Implantology represents the gold standard in oral rehabilitation. Unfortunately, a new pathology begins to show itself to clinicians that no longer affects only and solely the supporting tissues of the tooth but also dental implants and peri-implantitis. In this study, we present a case report regarding a tissue regeneration maneuver involving dental implants. The clinical and radiographic results are encouraging, regarding the use of these techniques on implant surfaces. Surely, the advent of new biomaterials and surgical techniques will make this practice safe and predictable. The insertion of dental implants in clinical practice necessarily involves facing, statistically, a variable number of cases of mucositis and peri-implantitis.Mucositis is a reversible inflammatory process, limited to the peri-implant soft tissue, without affecting the attachment epithelium or the bone tissue.Peri-implantitis, on the other hand, is an inflammatory process which, in addition to affecting the soft tissues, is associated with peri-implant bone loss.Several studies have evaluated the incidence of peri-implantitis. According to Derks et al,To safeguard the osseointegration process, therapies are used that include the use of antibiotic and anti-inflammatory drugs, as well as a possible revision of surgical curettage of the affected area, and also guided bone regeneration (GBR). All therapies aim to eliminate bacteria from the surface of the implant both in the covered (without affecting the gum) and in the open (incising the gum and lifting it). When inflammation is present, therefore, it is considered necessary to use methods to decontaminate implant surfaces, with the goal of prolonging the prognosis of rehabilitations. In fact, the complete replacement of affected implants is not indicated, both in terms of morbidity and costs. Instead, we should aim at the development of predictable methods to restore implant health.Several methods of implant decontamination have been suggested, including mechanical therapies aimed at removing bacterial biofilm and smoothing the involved implant surfaces and chemical therapies such as application of antiseptics and local and systemic antibiotics. However, there is no consensus on the most effective protocol for detoxification of implant surfaces.Mechanical removal of bacterial aggregates on the surfaces, using powder spray with erythritol particles, accelerated by air pressure, is a method that is positively reported in the literature with regard to clinical improvements in depth and bleeding on probing.It has also been demonstrated that local antimicrobial agents play an important role in peri-implant bacterial control, particularly doxycycline, a bacteriostatic molecule belonging to the tetracycline class which is inserted into the peri-implant pocket and can be effective for up to 14 days.Another critical site that easily colonized by bacteria and difficult to reach for decontamination is the fixture-abutment interface, in this regard do Nascimento et alHowever, the exclusively nonsurgical approach was inadequate for the treatment of moderate-to-severe peri-implantitis where a surgical approach is instead required to reach the deepest implant surfaces to be decontaminated to restore the anatomy, to eliminate the peri-implant pockets, and to perform a regeneration of the present bone defect.It has been shown that vertical peri-implant bone defects can and should be treated by regenerative surgery, using only autologous or heterologous bone in combination or not with a membrane (GBR) and growth factors.Studies have evaluated that platelet concentrates, obtained by centrifugal separation of venous blood which include growth factors, are involved in increased angiogenesis activity, stimulate fibroblast and osteoblast activity, and increase hard and soft tissue regeneration.The aim of this study is to present the management of a dental implant clinical case in the esthetic zone  affected by peri-implantitis, with a combination of both chemical and surgical techniques to restore implant health.This case report describes a clinical case of a patient, 62-year-old male, Caucasian, in good general health, without any systemic problems, nonsmoker, and not on medication .The patient has an implant  in zone 2.1 placed with a postextraction technique with immediate loading in 2014.The patient reported that he underwent 6-month maintenance therapy and, in fact, from the compilation of the periodontal chart and radiographic evaluation , a good periodontal health is described with only one >5-mm probing in the mesiopalatal site of tooth element (left maxillary first molar 2.6), corresponding to a prosthetic restoration and with slight plaque accumulation. A good oral hygiene status is noted given the absence of bleeding at the probing and a plaque index of 5%. In correspondence of the implant in zone 2.1, on the other hand, pathological probes were found, especially in the central vestibular site with PD = 9 mm .Periapical X-ray showed peri-implant bone resorption and cone-beam computed tomography (CBCT) showed a 5.5-mm circumferential deficit .Clinically, the texture of the peri-implant mucosa is edematous, violet colored, but without loss of substance and/or exposure of the implant coils. Occlusal vision shows a clear deficit of mucogingival volume and/or bone in the vestibular side of the 2.1 area .We proceed with the treatment starting with a professional oral hygiene session, with decontamination of the implant area with erythritol Aereosol through a dedicated disposable tip inserted in the peri-implant defect itself .Subsequently, PERIOSTAT gel (iclated doxycycline) is applied, via a carrier with a tip, within the defectAfter 1 week from decontamination, the crown on implant 2.1 is removed, the cap screw is inserted with application of iodoform pasteOnce the soft tissues have healed, after 4 weeks, we can proceed with a regenerative surgery to regenerate the portion of peri-implant bone tissue lost due to peri-implantitis .Once anesthesia with vasoconstrictor  is performed, a flap is incised according to Canullo et al.Vestibularly, the design of the flap is similar to a flap for the treatment of multiple recessions in mucogingival surgery therefore it involves the following:A crestal incision.Incisions to draw surgical papillae bilaterally up to three teeth distal from the area to be regenerated.Flap dissection at half thickness up to the amelocemental junction and at a full thickness apically to it.Deepithelialization of the anatomic papillae to create a connective receiving bed for the surgical papillae.The lateral extension of the incisions allows to have a passivation of the flap without the need of vertical unloading cuts.Once the flap has been removed, the defect degranulated and washed with rifampicin , the implant is decontaminated using an electrolytic approach using GS1000 GalvoSurge Dental AGOnce the electrolytic decontamination is completed, the bone defect is filled with a deproteinized bone graft  mixed with autologous bone harvested intraorally and then covered with a resorbable membrane  and PGCL 6.0 .To rinse after the first 24 hours with CHX mouthwash  at 0.12% during the same period of time twice a day.Prescribed: amoxicillin of 875 mg + 125 mg Ac. Clavulanic for 4 days 2 times a day and nonsteroidal anti-inflammatory drugs (NSAIDs) as needed.The patient is checked every 7 days during the first month and then monthly for 12 months, when a new CBCT is then performed .During the numerous controls performed in the first 12 months after surgery, no clinical problems were detected, with an excellent control by the patient of home hygiene and a stability of periodontal indices, completely within the physiological range.There is a gingival recession, especially on the distal side in relation to the lack of bone peak on the lateral incisor. At 12 months, both an endoral periapical control X-ray and a CBCT were performed, showing a complete circumferential filling of the treated peri-implant defect. In fact, a total bone coverage of the shoulder of the 2.1 implant can be seen, with a bone gain of 6 mm on the mesial aspect and 5 mm on the distal aspect.The treatment of peri-implant lesions has long been a controversial topic. The purpose of the present case-report was to define a new surgical and regenerative protocol to restore peri-implant tissue health and esthetics in the esthetic zone. The results of the follow-up of more than 2 years showed an excellent reosteointegration of the bone around the implant affected by a combined defect similar to a crater in the most apical part and a vertical defect in the distal region.It is important to emphasize that the result obtained from the clinical case is the sum of a series of biological and mechanical factors that a clinician should consider. First of all, a nonsurgical and antibiotic approach was used to treat the periodontal pocket that presented bleeding and suppuration phenomena. The aim of this first approach is also to make the tissues less edematous and more manageable from a surgical point of view.Microbiological studies conducted by Canullo et alIt is important to underline that the removal of the crown allows from a clinical point of view a better access to the pocket and to the surface to be decontaminated.When approaching a vertical regenerative case, one of the most complex aspects is certainly the management of the flap. For this reason, in this case, a platelet concentrate has been wrapped around the screw cap with the aim to enhance the healing of soft tissues. In addition, some studies in the literature have drawn attention to the fact that the presence of leukocytes in platelet concentrates may allow a greater control of postoperative infections and may be a protective factor in cases at risk of osteomyelitis.The surgical therapy used is initially characterized by the use of a coronally advanced flap for the treatment of multiple recessions. This allows for the avoidance of scarring in areas where release cuts might be necessary and ensures a greater blood supply to the flap.Total decontamination of the surfaces is required before regenerative surgery is performed. The presence of nano- and microparticles, bacterial-derived antigens, or ions on implant surfaces can lead to bone resorption or failure of osseointegration. To fully understand these biochemical mechanisms, osteoimmunology, a rapidly developing branch that studies the interrelationship between bone tissue cells and the immune system, has been introduced.Indeed, initially the inflammatory infiltrate together with macrophages allows for a proregenerative peri-implant environment. Subsequently, if the inflammation is not resolved or reactivated due to the immunogenic signals of the contaminants, infections with subsequent bone loss or aseptic inflammation could occur.Nonsurgical methods of surface decontamination have demonstrated suboptimal results.Methods of implant surface decontamination using mechanical, sonic, and ultrasonic scalers, laser, air flow, and various chemical solutions, such as chlorhexidine digluconate, citric acid, and hydrogen peroxide, have been proposed in many studies.However, in the literature, results about newly formed bone vary widely, and it is often difficult to quantify how much of the radiographically present bone is actually osseointegrated on the implant surfaces.Small areas of osteitis around the body of implants in peri-implantitis may remain contaminated despite mechanical removal of granulation tissue, so it may be useful to treat contaminated bone by topical application of rifampicin.