Health-related Disorders Research Articles

Comorbidity of problematic substance use and other addictive behaviors and anxiety, depression, and post-traumatic stress disorder: a network analysis.

Among those with common mental health disorders (e.g. mood, anxiety, and stress disorders), comorbidity of substance and other addictive disorders is prevalent. To simplify the seemingly complex relationships underlying such comorbidity, methods that include multiple measures to distill which specific addictions are uniquely associated with specific mental health disorders rather than due to the co-occurrence of other related addictions or mental health disorders can be used. In a general population sample of Jewish adults in Israel (N = 4002), network analysis methods were used to create partial correlation networks of continuous measures of problematic substance (non-medical use of alcohol, tobacco, cannabis, and prescription sedatives, stimulants, and opioid painkillers) and behavioral (gambling, electronic gaming, sexual behavior, pornography, internet, social media, and smartphone) addictions and common mental health problems (depression, anxiety, and post-traumatic stress disorder [PTSD]), adjusted for all variables in the model. Strongest associations were observed within these clusters: (1) PTSD, anxiety, and depression; (2) problematic substance use and gambling; (3) technology-based addictive behaviors; and (4) problematic sexual behavior and pornography. In terms of comorbidity, the strongest unique associations were observed for PTSD and problematic technology-based behaviors (social media, smartphone), and sedatives and stimulants use; depression and problematic technology-based behaviors (gaming, internet) and sedatives and cannabis use; and anxiety and problematic smartphone use. Network analysis isolated unique relationships underlying the observed comorbidity between common mental health problems and addictions, such as associations between mental health problems and technology-based behaviors, which is informative for more focused interventions.

Prevalence of metabolic syndrome and its risk factors among the government bank’s employees of district Bijnor, Uttar Pradesh: A cross-sectional study

ABSTRACT Background: Metabolic syndrome (MetS) involves having at least 3 out of 5 health conditions that increase the risk of cardiovascular disease, stroke, and type 2 diabetes mellitus. These conditions include increased blood pressure (BP), high blood sugar, excess body fat around the waist, and abnormal cholesterol or triglyceride levels. Each of these conditions is treatable with lifestyle changes and/or medication. Objective: 1). To find out the prevalence of MetS and various risk factors associated with it through MetS’s screening criteria. 2) To find out the health risk status and stress level among bank’s employees in the government sector. Material and Methods: A medical health camp was organised for all bank’s employees to rule out the various health-related disorders. Thus, 64 beneficiaries were participated. A detailed history was taken regarding their socio-demographic profile, risk factors affecting the MetS, and stress levels among each individual through the direct personal interview method. Results: As per MetS’s screening criteria (NCEP-ATP III), the prevalence of MetS was 7.81% among the bank’s employees. The various risk factors affecting the MetS are elevated serum triglyceride level, elevated fasting blood glucose (FBG), raised BP, enlarged WC, etc., The majority of individuals had a high risk of health status 27 (42.1%) and a moderate level of stress, i.e., 38 (59.4%), respectively. Most of the participants were hypertensive 49 (76.6%), diabetic 16 (28.6%), and obese 37 (57.8%). Conclusion: Common concerns of male gender, increasing age and BMI, sedentary lifestyle, stress and positive family history should be considered for early identification and appropriate intervention to fight against the growing MetS epidemic.

Exploring the Frontier of Cyclic Dipeptides: A Bioinformatics Approach to Potential Therapeutic Applications in Schizophrenia.

Cyclic dipeptides (CDPs), known for their diverse biological activities, have potential therapeutic applications in mental and behavioral disorders (MBDs), particularly schizophrenia. This study explores the CDPs' therapeutic potential using bibliometric analysis, network pharmacology, molecular docking, and experimental verification, focusing on the interactions with the SIGMA1 receptor. A literature review over three decades utilizing the Web of Science Core Collection (WOSCC) was conducted to identify the emerging trends in CDPs research. A compound library was constructed from the PubChem database, and target prediction using SwissTargetPrediction revealed 800 potential protein targets. A compound-target network highlighted the key interactions with kinases, G protein-coupled receptors, and chromatin-modifying enzymes. Enrichment analysis revealed significant associations with schizophrenia and other MBDs. Schizophrenia-related targets among the potential protein targets were identified using the GEO database. Molecular docking results showed interactions of MC4R, OPRK1, SIGMA1, and CDK5R1 with various CDPs compounds, with SIGMA1 being especially noteworthy. Most CDPs exhibited lower binding energies than the control compounds NE-100 and duloxetine. Experimental validation demonstrated that CDPs such as Cyclo(Ala-Gln), Cyclo(Ala-His), and Cyclo(Val-Gly) exhibited IC50 values of 13.4, 19.4, and 11.5 μM, respectively, against SIGMA1, indicating biological activity. Our findings underscore their potential as therapeutic agents for schizophrenia, highlighting the need for further modifications to enhance specificity and efficacy. This work paves the way for future investigations into CDPs, contributing to developing targeted treatments for schizophrenia and related mental health disorders.

