the predictions for NetMHCpan4.0 to MHCflurry1.2.0 and NetCTL1.2.p = 0.0000005). MHCflurry1.2.0 similarly predicted all but 2 of the peptides that NetMHCpan4.0 predicted and NetCTL1.2 predicted only 14 of the 93 experimental peptides.NetMHCpan4.0 performed best correctly predicting 88 of the 93 experimentally mapped epitopes for a set length of 9-mer and matched HLA class I alleles. Receiver Operator Characteristic (ROC) analysis gave an area under the curve (AUC) of 0.928. Setting NetMHCpan4.0 to predict 11-14mer length did not improve the prediction (37–79 of 93 peptides) with an inverse correlation between the number of predictions and length set. Late time point peptides were significantly stronger binders than early peptides (Wilcoxon signed rank test: NetMHCpan4.0 class I epitope predictions covered 95% of the epitope responses identified in six HIV-1 infected individuals, and would have reduced the number of experimental confirmatory tests by > 80%. Algorithmic epitope prediction in conjunction with HLA allele frequency information can cost-effectively assist immunogen design through minimizing the experimental effort. Computational algorithms were initially demonstrated as useful tools for predicting potential epitopes that might elicit quality T-cell responses , 2. Compag genes  in cynomag genes  necessarag genes . Computaag genes , therefoag genes –10.For HIV-1 vaccine design purposes an important consideration for the suitability of a computational algorithm is the breadth of discrete number of T-cell epitopes it generates that could reach particular levels of coverage  of circuin-silico approaches in epitope prediction and its application for vaccine design reported a meagre 22, 44%, and relatively higher 78% match for three computational tools namely YFPEITHI, CTLPRED and IEDB respectively [A reliable pan-HLA-specific algorithm NetMHCpan4.0 –20 that ectively . Using eet.al [The data used was from an independent study that did not include this analysis in its objectives. Experimental data of peptides previously mapped for HIV-1 epitope recognition of 6 individuals for a separate study . The web version of NetMHCpan4.0 [http://www.cbs.dtu.dk/services/NetMHCpan/) was configured to predict 9mer through 14mer epitopes for 22 HLA class I alleles  plot. The hit rate (sensitivity) and false hit rate (specificity) of binder predictions as determined by the NetMHCpan4.0 threshold of peptides within the top 2% (with a score of 2 or less) were calculated and the strength of the model was determined by calculating the area under the curve, AUC of the ROC plot –43. PearTo experimentally determine epitopes for 757 peptides spanning the whole HIV-1 proteome for clades A and D as well as both time points of the 6 individuals required a total of 4230 test assay wells. For each test subject these included 9 antigen proliferation wells, 384 culture ELISPOT wells and an average of 164 epitope mapping ELISPOT wells . Using the 22 HLA alleles represented in the study subjects we were able to computationally predict 95% of the experimentally mapped epitopes. This approach could have reduced the test assays by eliminating all the T-cell antigen proliferation and culture ELISPOT steps totalling to 3258 assay wells (77%) and leaving only 972 (23%) epitope mapping assays required. Applying a pooling strategy to the computational predictions similar to that used in the experimental pooling where each pool contained approximately 20 peptides with a coverage of 3 per peptide pool, the 923 potential peptides  eligible epitope mapping peptides) would make at most 46 pools. Consequently the computational prediction approach could have reduced the experimental assays by at least 80%.rs = 0.88  epitopes were experimentally mapped of which 12 were recognized at both baseline and later time points, 34 only at baseline and 54 only at the later time point. Comparison of the ranked computational score for Netmhcpan4.0 binders of early (n = 34) versus later peptides showed that the later time point predictions were stronger binders reaching statistical significance  (Fig. The experimental peptide mapping data was derived from a baseline time point corresponding to HIV-1 Fiebig stages IV, V and VI (Table In this analysis we showed that the computational method NetMHCpan4.0 predicted 95% of previously experimentally mapped HIV-1 epitopes in 6 HIV-1 infected individuals expressing a total of 22 different HLA class I alleles. In our IFN-γ ELISPOT assays we evaluated 757 17mer peptides overlapping by 11 amino acids and covering the whole HIV-1 subtype A1 and D consensus proteomes. Out