+) are dissociated by the current. The highly reactive H+ions form hydrogen bubbles on interaction with the stray electrons which lift the biofilm from the implant surface.in vitrostudy demonstrated complete sterilization of surfaces after electrolytic treatment.Once the granulation tissue around the implant was removed and the recipient bone site was exposed, a new tool called GalvoSurge was introduced to decontaminate the surface. The recently developed system involves using an electric current on an implant treated with sodium formicate. Hydrogen anion (OH − ) and cation (HAn extremely interesting aspect is represented by the possibility to decontaminate an implant surface without changing its surface microtopography and therefore without affecting its physical properties.Promising reosteointegration of contaminated implant surfaces after electrolytic cleaning has been demonstrated in two clinical studies.The limitations of this technique are represented by the impossibility to regenerate defects above the bone peaks, so a combined regenerative and resective approach should not be underestimated in cases that require it. The use of GalvoSurge in fact would allow the removal of particular matter resulting from the release of titanium particles around the surface without affecting the healing process. In the literature, there is much debate about the influence of metal particles on tissues. In fact, this same particulate could result in a negative modulation of osteoimmunology and could result in an aseptic foreign body reaction around the implant.Ultimately, it can be said that electrolytic cleaning, although recently introduced, is an extremely interesting method for the regenerative management of peri-implants. Future studies will be needed to understand the dynamics around healing of sites treated with GalvoSurge.Nonmechanical therapies involve the use of antiseptic and antibiotic solutions, both in the form of washes and in slow-release forms from the gel to the impregnated fibers. The laser can sterilize surfaces. The common limitation of all therapies that are limited to eliminating bacteria by disinfecting or sterilizing is that they will recolonize the spaces as bacteria are not found only on implants. It becomes essential to correct these bone defects, so that they do not return to being reservoirs of infection. GBR is useful in this sense, unless you resort to resective therapies that will bring decontaminated surface outdoors into cleanable areas. It must be observed, however, how important it is to intercept, together with the microbiological contamination, the possible iatrogenic background of the peri-implant disease. Failing in classifying the possible surgical or prosthetic triggering factors may lead to a failure in the treatment outcomes.The presented case demonstrated a new and promising protocol for the regenerative management of sites affected by peri-implantitis. The ability to regenerate healthy, viable bone around implants is critical in cases where esthetic demands are more demanding. Combining these surgical techniques and these pharmacological protocols will allow clinicians to offer safer and more predictable rehabilitations over time. Future studies will be necessary to fully understand the timing and dynamics regarding wound healing of sites treated with GalvoSurge. In addition, a comparison of the healing dynamics of treated sites in relation to different implant surfaces would be desirable.


The mindfulness trait is an intrinsic characteristic of one’s disposition that facilitates awareness of the present moment. Meditation has proven to enhance situational awareness. In this study, we compared the performance of participants that were split into two groups depending on their experience in mindfulness meditation (a control group naive to mindfulness meditation and a group of experienced mindfulness meditators). Choice-blindness happens when people fail to notice mismatches between their intentions and the consequences of decisions. Our task consisted of decisions where participants chose one preferred female facial image from a pair of images for a total of 15 decisions. By reversing the decisions, unbeknownst to the participants, three discrepancies were introduced in an online experimental design. Our results indicate that the likelihood of detecting one or more manipulations was higher in the mindful group compared to the control group. The higher FMI scores of the mindful group did not contribute to this observation; only the practice of mindfulness meditation itself did. Thus, this could be explained by better introspective access and control of reasoning processes acquired during practice and not by the latent characteristics that are attributed to the mindfulness trait. Cognitive biases are responsible for many of the behaviors that deviate from what would be considered rational in a given situation. Research has shown evidence supporting the idea that mindfulness meditation could reduce the effect of some well-known cognitive biases  effect, first observed by Johansson and collaborators , is one According to Petitmengin and collaborators , the CB The results of this research indicate that studying the effect of CB on experienced mindfulness meditators may be a relevant direction to follow. In doing so, we could investigate whether this effect can be found in participants who have acquired abilities similar to those triggered by the explanatory interviews. For this reason, experienced mindfulness meditators should be able to avoid the CB effect with greater ease than inexperienced meditators. Should this hypothesis be correct, it could have consequences in the field of decision-making.This article highlights the literature indicating a potential link between a decrease in CB and mindfulness meditation and replicates the study of Johansson and collaborators  with a gMindfulness consists of both a natural psychological predisposition as well as a personality trait that is developed and maintained through the practice of mindfulness meditation . The praTang and collaborators present a model of mindfulness meditation including at least three components: “enhanced attention control, improved emotion regulation, and altered self-awareness ”. The interaction between these three factors enhances self-regulation  (p. 2).Others describe mindfulness as a specific form of mental training to develop self-awareness, self-regulation, and self-transcendence  and as aStudies have shown that people who regularly meditate often develop trait, or dispositional, mindfulness . The minTrait mindfulness can also decrease the influence of some cognitive biases related to decision-making ,2,3,4,32FMI-14 items is validated for use outside of a Buddhist context and can be completed by people without any knowledge of meditation [Trait mindfulness is often measured with a scale called the Freiburg Mindfulness Inventory (FMI). The version ditation ,39. Studditation ,40 and tditation , indicatditation . We ensuThe CB paradigm involves giving participants false feedback on their choices, thus creating a mismatch between their intentions and the outcome of their choices ,16,42,43Two interpretations of the CB phenomenon are of interest here. CB could be the result of insufficient introspection ,11,12 anMoreover, positive emotions increase the perception of false feedback in a visual task of CB , and theIn this study, we replicated a computer-mediated version of the original paradigm of CB ,50,51. AAs we described above, greater access to state mindfulness could potentially counter CB by remedying insufficient introspection and underestimation of the influences of environmental and situational factors, as the lack of these two aptitudes is the main cause of CB described in the literature.The main hypothesis is that mindfulness meditators should be less sensitive to the CB effect compared to non-meditators. Thus, we suppose experienced mindfulness meditators will be able to detect more manipulations in this CB context compared to non-meditators. To investigate this, we conducted a comparative and correlational study including two groups: a group of experienced mindfulness meditators  and a group of non-meditators (control group). We counted the number of times participants in each group reported detecting a manipulation.We thus expect to observe a higher rate of manipulation detection in the group of mindfulness meditators compared to the control group.http://paris-reasoning.eu, accessed on 2 November 2022. The ethics committee declaration is available at https://doi.org/10.17605/OSF.IO/37GPY, accessed on 2 November 2022).A total of 66 participants aged between 25 and 55 participated in the study , and to have practiced within an institution (association or club). The different types of meditation practices included were mindfulness exercises supervised by an instructor . Participants in the group of non-meditators were required to have no experience of mindfulness-related practices, including meditation, yoga, tai chi, qigong or martial arts, but were potentially interested in them. The group formation methodology is similar to those used in several studies ,53,54,55After assigning the participants to one of the two groups (experienced meditators or non-meditators), we checked that the experienced meditators had a higher level of trait mindfulness than non-meditators. To do so, participants answered the validated French version  of the FThe experiment was a computer-mediated replication of CB paradigms ,50,51. Phttps://www.wilmabainbridge.com/facememorability2.html, accessed on 2 November 2022) [The survey for the experiment was created with the online software Qualtrics. We used greyscale pictures of human faces extracted from the 10k US Adult Faces Database  . The sizer 2022) , we onlyParticipants were asked to follow the experiment from home in a quiet place for half an hour (duration of the experiment), during which they should not be disturbed. In order to check if they had been disturbed, they were encouraged to report it and to describe the nature of the disturbance in a free comment space at the end of the questionnaire. No participants reported being disturbed during the experiment.A total of 15 pairs of grayscale pictures of women’s faces were shown to each participant in random order. Overall, 9 out of the 15 pairs were distractors, and 6 were used to evaluate the participant’s ability to notice that the outcome of their choice was manipulated. Participants had an unlimited amount of time to make their choices. A total of 3 out of these 6 pairs were manipulated (M), and the remaining 3 were not (NM). Once the choice was made, the pictures were hidden. For these 6 pairs (M and NM), the participants were asked to explain their choices. Then, the protocol differed for M and NM. For NM, the chosen picture was then displayed again and disappeared once more prior to this face being rated for attractiveness on a 10-point scale. The other face was not rated. For the M pairs, the picture that did not correspond to their choice was displayed and then rated .Participants were then given the opportunity to freely express themselves. To avoid making the participants suspicious regarding the intent of this open field, the question remained as neutral as possible (“Do you have any remarks or comments to add?” (“Avez-vous des remarques ou commentaires à ajouter”)). These instructions were repeated for all 6 pairs of faces used during the evaluation. Once all 15 pairs had been presented, participants were asked if they had noticed anything strange during the experiment with