Hasil untuk "Therapeutics. Psychotherapy"

Niklas Jacobs, Manuel C. Voelkle, Norbert Kathmann et al.

In the context of personalized medicine, machine learning algorithms are growing in popularity. These algorithms require substantial information, which can be acquired effectively through the usage of previously gathered data. Open data and the utilization of synthetization techniques have been proposed to address this. In this paper, we propose and evaluate alternative approach that uses additional simulated data based on summary statistics published in the literature. The simulated data are used to pretrain random forests, which are afterwards fine-tuned on a real dataset. We compare the predictive performance of the new approach to random forests trained only on the real data. A Monte Carlo Cross Validation (MCCV) framework with 100 iterations was employed to investigate significance and stability of the results. Since a first study yielded inconclusive results, a second study with improved methodology (i.e., systematic information extraction and different prediction outcome) was conducted. In Study 1, some pretrained random forests descriptively outperformed the standard random forest. However, this improvement was not significant (t(99) = 0.89, p = 0.19). Contrary to expectations, in Study 2 the random forest trained only with the real data outperformed the pretrained random forests. We conclude with a discussion of challenges, such as the scarcity of informative publications, and recommendations for future research.

Shijie Yuan, Jiaxin Liu, Zhihua Gong et al.

We consider basket trials in which a biomarker-targeting drug may be efficacious for patients across different disease indications. Patients are enrolled if their cells exhibit some levels of biomarker expression. The threshold level is allowed to vary by indication. The proposed SIMBA method uses a decision framework to identify optimal biomarker subgroups (OBS) defined by an optimal biomarker threshold for each indication. The optimality is achieved through minimizing a posterior expected loss that balances estimation accuracy and investigator preference for broadly effective therapeutics. A Bayesian hierarchical model is proposed to adaptively borrow information across indications and enhance the accuracy in the estimation of the OBS. The operating characteristics of SIMBA are assessed via simulations and compared against a simplified version and an existing alternative method, both of which do not borrow information. SIMBA is expected to improve the identification of patient sub-populations that may benefit from a biomarker-driven therapeutics.

Bryce-Allen Bagley, Navin Khoshnan

The complexity of human cognition has meant that psychology makes more use of theory and conceptual models than perhaps any other biomedical field. To enable precise quantitative study of the full breadth of phenomena in psychological and psychiatric medicine as well as cognitive aspects of AI safety, there is a need for a mathematical formulation which is both mathematically precise and equally accessible to experts from numerous fields. In this paper we formalize human psychodynamics via the diagrammatic framework of process theory, describe its key properties, and explain the links between a diagrammatic representation and central concepts in analysis of cognitive processes in contexts such as psychotherapy, neurotechnology, AI alignment, AI agent representation of individuals in autonomous negotiations, developing human-like AI systems, and other aspects of AI safety.

Ammara Rafique

Abstract: Background: Cerebral palsy (CP) is a neurological disorder that impacts movement, posture, and muscle tone due to brain damage in fetal development, infancy, or early childhood. Objective: To compare anxiety and depression among primary caregivers of male versus female children with cerebral palsy. Methodology: This cross-sectional comparative study was carried out between February 2020 and March 2021 with the caregivers of CP-inflicted children admitted at a rehabilitation center in Karachi, Pakistan. Among 46 approached caregivers, only 30 (75%) voluntarily participated in the study. Group 1 encompassed caregivers of male CP-inflicted patients (n=19) and group 2 encompassed caregivers of female CP-inflicted patients (n=11). Data on physical characteristics and additional impairments accompanying CP was gathered whereas face-to-face meetings were arranged with primary caregivers to gather data for sociodemographic questionnaire and Hospital anxiety depression scale (HADS). Results: No significant differences were observed in the two groups concerning the physical characteristics of CP cases and sociodemographic characteristics of caregivers. Compared to the caregivers of female CP children, caregivers of male CP children had significantly higher anxiety (7.09±1.64; 8.42±1.6, p=0.044), depression (5.90±1.8; 8.10±1.88, p=0.004) and total HADS scores (6.50±1.79; 8.26±1.75, p=0.006). Conclusion: Caregivers of male CP children were more prone to anxiety and depression problems. There was no significant correlation found between the sociodemographic profile of the caregivers and the characteristics of CP with the gender of CP children. Keywords: Anxiety; Caregivers; Cerebral Palsy; Children; Depression; Pakistan

