Hasil untuk "Mental healing"

Sanhita Das, Nivedita Kumari

Autonomic interfacial self-healing in elastomers enables their reprocessing and recycling, making them valuable for applications such as ballistic resistance, surface coatings, adhesives, and biomedical materials. This article prescribes a geometry-based damage-healing theory for autonomic healing in elastomers, built on a framework where damage induces an incompatibility in the Euclidean material manifold, transforming it into a Riemannian manifold. Healing restores the Euclidean state through a reversing damage variable or an evolving healing variable. The reversing damage variable models the rebonding mechanism while the healing variable accounts for healing by chain diffusion and entanglement. The model also predicts healing where rebonding is preceded by chain diffusion. The microforce balance governs the evolution of the damage and healing variables, capturing rate-dependent damage and intrinsic temperature-independent healing. The model is validated through numerical simulations, including one-dimensional and two-dimensional simulations, demonstrating accurate predictions of coupling between damage and healing and post-healing mechanical response. The model also predicts the recovery of fracture toughness with healing time in supramolecular elastomers, aligning with experimental data. With minimal parameters, the model is versatile and can easily be used for material design and structural analysis, surpassing existing models in simplicity and predictive capability.

Rafael Almada, Nuno Araújo, Pedro Patrício

Embryonic healing in epithelial tissues is distinct from adult wound healing, as it lacks inflammatory responses or immune cell recruitments, making it ideal to test models of wound healing driven primarily by epithelial dynamics. Many models have been developed to describe this process, ranging from simple mechanistic models to more elaborate multiscale simulations. We review different classes of physical models, from discrete to continuum models, and how they address key questions about the mechanics, signaling, and coordination of cells during wound closure. We highlight tensions between model complexity and interpretability and discuss recent efforts to bridge gaps across scales. Finally, we identify directions for hybrid modeling and model-experiment integration that could push forward our understanding of epithelial repair in development and disease.

Hiroshi Tateishi, Hiroko Kunitake, Masahiro Ohgidani et al.

Background The neuroinflammatory hypothesis has been proposed as the pathophysiology of depression, and microglia are suggested to have crucial roles by modulating neuroinflammatory responses in patients with depression. We have originally developed human blood induced microglia-like (iMG) cells, which are surrogate cells to predict activities of human brain microglia for reverse-translational research. Repetitive transcranial magnetic stimulation (rTMS) is an effective therapeutic method for improving depressive symptoms in patients with treatment-resistant depression (TRD); however, its details remain unknown. The aim of this study was to predict how rTMS alters the phenotype of microglia using iMG cells of patients with TRD.Methods Five patients with TRD were enrolled in a frequency (10 Hz) rTMS study. Microarray analysis of the iMG cells of patients with TRD at baseline and the end of the 6-week rTMS treatment was performed in the five domains of immunity, inflammation, phagocytosis, metabolic syndrome, and lipids.Results Three of the five were rTMS responders and two were non-responders for depressive symptoms. Microarray analysis of responders showed that rTMS treatment significantly increased the RNA expression of 21 genes, including genes related to neuroinflammation, acting in a direction to promote neuroinflammation, and significantly decreased four genes.Limitations The main limitations were the small sample size and the lack of control conditions using the sham rTMS procedure.Conclusion This study suggests that rTMS treatment may alter iMG genes, including immune-related genes, in patients with TRD. Future studies should confirm these findings using a larger patient sample size and a sham rTMS procedure.

K. Hylkilä, N. Männikkö, A. Peltonen et al.

Background: This systematic review aimed to synthesize current evidence of an association between problematic social networking site use (PSNSU) and social well-being and predictors of PSNSU among young adults (18–35 years). Methods: The systematic review considered cross-sectional and cohort studies that assessed the association between PSNSU and social well-being among young adults. The JBI systematic review methodology of etiology and risk was followed. Data were collected from eight electronic databases and manually from reference lists of selected studies. Two independent reviewers selected studies by screening titles, abstracts and full texts and assessed the quality of the included studies. Data were extracted and synthesized with narrative methods. Results: Twenty one (n = 21) studies were included in the final review. The results showed that there were associations between PSNSU and different social well-being factors, e.g., associations were found between PSNSU and social and parasocial relationships on social networking sites and social media anxiety. Also some predictive factors were found. Limitations: Although, the search strategies were developed in conjunction with an information specialist, some keywords might have been missed, which could have affected the search results. Social well-being and PSNS use can be defined in many ways, which may have affected which studies were excluded. Language limitations might affect to the study inclusion. Conclusions: In most cases, PSNSU was associated with lower social well-being, although some mixed results were obtained. Definitions of PSNSU and social well-being varied widely. Therefore, in the future, it would be beneficial to have clear concepts for PSNSU and social well-being. It is also important to consider social aspects in PSNSU.