an open-ended question. Finally, they were asked whether they knew about CB .We first analyzed the socio-demographic data by performing descriptive statistics to visualize the distribution of the data of the demographic variables , as well as the means of the FMI score, according to the groups .We then performed 2 classical ANOVAs and 1 Bayesian ANOVA to investigate the influence of these variables on manipulation detection (demographic variables and FMI score). Non-significant results would indicate the independence of these variables with respect to the participant’s ability to detect manipulations.The second analysis concerns the manipulation detection score by group (experienced meditators and non-meditators) expressed in percentages and detection means. In total, the experienced meditator and non-meditator groups were exposed to 93 and 105 manipulations, respectively. We calculated how many manipulations were detected in each group and transformed them into percentages to make the scores comparable.The third analysis considers the number of manipulations detected per subject . Two main variables were used in this experiment. The independent variable was the presence or absence of meditation practice. The dependent variable was an ordinal variable with four modalities: the number of detected manipulations.To find out whether meditators detected more manipulations than non-meditators, we used a multinomial logistic regression for the analysis of the collected data. Two multinomial models were adjusted. First, we adjusted the model in which the linear predictor contained the independent variable , and then we adjusted the null model, which did not contain any predictor .We then calculated the chances of detecting manipulations as a function of group membership using the odds ratio method.Descriptive analyses were performed on the participants’ socio-demographic data. The socio-demographic variables, such as age, sex, education level, and profession, did not have any effect on the detection of manipulations (an ANOVA was run with these variables in the predictive model. Results indicated that sex did not have any effect on the number of detections (We found no direct influence of FMI scores on the detection of manipulations (with ANOVA) with very strong evidence in favor of the null hypothesis (H0: no effect of FMI scores on the detection of manipulations)  .p-value is obtained with Fisher’s exact test (FET).)), The experienced meditators’ likelihoods (odds ratio) of detecting 1 or more, 2 or more, or all 3 manipulations were Results suggest that cultivated mindfulness could influence the detection of manipulations but not dispositional (or trait) mindfulness. CB was reduced for experienced meditators in comparison to what we could observe for non-meditators, as they were more likely to detect manipulations. Furthermore, the socio-demographic variables such as sex, age, profession, and study level cannot explain the better result of the mindful group on the detection of manipulations as there was no statistical difference between the two groups for any of them, leaving only the experience of mindfulness meditation as a predictor of the observed effect on CB.We believe that the ability of experienced meditators to better detect manipulation can be explained by the habit of meditation because it improves two processes responsible for CB: introspective access ,6 and a The development of better introspective access can be of great help in countering CB. Indeed, a lack of introspection, which is one of the primary explanations for CB, can be caused either by self-ignorance of our choices or ignorance of the mismatched outcomes ,11,12. IIncreased well-being in mindfulness meditators ,48,49 miMoreover, mindfulness not only improves one’s ability to focus on environmental details ,8, but iAnother primary explanation for CB is the under-estimation of the influence of environmental and situational factors in decision-making , likely It is also possible that experienced meditators had higher detection scores than non-meditators because they acted with more autonomy . Having Mindfulness has already been linked to the decreased prevalence of certain cognitive biases  that couIt would thus seem that mindfulness meditators could more easily de-automatize their mental operations ,58, switGiven that this study is only correlational, it could be argued that an alternative interpretation of our results would be that experienced meditators could have already had a greater ability for introspection even before practicing mindfulness. This predisposition could then have been enhanced and maintained by regular mindfulness practice.This study focuses on a population of self-reported meditators. All participants had to certify that they regularly practiced mindfulness meditation in the context of a club or association to consolidate the meditator group. The higher FMI score of meditators compared to that of non-meditators allows the validation of the groups. However, it would be interesting to reproduce this experiment in a longitudinal study to more strictly control the practice of meditation in order to further strengthen the conclusions drawn from these data.It is also important to point out that FMI scores are not directly correlated with the better detection of manipulations. This may seem counter-intuitive, as both groups had different FMI scores and different detection rates, but this does not hold at an individual level. This observation highlights the weakness regarding the reliability of the FMI survey in regard to the assessment of the mindfulness trait of individuals.Moreover, the FMI score seems to be difficult to compare between expert and naive participants. Indeed, this comparison is controversial for two reasons. First is the occurrence of the Dunning–Kruger effect. This effect appears when a lack of expertise in a particular field causes errors in self-assessment ,61. We cThe second reason is that the FMI scale is not systematically understood in the same way by meditators and non-meditators . These tAnother potential limitation of our study is the disagreement between the model selection criteria (AIC and BIC), which could indicate ambiguous models. Each criterion has a different purpose. AIC aims at selecting the best model which predicts the data, while BIC aims at selecting the true model which generated the data. As a consequence, AIC has the tendency of favoring overly complex models, while BIC has the opposite tendency of favoring overly simple models when the true model is not in the list of tested models. Much debate exists concerning the criterion that should be used, and for what purpose (see  for a coThis study showed that CB was reduced in experienced meditators compared to non-meditators. These results suggest that the experienced meditators possess characteristics not measured by the FMI, which could explain the results obtained. While this experiment does not allow the investigation of which specific characteristics are involved, we hypothesize that they are related to the regular training of attentional control during meditation practice.To go further, conducting a longitudinal study on meditators would be interesting in order to confirm these results. Indeed, such a study would allow us to see when this difference in CB sensitivity starts manifesting itself: before the first meditations, which would indicate pre-existing characteristics influencing CB sensitivity, early following the first meditations, which would indicate that the mere awareness of these processes would be enough, or only after a certain time with regular meditation, which would indicate an actual training to de-automatize certain processes.The question of the de-automatization of decision-making through mindfulness and the investigation of the effects state mindfulness and trait mindfulness each have on cognition should also be further investigated in order to consolidate these results.


Protein machines are clusters of protein assemblies that function in order to control the transfer of matter and energy in cells. For a specific protein machine, its working mechanisms are not only determined by the static crystal structures, but also related to the conformational transition dynamics and the corresponding energy profiles. With the rapid development of crystallographic techniques, the spatial scale of resolved structures is reaching up to thousands of residues, and the concomitant conformational changes become more and more complicated, posing a great challenge for computational biology research. Previously, a coarse-grained (CG) model aiming at conformational free energy evaluation was developed and showed excellent ability to reproduce the energy profiles by accurate electrostatic interaction calculations. In this study, we extended the application of the CG model to a series of large-scale protein machine systems. The spike protein trimer of SARS-CoV-2, ATP citrate lyase (ACLY) tetramer, and P4-ATPases systems were carefully studied and discussed as examples. It is indicated that the CG model is effective to depict the energy profiles of the conformational pathway between two endpoint structures, especially for large-scale systems. Both the energy change and energy barrier between endpoint structures provide reasonable mechanism explanations for the associated biological processes, including the opening of receptor binding domain (RBD) of spike protein, the phospholipid transportation of P4-ATPase, and the loop translocation of ACLY. Taken together, the CG model provides a suitable alternative in mechanistic studies related to conformational change in large-scale protein machines. Protein machines are the basic units to perform biological functions in cells. By responding to biological stimulus such as substrate binding or nucleoside triphosphate hydrolysis, they can execute directional molecular movements or specific chemical reaction pathways, and they play an important role in the cycle of matter and energy in cells . A largeThe technique of molecular dynamics simulation can reproduce conformational ensembles for a given molecule based on the application of empirical atomic force fields and the classical Newtonian dynamic equations, constituting an effective tool to analyze protein conformational changes. However, the exploration of conformational pathways for biological macromolecules are often limited by a series of factors such as the temporal or spatial scale of the involved biological processes, and the accuracy of empirical force fields . For proThe application of coarse-grained models is an effective approach for studying the conformational change of complex macromolecules and the associated energetics and dynamic features. In all CG models, a common purpose of reducing the freedom complexity of modeling systems was achieved by simplifying the amino acid side-chain or even the entire amino acid . DependiHere, we tried to expand the application of the CG model developed by Warshel and coworkers to a series of large-scale protein machines reported currently. The CG model was developed in the 1970s for solving the protein folding problem , and wasIn this study, we further applied CG models to conformational pathway analysis of large-scale biomolecular systems, including protein–protein interaction, enzymes, and transmembrane protein systems. A complete workflow comprising molecular modeling, acquisition of intermediate conformations, determination of electrostatic charge, and conformational free energy calculation was built and applied to describe the working processes of different