Evaluation of the reliability of measuring lower back muscles cross-sectional area based on manual segmentation within multi-level MRI images

IntroductionManual segmentation of paraspinal muscle cross-sectional area (CSA) is widely used to assess related health disorders. This study aimed to evaluate the reliability of this segmentation process for each paraspinal region of interest across the three intervertebral levels commonly used for segmentation (L3/4, L4/5, and L5/S1). MethodsAxial-T2-weighted MRI images for 238 patients were divided among five raters (47 ± 1 cases each). To conduct the intra-rater reliability study, the CSA of each paraspinal lumber muscle (psoas major (PM), multifidus (MF), and erector spinae (ES)) and the intervertebral disc (ID) were manually segmented twice on all targeted levels before being assessed for each region per rater. The Inter-rater reliability was determined by comparing the results of different readers who segmented the same dataset. The Intraclass Correlation (ICC) and Coefficient-of-Variation percentage (CV%) were reported for each analysis. ResultsLow intra- and inter-rater variability (CV%<11) was found for each reader in each region and intervertebral level. The inter-rater reliability was excellent (ICC>0.9) for the PM, ID, and ES at L3/4. However, it was very good for MF at all levels and ES at L4/5, L5/S1 (ICC range: 0.82–0.88) affected by the fat-infiltration nature of the ES and MF muscles, their proximity to each other, and their smaller size (correlation between muscle size and ICC = 0.6, P < 0.01). The ID segmentation has the lowest CV (<3 %) and excellent ICC (>0.93). ConclusionManual paraspinal muscle segmentation using axial-T2-weighted MRI is reliable at all commonly segmented intervertebral levels. However, the reliability level can be degraded by the presence of high-fat infiltrate, unclear muscle boundaries, and muscle size. Implications for practiceFollowing consistent guidelines can help improve segmentation results. The IDs can be used as reliable internal references.

Unveiling the silent struggle: navigating the labyrinth of mental health for parents of children with life-threatening illnesses in Pakistan.

Dear Editor, We write this letter to highlight the scarcely recognised complexity associated with the unrecognised mental health needs of parents of children diagnosed with life-threatening or life-limiting illnesses. It has been widely established that parents of children with disabilities are at an increased risk of developing variants of mental diseases when compared to parents of children without such disabilities. Parents tend to alter their lives socially to acclimatize themselves as caregivers for their children, therefore adopting a role that becomes far more labyrinthine as both parent and caregiver. (1) Mental health in general, is a subject that is insufficiently addressed in societal and scholarly contexts, specifically in Pakistan, particularly among parents. Within the scope of parents acting as sole caregivers, stress is a prominent determinant contributing to their mental health. Stress can attenuate parents’ and children’s abilities to navigate these circumstances and diminish their capacity for problem-solving and coping. (2) There are a myriad of factors that contribute to the reported prevalence of mental health-related disorders among parents of children with disabilities. Mental health remains a stigmatised entity. Such disregard impedes the delivery of healthcare towards patients suffering from mental health illnesses. There is a noteworthy hindrance in individuals facing such factors when amalgamatinge into society. When considering parental figures of diseased children, this facet serves to isolate further and reinforce such mental health illnesses. The lack of quantifiable data on anti-stigma interventions in Low and Middle-Income Countries, including Pakistan, underscores the urgent need for research. (3) Parents of children admitted to the ICU have a near-pervasive struggle with mental health and an innate inability to disclose their requirements for support. Factors barricading such disclosure should be identified and broken down through interventions, facilitating access to vital mental health support. (4) Caregivers must establish coping strategies, and remain a steady pillar of support and comfort to their child. The Keeping Hope Alive Toolkit intervention was established, which worked on fostering emotional experiences, living in the moment, remembering self and supporting social preferences, this intervention provided a template for emotional support. (5) We hope this letter can underscore how important supporting parental disclosure of unmet mental health needs is – a rampant and insufficiently reported plight in Pakistan. The ability to recognise these emotions and rectify them is not highlighted in this region but is imperative to implement, to improve the provision of healthcare to diseased children and their parents alike.

