Comparison of Cytotoxic and Antibacterial Effects of Elettaria cardamomum Extract and Essential Oil

Objectives This study aimed to investigate the cytotoxic and antibacterial properties of essential oils and hydroalcoholic extracts from Elettaria cardamomum fruit (E. cardamomum). Methods Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans) was used as the test subject for the agar diffusion test in this in-vitro investigation to determine the antibacterial effect of the extract and essential oil. The broth microdilution method was used to calculate their minimum bactericidal concentration (MBC) and minimum inhibitory concentration (MIC). The methyl thiazolyl tetrazolium (MTT) assay was used to assess their cytotoxicity against human gingival fibroblasts. Tukey's test (alpha=0.05) and ANOVA were used to evaluate the data. Results The E. cardamomum hydroalcoholic extracts and essential oil demonstrated strong antibacterial activity on A. actinomycetemcomitans. E. cardamomum essential oil (91.5±1.1 mm) and E. cardamomum extract (9.5±0.4 mm) had the highest and lowest growth inhibition zones, respectively. For E. cardamomum essential oil, the MIC and MBC were 1.45%, and for E. cardamomum extract, they were 11.5% (v/v). The essential oil exhibited appreciable cytotoxicity at low doses, while the extract did not. Conclusion Because of its antibacterial properties and low cytotoxicity at low concentrations, the hydroalcoholic extract of E. cardamomum, one of the compounds examined, may have applications as an organic mouthwash

Perceived social support, perceived stress, and quality of sleep among COVID-19 patients in Iran: assessing measurement invariance of the multidimensional scale of perceived social support across gender and age

BackgroundPerceived social support (PSS) plays a considerable role in mental health. The Multidimensional Scale of Perceived Social Support (MSPSS) is one of the most widely used scales, leading to much research evidence. The present study investigated its measurement model, equivalence across gender (male and female) and age groups (older patients= above 60 and non-older patients= below 60), and concurrent validity.MethodsA cross-sectional survey was conducted between March and October 2020, on patients hospitalized due to COVID-19 in Tehran, Iran. The scales were administered to 328 COVID-19 patients (54.6% male, aged 21 to 92) from two general hospitals; participants completed MSPSS (including friends, family, and significant others subscales), Pittsburgh Sleep Quality Index (PSQI, include sleep latency, subjective sleep quality, habitual sleep efficiency, sleep duration, use of sleep medication, daytime dysfunction, and sleep disturbances subscales), and the Perceived Stress Scale-10 (PSS-10, to assess patients’ appraisal of stressful conditions).ResultsThe MSPSS three-factor structure was confirmed among COVID-19 patients by Confirmatory Factor Analysis (CFA). The results support the MSPSS internal consistency and configural, metric, and scalar invariance across gender and age groups. Nevertheless, small but significant differences were found across ages based on the latent factor mean of the MSPSS from friends, with a lower mean level in older patients. The coefficients of Cronbach’s alpha (ranging from.92 to.96), the ordinal theta (ranging from.95 to.98), and Omega (ranging from.93 to.97) suggested high internal consistency of MSPSS. The concurrent validity of MSPSS was evidenced by its significant negative correlation with PSS-10 (τb = -.13, p <.01) and also subjective sleep quality (τb = -.22, p <.01), sleep disturbances (τb = -.26, p <.001), and daytime dysfunction (τb = -.26, p <.001).ConclusionsThe MSPSS was valid and reliable for measuring individuals’ perception of social support between males and females and older and non-older COVID-19 patients

The Effect of Aqueous Extract of Cinnamon on the Metabolome of Plasmodium falciparum