protein machines from the perspective of energy profiles. Although these systems had different solvent environments, biological function, and conformational changes, the CG models can provide a reasonable trend of conformational free energy change. We hope that the energy analysis and conformational exploration of the CG model can be applied to more systems.The coarse-grained (CG) model applied in this work is based on the solvation of ionizable residues and emphasizes the electrostatic effects within proteins. In the CG model, the sidechain atoms are united into a simplified atom, while the atoms of the main chain are explicitly represented. The simplified atom is located at the mass center of side chains for polar and nonpolar residues, and at the center of the charged part for ionizable residues. The CG model is derived by fitting to the observed absolute stability, which means the folding free energy of proteins is expressed as:pKa under protein environment, the pKa in water of the ith ionizable residue, the folded states interaction potential, the unfolded states interaction potential of ionized groups, and the term that describes the scaled-down effect of changing the protonation state of an ionizable residue upon unfolding, respectively. For the estimation of The mainchain interaction involves van der Waals interactions and electrostatic effects, and all bonding terms are calculated by ENZYMIX force field . The keymth charge configuration mth charge configuration. When a lower value of electrostatic free energy is achieved or the Metropolis criteria are met, the charge configuration is accepted. The minimized The Metropolis Monte Carlo (MC) approach is applied to determine the ionization states of protein residues under given pH and temperature ,32. Eachith residue in its ionized state . U is effective potential, and ith residue, respectively. The empirical function The ulations . Nmem isproteins .Here, we present a molecular modeling workflow to explore the dynamic properties of protein machines in terms of their conformational pathways and free energy profiles. The complete workflow consists of four steps, namely, molecular modeling, acquisition of intermediate conformations, determination of electrostatic charge, and conformational free energy calculation.TMDF) on each target atom is given by the equation:k represents the spring constant and N represents the number of targeted atoms. (t)RMS is the current RMS value. RMS(0) is a reference value which evolves linearly from the initial RMSD to the final RMSD [2. The system was restrained throughout the simulation to prevent abnormal translation and rotation. When TMD from the initial state to the target state was completed, the initial and final states were interchanged, so we can obtain the intermediate structures of the whole transition process. Then, the accurate electrostatic charge was computed by the Monte Carlo Proton Transfer (MCPT) method. Finally, each structure was converted into coarse-grained (CG) representation and the CG free energy was calculated to obtain the conformational free energy profiles. For transmembrane proteins, membrane particles were added, and molecular dynamics relaxation was carried out to attain energy convergence. All simulations were completed by Molaris-XG software [Firstly, the initial endpoint assemblies connecting a specific biological process were built based on the crystal structures from the Protein Data Bank database . The misnal RMSD . The inisoftware .Protein–protein interaction (PPI) is the basic cooperation form wherein proteins perform their functions together. The formation of interfacial interactions is coupled with specific conformational states of each protein partner; therefore, the conformational change is an important regulatory mechanism for the binding and unbinding process of protein–protein interaction systems. Starting from the unbinding conformation, the protein will go through a series of intermediate conformations until it finally reaches another protein to form binding interactions. The energic profile of a protein’s conformational change process can explain detailed mechanisms for the existence of a PPI relationship with its partner.The spike protein of SARS-CoV-2 is a typical molecular machine that depends on conformational changes to form protein–protein interaction. It locates on the surface of the viral envelope and mediates the viral entry into cells by interacting with the ACE2 receptor of human cells through its receptor binding domain (RBD) ,39. A coHere, we constructed CG models of the spike protein to reduce the resource demand for molecular modeling. The structural models of three conformations of the spike trimer were built by the Cryo-EM structures  resolved by Xu et al. . Then, tAs a special class of protein machines, enzymes reduce the energy barriers of chemical reactions with the help of key residues or cofactors under the protein environment. Upon substrate binding, an enzyme may undergo a wide range of conformational changes, but only some specific intermediate states are important and meaningful for their stabilities on kinetic and thermodynamic properties . It is h2+-ATP and citrate. The overall reaction is as follows: Mg2+-ATP + Citrate + CoA → Mg2+-ADP + Pi + Ac-CoA + oxaloacetate. Its substrate-binding process is accomplished with the successive binding of Mg2+-ATP, Citrate, CoA, and the related chemical reactions, as shown in 2+-ATP site to the citrate site after reaction (i), and (2) the CCS domain on each monomer underwent significant conformational changes compared to the CCL domain. Owing to the structural lack of His760-located loop in both apo and substrate-binding crystal structures, it is unclear whether these two conformational changes occur in cascade or in coupled ways. Therefore, we tried to construct a detailed free energy profile of conformational change and provide a clear mechanistic explanation.ATP-citrate lyase (ACLY) is a representative central metabolic enzyme linking carbohydrate and lipid metabolism . It cataHere, the ACLY tetramers along the substrate-binding process were built based on the D2-symmetrical Cryo-EM structures solved by Wei et al. . The two2+-ATP at the starting point is the driving force of the conformational shift of His760-located loop [2+-ATP activation in the catalytic cycle of ACLY. A comparison between the energy barriers of three pathways shows that the coupling of conf. 1 and conf. 2 in pathway 1 could effectively reduce the highest energy barriers of conf. 1 , which preliminarily showed the synergy between different domains during the conformational change process.As shown in ted loop . The aboTransmembrane proteins are integral to many biological processes such as membrane trafficking, enzymatic activity, and cell–cell recognition, to name a few . The funForm2MC  in the E1P state conforms to the assumption that the electrostatic term usually contributes the most from the different interaction items in biophysical systems [Here, the initial models were constructed based on the Cryo-EM structures solved by Hiraizumi and coworkers . The six systems .We also analyzed the whole energy transition for the transport cycle along the lipid flipping reaction, as shown in Here, we reported the application of the CG model on several large-scale protein machine systems. It is important to mention that our results still follow the philosophy of capturing more relevant physical features and focusing less on minute details . It is n2+, and ATP to carry out chemical reactions; and the lipids need to bind to P4-ATPase to be transported. There is no doubt that the participation of these biomolecules may promote or depend on the conformational changes of the protein machines. It is important to understand the coupling relationship between conformational change and biological events and then gain a deeper understanding of protein functions. Achieving this goal requires more efficient modeling of the free energy landscape of biological process, which must extend the application of the CG model by combining it with other computational methods—for example, using the empirical valence bond (EVB) method [With the development and application of cryo-electron microscopy, more and more intermediate conformation states of protein machine systems will be resolved, and the CG model will be more widely applied in this context. The most important application of the CG model is in studying the coupling of a protein’s conformational changes with specific reactions. Most protein machines cannot function solely by conformational transitions and need to be coupled with interactions with other biomolecules. For instance, the spike proteins must interact with the ACE2 receptor to invade cells; the catalytic reaction of ACLY involves the substrate binding of CoA, Mg) method  to compu) method  to calcu


Ozone concentrations are key indicators of air quality. Modeling ozone concentrations is challenging because they change both spatially and temporally with complicated structures. Missing data bring even more difficulties. One of our interests in this paper is to model ozone concentrations in a region in the presence of missing data. We propose a method without any assumptions on the correlation structure to estimate the covariance matrix through a dimension expansion method for modeling the semivariograms in nonstationary fields based on the estimations from the hierarchical Bayesian spatio-temporal modeling technique (Le and Zidek). Further, we apply an entropy criterion  based on a predictive model to decide if new stations need to be added. This entropy criterion helps to solve the environmental network design problem. For demonstration, we apply the method to the ozone concentrations at 25 stations in the Pittsburgh region studied. The comparison of the proposed method and the one is provided through leave-one-out cross-validation, which shows that the proposed method is more general and applicable. Ozone concentrations are the daily maximum 8 h moving averages of hourly ozone concentration data recorded in micrograms per cubic meter, ented in , althougented in ,2, amonghierarchical Bayesian spatio-temporal (HBST) modeling proposed in ,,add sitejth sample generated from the predictive distributions and i on time t. The results are given in In this section, we use the leave-one-out cross-validation to evaluate the accuracy of the predictive model derived using the proposed method and compare the proposed method with the one in . We seleIn In this paper, we have derived a predictive model through the hierarchical Bayesian spatio-temporal modeling technique given in  at ungau