Psychosocial Impact of Acne in Adolescents: Prevalence, Contributing Factors, and Management Approaches

Objectives: Acne is a chronic inflammatory skin disease caused by bacteria that leads to the destruction of the pilosebaceous units on the face and body. This condition, particularly prevalent among adolescents, can have negative psychosocial effects. This study examines the psychological aspects of acne and its related mental health disorders. Methods: This research was conducted as a review study, investigating the psychosocial impacts of acne on adolescents and management strategies. Using reputable scientific databases and a combination of relevant keywords, 1200 articles were identified, and after screening, 33 articles were selected for final analysis. Data from the selected articles were analyzed through narrative synthesis, and article quality was assessed using the Newcastle-Ottawa scale. Results: Acne has multiple psychological effects, including anxiety, depression, reduced self-esteem, and body image disturbances. These effects are particularly prominent in adolescents due to hormonal and social changes during puberty. Additionally, misconceptions about the causes and exacerbating factors of acne often lead to delays in receiving appropriate treatment. Conclusion: Acne is not only a skin disease but also a psychosocial challenge that requires a multifaceted management approach. Addressing the psychological dimensions of patients and providing accurate education can improve their quality of life.

A robust deep learning system for screening of obstructive sleep apnea using T-F spectrum of ECG signals

Obstructive sleep apnea (OSA) is a non-communicable sleep-related medical condition marked by repeated disruptions in breathing during sleep. It may induce various cardiovascular and neurocognitive complications. Electrocardiography (ECG) is a useful method for detecting numerous health-related disorders. ECG signals provide a less complex and non-invasive solution for the screening of OSA. Automated and accurate detection of OSA may enhance diagnostic performance and reduce the clinician’s workload. Traditional machine learning methods typically involve several labor-intensive manual procedures, including signal decomposition, feature evaluation, selection, and categorization. This article presents the time-frequency (T-F) spectrum classification of de-noised ECG data for the automatic screening of OSA patients using deep convolutional neural networks (DCNNs). At first, a filter-fusion algorithm is used to eliminate the artifacts from the raw ECG data. Stock-well transform (S-T) is employed to change filtered time-domain ECG into T-F spectrums. To discriminate between apnea and normal ECG signals, the obtained T-F spectrums are categorized using benchmark Alex-Net and Squeeze-Net, along with a less complex DCNN. The superiority of the presented system is measured by computing the sensitivity, specificity, accuracy, negative predicted value, precision, F1-score, and Fowlkes-Mallows index. The results of comparing all three utilized DCNNs reveal that the proposed DCNN requires fewer learning parameters and provides higher accuracy. An average accuracy of 95.31% is yielded using the proposed system. The presented deep learning system is lightweight and faster than Alex-Net and Squeeze-Net as it utilizes fewer learnable parameters, making it simple and reliable.

Impulsivity: A Transdiagnostic Approach to Understanding Adolescent Substance Use

Impulsivity: A Transdiagnostic Approach to Understanding Adolescent Substance Use

Evaluation of metabolic changes in clinic attendees with therapeutic carbohydrate restriction