Malaria is responsible for estimated 584,000 deaths in 2013. Researchers are working on new drugs and medicinal herbs due to drug resistance that is a major problem facing them; the search is on for new medicinal herbs. Cinnamon is the bark of a tree with reported antiparasitic effects. Metabonomics is the simultaneous study of all the metabolites in biological fluids, cells, and tissues detected by high throughput technology. It was decided to determine the mechanism of the effect of aqueous extract of cinnamon on the metabolome of Plasmodium falciparum in vitro using 1HNMR spectroscopy. Prepared aqueous extract of cinnamon was added to a culture of Plasmodium falciparum 3D7 and its 50% inhibitory concentration determined, and, after collection, their metabolites were extracted and 1HNMR spectroscopy by NOESY method was done. The spectra were analyzed by chemometric methods. The differentiating metabolites were identified using Human Metabolome Database and the metabolic cycles identified by Metaboanalyst. 50% inhibitory concentration of cinnamon on Plasmodium falciparum was 1.25 mg/mL with p<0.001. The metabolites were identified as succinic acid, glutathione, L-aspartic acid, beta-alanine, and 2-methylbutyryl glycine. The main metabolic cycles detected were alanine and aspartame and glutamate pathway and pantothenate and coenzyme A biosynthesis and lysine biosynthesis and glutathione metabolism, which are all important as drug targets

Drift Diffusion Model of Animacy Categorization Task Can Detect Patients with Mild Cognitive Impairment and Mild Alzheimer's Disease

Purpose: The process of neurodegeneration in Alzheimer's Disease (AD) is irreversible using current therapeutics. An earlier diagnosis of the disease can lead to earlier interventions, which will help patients sustain their cognitive abilities for longer. Individuals within the early stages of AD, shown to have trouble making confident and sounds decisions. Here we proposed a computational approach to quantify the decision-making ability in patients with mild cognitive impairment and mild AD. Materials and Methods: To study the quantified decision-making abilities at the early stages of the disease, we took advantage of a 2-Alternative Forced-Choice (2AFC) task. We applied the Drift Diffusion Model to determine whether the information accumulation process in a categorization task is altered in patients with mild cognitive impairment and mild AD. We implemented a classification model to detect cognitive impairment based on the Drift Diffusion Model's estimated parameters. Results: The results show a significant correlation of the classification score with the standard pen-and-paper tests, suggesting that the quantified decision-making parameters are undergoing significant change in patients with cognitive impairment. Conclusion: We confirmed that the decision-making ability deteriorates at the early stages of AD. We introduced a computational approach for measuring the decline in decision-making and used that measurement to distinguish patients from healthy individuals

Measurement invariance of the General Health Questionnaire (GHQ-12) across gender and age: Demographic and medical correlates of mental health in patients with COVID-19

Introduction: The present cross sectional study aimed to evaluate the construct and criterion validity, reliability, and gender and age differences of the 12-item General Health Questionnaire (GHQ-12) among hospitalized patients with COVID-19 in 2020. The criterion validity was assessed via its link with perceived stress, sleep quality, daily life activities, and demographic and medical characteristics. Methods: A total of 328 COVID-19 patients (55.8% men; Mage = 50.49, SD = 14.96) completed the GHQ-12, the Perceived Stress Scale (PSS), the Pittsburgh Sleep Quality Index (PSQI), the Activities of Daily Life (ADL)-Katz Scale, and the Lawton Instrumental Activities of Daily Living Scale (IADL). Results: Among 13 factorial models, the three-factor model (successful coping, self-esteem, and stress) was shown to have the best fit. GHQ-12 was positively associated with PSQI, PSS, Hyperlipidemia, psychiatry disorders, hospitalization duration, the change in sleep time, and use of sleeping pills, and negatively correlated with educational level, and the number of family members. The GHQ-12 also had a negative correlation with ADL and IADL in over 60 years of age group. Females scored higher on total GHQ-12 scores, compared to males. Finally, the hospitalization duration was longer for patients over 60 (mean = 8.8 days, SD = 5.9) than patients under 60 (mean = 6.35 days, SD = 5.87). Discussion: Overall, the findings provided evidence that mental distress in patients with COVID-19 is correlated with high perceived stress, low sleep quality, low ADL and IADL, and a range of demographic features and medical conditions. Designing psychological interventions for these patients that target the aforementioned correlates of mental distress is warranted.publishedVersio