of the 5 experimentally determined epitopes missed by the algorithm Table , 4 were As the participants had been enrolled in the acute/early phase of HIV-1 infection and we had observed intra-participant changes in epitope recognition between early and late time points after infection, we compared the binding scores of confirmed epitopes at these time points and found a statistically significant change towards recognition of higher binding peptides as the infection entered the chronic phase. This might represent better support of the T-cell response directed at more stable HLA/peptide complexes as the infection progresses into chronicity.The NetMHCpan4.0 algorithm, which is based on binding affinity and integrates data on eluted naturally processed ligands, reflected optimal HLA class I binding for 9-mers, producing a decreasing number of predictions when the peptide size was increased from 9 to 11 amino acids. With a single exception, predicted binders between 11 and 14 amino acids included at least one 9mer predicted to bind on its own, suggesting a destabilizing effect of the extra amino acids beyond the canonical HLA class I binding pockets at positions 2 and 9 could account for fewer predictions.Important limitations are the lack of predictions of HLA class II restricted epitopes, which might have contributed to a fraction of IFN-γ ELISPOT responses. Approximately 5% of the computational predictions may be false positives that only increase the size of planned wet experiments and approximately 1% of true positives may also be missed.In this analysis, using NetMHCpan4.0, MHCflurry and NetCTL to predict previously experimentally mapped epitopes, we demonstrate that the computational methods reliably predict an acceptable portion of binder epitopes. We recommend the use of such computational methods to reduce the size of experiments required cost associated.


Anopheles gambiae ovary, as much as 11% of piRNAs map to protein-coding genes. Here, we show that ovarian mRNAs and long non-coding RNAs (lncRNAs) are processed into piRNAs that can direct other transcripts into the piRNA biogenesis pathway. Targeting piRNAs fuel transcripts either into the ping-pong cycle of piRNA amplification or into the machinery of phased piRNA biogenesis, thereby creating networks of inter-regulating transcripts. RNAs of the same network share related genomic repeats. These repeats give rise to piRNAs, which target other transcripts and lead to a cascade of concerted RNA slicing. While ping-pong networks are based on repeats of several hundred nucleotides, networks that rely on phased piRNA biogenesis operate through short ~40-nucleotides long repeats, which we named snetDNAs. Interestingly, snetDNAs are recurring in evolution from insects to mammals. Our study brings to light a new type of conserved regulatory pathway, the snetDNA-pathway, by which short sequences can include independent genes and lncRNAs in the same biological pathway.PIWI-interacting RNAs (piRNAs) target transcripts by sequence complementarity serving as guides for RNA slicing in animal germ cells. The piRNA pathway is increasingly recognized as critical for essential cellular functions such as germline development and reproduction. In the  Drosophila melanogaster, piRNAs bound to the PIWI protein Aubergine (Aub) show a “1U” signature corresponding to a high proportion of uracil at their 5′-end. piRNAs bound to Argonaute 3 (Ago3) often have an adenine at position 10. This “10A” signature corresponds to the nucleotide that faces the 5′-uracil of the complementary piRNA and is attributed to a preference of Aub for an A at this position of the target RNA [PIWI-interacting small RNAs (piRNAs), 24 to 29 nucleotides (nt) long, are essential actors in controlling transposable elements (TEs) in animal gonads. Specific genomic loci called piRNA clusters, of tens or even hundreds of kilobases (Kb), produce large amounts of piRNAs. Owing to sequence complementarity, piRNAs from piRNA clusters guide PIWI proteins to cleave TE transcripts and induce their processing into new piRNAs. These new piRNAs can themselves act as PIWI guides for the cleavage of complementary transcripts inducing production of piRNAs that are identical to the “initiator” piRNAs that originated from the piRNA clusters. This leads to a piRNA amplification process, which has been called the ping-pong cycle ,2, revieD. melanogaster germline also operates with Aub and Ago3 as ping-pong does but it does not necessarily lead to an amplification loop [D. melanogaster [Phased piRNA biogenesis in the ion loop ,6. It leion loop  or “inition