T. S. Sathyanarayana Rao, Chittaranjan Andrade

Jodie C. Stevenson, Umair Akram

The present study examined the concurrent and longitudinal relationships between multidimensional perfectionism, perceived stress, and self-critical thinking in a sample of UK university students. Specifically, to determine whether self-critical thinking at baseline mediated the longitudinal relationship between baseline perfectionism and future stress at follow-up. At baseline, N=220 students completed measures of multidimensional perfectionism, perceived stress, and self-critical thinking, whereas N=84 completed the same measures at follow-up. Socially prescribed, and self-oriented perfectionism were related to increased stress, self-hatred, and self-inadequacy at baseline. Longitudinal analysis revealed that baseline self-oriented and socially prescribed perfectionism were significantly related to increased reports of stress and self-critical thinking fifteen weeks later at follow-up. More crucially, multiple mediation analysis found self-hatred and inadequacy at baseline mediated the longitudinal relationship between baseline perfectionism and perceived stress at follow-up. Perfectionistic and self-critical thinking appears to accentuate the experience of perceived stress in the university student population. Student-based interventions to reduce self-critical thinking may prove beneficial in preventing the onset of perceived stress.

Subhadeep Roy, Takahiro Hatano

To understand the general properties of creep failure with healing effects, we study a mean-field fiber bundle model with probabilistic rupture and rejoining processes. The dynamics of the model are determined by two factors: bond breaking and the formation of new bonds. Steady states are realized due to the balance between breaking and healing beyond a critical healing factor, below which the bundle breaks completely. Correlation between the fluctuating value of strain generated in the model with time at the steady-state leads to a characteristic time that diverges in a scale-free manner as we approach the critical healing factor. Transient behaviors in strain rate also involve a power law with a non-universal exponent.

Hy Dang

The process of wound healing has been an active area of research around the world. The problem is the wounds of different patients heal differently. For example, patients with a background of diabetes may have difficulties in healing [1]. By clearly understanding this process, we can determine the type and quantity of medicine to give to patients with varying types of wounds. In this research, we use a variation of the Alternating Direction Implicit method to solve a partial differential equation that models part of the wound healing process. Wound images are used as the dataset that we analyze. To segment the image's wound, we implement deep learning-based models. We show that the combination of a variant of the Alternating Direction Implicit method and Deep Learning provides a reasonably accurate model for the process of wound healing. To the best of our knowledge, this is the first attempt to combine both numerical PDE and deep learning techniques in an automated system to capture the long-term behavior of wound healing.

Di Zuo, Yiqian He, Stéphane Avril et al.

When they are damaged or injured, soft biological tissues are able to self-repair and heal. Mechanics is critical during the healing process, as the damaged extracellular matrix (ECM) tends to be replaced with a new undamaged ECM supporting homeostatic stresses. Computational modeling has been commonly used to simulate the healing process. However, there is a pressing need to have a unified thermodynamics theory for healing. From the viewpoint of continuum damage mechanics, some key parameters related to healing processes, for instance, the volume fraction of newly grown soft tissue and the growth deformation, can be regarded as internal variables and have related evolution equations. This paper is aiming to establish this unified framework inspired by thermodynamics for continuum damage models for the healing of soft biological tissues. The significant advantage of the proposed model is that no \textit{ad hoc} equations are required for describing the healing process. Therefore, this new model is more concise and offers a universal approach to simulate the healing process. Three numerical examples are provided to demonstrate the effectiveness of the proposed model, which is in good agreement with the existing works, including an application for balloon angioplasty in an arteriosclerotic artery with a fiber cap.

