Thallium Intoxication in Relation to Drug Abuse and Cigarette Smoking in Iran

Thallium (Tl) is a highly toxic heavy metal with atomic number 81. It is a soft, bluish-white or gray water-insoluble metal but the salt forms are colorless, tasteless, and odorless. Tl is readily absorbed via ingestion, inhalation, and dermal contact. Any amount of Tl in the body is abnormal. The clinical manifestation of thallotoxicosis has a wide spectrum but painful ascending peripheral neuropathy, gastrointestinal, and dermatologic manifestations are major characteristics in Tl toxicity. Tl intoxication has been identified in drug abuse and cigarette smoking leading to various signs and symptoms. Substance abuse and cigarette smoke are a major public health hazard across the world

Examining Metabolic Profiles in Opioid-Dependent Patient

Background: Drug abuse is a social burden and a public health disorder. Previous evidencesuggested numerous illicit substances (e.g., opioids, amphetamines, cocaine, & cannabis)affect immune system functions, oxidative stress mechanisms, inflammatory cytokines, andreactive oxygen species production.This study aimed to determine the extent of these metabolic parameters in opioid-dependentpatients. We also compared these patients with a healthy control group.Methods: This study was conducted in Amirie Clinic, Kashan, Iran. Plasma and serumsamples from 50 illicit opioid users (study group) and 50 non-opioid users (control group)were studied. Metabolic levels for MDA, NO, TAC, GSH, Insulin, HOMA-IR, and hs-CRPwere assessed in both research groups (N=100).Results: There was a significant difference in the status of MDA (P=0.003), NO (P=0.01), TAC(P=0.003), GSH (P=0.001), insulin (P=0.04), HOMA-IR (P=0.02), and hs-CRP (P=0.001)between the study and control groups. Furthermore, there was a significant correlation amongthe duration of illicit opioid use and MDA concentrations (r=-0.424, P=0.002), as well as TAClevels (r=0.314, P=0.02).Conclusion: The study results suggested metabolic profiles were impaired in the study group,compared to the controls

The Effects of Quetiapine on Craving and Withdrawal Symptoms in Methamphetamine Abuse: A Randomized, Double-Blind, Placebo-Controlled Trial

Background: Patients with Methamphetamine Abuse (MA) are susceptible to many complications like craving, and withdrawal symptoms. These trials were designed to evaluate the effect of quetiapine administration on craving and withdrawal symptoms in MA abuse.Methods: This trial was conducted on 60 people with MA abuse to receive either 100 mg quetiapine (n=30), or placebo (n=30) every day for 2 months. The Desire for Drug Questionnaire (DDQ) and Amphetamine Withdrawal Questionnaire (AWQ) scores were evaluated at baseline and after 2 months’ intervention. For data analysis, t test, and the Chi-square test were applied in SPSS v. 18.Results: Quetiapine significantly decreased DDQ (P=0.002) and AWQ symptoms (P=0.001) compared to the placebo. Furthermore, there was a significant difference among groups in terms of the frequency of negative urine tests (P<0.001).Conclusion: This trial showed that administration of quetiapine supplements for 2 months in individuals with MA abuse had beneficial effects on craving and withdrawal syndrome

INFLUENCE OF MUSIC TYPE LISTENING ON ANAEROBIC PERFORMANCE AND SALIVARY CORTISOL IN MALES ATHLETES

Music has been widely recommended as a technique to enhance the psychophysical state of participants in sport and exercise. However, there is scant scientific evidence to clarify its proposed benefits. Therefore, the aim of this study was to determine the effect of fast and slow rhythm of music on anaerobic performance and salivary cortisol concentration in trained men. Thirty male physical education college students (ages: 25.66±3.89 yr, height: 176.65 ± 7.66 cm, body mass: 78.45±16.20 kg) voluntary participated in this study and divided to three groups: fast music, slow music, and no music(control). All subjects performed the coninghum test following a 20% grate and 14.3km/h speed on the treadmill. For measuring of cortisol, not stimulated samples of saliva collected, 15 minutes befor and immediately 5 and 30 minute after the exercise. No significant differences were found in anaerobic performance among the three groups in pretest indicating homogeneity of the groups. However, salivary cortisol no significant in anaerobic performance 5 and 30 minute after exercise as well. Summarily, Music doed not have a positive effect on performance, this study provided some support for the hypothesis that listening fast and slow music not significantly impacted during supramaximal exercise

Prognostic investigations of B7-H1 and B7-H4 expression levels as independent predictor markers of renal cell carcinoma.

In order to evaluate the correlation of B7-H4 and B7-H1 with renal cell carcinoma (RCC), we analyzed B7-H1 and B7-H4 expressions and their clinical significance by immunohistochemical method. Our result indicated that B7-H4-positive staining was detected in 58.13 % of RCC tissues (25 tissues tumors), and there were 18 tissues of patients without detectable B7-H4. Furthermore, 21 cases (48.83 %) were B7-H1-positive. Positive tumor expressions of B7-H4 and B7-H1 were markedly related to advanced TNM stage (P = 0.001; P = 0.014), high grade (P = 0.001; P = 002), and larger tumor size (P = 0.002; P = 024) in RCC tissues than patients with B7-H4-negative and B7-H1-negative in RCC tissues. The patients with B7-H1 and B7-H4-positive expressions were found to be markedly correlated with the overall survival of the patients (P < 0.05) and tended to have an increased risk of death when compared with negative expression groups. Univariate analysis showed that B7-H4 and B7-H1 expressions, TNM stage, high grade, and tumor size were significantly related to the prognosis of RCC. Furthermore, multivariate analysis showed that B7-H4 and B7-H1 expressions decreased overall survival. The adjusted HR for B7-H1 was 2.83 (95 % CI 1.210-2.971; P = 0.031) and also was 2.918 (95 % CI 1.243-3.102; P = 0.006) for B7-H4 that showed these markers were independent prognostic factors in RCC patients. The expressions of B7-H1 and B7-H4 in RCC patients indicate that these markers may be as a predictor of tumor development and death risk. Further investigations can be helpful to confirm B7-H1 and B7-H4 roles as an independent predictor of clinical RCC outcome

