Validity of mental and physical stress models

Evidence for the association between psychological stress and peri-implant health among middle-aged and elderly adults: A systemic review

BACKGROUND

Chronic psychological stress (CPS) is increasingly recognized for its detrimental effects on systemic and oral health, yet its impact on peri-implantitis remains underexplored.

AIM

To evaluate the evidence linking CPS to peri-implantitis.

METHODS

This systematic review was conducted according to the PRISMA guidelines. Publications searching PubMed, EMBASE, MEDLINE, Cochrane Library, and ClinicalTrials.gov for human studies published in English from 1983 to December 2024. Additionally, quality assessment of selected full-text articles were performed using the modified Newcastle–Ottawa Scale.

RESULTS

From an initial total of 3964 studies, 4 cross-sectional studies comprising 432 participants met the inclusion criteria and consistently demonstrated a positive association between CPS and peri-implantitis. However, the findings are compromised by small sample sizes, study design limitations, methodological heterogeneity, and inadequate adjustment for critical confounders such as smoking and prior periodontitis.

CONCLUSION

Cortisol levels in peri-implant sulcus fluid were linearly correlated with probing depth, with evidence suggesting this relationship may be independent of hyperglycemia. Depression emerged as the most significant CPS subtype associated with peri-implantitis. Additionally, CPS may amplify peri-implantitis inflammation by modulating cytokine expression effects. Long-term studies with larger, more diverse patient populations and careful control of confounding variables are needed to establish causality and understand the underlying mechanisms. Including psychological evaluations and stress management techniques in peri-implant care protocols could improve treatment outcomes and patient health.

Stress monitoring using low-cost electroencephalogram devices: A systematic literature review

INTRODUCTION

The use of low-cost, consumer-grade wearable health monitoring devices has become increasingly prevalent in mental health research, including stress studies. While cortisol response magnitude remains the gold standard for stress assessment, an expanding body of research employs low-cost EEG devices as primary tools for recording biomarker data, often combined with wrist and ring-based wearables. However, the technical variability among low-cost EEG devices, particularly in sensor count and placement according to the 10-20 Electrode Placement System, poses challenges for reproducibility in study outcomes.

OBJECTIVE

This review aims to provide an overview of the growing application of low-cost EEG devices and machine learning techniques for assessing brain function, with a focus on stress detection. It also highlights the strengths and weaknesses of various machine learning methods commonly used in stress research, and evaluates the reproducibility of reported findings along with sensor count and placement importance.

METHODS

A comprehensive review was conducted of published studies utilizing EEG devices for stress detection and their associated machine learning approaches. Searches were performed across databases including Scopus, Google Scholar, ScienceDirect, Nature, and PubMed, yielding 69 relevant articles for analysis. The selected studies were synthesized into four thematic categories: stress assessment using EEG, low-cost EEG devices, datasets for EEG-based stress measurement, and machine learning techniques for EEG-based stress analysis. For machine learning-focused studies, validation and reproducibility methods were critically assessed. Study quality was evaluated and scored using the IJMEDI checklist.

RESULTS

The review identified several studies employing low-cost EEG devices to monitor brain activity during stress and relaxation phases, with many reporting high predictive accuracy using various machine learning validation techniques. However, only 54% of the studies included health screening prior to experimentation, and 58% were categorized as low-powered due to limited sample sizes. Additionally, few studies validated their results using an independent validation set or cortisol response as a correlating biomarker and there was a lack of consensus on data pre-processing and sensor placement as a key contributor to improving model generalization and accuracy.

CONCLUSION

Low-cost consumer-grade wearable devices, including EEG and wrist-based monitors, are increasingly utilized in stress-related research, offering promising avenues for non-invasive biomarker monitoring. However, significant gaps remain in standardizing EEG signal processing and sensor placement, both of which are critical for enhancing model generalization and accuracy. Furthermore, the limited use of independent validation sets and cortisol response as correlating biomarkers highlights the need for more robust validation methodologies. Future research should focus on addressing these limitations and establishing consensus on data pre-processing techniques and sensor configurations to improve the reliability and reproducibility of findings in this growing field.