Background: Obesity and related metabolic health disorders are major clinical problems that have become increasingly prevalent worldwide.Aim: This before-after study examined the impact of therapeutic carbohydrate restriction (TCR) in managing metabolic health and promoting weight loss in a clinical setting using indirect calorimetry (IC).Setting: Data were collected from medical records obtained from a specialised allied health clinic focusing on metabolic health.Methods: The study analysed retrospective data from 202 overweight or obese participants (77% female, mean age 47.3) who received TCR as part of a behavioural modification programme involving multiple visits where their lifestyle, body composition and respiratory quotient (RQ), a key indicator of fat oxidation were recorded.Results: The study found that TCR improved fat oxidation in 84% of participants at short term visit (around 2 weeks), with an average weight loss of 1.8 kg. At medium term visit (around 12 weeks), 82% of participants maintained an increase in fat oxidation rate, with an average weight loss of 3.9 kg. In addition, among those with recorded body composition and waist circumference, 71% of weight lost was from fat, with an average reduction of 4.9 cm in waist measurements.Conclusion: This real-world study suggests that personalised TCR guided by IC can be an effective strategy for improving metabolic flexibility to help manage excess weight and related co-morbidities in a free-living population. Further research is needed to examine the long-term effects of TCR using this approach.Contribution: The utilisation of IC allows for the examination of individual shifts and improvements in metabolism among patients undergoing TCR.

Depression Intensity Identification using Transformer Ensemble Technique for the Resource-constrained Bengali Language

Depression is an ordinary mental health-related disorder that hampers people’s daily activities, and sometimes, it destroys an individual’s life. It is one of the major social issues at present. Since depressed people use various social networking sites for sharing their thoughts and feelings, many scholars have tried to identify depression texts in highly resourced languages like English; however, only a small quantity of papers are detected in the resource-constrained Bengali language. This paper focuses on developing a depression intensity detection system from Bengali text data. In this regard, this study experiments on a 2,596 sample-sized dataset with four levels of depression by utilizing five state-of-the-art transformer models, including multilingual Bidirectional Encoder Representations from Transformers, DistilmBERT, XLM-RoBERTa, Bangla-BERT-Base, and BanglaBERT, and suggests a new ensemble method called MaxOfAvgProb. This method goes beyond the performance of the previous work on the same dataset, scoring 63.47% F1-score and 62.90% accuracy. To increase the reliability of the proposed method, we utilize this approach on another available dataset with 4,897 entries. In this case, our recommended method also surpasses the performance of the existing work on the same dataset, with accuracy at 86.45% and F1-score at 86.35%. Identifying the intensity of depression, depressed people may get proper counseling or treatment from their respected guardians or psychologists according to the victims’ level of depression.

Concept analysis of self-neglect in the elderly: a hybrid model.

Clarifying the concept of elder self-neglect. Researchers investigated the concept of elder self-neglect using a hybrid approach, including theoretical, fieldwork, and final analysis phases. After an extensive review of related literature to define the concept of self-neglect and describe its characteristics, the fieldwork phase was carried out to illustrate its empirical features. Accordingly, it led to the extraction of the elder self-neglect attributes from the first two phases. Elder self-neglect includes "subjective and objective high-risk behaviors pertinent to physical and spiritual health as well as restricted social interactions, disregarding the living environment, and a lack of compliance to personal hygiene routines that the elderly demonstrate deliberately or unintentionally. Various factors can contribute to such behaviors, including individual features, poor physical performance, elderly-oriented psychological disorders, financial challenges, detrimental stressors, unsuccessful social interactions, inaccessible supportive resources, inadequate educational resources, and inappropriate cultural norms. Consequently, such behaviors result in impaired physical and psychological health status, higher risk of misbehavior, poor quality of life, extra caregiving-treatment burden, and affected mental security in society." Given that elder self-neglect is considered a relatively unknown concept in Iran, the study findings can pave the way for future extensive research in the Iranian context by clarifying the concept. It can play a significant role in developing related tools to design more efficient interventions and improve the quality of nursing care services. The elder self-neglect concept can lead to numerous health-related disorders among the elderly in society. Nurses cannot deal with an unknown phenomenon without exploring and identifying its exact meaning. It is, therefore, imperative to illustrate the different dimensions of this concept to help create a deep understanding among the nurses and perform timely diagnosis and interventional procedures.

Patient-Centered Approaches for Designing Destigmatizing Sexual Pain-Related Web-Based Platforms: Qualitative Study.