The Relationship Between Vitamin D Levels and the Severity of Anxiety and Depression in Patients Under Methadone Maintenance Treatment

Background: Hypovitaminosis D, low bone mineral density, non-specific musculoskeletal pain, increased risk of fracture, and periodontal disease were reported in most subjects recruited from the Methadone Maintenance Treatment (MMT) program. This study aimed to determine the relationship between vitamin D levels and the severity of anxiety and depression in patients under MMT.Methods: In a cross-sectional study, serum vitamin D levels were measured among 500 patients under MMT from Kashan Province, Iran. Correlation tests were used to assess the association of vitamin D levels with the severity of anxiety and depression in the explored patients.Results: We found that serum vitamin D levels were positively correlated with the scores of the Beck Depression Inventory (BDI) (r=0.107, P=0.017) and the Beck Anxiety Inventory (BAI) (r=0.129, P=0.004). Additionally, there was a negative correlation between serum vitamin D levels, MMT dosage (r=-0.011, P=0.8), and the duration of MMT (r=-0.017, P=0.7).Conclusion: Our findings demonstrated that serum vitamin D levels were independently correlated with the BDI and BAI scores. Further studies are required to confirm our findings

Identifying TBI Physiological States by Clustering Multivariate Clinical Time-Series Data

Determining clinically relevant physiological states from multivariate time series data with missing values is essential for providing appropriate treatment for acute conditions such as Traumatic Brain Injury (TBI), respiratory failure, and heart failure. Utilizing non-temporal clustering or data imputation and aggregation techniques may lead to loss of valuable information and biased analyses. In our study, we apply the SLAC-Time algorithm, an innovative self-supervision-based approach that maintains data integrity by avoiding imputation or aggregation, offering a more useful representation of acute patient states. By using SLAC-Time to cluster data in a large research dataset, we identified three distinct TBI physiological states and their specific feature profiles. We employed various clustering evaluation metrics and incorporated input from a clinical domain expert to validate and interpret the identified physiological states. Further, we discovered how specific clinical events and interventions can influence patient states and state transitions.Comment: 10 pages, 7 figures, 2 table

D-1 Gene Polymorphism in Salivary Gland Tumors

Objectives This study aimed to assess PD-1gene polymorphism in salivary gland tumors in patients referred to Khalili Hospital in Shiraz. Methods This case-control study evaluated 48 patients with salivary gland tumors and 100 age- and sex-matched healthy controls. First, 5cc blood samples were obtained from patients and transferred to vials containing anti-coagulated EDTA. DNA was extracted, and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was performed on the samples. The PD-1 gene genotype was determined using the Fermentas kit. After 24 hours of incubation, all the samples were electrophoresed. The genotypes were reported based on the size of bands, and the chi-square test was applied. To compare the alleles, the Fisher’s Exact test was applied. The Yates correction was used to compare the genotype and genotypic alleles based on the tumor grade. Results The mean age was 44.81±15.69 years in patients and 46.54± 13.86 years in controls. Statistical analysis did not show any significant difference in PD1 gene polymorphism between the two groups (P=0.098). No significant correlation was found between the genotype frequency and lymph node involvement (P=0.06), tumor genotype (P=0.12), side (right or left) (P=0.22), tumor location (P=0.27), and size or invasion of the tumor to the surrounding tissue (P=0.14). PD1.3 genotype frequency did not differ significantly between malignant and benign tumors (P=0.6). Conclusion This study did not reveal any significant difference in genotype frequency of PD1.3 in the patient and control groups; however, further studies are needed with a larger sample size to obtain more accurate results

A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to TBI Phenotyping

Self-supervised learning approaches provide a promising direction for clustering multivariate time-series data. However, real-world time-series data often include missing values, and the existing approaches require imputing missing values before clustering, which may cause extensive computations and noise and result in invalid interpretations. To address these challenges, we present a Self-supervised Learning-based Approach to Clustering multivariate Time-series data with missing values (SLAC-Time). SLAC-Time is a Transformer-based clustering method that uses time-series forecasting as a proxy task for leveraging unlabeled data and learning more robust time-series representations. This method jointly learns the neural network parameters and the cluster assignments of the learned representations. It iteratively clusters the learned representations with the K-means method and then utilizes the subsequent cluster assignments as pseudo-labels to update the model parameters. To evaluate our proposed approach, we applied it to clustering and phenotyping Traumatic Brain Injury (TBI) patients in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study. Our experiments demonstrate that SLAC-Time outperforms the baseline K-means clustering algorithm in terms of silhouette coefficient, Calinski Harabasz index, Dunn index, and Davies Bouldin index. We identified three TBI phenotypes that are distinct from one another in terms of clinically significant variables as well as clinical outcomes, including the Extended Glasgow Outcome Scale (GOSE) score, Intensive Care Unit (ICU) length of stay, and mortality rate. The experiments show that the TBI phenotypes identified by SLAC-Time can be potentially used for developing targeted clinical trials and therapeutic strategies.Comment: Submitted to the Journal of Biomedical Informatic