Noise is a common problem in wearable electrocardiogram (ECG) monitoring systems because the presence of noise can corrupt the ECG waveform causing inaccurate signal interpretation. By comparison with electromagnetic interference and its minimization, the reduction of motion artifact is more difficult and challenging because its time-frequency characteristics are unpredictable. Based on the characteristics of motion artifacts, this work uses adaptive filtering, a specially designed ECG device, and an Impedance Pneumography (IP) data acquisition system to combat motion artifacts. The newly designed ECG-IP acquisition system maximizes signal correlation by measuring both ECG and IP signals simultaneously using the same pair of electrodes. Signal comparison investigations between ECG and IP signals under five different body motions were carried out, and the Pearson Correlation Coefficient |r| was higher than 0.6 in all cases, indicating a good correlation. To optimize the performance of adaptive motion artifact reduction, the IP signal was filtered to a 5 Hz low-pass filter and then fed into a Recursive Least Squares (RLS) adaptive filter as a reference input signal. The performance of the proposed motion artifact reduction method was evaluated subjectively and objectively, and the results proved that the method could suppress the motion artifacts and achieve minimal distortion to the denoised ECG signal. In recent years, there has been an increasing interest in wearable electrocardiogram (ECG) monitoring systems. This interest comes from two aspects: societal needs and technology drive. Wearable ECG monitoring systems provide real-time vital sign monitoring, early disease detection, and telemedicine interventions, providing a good solution to the medical challenges posed not only by rapid population aging and healthcare cost inflation, but also by wellbeing requirements of an increasingly more health-conscious society. There is a huge demand for the latter, because as people are becoming more aware of their wellbeing and doing more exercise, these devices help them conduct their own, personal health monitoring independently. This has become possible with the miniaturization of electronics, improvements in the performance of low-power microprocessors, the ability of electronic textiles, and the development of artificial intelligence, rendering wearable healthcare monitoring systems to become increasingly portable, accurate, and powerful.The ECG signal reflects the electrical activity of the heart, which is a weak physiological signal and hence very susceptible to various kinds of noise . HoweverMotion artifacts have long been a problem in ECG measurement, the reduction of motion artifacts is difficult and challenging not only because the spectrum of motion artifacts is considerably overlapped with the important spectral components of the ECG signal, but also because the presence of the motion artifacts is inevitable and unpredictable in the wearable ECG measurement data. Motion artifacts are transient (but not step) baseline wander resulting from movement of the wearer, or the electrode . The mosThe skin potential is usually negative, and the magnitude of the skin potential varies depending on the subject, skin site, and the condition of the skin. Floyd and Keele  found thTo make wearable ECG monitoring systems practically applicable, motion artifact reduction is one of the most challenging problems that need to be overcome. The performance of different motion artifact reduction methods has been investigated in many studies ,16,17,18In this article, we aimed to use an adaptive filtering technique to solve the problem of motion artifact in wearable ECGs. We have studied the motion artifact reduction performance of adaptive filters that use an impedance pneumography (IP) signal as a reference input signal. To ensure that the IP signal correlated with the motion artifact in ECG signals, we designed hardware that records ECG and IP simultaneously. The correlation between the IP and the motion artifact in the ECG signal was studied in order to test whether the IP signal is suitable as the reference input for adaptive filtering. Finally, we evaluated the performance of the proposed motion artifact reduction method with noisy ECG signals that were recorded while the subjects performed five typical upper body motions. The adaptive filtering method attracted our attention because it can adaptively track the signal under non-stationary conditions and can adjust its impulse response to filter out the noise in the input with little or no prior knowledge of the signal and noise characteristics . The adaX’(n) that is the best fit in the least squares sense to the signal X(n) by feeding the system output back to the adaptive filter and adjusting the filter through an adaptive algorithm to minimize total system output power [e(n). The reference signal S(n) is fed into a digital filter to produce an output N’(n), which is as close as possible to the replica of the noise N(n). Subsequently, this filtered signal output y(n) is subtracted from the primary input d(n) to obtain the estimated desired signal X’(n) [ut power . The adaal X’(n) . As can N’(n) to reduce the unwanted high-frequency components, the results of the denoised ECG using an RLS adaptive filter and a 5 Hz low-pass filter are shown in Least mean squares (LMS), Normalised Least Mean Squares (NLMS), and Recursive Least Squares (RLS) are the three most commonly used algorithms in adaptive filtering. In our preliminary trials, we found the three adaptive algorithms LMS, NLMS, and RLS are all capable of removing motion artifacts from the noisy ECG signal, but their noise reduction performance varies with the selection of the step size As for the reference input signal, according to the principles of adaptive filtering, a suitable reference input signal should correlate in some way with the noise to be removed but uncorrelated with the desired signal . HoweverIn summary, a desired reference input signal for motion artifact reduction should have a good correlation with motion artifacts and should not be correlated with the ECG signal itself. Therefore, in our proposed method, we used specially designed hardware to simultaneously record both the ECG signal and the reference input signal in order to maximize the correlation between the primary input and the reference input. Furthermore, we applied a 5 Hz low-pass filter to eliminate uncorrelated noise and unwanted ECG components from the reference input signal. The proposed adaptive motion artifact reduction method is shown in The Impedance Pneumography (IP) signal is a measure of the electrical impedance change of the subject’s thorax caused by respiration, as any increase in the volume of air respiration during each breathing cycle the electrical conductivity of the person’s thorax is reduced. In fact, if we consider the IP signal generated by the change in impedance as noise, it reflects the respiratory motion artifact as well as the motion artifact caused by skin deformation. Thus, from the origin of IP signals, there is a certain correlation between IP signals and the motion artifacts in ECG signals, which makes the IP signal a good option when looking for a reference input signal to adaptive reduce motion artifacts. In order to suppress motion artifacts from ECG signals, we designed a wearable ECG-IP acquisition system consisting of a microcontroller MSP430F5438A , an analogue front-end (AFE), a Bluetooth module RN41 , and three textile electrodes. The AFE circuit board contains an analogue pre-amplifier ADS1292R  and its peripheral circuitry to simultaneously record ECG and IP signals. The ADS1292R used in the AFE is of low power, and it is characterized by a high common-mode rejection ratio (−120 dB), 2-channels, and a 24-bit delta-sigma analog-to-digital converter (ADC) with integrated programmable gain amplifiers (PGAs). It is able to sample the ECG and IP signals, convert them from analog to digital and send data via a Serial Port Interface. With the integration of the respiration impedance measurement module, the ADS1292R measures the sum of the skin-electrode impedance and thoracic impedance. The respiration module in the ADS1292R contains a modulation block and a demodulation block. The modulation block produces a 2.42 V, 32 kHz square wave and injects it into the body as a carrier that is amplitude-modulated by a low-frequency signal generated as a result of the breathing action. The generated 32 kHz square wave is fed into the electrodes through the RESP_MODP and RESP_MODN pins, and the amplitude-modulated signal is received by the IN1P and IN1N pins of the ADS1292R. The measurement of the respiration impedance uses the same pair of electrodes for ECG measurement, so the measured IP signal has some correlation with the motion artifacts in the ECG signal. As can be seen in The aim of this work was to reduce the motion artifacts in the ECG signal by adaptive filtering, so the feasibility of using an IP signal as a reference input signal to adaptively reduce motion artifacts from the ECG signal was discussed. Since the ideal reference input for an adaptive filter should be correlated with the motion artifacts to be canceled but uncorrelated with the ECG signal, the motion artifacts in the IP signal should be preserved, but the cardiac-related signal should be eliminated. The frequency of cardiac-related artifacts in the IP signals is usually related to the QRS complex of ECG waves, which has a fundamental frequency of about 10 Hz . As for In the experiments, three textile electrodes were used to measure wearable ECG and IP signals, two of which were connected to the ELA and ERA pin of the AFE circuit board for 1-lead ECG recording and IP recording, and the remaining one textile electrode was connected as a ground electrode to the ERL pin of the AFE circuit board for common mode noise rejection. The fabrication of textile electrodes and their performance for ECG measurement has been discussed in another of our articles . The thrIn order to evaluate the performance of our proposed adaptive motion artifacts reduction method with the actually recorded noisy ECG signals, we simulated five common motions of daily life, and used the designed ECG-IP acquisition system to record the raw ECG and IP signals as disturbed by the different types of motion, as shown in As shown in According to the principles of adaptive filtering, the performance of an adaptive filter in reducing motion artifacts is highly dependent on the characteristics of the reference signal. The higher the correlation between the reference signal and the motion artifacts, the better the performance in reducing motion artifacts. Therefore, the Pearson correlation coefficient was used as an indicator to determine whether the IP signal can be used as a reference input signal for the motion artifacts reduction.The absolute value of the Pearson correlaion coefficient Parameters such as the improvement of signal-to-noise ratio (SNR), correlation coefficient (c), mean-squared error (MSE), and R-square were often used to evaluate the noise reduction performance of different filters. However, the calculation of these parameters requires prior knowledge of the “clean” signal, which is the main reason that the simulated noisy ECGs were widely used in other relevant studies. But in our work, the actual recorded noisy ECGs were used instead of the simulated noisy ECGs, so there is no independent noise-free “clean” ECG signal that can be used to calculate parameters such as SNR. Therefore, in this study, the concept “goodness-of-fit”  was usedThe performance of the adaptive motion artifact reduction method was also compared with the 0.5 Hz IIR high-pass filter commonly used in practice to verify the efficiency of the proposed method. For this comparison, the standard deviation of the original ECG signal and the standard deviation of the denoised ECG signal were used to measure the reduction of motion artifacts. In statistics, the standard deviation is a measure of the amount of variation in a set of values. Because the motion artifacts are reflected as ECG baseline drift, a low standard deviation indicates less baseline drift (fewer motion artifacts), and a high standard deviation indicates more baseline drift (more motion artifacts). Therefore, the performance of the adaptive motion artifact reduction method and the IIR filter can be evaluated by comparing the STD values of the original noisy ECG and the denoised ECG. The standard deviation (STD) is defined as:2 were calculated. The