Sexual pain is a common but neglected disorder that affects approximately 3% to 18% of women and an unmeasured number of gender-diverse people worldwide. Despite its wide prevalence, many people feel reluctant to visit conventional health care services or disclose their symptoms due to the fear of stigmatization. To alleviate this stigma, various web-based interventions have been developed to complement and, in some cases, replace conventional sexual health interventions. However, the way these web-based interventions are developed could inadvertently reproduce, perpetuate, or exacerbate stigma among end user patients. The purpose of this study was to understand patients' perspectives on how sexual pain-related web platforms can be designed to alleviate stigma or prevent the unintended effects of stigma among patients who use web-based interventions. Individual semistructured interviews were conducted among 16 participants with lived experiences of painful sex in a large urban city in Western Canada. Participants were recruited via social media platforms, newsletters, and a provincial health volunteer website. Using a sample sexual pain website to provide context, participants were interviewed about their experiences of stigma and how they think web platforms could be designed to address stigma. The interviews were conducted via Zoom (Zoom Technologies Inc) and analyzed using thematic analysis. The findings revealed 4 overarching themes that represented participants' perspectives on designing web platforms that may alleviate or prevent the unintended effects of stigma. These findings suggested the design of inclusive web platforms, having a nonprovocative and calming user interface, having features that facilitate connections among users and between users and providers, and displaying personal testimonials and experiences of sexual pain. This study highlighted patient-centered design approaches that could serve as a reference guide in developing web platforms that alleviate or prevent the unintended effects of stigma, particularly among nonheterosexual and gender-diverse people. While this study was conducted in the context of sexual pain, the results might also apply to web platforms on other potentially stigmatizing health-related disorders or conditions.

Increased oxidative stress in shoe industry workers with low-level exposure to a mixture of volatile organic compounds.

This study aimed to assess the redox status and trace metal levels in 49 shoe industry workers (11 men and 38 women) occupationally exposed to a mixture of volatile organic compounds (VOCs), which includes aliphatic hydrocarbons, aromatic hydrocarbons, ketones, esters, ethers, and carboxylic acids. All measured VOCs were below the permitted occupational exposure limits. The control group included 50 unexposed participants (25 men and 25 women). The following plasma parameters were analysed: superoxide anion (O2 •-), advanced oxidation protein products (AOPP), total oxidative status (TOS), prooxidant-antioxidant balance (PAB), oxidative stress index (OSI), superoxide dismutase (SOD) and paraoxonase-1 (PON1) enzyme activity, total SH group content (SHG), and total antioxidant status (TAS). Trace metal levels (copper, zinc, iron, magnesium, and manganese) were analysed in whole blood. All oxidative stress and antioxidative defence parameters were higher in the exposed workers than controls, except for PON1 activity. Higher Fe, Mg, and Zn, and lower Cu were observed in the exposed vs control men, while the exposed women had higher Fe and lower Mg, Zn, and Cu than their controls. Our findings confirm that combined exposure to a mixture of VOCs, even at permitted levels, may result in additive or synergistic adverse health effects and related disorders. This raises concern about current risk assessments, which mainly rely on the effects of individual chemicals, and calls for risk assessment approaches that can explain combined exposure to multiple chemicals.

Chitosan-Based Nanoencapsulated Essential Oils: Potential Leads against Breast Cancer Cells in Preclinical Studies.

Since ancient times, essential oils (EOs) derived from aromatic plants have played a significant role in promoting human health. EOs are widely used in biomedical applications due to their medicinal properties. EOs and their constituents have been extensively studied for treating various health-related disorders, including cancer. Nonetheless, their biomedical applications are limited due to several drawbacks. Recent advances in nanotechnology offer the potential for utilising EO-loaded nanoparticles in the treatment of various diseases. In this aspect, chitosan (CS) appears as an exceptional encapsulating agent owing to its beneficial attributes. This review highlights the use of bioactive EOs and their constituents against breast cancer cells. Challenges associated with the use of EOs in biomedical applications are addressed. Essential information on the benefits of CS as an encapsulant, the advantages of nanoencapsulated EOs, and the cytotoxic actions of CS-based nanoencapsulated EOs against breast cancer cells is emphasised. Overall, the nanodelivery of bioactive EOs employing polymeric CS represents a promising avenue against breast cancer cells in preclinical studies.