Kresna Agung Yudhianto, Marni, Nur Azma Amin

Effective communication between nurses and patients is essential in building therapeutic relationships, increasing patient trust, and enhancing satisfaction with healthcare services. This study employs a cross-sectional design to evaluate the impact of a psychology-based model of empathic communication in nursing on patient trust and satisfaction. The model, which emphasizes understanding, active listening, and emotional presence, is grounded in psychological principles that support patient-centered care. Data were collected through a structured survey administered to patients in healthcare settings in Indonesia and Malaysia. The study analyzes how empathic communication influences patient trust, reduces anxiety, and improves satisfaction with care. Findings indicate that implementing a structured empathic communication model significantly enhances nurse-patient interactions and contributes to better health outcomes. The results underscore the importance of integrating psychological principles into nursing communication practices to improve patient care quality.

Saad Tariq, Mamoona Tasleem Afzal, Anam Javed et al.

Background: Neck pain is a disorder that has lifetime and point prevalence almost as high as low back pain. It also leads to substantial disability and economic burden on society. Physical therapists use several interventions with this population such as ischemic compression which is a standard treatment used for the treatment of trigger point release in routine physical therapy practice. Dry needling is comparatively a newer treatment intervention in practice now for the relieve of pain causing trigger points not specifically in case of neck pain but in other condition such as Fibromyalgia, Myofascial Pain Syndrome as well. Objective: To determine the effectiveness of Trigger point Dry Needling compared with ischemic compression release in the patients having neck pain due to myofascial trigger points and to create awareness about better treatment intervention for trigger point release among medical community. Methodology: A Randomized Clinical Trail of 16 weeks duration is conducted in Physical Therapy Department of Holy Family Hospital Rawalpindi comprised of patients with neck pain associated with trigger points. A sample of 30 patients was taken fulfilling the inclusion & exclusion criteria. Initially the patients were recruited using non-probability convenient sampling, later the allocation between the groups was done randomly using sealed envelope method. Participants were randomly divided in dry needling group (N = 15) and trigger point compression release group (N = 15). The data was collected at 1st week and final (4th) week. Improvement was assessed through Visual Analog Scale(VAS) and Northwick Park Neck Pain Questionnaire(NPQ). Results: Findings from independent t- test used for comparison between the two groups showed significant p-value at the final week which is less than 0.05 for both VAS and NPQ (P=0.038; 0.018 respectively). Within the group comparison using repeated measure ANOVA showed significant improvement in the experimental group for both the variables after week 2, with the significant value of wilk’s lambda ^ (^=0.001) which is less than 0.05. Conclusion: Dry needling is more effective than ischemic compression for the trigger point release. Key Words: Dry needling, Ischemic compression, Neck pain

Leyao Wang, Rishab Pulugurta, Pranay Vure et al.

Peptide therapeutics, including macrocycles, peptide inhibitors, and bioactive linear peptides, play a crucial role in therapeutic development due to their unique physicochemical properties. However, predicting these properties remains challenging. While structure-based models primarily focus on local interactions, language models are capable of capturing global therapeutic properties of both modified and linear peptides. Protein language models like ESM-2, though effective for natural peptides, cannot however encode chemical modifications. Conversely, pre-trained chemical language models excel in representing small molecule properties but are not optimized for peptides. To bridge this gap, we introduce PepDoRA, a unified peptide representation model. Leveraging Weight-Decomposed Low-Rank Adaptation (DoRA), PepDoRA efficiently fine-tunes the ChemBERTa-77M-MLM on a masked language model objective to generate optimized embeddings for downstream property prediction tasks involving both modified and unmodified peptides. By tuning on a diverse and experimentally valid set of 100,000 modified, bioactive, and binding peptides, we show that PepDoRA embeddings capture functional properties of input peptides, enabling the accurate prediction of membrane permeability, non-fouling and hemolysis propensity, and via contrastive learning, target protein-specific binding. Overall, by providing a unified representation for chemically and biologically diverse peptides, PepDoRA serves as a versatile tool for function and activity prediction, facilitating the development of peptide therapeutics across a broad spectrum of applications.

Aylin Gunal, Baihan Lin, Djallel Bouneffouf

Given the increasing demand for mental health assistance, artificial intelligence (AI), particularly large language models (LLMs), may be valuable for integration into automated clinical support systems. In this work, we leverage a decision transformer architecture for topic recommendation in counseling conversations between patients and mental health professionals. The architecture is utilized for offline reinforcement learning, and we extract states (dialogue turn embeddings), actions (conversation topics), and rewards (scores measuring the alignment between patient and therapist) from previous turns within a conversation to train a decision transformer model. We demonstrate an improvement over baseline reinforcement learning methods, and propose a novel system of utilizing our model's output as synthetic labels for fine-tuning a large language model for the same task. Although our implementation based on LLaMA-2 7B has mixed results, future work can undoubtedly build on the design.