m_MSE value closer to 0 and the m_R2 value closer to 1 indicate that the performance of motion artifact reduction is better. Results are shown in 2 is larger than 0.7. These results indicate that the proposed adaptive motion artifact reduction method has good performance in reducing motion artifacts. As can be seen in Driven by social needs and technology, the demand for wearable healthcare monitoring devices is growing and is expected to accelerate in the future. Wearable ECG devices have attracted a lot of attention because it makes long-term ambulatory ECG monitoring possible, which helps to identify arrhythmias that are not detected by resting ECG or Holter ECG systems. However, due to the mobility of the human body and the various types of body movement in daily life, motion artifacts are a common and persistent problem for effective wearable ECG monitoring. The occurrence of motion artifacts can corrupt the ECG waveform causing inaccurate signal interpretation, so reducing their presence is necessary.In this paper, an adaptive motion artifact reduction method based on an improved RLS adaptive filter is proposed to solve the motion artifact problem in wearable ECGs. In this method, the IP signal was used as the reference input signal of the improved RLS adaptive filter. In order to ensure correlation between the reference input signal IP and the motion artifacts in the ECG signal, we have specially designed the ECG-IP synchronous acquisition system discussed, to record both the ECG and the IP signal through the same pair of electrodes. To further improve the signal correlation, we applied a 5 Hz low-pass filter on the IP signal to eliminate the cardiac-related signal in the IP signal while preserving motion artifacts. According to the signal correlation study, we found that the processed IP signal has a good correlation (|r| > 0.6) with the motion artifacts, which proves that the IP signal is suitable as the reference input signal of the adaptive filter for motion artifact reduction. 2) is larger than 0.7, which indicates that the estimated noise by the proposed method has a good fitness with the actual motion artifact. Finally, the results prove that the adaptive motion artifact method can suppress most of the motion artifacts and achieve minimal distortion to the denoised ECG signal. In addition, when processing pathological ECG signals, our proposed method should have better performance in preserving pathological characteristics of ECG waveform because it can suppress motion artifacts in the frequency range of 0 to 5 Hz while retaining all frequency components of the pathological ECG waveform. However, this could not be proved in experiments because ECG measurement on wearers who are suffering from heart problem may put wearers at risk, which is contrary to experimental ethics and in any case out of the scope of this research. Supported by the specially designed ECG-IP acquisition system, the performance of the proposed adaptive motion artifact reduction method was investigated by using real recorded noisy ECG signals. By analyzing the denoised ECG signals, it was found that most motion artifacts were removed and little distortion can be noticed from the denoised ECG waveform. By calculating the evaluation parameters, it was found that the mean squared error (m_MSE) is smaller than 0.15 and the R-square (m_RThis work provides a solution to the noise problem in wearable ECG measurements. Since the presence of motion artifact in the ECG signal may corrupt the ECG waveform resulting in an incorrect diagnosis of heart disease in medical, or performance in sports and well-being, the motion artifact reduction system proposed in this paper can effectively improve the quality of the ECG signal and reduce the possibility of misdiagnosis. In the recent COVID-19 outbreaks, there was a huge demand for wearable health systems that measure heart rate and respiration , and the


In recent years, the increasing incidence of morbidity of brain stroke has made fast and accurate segmentation of lesion areas from brain MRI images important. With the development of deep learning, segmentation methods based on the computer have become a solution to assist clinicians in early diagnosis and treatment planning. Nevertheless, the variety of lesion sizes in brain MRI images and the roughness of the boundary of the lesion pose challenges to the accuracy of the segmentation algorithm. Current mainstream medical segmentation models are not able to solve these challenges due to their insufficient use of image features and context information. This paper proposes a novel feature enhancement and context capture network (FECC-Net), which is mainly composed of an atrous spatial pyramid pooling (ASPP) module and an enhanced encoder. In particular, the ASPP model uses parallel convolution operations with different sampling rates to enrich multi-scale features and fully capture image context information in order to process lesions of different sizes. The enhanced encoder obtains deep semantic features and shallow boundary features in the feature extraction process to achieve image feature enhancement, which is helpful for restoration of the lesion boundaries. We divide the pathological image into three levels according to the number of pixels in the real mask area and evaluate FECC-Net on an open dataset called Anatomical Tracings of Lesions After Stroke (ATLAS). The experimental results show that our FECC-Net outperforms mainstream methods, such as DoubleU-Net and TransUNet. Especially in small target tasks, FECC-Net is 4.09% ahead of DoubleU-Net on the main indicator DSC. Therefore, FECC-Net is encouraging and can be relied upon for brain MRI image applications. Chronic stroke is an acute cerebrovascular disease with a high disability rate and high mortality rate. At present, chronic stroke is one of the most common diseases, and the number of deaths due to chronic stroke each year accounts for a large proportion ,2. ActivWith the rapid development of deep learning, convolutional neural networks (CNNs) have played an indispensable role in the field of medical segmentation. In particular, the encoder–decoder architecture represented by U-Net is widely used ,4,5,6. H(1)In view of the problem that the current medical image segmentation model parameters are large and cause the inference speed to be limited, we propose a new encoder–decoder structure. This work greatly reduces the model parameters and ensures that both shallow surface features and deep semantic features are fully extracted.(2)The current mainstream medical image segmentation encoder inevitably produces loss of the shallow edge features in the process of downsampling. Therefore, we propose an enhanced encoder composed of depthwise separable convolutions to enhance the boundary features and effectively restore the lesion boundary.(3)Medical images usually present imbalanced foreground information and background information, which causes the network training to fall into a local optimal state. This paper proposes hybrid loss to effectively solve the aforementioned problems and accelerate the model’s convergence speed.(4)The proposed model’s effectiveness was evaluated on an open-source dataset, ATLAS, based on MRI images, and the results show that our network is superior to state-of-the-art methods and can be used as a baseline for brain MRI image segmentation.Combining the two aforementioned reasons, this paper proposes a medical image segmentation model with small parameters and excellent performance that conforms to the application scenario. This paper has made the following contributions:Due to the powerful calculations of computers, image segmentation algorithms based on deep learning have become the most essential tool for automatically locating lesion information. In 2015, Long J et al.  proposedChronic stroke is a disease in which brain tissue is damaged due to the sudden rupture of blood vessels in the brain or the obstruction of blood vessels leading to the inability of blood to flow into the brain. A severe stroke will cause permanent nerve damage. If not diagnosed and treated in time, it will cause serious complications and even death. At present, large-scale neuroimaging studies are optimistic about the prospects of stroke recovery and point out the potential of deep learning. As we know, deep learning algorithms require large datasets to optimize performance. Therefore, a large number of medical datasets ,19 are oFrom the aforementioned works, we can observe that there have been substantial efforts to link segmentation algorithms with medical imaging. In recent years, these works have been widely applied to the processing of brain MRI images. In 2021, Kadry et al.  solved tThe proposed FECC-Net architecture is illustrated in There have been many experiments indicating that deeper neural networks bring adequate performance for medical image segmentation, but a network with too many layers may encounter problems, such as huge parameters and gradient explosions, which are not suitable for practical applications. We propose a new encoder–decoder architecture that solves the aforementioned problems and obtains better results.This paper designs an ultra-light encoder in which each encoder block only needs to perform two 3 × 3 convolution operations, each followed by a batch normalization. The batch normalization reduces the internal co-variant shift and also regularizes the model. A rectified linear unit (ReLU) ,25,26,27U-Net is the benchmark for medical image segmentation, but its ability to obtain image context information is limited. In this paper, the output of the high-resolution features by the encoder is input into atrus spatial pyramid pooling (ASPP). ASPP can integrate semantic information of different scales and fully capture context information. Finally, the depth features fused with multi-scale information are upsampled to restore the spatial features. The experimental results show that the network’s main structure proposed in this paper greatly reduces the amount of calculation and significantly improves the performance.The encoder–decoder architecture combines the intermediate features of the encoder with the decoded output via skip connections, allowing the network to obtain high-level semantics and low-level fine-grained surface features. We inherited this contextual information fusion strategy. However, simple feature connections cannot fully recover the loss of object boundary information during downsampling. Therefore we propose a novel encoder for boundary feature enhancement. In MRI images of the brain, the lesion area of stroke disease is usually small. In the training process, much background information may dominate the direction of model training and eventually fall into a local optimal state. Therefore, a suitable loss function is particularly important. For the ATLAS dataset, we propose a hybrid loss function to balance the influence of the foreground factor and the background factor on the training trend.y represents the distribution of real marks, and N represents the number of images in the training set during the training process and represents the number of images in the validation set during the validation set process, and i represents the number of images in the corresponding dataset.The binary cross entropy (BCE) loss is often used as a binary classification problem, which can measure the similarity between the real result and the predicted result. In particular, the use of the sigmoid function in the gradient descent can avoid the problem of a reduction in the learning rate of the mean square error loss function, so that the learning rate can be adjusted reasonably according to the output. In the brain MRI images, BCE loss makes the model fit correctly and prevents the model from entering the local optimal state in the initial training stage. As shown in Equation , y reprey represents the ground truth, and N represents the number of images in the training set or validation set. In the brain MRI images, the number of healthy samples is greater than that of stroke samples. The unevenness of positive and negative samples causes the model to be more sensitive to irrelevant information while ignoring the extraction of main features. Therefore, we introduced dice loss to optimize the sample imbalance. As shown in Equation , y repreWe propose the hybrid loss (HL) function based on the two loss functions above and use their L2 paradigm as a new loss function to optimize the gradient change of each iteration and speed up the convergence time of training. The formula for the hybrid loss function is shown in Equation .