loop  or “trainogaster ,6. TE-related sequences are not the only producers of piRNAs. In several organisms, piRNAs originating from the 3′ untranslated regions (UTR) of gene transcripts have been reported ,8,9,10. Anopheles gambiae ovaries. The African malaria vector An. gambiae particularly suits this analysis because, first, piRNAs with a ping-pong signature are produced in the ovarian tissue [An. gambiae resulting from ping-pong amplification between transcripts from distant genes. We identify a novel “intrinsic ping-pong amplification”, which is achieved with genome-unique piRNAs originating from the same single gene. We also evidence phased piRNA biogenesis from genes and lncRNAs, which is initiated by trigger-piRNAs that are not related to nowadays known TEs and originate from other genes and lncRNAs at distant loci. When examined across distant species, we further bring evidence for a new type of regulatory pathway, named snetDNA-pathway, conserved throughout evolution and based on particularly short genomic sequences, the snetDNAs , which establish regulatory networks through piRNA targeting and phased piRNA biogenesis.Here, we sought to address whether piRNAs, if produced from protein-coding genes and unrelated to any TE-sequences, may lead to piRNA-guided mRNA cleavage and may establish a piRNA regulation network dedicated to gene regulation. To explore this possibility, we studied piRNAs from n tissue ,22,23 ann tissue . We hereAn. gambiae ovaries [https://www.ncbi.nlm.nih.gov/sra); GSM830467 for Ae. aegypti adults [https://www.ncbi.nlm.nih.gov/gds).Small RNA libraries were SRX966734 for  ovaries , availabi adults ; GSM1318i adults ; and GSMi adults , these dAn. gambiae and Ae. aegypti respectively, allowing zero mismatch, using sRNAPipe [An. gambiae) and AaegL3.2 (Ae. aegypti), available at VectorBase [http://www.girinst.org) [Reads were mapped against AgamP4.2 and AaegL3, genome assemblies for sRNAPipe . Small RsRNAPipe , Bowtie2sRNAPipe  or NucBasRNAPipe . RPM  , allowinBona fide reads were defined as small RNAs which do not map microRNAs (miRNAs), ribosomal RNAs (rRNAs), small nuclear RNAs (snRNAs) or transfer RNAs (tRNAs). “Collapsed” counts were determined from collapsed libraries where all identical reads were reduced to one single read. “Non-collapsed” counts originate from the initial sequencing libraries. “Multiplicity” was calculated as the ratio of the non-collapsed count of piRNAs over the collapsed count .The application “Tablet” was used for visual exploration of piRNA mapping .Ping-pong signature was analysed essentially as in Grentzinger et al. . The puthttp://www.girinst.org, and all insect TEs are available at Repbase [For repeat-masking, we used CENSOR at  Repbase .https://www.vectorbase.org/blast, E = 1 or E = 10, Word size: 11, Complexity Masking: Off) or by command-line BLASTN, with the settings matching those of VectorBase, for Drosophila, human, mouse and rat , these genomes being unavailable at VectorBase. In the case of command-line BLASTN, for the figures with alignments respecting a maximal E-value of 1, the alignments with an E-value > 1 were dropped. Redundancy within BLASTN results was suppressed before making heat maps: For overlapping, nested alignments, only the longest alignment was retained. BLASTN  alignments were done at VectorBase  for diseAn. gambiae AgamP4, Ae.aegypti AaegL3, mouse GRCm38.p5 and human GRCh38.p8) and aligned using “Muscle” and “ClustalW” multiple sequence alignment tools included in MacVector 17.0.5.To build snetDNA consensus sequences, the genomic sequences that aligned to 2R_lncs_14 and AGAP011923 snetDNAs and flanking sequences  were extracted from the respective genomes (https://www.R-project.org/). Principal component analysis was proceeded using “FactoMineR” [http://www.sthda.com/english/rpkgs/factoextra). Euler diagram was made with eulerr  Heatmaps were made using “R” package gplots (https://CRAN.R-project.org/package=gplots). Correlograms were made using “R” packages “corrplot” (https://CRAN.R-project.org/package=corrplot) and “Hmisc” (https://CRAN.R-project.org/package=Hmisc). “ratioBsBas” and “LOGratioBsBas” for correlograms and PCA were computed as follows: “Bs” being the count of all bona fide sense reads in RPM; “Bas” being the count of all bona fide antisense reads in RPM; “ratioBsBas” was computed as Bs/Bas, as (Bs + 0.06)/Bas when Bs = 0 or as Bs/(Bas+0.06) when Bas = 0; and “LOGratioBsBas” is log(ratioBsBas). Coverage of transcripts by piRNAs was analysed using bedtools genomecov [Barplots, scatter plots, heatmaps, Euler diagram, Principal component analysis