Junwei Sun, Siqi Ma, Yiran Fan et al.

We aim to evaluate the efficacy of traditional machine learning and large language models (LLMs) in classifying anxiety and depression from long conversational transcripts. We fine-tune both established transformer models (BERT, RoBERTa, Longformer) and more recent large models (Mistral-7B), trained a Support Vector Machine with feature engineering, and assessed GPT models through prompting. We observe that state-of-the-art models fail to enhance classification outcomes compared to traditional machine learning methods.

Yang Liu, Jie Gao, Xiaonan Zhang et al.

Messenger RNA (mRNA) vaccines and therapeutics are emerging as powerful tools against a variety of diseases, including infectious diseases and cancer. The design of mRNA molecules, particularly the untranslated region (UTR) and coding sequence (CDS) is crucial for optimizing translation efficiency and stability. Current design approaches generally focus solely on either the 5' UTR or the CDS, which limits their ability to comprehensively enhance translation efficiency and stability. To address this, we introduce LinearDesign2, an algorithm that enables the co-design of the 5' UTR and CDS. This integrated approach optimizes translation initiation efficiency (TIE), codon adaptation index (CAI), and minimum free energy (MFE) simultaneously. Comparative analyses reveal that sequences designed by LinearDesign2 exhibit significantly higher TIE than those designed by LinearDesign, with only a slight increase in MFE. Further, we validate the accuracy of the computational TIE metric using large-scale parallel translation experimental data. This study highlights the importance of a joint design strategy for the 5' UTR and CDS in optimizing mRNA performance, paving the way for more efficient mRNA vaccines and therapeutics.

Honggen Zhang, Xiangrui Gao, June Zhang et al.

Messenger RNA (mRNA)-based vaccines are accelerating the discovery of new drugs and revolutionizing the pharmaceutical industry. However, selecting particular mRNA sequences for vaccines and therapeutics from extensive mRNA libraries is costly. Effective mRNA therapeutics require carefully designed sequences with optimized expression levels and stability. This paper proposes a novel contextual language model (LM)-based embedding method: mRNA2vec. In contrast to existing mRNA embedding approaches, our method is based on the self-supervised teacher-student learning framework of data2vec. We jointly use the 5' untranslated region (UTR) and coding sequence (CDS) region as the input sequences. We adapt our LM-based approach specifically to mRNA by 1) considering the importance of location on the mRNA sequence with probabilistic masking, 2) using Minimum Free Energy (MFE) prediction and Secondary Structure (SS) classification as additional pretext tasks. mRNA2vec demonstrates significant improvements in translation efficiency (TE) and expression level (EL) prediction tasks in UTR compared to SOTA methods such as UTR-LM. It also gives a competitive performance in mRNA stability and protein production level tasks in CDS such as CodonBERT.

J. M. Armitage, R. E. Wootton, O. S. P. Davis et al.

Abstract Educational attainment is associated with a range of positive outcomes, yet its impact on wellbeing is unclear, and complicated by high correlations with intelligence. We use genetic and observational data to investigate for the first time, whether educational attainment and intelligence are causally and independently related to wellbeing. Results from our multivariable Mendelian randomisation demonstrated a positive causal impact of a genetic predisposition to higher educational attainment on wellbeing that remained after accounting for intelligence, and a negative impact of intelligence that was independent of educational attainment. Observational analyses suggested that these associations may be subject to sex differences, with benefits to wellbeing greater for females who attend higher education compared to males. For intelligence, males scoring more highly on measures related to happiness were those with lower intelligence. Our findings demonstrate a unique benefit for wellbeing of staying in school, over and above improving cognitive abilities, with benefits likely to be greater for females compared to males.