(3)HL dataset  is a chaIn our experiments, we used the Keras framework  with TenIn this section, we will show the segmentation process of FECC-Net and compare our proposed model with the mainstream medical segmentation model. We also evaluated three different tasks for the ATLAS dataset and show the qualitative results to prove the superiority of FECC-Net. To verify the influence of different components of FECC-Net on segmentation performance, we conducted ablation experiments on enhanced-encoder and loss function. Considering the real-life application of the model, this paper conducts noise addition experiments on images, discusses the robustness of our proposed method to noise.Our quantitative results on the ATLAS dataset are summarized in In As shown in The second case was conducted on the medium target from ATLAS. From The third experiment was conducted on the large target task. As indicated in The motivation of the enhanced encoder is to compensate for the loss of apparent information caused by the downsampling process of the image and to achieve the enhancement of boundary features. To verify the effect of different baseline feature enhancements, we evaluated VGG19 , ResNet We compared our proposed hybrid loss with several common loss functions in segmentation tasks and quantified these four kinds of losses in The noise in real-world biomedical images is a well-known problem that reduces the accuracy of diagnostics. In order to verify the robustness of our proposed model to noise, we processed images of large, medium, and small tasks with Gaussian noise, and we set the In this section, based on the experimental results above, we discuss the effectiveness and researchability of segmentation in brain MRI images through deep learning models:Effectiveness of deep learning models for segmentation of brain MRI images. In the Introduction section of this paper, we listed and analyzed the current brain MRI segmentation methods, which are mainly divided into threshold methods based on image processing and methods based on deep learning. It is well known that threshold methods cannot effectively segment the results under conditions of large amounts of noise. Therefore, more and more scholars have recently adopted U-Net for segmentation in brain MRI images and proved the effectiveness of deep learning models in brain MRI images. However, the current deep learning model relies too much on the ontology structure of U-Net, and there are problems, such as insufficient context information extraction and large model parameters. Our research proposes a light encoder–decoder framework and feature enhancement module, which reduces the parameters while improving the model’s accuracy, proving that the medical image segmentation model can achieve the requirements of high precision and small parameters. Such a baseline is more realistic for application to life.Researchability of deep learning models in brain MRI segmentation. In the Experimental section, we conducted a comparison experiment on the test samples before and after adding noise. It can be observed that the noise still interferes with the deep learning model, especially for targets that are difficult to focus on with the naked eye. Therefore, some works combine semantic segmentation and image denoising to achieve high-precision semantic information classification . We planThis paper proposes a novel feature enhancement and context capture network (FECC-Net) based on brain MRI images. We achieved low-density cerebral infarct lesion localization on the ATLAS dataset and compared FECC-Net with current medical image segmentation models. FECC-Net reached the leading position for all indicators and, most especially, is 8.97% higher than DoubleU-Net (the second-ranked method) in DSC and 9.78% higher in mIoU. FECC-Net is currently the medical image segmentation model with the smallest total network parameters, only 7.0M, which is half of U-Net. It is worth mentioning that our proposed FECC-Net-lite achieves as high as 0.6353 on DSC, which leads DoubleU-Net by 4.61%. The experimental results of FECC-Net-lite show that: (1) The lightweight encoder–decoder architecture can be used as a baseline for medical image segmentation, and (2) feature enhancement plays an indispensable role in the performance optimization of medical image segmentation. We believe that these encouraging results from FECC-Net will become the baseline for brain MRI image segmentation.


Regarding the nose tip, the sample entropy showed significant differences  = 11.5; p = 0.041). The findings from this study suggests that this approach can be used to evaluate in a contactless manner the psychophysiological condition of the children with CP during RAGT, allowing to monitor their engagement to the therapy, increasing the benefits of the treatment.Cerebral palsy (CP) is a non-progressive neurologic pathology representing a leading cause of spasticity and concerning gait impairments in children. Robotic-assisted gait training (RAGT) is widely employed to treat this pathology to improve children’s gait pattern. Importantly, the effectiveness of the therapy is strictly related to the engagement of the patient in the rehabilitation process, which depends on his/her psychophysiological state. The aim of the study is to evaluate the psychophysiological condition of children with CP during RAGT through infrared thermography (IRT), which was acquired during three sessions in one month. A repeated measure ANOVA was performed  extracted from the temperature time course collected over the nose and corrugator, which are known to be indicative of the psychophysiological state of the individual. Concerning the corrugator, significant differences were found for the sample entropy  = 6.888;  Cerebral palsy (CP) is a non-progressive neurologic condition due to a brain injury that occurs before the complete cerebral development , represeAmong the several clinical scales employed to evaluate the severity of motor disorders of CP, the Gross Motor Function Classification System (GMFCS) is one of the most commonly employed in clinical practice . This scTo enhance the quality of life and social integration of CP patients, several pharmaceutical strategies  and rehaIn fact, it was proved that the spinal cord’s central pattern generators (CPG), or gait centers, could be activated by passive motions of the limbs . MoreoveEnd-effectors and exoskeletons are the two types of RAGT devices that are readily accessible on the market. End-effectors essentially consist of a double crank and rocker gear system to exert forces on the distal segments of limbs, and a servo-controlled motor guides the patient during walking. Exoskeleton-type devices direct the patient’s legs according to a preprogrammed gait pattern using a robotic orthosis coupled with a harness-supported body weight system coupled with a treadmill.®  is one of the commercially available exoskeletons that supports the patient on a treadmill while a robotic device helps with inter-limb coordination and gait timing [The Lokomatt timing . The syst timing . In factt timing .In comparison to the traditional body weight support treadmill training methods, RAGT can result in a higher level of spine and brain neuroplasticity . The cenHowever, it should be highlighted that the effectiveness of the therapy is strictly related also to the engagement of the patient in the treatment. It has been suggested that the concept of “rehabilitation engagement” encompasses a number of factors, including the patient’s attitude toward therapy, their level of understanding or acknowledgment of a need for treatment, their requirement for verbal or physical prompts to participate, their level of active participation in therapy activities, and their level of attendance throughout the rehabilitation program . GreaterANS activity could be inferred through the evaluation of the heart rate variability (HRV) and through electrodermal activity (EDA). Heart rate variability (HRV) is the fluctuation in the time between successive heartbeats that is primarily influenced by the control of heart rate (HR). The status of the ANS and overall cardiac health can be evaluated through HRV analysis ,17,18. PEDA measures skin conductance, which changes depending on the activity of the skin’s sweat glands. Skin conductance is a sign of psychological or physiological arousal since sweating is regulated by the sympathetic nervous system . SweatinHowever, positioning sensors on palmar surfaces is not recommended when recordings are likely to contain motion and pressure anomalies. Notably, when a human subject exhibits uncontrollable movements, such as in hyperkinetic CP, these artifacts are common .To overcome this issue, the employment of contactless sensors able to infer human psychophysiological condition, such as infrared thermography (IRT), could be preferable since they do not need a preparation of the patients and they are completely non-invasive and comfortable also for long-term monitoring. IRT is able to measure the superficial temperature of a body at a distance. In the biomedical field, this technique is employed to measure the modulation of skin temperature, which is an indicator of a subject’s psychophysiological condition . In factHence, IRT has already been used to investigate the workload , the leaThe aim of this study is to assess the psychophysiological condition of children affected by CP during RAGT through IRT. To the best of the authors’ knowledge, this study is the first attempt to investigate the psychophysiological condition of CP patients during the RAGT, in order to provide information regarding the engagement of the children in the therapy.The participants were enrolled in accordance with the GMFCS, which offers a way to categorize patients with cerebral palsy into one of five levels secondary to their functional abilities. Children in level V have trouble managing their head and trunk posture in most postures and in attaining any voluntary control of movement, while children in level I can complete all the activities of their age-matched peers, but with some difficulty with speed, balance, and coordination .Children with CP between the ages of 3 and 18 years-old who had a GMFCS level of I to V, the capacity to express discomfort or suffering, and the comprehension of straightforward instructions were included in the study.Medical issues that would interfere with the locomotor training or physical restrictions on utilizing the robotic device were among the exclusion criteria. Moreover, children showing severe lower-extremity muscle contractures, hip