Lina Begdache, Mei-Hsiu Chen, Casey E. McKenna et al.

Background: Diet quality, exercise and sleep are dynamic modifiable factors that impact mental health. However, taking into consideration gender and age-groups as risk factors may be necessary to customize therapies. The purpose of the study was to assess the dynamic interactions between diet quality, and lifestyle factors in relation to mental distress in these sub-groups. Method: A total of 52 adult participants provided 4 week-daily records using the Food-Mood questionnaire. Data were collected for 2 years during the summer and fall seasons. Spearman's correlation as well as multivariate and multilevel regression analyses were used to identify correlations and model the relationships, respectively, between the variables of interest. Results: There was a mild negative correlation between AHEI and K-6 scores;rs= -0.08 (95% confidence interval = [-0.14, -0.02]). Men and participants aged 30 years or older had lower K-6 scores than women (0.8 vs 1.8, p < 0.001), and younger adults (0.6 vs 1.9, p < 0.001), respectively. Lower K-6 scores associated with 20 min or more exercise compared to days without exercise or exercised less than 20 min (1.2 versus 1.9, p < 0.001). Seasonal changes were associated with alterations in diet quality and mental wellbeing (P < 0.001). Limitations: A convenience sample was used. Conclusion: Our results suggest that adjusting one modifiable factor may lead to improvement in others. In addition, these factors are age and gender dependent. Therefore, customization of dietary and lifestyle factors based on gender and age-groups is recommended to optimize mental wellbeing.

Nicola Cherry, Jean-Michel Galarneau, Andrea Melnyk et al.

Background: We aimed to determine the relationship between childhood abuse and mental ill-health in firefighters deployed to a devastating fire that engulfed Fort McMurray Methods: A stratified sample of 282 firefighters was selected from a cohort of 1234 for assessment by Structured Clinical Interview (SCID) for DSM-5 diagnostic criteria and the Childhood Experience of Care and Abuse questionnaire (CECA-Q). Diagnoses were grouped as post-traumatic stress disorder (PTSD), anxiety disorders, depressive disorders and substance use disorders. Scales extracted from the CECA-Q included parental loss, antipathy, neglect, physical punishment, sexual abuse and support from a same-age confidant. The relation to diagnostic group was examined by multivariable logistic regression Results: 192 SCID interviews and 188 CECA-Qs were completed: 124 met DSM-5 criteria for diagnoses including anxiety disorder (56), depressive disorder (54), PTSD (77) and substance use disorder (43). Childhood sexual abuse was reported by 24 firefighters all of whom met DSM-5 diagnostic criteria. Sexual abuse and a childhood confidant differentiated diagnoses in an initial multivariable model of those with psychiatric disorders. Compared to those without a psychiatric diagnosis, father's antipathy was related to anxiety and substance use, physical punishment to PTSD and substance use. A childhood same-age confidant protected against anxiety, depression and PTSD. Fire exposures related only to PTSD. Limitations: The comparison group without mental disorders was small. Childhood abuse information was collected retrospectively and may be biased by current state. Conclusions: Firefighters’ mental health is a function of both work-role traumas and childhood events. Occupational health provision must address this complexity.

Systla Rukmini, Paulomi M. Sudhir, Adhin Bhaskar et al.

Background: Process research aims to identify mediators of therapy which can help increase the efficacy and optimization of therapy. The present study examined the role of estimated social cost, perceived social self-efficacy and perceived emotional control as potential mediators in Cognitive Behaviour Therapy (CBT) and Exposure Therapy (EXP) in individuals with social anxiety disorder. Methods: Fifty adults with a primary diagnosis of social anxiety disorder (SAD) were recruited from a tertiary treatment center and randomly assigned to receive either CBT (N=25) or EXP (N=25).Levels of social anxiety, estimated social cost, perceived social self-efficacy, and perceived emotional control were assessed at the beginning of each session. Multilevel modeling was used to estimate the effects of the above variables on social anxiety and examine differences between the two groups. Results: Changes in perceived social self-efficacy and estimated social cost predicted changes in social anxiety. Perceived emotional control was not a significant predictor of changes in social anxiety. There were no significant differences between the two groups. Limitations: The study has a small sample size, and there is a lack of adequate follow-up data. A single therapist delivered both interventions, which could limit external validity. Conclusions: Perceived social self-efficacy and estimated social cost emerged as mediators of both CBT and EXP. The two interventions had common meditational pathways, and there was an interactive bi-directional relationship between social anxiety and the studied mediators.