Naïg Chenais, Naïg Chenais, Arno Görgen

Digital immersive technologies have become increasingly prominent in clinical research and practice, including medical communication and technical education, serious games for health, psychotherapy, and interfaces for neurorehabilitation. The worldwide enthusiasm for digital health and digital therapeutics has prompted the development and testing of numerous applications and interaction methods. Nevertheless, the lack of consistency in the approaches and the peculiarity of the constructed environments contribute to an increasing disparity between the eagerness for new immersive designs and the long-term clinical adoption of these technologies. Several challenges emerge in aligning the different priorities of virtual environment designers and clinicians. This article seeks to examine the utilization and mechanics of medical immersive interfaces based on extended reality and highlight specific design challenges. The transfer of skills from virtual to clinical environments is often confounded by perceptual and attractiveness factors. We argue that a multidisciplinary approach to development and testing, along with a comprehensive acknowledgement of the shared mechanisms that underlie immersive training, are essential for the sustainable integration of extended reality into clinical settings. The present review discusses the application of a multilevel sensory framework to extended reality design, with the aim of developing brain-centered immersive interfaces tailored for therapeutic and educational purposes. Such a framework must include broader design questions, such as the integration of digital technologies into psychosocial care models, clinical validation, and related ethical concerns. We propose that efforts to bridge the virtual gap should include mixed methodologies and neurodesign approaches, integrating user behavioral and physiological feedback into iterative design phases.

Makiko Omura, Samuele Cortese, Marion Bailhache et al.

Abstract Socioeconomic status (SES) influences the risk of both physical diseases, such as asthma, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD). Using Causal Mediation Analysis on French birth-cohort data, we found a causal pathway from SES to ADHD symptoms, in part mediated by asthma. An increase in family income at age 3 by one unit resulted in lower ADHD symptoms at age 5, by −0.37 [95% CI: −0.50, −0.24] SDQ-score-points, with additional −0.04 [95% CI: −0.08, −0.01] points reduction indirectly via asthma at age 3, both with statistical significance. Importantly, family income at age 3 exerted both direct and indirect (via asthma) negative effects on later ADHD symptoms with much higher magnitudes for the direct effect. Our findings underscore the importance of apprehending ADHD symptoms in the broader context of socioeconomic disparities, along with their comorbidities with asthma, potentially influencing public health interventions and clinical practice in managing ADHD.

Dheeraj Pratap, Rizul Gautam, Amit Kumar Shaw et al.

Longer near-infrared wavelengths provide better penetration depth in biological tissues, so these are useful for plasmonic photothermal cancer therapeutics. In the context of nanoparticles for such applications, the absorption can be tuned for longer NIR wavelengths. However, on increasing the size of the nanoparticle, the scattering is enhanced and thus is not suitable for plasmonic therapeutics. Therefore, to overcome this issue, different types of small gold nanorods were synthesized and converted into stable aggregates to red-shift the plasmonic resonance wavelength to longer near-infrared wavelengths. The gold nanorod aggregates were embedded into the agarose gel phantoms mimicking the tumor-tissue-like structure. The photothermal response was measured through the prepared phantoms using a broadband near-infrared light source. It was shown that even in an extremely dilute concentration of gold nanorods, the photothermal heat generation could increase after the aggregation and also give gives deeper penetration of thermal energy. The observed photothermal response was also verified through numerical simulation. The current study shows better performance by increasing the plasmonic coupling, reducing the mismatch issue of plasmonic resonance shift in the second biological therapeutic window for the aggregates without increasing the size of individual nanoparticles. The aggregates provide better light penetration at deeper tissue by red-shifting the absorbance resonance wavelength which is useful for plasmonic photothermal cancer therapy.

Baihan Lin, Stefan Zecevic, Djallel Bouneffouf et al.

We present the TherapyView, a demonstration system to help therapists visualize the dynamic contents of past treatment sessions, enabled by the state-of-the-art neural topic modeling techniques to analyze the topical tendencies of various psychiatric conditions and deep learning-based image generation engine to provide a visual summary. The system incorporates temporal modeling to provide a time-series representation of topic similarities at a turn-level resolution and AI-generated artworks given the dialogue segments to provide a concise representations of the contents covered in the session, offering interpretable insights for therapists to optimize their strategies and enhance the effectiveness of psychotherapy. This system provides a proof of concept of AI-augmented therapy tools with e in-depth understanding of the patient's mental state and enabling more effective treatment.

Mamoona Tasleem Afzal, Umme Farwa, Mayam Attiq et al.