instability or subluxation, recent Botulinum toxin-A (BTX-A) injections to the lower limbs, an uncontrolled seizure disorder, open skin lesions, and a vascular disorder of the lower limbs were excluded from the study.Ten children with CP were enrolled in this study between November 2021 and April 2022 at the Neurorehabilitation Unit “Gli Angeli di Padre Pio” of the Padre Pio Foundation and Rehabilitation Centers, San Giovanni Rotondo, Foggia, Italy. After two of them tested positive for SARS-CoV-2 during the training, they withdrew, leaving the final sample to be made up of eight children (age: 9.88 ± 4.73 years) affected by spastic CP subtype . In agreement with the GMFCS classification, one participant was classified as level I, one in level III, five in level IV, and one in level V.The participants underwent a total of 12 RAGT sessions in one month (three times per week) lasting 30 min. The Lokomat’s biofeedback was used to administer RAGT. Notably, the individuals received conventional therapy in addition to the RAGT. To assess the participants’ changes in their motor skills, the Gross Motor Function Measure-88 (GMFM-88) was administered before (T0) and after the training (T2). This test measures 88 movements across five dimensions: lying down and rolling over; sitting; crawling and kneeling; standing; and walking, running, and jumping .The Shapiro–Wilk normality test was used to determine whether the distribution of the clinical data scores was normal. The Wilcoxon signed-rank test was used to compare the results from the two sessions  in order to assess the change in muscle tone and degree of spasticity in response to RAGT because the data did not conform to the assumption of normality.The RAGT experimental procedure was given to the subjects once they were tethered to the Lokomat a. The chThe FLIR SC660   digital thermal infrared camera was used to measure the facial temperature during the first (T0), the sixth (T1), and the twelfth (T2) sessions. The subject was positioned with the camera 60 cm away and pointed directly at his/her face. The frequency rate was set to 10 Hz. The camera was blackbody calibrated to reduce any potential sensor response drift/shift as well as optical artifacts.The children arrived in the experimental room 15 min before the start of the session, to allow their baseline skin temperature to stabilize. The temperature and humidity of the room were kept stable at 23 °C and 50–60%, respectively, and controlled through a thermostat. The recommendations for thermal measurements made by Ring and Ammer (2012) , Diakiden (n = 2 in this case) standard deviations from the median. The ROIs placement on the face of a representative participant is reported in Regarding the IRT signals data analysis, visual inspection was used to assess the captured thermal signals’ quality first; no video was disallowed. Two regions of interest (ROI) were chosen on the nose tip and forehead (corrugator) of each subject . These rSubsequently, the following features were computed from the thermal signals for each ROI:MeanTemp)—average value of the thermal signal T over time  defined as:Mean value (STD)—standard deviation of the thermal signal T overtime  defined as:Standard deviation (SampEn): defined as the negative natural logarithm of the conditional probability that signals that the subseries of length m (pattern length) that match pointwise within a tolerance r (similarity factor) also match at the m + 1 point. SampEn of a time series {t1,……,Nt} of length N is computed employing the following set of equations:Sample Entropy  were conducted to determine which temporal recordings offered statistical differences. The statistics were then corrected for multiple comparisons  to eliminate false positives.The one-way repeated measure ANOVA (RM-ANOVA) has been employed in order to evaluate statistical differences between the thermal features at T0, T1, and T2, considering the temporal session as within factor. Then, multiple comparisons (paired p = 0.008). The modification of the GMFM-88 for each participant is reported in Concerning the clinical scales evaluation, the GMFM-88 showed a significant change between T0 and T2  and the mean value  = 5.88; p = 0.047) specifically with reference to the corrugator. The SampEn revealed significant differences with regard to the tip of the nose  = 11.5; p = 0.041). A boxplot showing the modifications of the thermal features across the sections is reported in A statistical analysis revealed that the patients’ emotional state changed during the course of the many sessions. A significant difference was reported for the SampEn  = 6.888; Multiple comparisons, FDR corrected, revealed a significant difference for the SampEn computed over the nose tip across all sessions, but only between T0 and T2 for the metrics evaluated on the corrugator temperature time course. The multiple comparisons results are summarized in The aim of this study was to assess the psychophysiological correlates associated with RAGT in children with CP using IRT. The rationale of the study relies on previous findings demonstrating that children should actively participate in the therapeutic process to maximize the benefits of rehabilitation ,45. In fHowever, it should be highlighted that these mentioned studies evaluate the engagement of the children to therapy through interviews to the children and to their parents, but they do not provide a physiological correlate of the psychophysiological condition of the child during the treatment. In fact, techniques such as IRT can provide information on the affective states of children which are related to the participation to therapy.To the best of the authors’ knowledge, this is the first study investigating the autonomic implications of RAGT in CP patients. To this aim, IRT has been demonstrated to be highly accepted by the children during testing thanks to its contactless and non-invasive features.The findings demonstrated a modulation of the thermal response across the sessions. Particularly, a decrease of the SampEn evaluated on the temperature time course of both the corrugator and the tip of the nose was found, whereas a significant decrease of the MeanTemp of the corrugator was assessed.The temperature decrease assessed on the forehead could be associated with the activation of the sympathetic system, whose activation is associated also with attention and concentration . This inConcerning this complexity analysis, SampEn’s embedding dimension (m) and time delay (τ) need to often be optimized based on the dynamic nature of the target signal. However, there is a practical limitation based on the sampling frequency and overall recording time . Richman and Moorman specifically proposed and tested the SampEn metric, which limits the m value based on the total number of samples of the target signal to be contained in the range of 10–20 m . FurtherThese findings suggest an improvement of the engagement of the children during the different RAGT sessions. Notably, the multiple comparisons analysis assessed significant differences, FDR corrected, mostly between T0 and T2. Hence, the results suggest that modulations of the psychophysiological state occur in children after several sessions. However, further studies should investigate different RAGT protocols  to assess which induces the best benefits to the children’s engagement.Furthermore, it should be highlighted that the sympathetic activity is also related to negative affective states, such as stress and perception of danger. Hence, further studies should be performed to investigate the affective state of the CP children, developing models of affective computing suitable for this kind of pathology. An interesting approach could rely on multimodal monitoring of the autonomic activity of the children during RAGT , paying attention to preserving the ergonomic state of the patients during the therapy.However, the significant increase in the GMFM-88 scores after the whole sessions could suggest that the increased sympathetic activity assessed in this study could be related to an increase of the engagement of the children to the therapy. This result is consistent with other research showing the RAGT’s advantages for diplegic children with CP. For instance, Wallard et al. found that RAGT therapy administered through Hocoma Lokomat significantly improved the kinematic data of the full body in the sagittal and frontal planes as well as the gross motor function measure test, demonstrating the value of RAGT in enhancing balance control in gait . Van KamNotably, all the participants exhibited an improvement of the GMFM-88 scores, and, specifically, the highest modifications were associated with the lower GMFCS levels. This finding could suggest that RAGT is more effective in patients with severely compromised motor abilities. Importantly, the GMFM-88 was preferred with respect to other clinical scales because it investigates several motor abilities, not only related to the standing or gait activity. In fact, the five dimensions evaluated by the GMFM-88 are: lying and rolling (GMFM-A); sitting (GMFM-B); crawling and kneeling (GMFM-C); standing (GMFM-D); and walking, running, and jumping (GMFM-E). Since most of the children considered in this study were not able to walk autonomously (seven out of eight participants), the GMFM-88 was adopted to evaluate the rehabilitation outcome improvements. However, further studies should be performed employing other clinical scales to assess the rehabilitation outcomes. For instance, the modified Ashworth scale (MAS) created by Bryan Ashworth as a tool for evaluating spasticity is suitable for this typology of patients. The original Ashworth scale was a five-point numerical scale, with 0 denoting no resistance and 4 denoting a rigid limb in flexion or extension, and it was used to grade spasticity. However, in order to boost sensitivity, Bohannon and Smith added 1+ to the Ashworth scale. Since there is no increase in muscle tone, MAS ranges from 0 (no rigidity in flexion or extension) to 4 . These fIt should be emphasized that the protocol did not apply to uncooperative participants or to children who could not understand the augmentative feedback displayed on Lokomat’s screen. Future research should focus on determining whether intense RAGT can aid children with severe cognitive deficits who are typically excluded from robotic rehabilitation procedures because of their uncooperativeness.Finally, it should be stressed that this approach could be relevant to patients that are not able to speak and provide feedback during the procedure . In fact, CP is often accompanied by several impairments such as behavior disorders and inability to talk. This study could pave the way for further experimentations aiming to monitor and predict the effectiveness of the rehabilitation also in other pathologies with the goal to administrate the more suitable and acceptable therapy for each patient.This research reports about the capability of employing IRT during RAGT in order to evaluate the psychophysiological state of CP children during the therapy. The findings demonstrated that CP patients enhance their attention, concentration, and motor control during the therapy across the different RAGT sessions. This method can be utilized to customize clinical treatments, enhancing the success of CP children’s rehabilitation and, as a result, their quality of life. This work may open the way for additional research targeted at tracking and forecasting the efficacy of rehabilitation also in other disorders with the goal of providing each patient with the most appropriate therapy.