Emil Karshalev, Cristian Silva-Lopez, Kyle Chan et al.

Herein, self-healing small-scale swimmers capable of autonomous propulsion and on-the-fly structural recovery are described. The new strategy instantaneously restores the functionality of the swimmer after it has suffered severe damage. Incorporation of magnetic microparticles in strips along with the printed functional body layers (consisting of conductive carbon, low-density hydrophobic polymer and catalytically active metal) results in rapid reorientation and reattachment of the moving damaged catalytic tail to its complimentary broken static body piece. Such magnetic alignment and attraction restores the original swimmer structure and propulsion behavior, independent of user input, displaying healing efficiencies as high as 88 percent. Modeling of the magnetic fields and simulations of various swimmer configurations are used to study the magnetic force field distribution around the swimmers. The influence of the damage position and pattern of multiple magnetic healing strips is examined and their influence upon healing efficiency is compared. Owing to its versatility, fast recovery, simplicity, and efficiency, the new on-the-fly self-healing strategy represents an important step towards the development of new classes of robots that can regain their functionality in situations of extreme mechanical damage where repair is not possible or challenging.

Flavia Regina Souza Ramos, Priscila Orlandi Barth, Laura Cavalcanti de Farias Brehmer et al.

Abstract Objective: To evaluate the frequency and intensity of moral distress in Brazilian nurses. Method: Cross-sectional study performed with nurses from 27 Brazilian states through application of the Brazilian Moral Distress Scale in Nurses (Portuguese acronym: EDME-Br) and descriptive statistical analysis. Results: Participation of 1,226 Brazilian nurses in the study. The intensity and frequency of overall moral distress were rated as moderate level, with averages of 3.08 (± 1.45) and 2.94 (± 1.37), respectively. Specifically, the highest intensity and frequency was related to the factors Acknowledgement, power and professional identity and Work teams, while the lowest was related to the factor Defense of values and rights. Conclusion: Moral distress occurs in precarious work environments, with little expressiveness of the nurses’ role. One highlights the importance of the problem in terms of its amplitude and multicausality, reaching professionals acting in different work contexts.

Yiqian He, Di Zuo, Klaus Hackl et al.

Healing of soft biological tissue is the process of self-recovering or self-repairing the injured or damaged extracellular matrix (ECM). Healing is assumed to be stress-driven, with the objective of returning to a homeostatic stress metrics in the tissue after replacing the damaged ECM with new undamaged one. However, based on the existence of intrinsic length-scales in soft tissues, it is thought that computational models of healing should be non-local. In the present study, we introduce for the first time two gradient-enhanced con-stitutive healing models for soft tissues including non-local variables. The first model combines a continuum damage model with a temporally homogenized growth model, where the growth direction is determined according to local principal stress directions. The second one is based on a gradient-enhanced healing model with continuously recoverable damage variable. Both models are implemented in the finite-element package Abaqus by means of a user sub-routine UEL. Three two-dimensional situations simulating the healing process of soft tissues are modeled numerically with both models, and their application for simulation of balloon angioplasty is provided by illustrating the change of damage field and geometry in the media layer throughout the healing process.

Mohammadjavad Kazemi, Ahmad Goli, Abbas Mohammadi et al.

Considering much distresses occurring at the surface of the asphalt roads, self-healing phenomenon attracted much attention because of reducing the road surface distresses and its benefits. The use of polymers, which are mainly used to improve the properties of asphalt mixtures, is one of the ways to increase self-healing properties. In this study, four polymer-modified bitumen mixtures were made applying the most common polyurethanes (by combining three different types of polymers and a nanographene particle). Then the mixtures were exposed to long-term aging under PAV to be evaluated in situations where less healing occurs. Finally, by performing a time sweep test and measuring the shear complex modulus (G *) before and after the rest period, the healing rate of these mixtures was measured and compared. By examining the results, it was found that the TDI-CO polymer-modified mixture is the best mixture for bitumen healing.