and correlograms were made using “R”  for human and mouse and available from the UCSC portal [We extracted gene annotations from GENCODE basic annotations v28 for the human genome (GRCh38.p12) as well as GENCODE basic annotations v19 for the mouse genome (GRCm38.p6) , downloaC portal . To bettC portal . The GenWe investigated expression enrichment towards particular tissues amongst protein-coding genes containing a snetDNA, using the TissueEnrich package . TissueEThe scripts are available upon request.All small RNA sequencing data used here are available at the NCBI SRA database or NCBI GEO DataSets. They have been published by us or by others and are publicly available. The accession numbers are given in the An. gambiae ovaries show a bimodal length distribution with one peak at 22 nt attributed to microRNAs and a broad peak spanning 24–29 nt [Small RNAs from 24–29 nt . Here, wAn. gambiae genome. The majority of the 870 mRNAs produce only sense piRNA reads (564 transcripts), four mRNAs produce only antisense, and 302 mRNAs map both sense and antisense piRNA reads (We focused on piRNAs mapping to protein-coding genes without mismatch. We found that 870 mRNAs map >3 Reads Per Million (RPM) of piRNAs. piRNAs mapping to these 870 mRNAs make up 10.4% of all genome-mapping piRNAs. Among the mRNA-mapping piRNAs, 93.3% is genome-unique, i.e., they map only once in the NA reads A. When both sense and antisense piRNAs are produced from the same mRNA, there is a possibility of ping-pong amplification . To testAn. gambiae genome. The results show that, for 82 out of 97 transcripts, the ping-pong-piRNAs map to repeats other than TEs. For the remaining 11 transcripts, all ping-pong-piRNAs map to genome-unique sequences.Until now, ping-pong amplification of endogenous piRNAs was known for TEs. Thus, we checked whether the ping-pong observed for 97 mRNAs might be due to the presence of TE-homologous sequences. We tested whether the piRNAs with a ping-pong partner (with 10-nt 5′-overlap), the “ping-pong-piRNAs”, map TEs. We found only four transcripts with a high proportion of ping-pong-piRNAs mapping TEs . Consequbona fide piRNAs (BZ and BpctPP respectively) and for genome-unique piRNAs (UZ and UpctPP respectively), the ratio of bona fide sense over antisense piRNAs (LOGratioBsBas), and the percentage of genome-repeated piRNAs (pctrepeats). The PCA distinguishes essentially three groups of transcripts mapping piRNAs: mRNAs without significant ping-pong, mRNAs mapping repeated or TE-matching piRNAs doing ping-pong, and mRNAs mapping genome-unique piRNAs doing ping-pong  A. We aimThese results indicate that both trail-piRNAs and responder-piRNAs can become trigger-piRNAs for piRNA-guided slicing. This leads to an amplification of piRNA processing by a process of back-targeting, which differs from a ping-pong loop if the back-targeted sequence is different from the initial trigger-producing site. An. gambiae ovary [In all cases, targeting by trigger-piRNAs very efficiently induces phased piRNA biogenesis. Relatively few trigger-piRNAs induce slicing of high amounts of responder-piRNAs, especially in the case of AGAP003387. Indeed, AGAP003387 is targeted by 63.9 RPM trigger-piRNAs from AGAP011923 and is sliced into 86624 RPM responder-piRNAs and 1767 RPM trail-piRNAs, totaling 9% of all genome-mapping piRNAs in the ae ovary  , to Drosophila melanogaster and to mammal genomes  by BLASTN . To find out whether similar piRNA networks exist in other species, we aligned the sequences of the five network transcripts from An. gambiae complex , 193 copies being clustered together in the same locus of 10.5 kb, organized in tandem repeats of 54-nt length  or at least over 80% of their length (AGAP011923 and unk_RNA_1) in the six species of the  complex . In the t length . We alsot length . MoreoveAn. gambiae, Ae. aegypti, mouse and human and found them highly similar in these evolutionary very distant species of mosquitoes and mammals . Actually, the eleven 2R_lncs_14 orthologs identified in Ae. aegypti  “ping-pong networks” grouping transcripts containing the same repeated sequences, 130 to 1130 base pairs long, producing piRNAs which integrate the ping-pong amplification cycle, and (b) “snetDNA networks” grouping transcripts containing snetDNAs, short repeats of size between 25 and 42 nucleotides that produce trigger- and responder-piRNAs which are at the origin of concerted phased piRNA biogenesis. In the latter network, transcripts producing trigger-piRNAs target other complementary transcripts and induce their slicing to responder- and trail-piRNAs. Responder- and