Objective: To find the frequency of Restless Legs Syndrome (RLS) among university students and to find out the association between RLS and its effects on daily life activities and quality of sleep among university students. Methodology: The study was carried out in universities of Rawalpindi and Islamabad from April to September 2022.A sample of 191 participants was taken fulfilling the inclusion criteria (Both genders, Age between 18 to 30 years, all those students fulfilling the diagnostic criteria using  International Restless legs Syndrome Study Group).Non probability convenient sampling technique was used. The data was collected using diagnostic criteria established by International Restless Legs Syndrome Study Group (IRLSSG). Data was analyzed by SPSS23. Results: Out of the 191 participants, the frequency of males was 71(37%) and that of females was 121(63%).The overall mean age of participants was 21.8±1.96 years. The frequency of Restless Legs Syndrome among university students was recorded to be 27(14.1%). The chi-square test was applied to see the correlation between RLS and its effect on sleep and daily life activities. Results showed that p-value was 0.00, which showed a strong association between RLS and quality of sleep and daily life activities of university students. Conclusion: The frequency of Restless Legs Syndrome among university students was 27 (14.1%) and the study concluded there was a strong association presents between RLS and university students due to prolong sitting (p-value was 0.00,p value<0.05).RLS effects daily life activities and quality of sleep. Keywords: Daily Life Activities ADLS, Quality of Sleep, Restless Legs Syndrome RLS

Cenk Demir, Shumon Koga, Miroslav Krstic

Neurological studies show that injured neurons can regain their functionality with therapeutics such as Chondroitinase ABC (ChABC). These therapeutics promote axon elongation by manipulating the injured neuron and its intercellular space to modify tubulin protein concentration. This fundamental protein is the source of axon elongation, and its spatial distribution is the state of the axon growth dynamics. Such dynamics often contain time delays because of biological processes. This work introduces an input delay compensation with state-feedback control law for axon elongation by regulating tubulin concentration. Axon growth dynamics with input delay is modeled as coupled parabolic diffusion-reaction-advection Partial Differential Equations (PDE) with a boundary governed by Ordinary Differential Equations (ODE), associated with a transport PDE. A novel feedback law is proposed by using backstepping method for input-delay compensation. The gain kernels are provided after transforming the interconnected PDE-ODE-PDE system to a target system. The stability analysis is presented by applying Lyapunov analysis to the target system in the spatial H1-norm, thereby the local exponential stability of the original error system is proved by using norm equivalence.

Farial Farial, Eka Sri Handayani

The Covid-19 pandemic that has not been resolved to date has changed human habits, especially in the field of education. One of the most obvious impacts is that students cannot go to school/college as before to prevent the spread of Covid-19. In addition, students are also required to adapt to technology or commonly known as Distance Education (PJJ). The COVID-19 pandemic has become a frightening specter for all people, making all aspects of life different from before some of these problems raise a lot of concerns related to the future of education management and services, the impact of Covid-19 is very influential on the psychology of teenagers. Changes in habits that occurred during the Covid-19 period certainly had an impact on all aspects, both technological adaptation, learning challenges, to the psychology of adolescents as students. Therefore, resilience is needed so that adolescents survive, rise, and adapt to difficult and stressful conditions. in the academic field. The method used in this study is a quantitative method with an experimental research strategy, the subjects in this study are teenagers at MA Muhammadiyah 2 Al-Furqon Banjarmasin in class XI which consists of 3 classes with a total of 99 students in the analysis stage using the T-test technique. For comparative test or difference test. Based on the results of hypothesis testing from both groups using the t-test, it was obtained that tcount = -2,317 and ttable = -1,661. Thus, tcount > ttable with = 5%. The value of tcount is in the rejection area H0, while Ha is accepted, so it can be concluded that there is an effectiveness of giving Al-Quran therapy in increasing post-pandemic adolescent resilience at MA Muhammadiyah 2 Al-Furqon Banjarmasin.

Fouzia Batool, Iqra Imtiaz, Zakir Hussain et al.

Objective :To determine the pain intensity of non-specific neck pain and find out the association of neck pain with stress, anxiety and depression. Methodology: A cross sectional study was carried out on 254 young adults in Shifa Tameer-e-Millat University Islamabad, Pakistan from July to December 2017. Participants of either gender in age range 18 to 24 years and have non-specific neck pain were included in the study. All the participants with any illness or trauma that might cause neck pain and pathological condition associated with neck were excluded from the study. “Numeric Pain Rating Scale” and “Depression Anxiety Stress Scale-21” were used to evaluate pain intensity and negative emotions such as depression, anxiety and stress.  Chi square test was applied to determine the association between pain and depression, anxiety and stress. The data was analyzed through SPSS v-21. Results: Out of total 254 participants 212 (83.5%) were females and 42 (16.5%) were males. Participants mean age was 20.66±1.83 (years). According to the results stress and depression had significant association with neck pain (p value <0.05). However, no association of neck pain was observed with anxiety as p value was >0.05. Conclusion: The study concluded that majority of the participants had mild level of non-specific neck pain and significant association of neck pain was found with depression and stress. Key words: Anxiety, Depression, Mental health, Pain, Stress.