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities

This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, incorporating both electroencephalography (EEG) patterns and cognitive abnormalities for enhanced classification. Data were collected from 45 participants, including 20 with BD II and 25 with BPD. Analysis involved utilizing EEG signals and cognitive tests, specifically the Wisconsin Card Sorting Test and Integrated Cognitive Assessment. The k-nearest neighbors (KNN) algorithm achieved a balanced accuracy of 93%, with EEG features proving to be crucial, while cognitive features had a lesser impact. Despite the strengths, such as diverse model usage, it’s important to note limitations, including a small sample size and reliance on DSM diagnoses. The study suggests that future research should explore multimodal data integration and employ advanced techniques to improve classification accuracy and gain a better understanding of the neurobiological distinctions between BD II and BPD

Measurement invariance of the General Health Questionnaire (GHQ-12) across gender and age: Demographic and medical correlates of mental health in patients with COVID-19

IntroductionThe present cross sectional study aimed to evaluate the construct and criterion validity, reliability, and gender and age differences of the 12-item General Health Questionnaire (GHQ-12) among hospitalized patients with COVID-19 in 2020. The criterion validity was assessed via its link with perceived stress, sleep quality, daily life activities, and demographic and medical characteristics.MethodsA total of 328 COVID-19 patients (55.8% men; Mage = 50.49, SD = 14.96) completed the GHQ-12, the Perceived Stress Scale (PSS), the Pittsburgh Sleep Quality Index (PSQI), the Activities of Daily Life (ADL)-Katz Scale, and the Lawton Instrumental Activities of Daily Living Scale (IADL).ResultsAmong 13 factorial models, the three-factor model (successful coping, self-esteem, and stress) was shown to have the best fit. GHQ-12 was positively associated with PSQI, PSS, Hyperlipidemia, psychiatry disorders, hospitalization duration, the change in sleep time, and use of sleeping pills, and negatively correlated with educational level, and the number of family members. The GHQ-12 also had a negative correlation with ADL and IADL in over 60 years of age group. Females scored higher on total GHQ-12 scores, compared to males. Finally, the hospitalization duration was longer for patients over 60 (mean = 8.8 days, SD = 5.9) than patients under 60 (mean = 6.35 days, SD = 5.87).DiscussionOverall, the findings provided evidence that mental distress in patients with COVID-19 is correlated with high perceived stress, low sleep quality, low ADL and IADL, and a range of demographic features and medical conditions. Designing psychological interventions for these patients that target the aforementioned correlates of mental distress is warranted

Staging of colorectal cancer using serum metabolomics with 1HNMR Spectroscopy

Objective(s): Determination of stages of colon cancer is done by biopsy usually after surgery. Metabolomics is the study of all the metabolites using LC-MS and 1HNMR spectroscopy with chemometric techniques. The stages of colon cancer were detected from patients' sera using 1HNMR. Materials and Methods: Five ml blood was collected from 16 confirmed patients referred for colonoscopy.  One group of eight patients were diagnosed with stage 0 to I colon cancer and the second group of 8 patients with II-IV stage colon cancer.  Sera were sent for 1HNMR. The differentiating metabolites were identified using HMDB  and the metabolic cycles from Metaboanalyst. Results: Six metabolites of which pyridoxine levels lowered, and glycine, cholesterol, taurocholic acid, cholesteryl ester and deoxyinosine increased. Conclusion: The different stages of cancer were identified by the main metabolic cycles such as primary bile acid biosynthesis, purine and vitamin B metabolic pathways and the glutathione cycle

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities

This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, incorporating both electroencephalography (EEG) patterns and cognitive abnormalities for enhanced classification. Data were collected from 45 participants, including 20 with BD II and 25 with BPD. Analysis involved utilizing EEG signals and cognitive tests, specifically the Wisconsin Card Sorting Test and Integrated Cognitive Assessment. The k-nearest neighbors (KNN) algorithm achieved a balanced accuracy of 93%, with EEG features proving to be crucial, while cognitive features had a lesser impact. Despite the strengths, such as diverse model usage, it’s important to note limitations, including a small sample size and reliance on DSM diagnoses. The study suggests that future research should explore multimodal data integration and employ advanced techniques to improve classification accuracy and gain a better understanding of the neurobiological distinctions between BD II and BPD

Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

BACKGROUND: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. METHODS: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. FINDINGS: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. INTERPRETATION: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. FUNDING: The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38)