trail-piRNAs may then become trigger-piRNAs targeting other complementary transcripts. If the responder-piRNAs are complementary to the initial trigger-producing transcript, they may target back the latter and induce piRNA amplification between these two transcripts either by trans-ping-pong or phased piRNA biogenesis.Here, we extended the knowledge on biogenesis of piRNA from genes and lncRNAs in For the “ping-pong networks”, we observed piRNA ping-pong amplification between transcripts from distant loci having the same repeats. In addition, for 11 other mRNAs, we identified a novel “intrinsic ping-pong amplification”, which is achieved with genome-unique piRNAs originating from the same single gene. Until now, ping-pong amplification had been observed between piRNAs from different loci, i.e., piRNA clusters on one hand and functional TEs on the other hand. Here, we identified 11 transcripts from 8 genes, which produce both sense and antisense ping-pong partners by their own without the need for targeting piRNAs from other loci. An open question now is how these genes become autonomous piRNA-producing loci.C. elegans, piRNA concentration does not limit targeting but probably correlates better with binding energy than with piRNA abundance [In snetDNA networks, we observed that relatively few trigger-piRNAs may induce slicing of high amounts of responder-piRNAs, especially in the case of AGAP003387. This suggests that, as observed in bundance .Drosophila have enriched 10A while Aub-bound piRNAs are enriched for 1U only [Drosophila and Anopheles, even if this still has to be tested, we hypothesize that trigger-piRNAs of the An. gambiae snetDNA network are essentially Ago3-bound and responder-piRNAs Aub-bound. Our data give insights into the mechanisms of target slicing. Ago3-bound piRNAs in Drosophila, it is known that responder-piRNAs are essentially bound onto Aub with a minority of them bound onto Ago3 [An. gambiae snetDNA network, trigger–responder pairs are not necessarily followed by phased trail-piRNAs , AGAP011204 and AGAP009509 [In the smatches . We assue “seed” , while oe “seed” . It is nons 2-11 . For theAP009509 . We propAP009509 .An. gambiae mRNAs and lncRNAs are processed into piRNAs that are able to target other transcripts and direct them into the piRNA pathway, thus creating piRNA-mediated regulation networks. Such networks are based on the presence within the network transcripts of short repeated sequences, the snetDNAs, which are conserved from insects to mammals, notably in the 38 tested species of disease-vectors . Due to the production of piRNAs from snetDNAs, networks of interdependent regulation are established between different genes and lncRNAs and may control their transcripts’ stability/slicing within specific tissues where piRNA pathway and ping-pong amplification are known to be active. It is important to note that such regulatory pathways may function with any repeated sequences that produce piRNAs. Still, the conservation of specific snetDNA consensus sequences indicates an evolutionary and functional advantage of these specific sequences.Our present data suggest that An. gambiae snetDNA network evidenced here. Remarkably, it has been shown that the level of AGAP003387 transcripts was increased in piRNA-pathway-impaired females, in which PIWI class proteins Ago3, AGAP011204 and AGAP009509 were knocked down. These results obtained by knocking-down independently the three different PIWI class proteins show that AGAP003387 is regulated by the piRNA pathway [An. gambiae snetDNA network reported here.Targeting of transcripts by trigger-piRNAs and subsequent slicing may interfere with the expression of the targeted transcripts. AGAP003387 transcripts are part of the  pathway . Our datIn mouse testes, piRNA-guided cleavage of mRNAs has been demonstrated by Zhang et al. . The funAn. gambiae and in Ae. aegypti, but it may be anticipated that many more will be discovered through further analyses. As snetDNAs, very short repeated sequences, are sufficient to establish trigger/responder-piRNA-based regulatory networks in An. gambiae, it is likely that other repeats, TE-related or not, inserted within genes may assure additional regulatory networks based on piRNA biogenesis. It is conceivable that target genes with such repeats are repressed in normal environmental conditions because their transcripts are sliced for piRNA production. Their repression may vary in a concerted manner if epigenetic events affect the piRNA pathway, contributing to a possible rapid plasticity in their expression levels.In this study, we detail networks in