Safety of medical personnel when using personal protective equipment during the liquidation of a biological and social emergency

Relevance. According to scientific publications, preventive measures undertaken amid the COVID-19 pandemic failed to did reliably protect healthcare workers from the new coronavirus infection. The use of personal protective equipment (PPE) that protected against biological factors failed to protect HCWs from becoming infected and in most cases contributed to the functional disorders and impaired health. The objective is to provide evidence-based justification of preventive measures aimed at increasing healthcare workers’ (HCW) safety by using PPE during elimination of biological and social emergencies (based on the case of the COVID-19 pandemic).Methods. The study design included four consecutive stages: occupational morbidity assessment for COVID-19, assessment of HCWs’ working conditions; assessment of HCWs’ safety when using PPE sets in real setting and simulation, and justification of preventive measures to improve safety of HCWs.Results and discussion. The first year of the COVID-19 pandemic saw the incidence of 30.4 % among all HCWs working at the Military Medical Academy, suggesting a high risk of infection transmission. Morbidity was utmost among HCWs specializing in infections, followed by a significant number of HCWs who do not work in contaminated areas on a daily basis (surgeons, urologists, traumatologists). In addition to high incidence rate, the new coronavirus infection pandemic demanded enforcement of specific measures associated with the use of PPE at increased physical stress, including amid elevated ambient temperature. A sociological survey and experimental data allowed to assess the risk of functional and heat-injury related health disorders, as well as injuries in HCWs using PPEs. In order to reinforce occupational safety and minimize occupational risks of health deterioration in HCWs wearing PPEs at work, the research results allowed to develop a two-stage preventive action plan: stage 1 includes identification of dangerous factors, whereas stage 2 focuses on preventive measures to eliminate negative impact of hazards and associated risks.Conclusion. A set of preventive measures developed for the COVID-19 pandemic suggests practical tools to reinforce occupational safety for HCWs who use PPEs to deliver biological and social emergency response and elimination.

An ensemble technique to predict mental illness using data mining techniques

The mental well-being of a person is their mental state. Chemical abnormalities in the brain cause mental health problems. It is important to monitor the mental health of different groups in order to predict health-related disorders. The community consists of working professionals and college students. It is widely believed that stress and grief affect people of all ages and backgrounds. Some serious mental health disorders, such as anxiety, bipolar disorder, and schizophrenia, often evolve and produce symptoms that can be recognized early. Such mental disorders could be avoided more successfully if abnormal mental states are detected in the early stages of the disease, allowing for additional care and treatment. This study analyzed the accuracy of four data mining techniques and introduced a new ensemble technique to improve their accuracy in identifying mental health issues. The data mining techniques are Logistic Regression, KNN Classifier, Decision Tree Classifier, and Random Forest. This paper provides scope for other researchers and practitioners seeking to achieve higher accuracy in identifying mental health issues using enhanced data mining algorithms to meet several accuracy criteria.

Impact Assessment of Textile Industry Effluent on Water Quality and Health - A Case Study of Hapur District, Western Uttar Pradesh

Abstract: The developmental activities, industrialization and urbanization are responsible for contamination of soil and aquatic system. Textile industry is one of the important and largest industrial sector of India which is responsible for economic growth of nation. Textile industry effluent contain heavy metals, dye, inorganic and organic contaminants and show negative impact on environment and human health. In the present study, survey was conducted in the Pilkhuwa industrial area of Hapur district, western Uttar Pradesh and responses of local residents were collected through questionnaire after interview and group discussion. The local residents reported that water of the Pilkhuwa industrial area is not clean and safe for drinking and most of the people of the area are suffering from various health related disorders such as skin diseases, asthma, and typhoid etc. Hence, there is an urgent need of cost-effective, eco-friendly and sustainable technologies for decontamination of industrial effluent before its release into the environment.

Transcutaneous Nerve Stimulation Current Thresholds Based on Nerve Bending Angle and Nerve Termination Point

There is increasing interest in using transcutaneous electrical stimulation to treat or suppress brain-related disorders. Primary headache disorder is a socioeconomic burden whose pharmaceutical and invasive treatment method may have troublesome side effects. There are various transcutaneous electrical nerve stimulation neuromodulation systems that are used for health-related disorders. TMany factors may affect these systems’ efficiency, including stimulus current levels. A device for primary headaches showed mixed results. This may be related to the higher stimulus current levels that are applied through the electrodes. A feasible solution to reduce the required current levels is considering the geometrical features of the target nerve bending and nerve termination trajectories. In this study, the impact of the geometrical features of the nerve, such as nerve bending and nerve termination, on the stimulus current thresholds were analyzed based on FEM hybrid models. Twenty nerve models were generated considering statistical variations to assess the effect of the nerve geometrical features on the target neuromodulatory system. Finally, the safety parameters were calculated based on the target neuromodulator settings. The results showed that the geometric features of the target nerve have a significant effect on the required stimulus current thresholds. These results may provide important guidance mainly for transcutaneous nerve stimulation and future electrical nerve stimulation design.