Treatments for weight gain in schizophrenia

PURPOSE OF REVIEW

Obesity and related metabolic disorders are extremely common in psychiatric patients, particularly in those with schizophrenia. Elucidating this link's neurobiology may inform clinicians and researchers of rational therapeutic approaches necessary to optimize clinical outcomes.

RECENT FINDINGS

Current literature highlights the pivotal role of the inflammation-oxidative stress-insulin resistance loop in the pathophysiology of both metabolic and neuropsychiatric disorders. The concept of 'diabetophrenia' is put forward to highlight the overlapping neurobiological mechanisms underlying metabolic dysfunction and schizophrenia symptoms. Innovative treatments, including the combination of xanomeline with trospium and incretin-based medicines, demonstrate encouraging potential in addressing such complex health challenges.

SUMMARY

The nuanced dynamics of chronic inflammation and psychiatric symptomatology underscore the significance of addressing both metabolic and mental health factors in a cohesive fashion while considering unique psychosocial contexts, dietary preferences, and lifestyle choices. A multidisciplinary strategy is essential for incorporating counseling, dietary interventions, behavioral therapies, and pharmacotherapy into the management of schizophrenia. The ensuing enhanced collaboration among healthcare professionals may render obsolete the prevailing siloed conceptualizations of mental disorders, opening new vistas for generating synergistic insights into the mind-body systems and leading to improved health and quality of life for patients with schizophrenia and other psychiatric conditions.

Rapid Mental Stress Evaluation Based on Non-Invasive, Wearable Cortisol Detection with the Self-Assembly of Nanomagnetic Beads

The rapid and timely evaluation of the mental health of emergency rescuers can effectively improve the quality of emergency rescues. However, biosensors for mental health evaluation are now facing challenges, such as the rapid and portable detection of multiple mental biomarkers. In this study, a non-invasive, flexible, wearable electrochemical biosensor was constructed based on the self-assembly of nanomagnetic beads for the rapid detection of cortisol in interstitial fluid (ISF) to assess the mental stress of emergency rescuers. Based on a one-step reduction, gold nanoparticles (AuNPs) were functionally modified on a screen-printed electrode to improve the detection of electrochemical properties. Afterwards, nanocomposites of MXene and multi-wall carbon nanotubes were coated onto the AuNPs layer through a physical deposition to enhance the electron transfer rate. The carboxylated nanomagnetic beads immobilized with a cortisol antibody were treated as sensing elements for the specific recognition of the mental stress marker, cortisol. With the rapid attraction of magnets to nanomagnetic beads, the sensing element can be rapidly replaced on the electrode uniformly, which can lead to extreme improvements in detection efficiency. The detected linear response to cortisol was 0-32 ng/mL. With the integrated reverse iontophoresis technique on a flexible printed circuit board, the ISF can be extracted non-invasively for wearable cortisol detection. The stimulating current was set to be under 1 mA for the extraction, which was within the safe and acceptable range for human bodies. Therefore, based on the positive correlation between cortisol concentration and mental stress, the mental stress of emergency rescuers can be evaluated, which will provide feedback on the psychological statuses of rescuers and effectively improve rescuer safety and rescue efficiency.

Neural Circuitries between the Brain and Peripheral Solid Tumors

The recent discovery of the pivotal role of the central nervous system in controlling tumor initiation and progression has opened a new field of research. Increasing evidence suggests a bidirectional interaction between the brain and tumors. The brain influences the biological behavior of tumor cells through complex neural networks involving the peripheral nervous system, the endocrine system, and the immune system, whereas tumors can establish local autonomic and sensory neural networks to transmit signals into the central nervous system, thereby affecting brain activity. This review aims to summarize the latest research in brain-tumor cross-talk, exploring neural circuitries between the brain and various peripheral solid tumors, analyzing the roles in tumor development and the related molecular mediators and pathologic mechanisms, and highlighting the critical impact on the understanding of cancer biology. Enhanced understanding of reciprocal communication between the brain and tumors will establish a solid theoretical basis for further research and could open avenues for repurposing psychiatric interventions in cancer treatment.