Blood-lead level in humans and drug addiction: a comprehensive study in Iran.

Drug abuse has a high prevalence worldwide and causes many health-related disorders. There are limited human exposure studies on establishing lead exposure levels and their propensity for drug addiction. In the present study, blood samples were tested for lead (Pb) concentrations in illicit drug users together with the related symptoms in comparison with control group of non-drug users. The study was performed on 250 volunteers divided equally in four drug groups, namely, opioids, hashish, methadone, and methamphetamine, and one control group of non-drug users. Participants were recruited from drug addiction clinics and camps in Kashan city, Iran, who were using drugs continuously for more than 1 year. Control group was recruited from companions of the patients with no drug use history. In the investigated groups of drug users, the highest blood-lead level (BLL) concentrations were observed in the opioid group (mean 37.57 µg/dL) with almost 3.7times higher than in the control group (mean 3.39µg/dL). In the methamphetamine group, type of occupation had the significant association with BLL concentrations. The positive correlation was revealed in the opioid and methadone groups for BLL concentrations and the duration of drug usage. In the opioid group, the highest BLL concentrations were observed among users who used both methods of drug use: smoking and eating. Also, several behavioral and life-style factors were identified which influence the blood-lead concentration in the drug users. The results of our study revealed that the BLL concentrations in investigated drug users' groups were significantly higher than in the control group (P < 0.001). That can be related with the Pb contents in illicitly used drugs. Apart other adverse health effects, long-term illicit drug use might cause to lead poisoning.

Virtual Reality for Pulmonary Rehabilitation: Comprehensive Review.

Pulmonary rehabilitation is a vital component of comprehensive care for patients with respiratory conditions, such as lung cancer, chronic obstructive pulmonary disease, and asthma, and those recovering from respiratory diseases like COVID-19. It aims to enhance patients' functional ability and quality of life, and reduce symptoms, such as stress, anxiety, and chronic pain. Virtual reality is a novel technology that offers new opportunities for customized implementation and self-control of pulmonary rehabilitation through patient engagement. This review focused on all types of virtual reality technologies (nonimmersive, semi-immersive, and fully immersive) that witnessed significant development and were released in the field of pulmonary rehabilitation, including breathing exercises, biofeedback systems, virtual environments for exercise, and educational models. The review screened 7 electronic libraries from 2010 to 2023. The libraries were ACM Digital Library, Google Scholar, IEEE Xplore, MEDLINE, PubMed, Sage, and ScienceDirect. Thematic analysis was used as an additional methodology to classify our findings based on themes. The themes were virtual reality training, interaction, types of virtual environments, effectiveness, feasibility, design strategies, limitations, and future directions. A total of 2319 articles were identified, and after a detailed screening process, 32 studies were reviewed. Based on the findings of all the studies that were reviewed (29 with a positive label and 3 with a neutral label), virtual reality can be an effective solution for pulmonary rehabilitation in patients with lung cancer, chronic obstructive pulmonary disease, and asthma, and in individuals and children who are dealing with mental health-related disorders, such as anxiety. The outcomes indicated that virtual reality is a reliable and feasible solution for pulmonary rehabilitation. Interventions can provide immersive experiences to patients and offer tailored and engaging rehabilitation that promotes improved functional outcomes of pulmonary rehabilitation, breathing body awareness, and relaxation breathing techniques. The identified studies on virtual reality in pulmonary rehabilitation showed that virtual reality holds great promise for improving the outcomes and experiences of patients. The immersive and interactive nature of virtual reality interventions offers a new dimension to traditional rehabilitation approaches, providing personalized exercises and addressing psychological well-being. However, additional research is needed to establish standardized protocols, identify the most effective strategies, and evaluate long-term benefits. As virtual reality technology continues to advance, it has the potential to revolutionize pulmonary rehabilitation and significantly improve the lives of patients with chronic lung diseases.