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Mental disorders are considered as one of the most important concerns among university students, potentially impacting their quality of life and academic performance. Limited data are available regards the association between dietary insulin index (DII) and dietary insulin load (DIL) and mental disorders especially in university students. This study aimed to evaluate the relationship between DII and DIL with depression, anxiety, and stress among students affiliated with Kashan University of Medical Sciences. This cross-sectional study included 330 university students from Kashan University of Medical Sciences in 2023. A validated Depression Anxiety Stress Scales-21 (DASS-21) was applied to assess the mental health of participants. Dietary intakes were obtained using a validated semi-quantitative food frequency questionnaire (FFQ-117). Multivariable analyses were performed to adjust for potential confounding factors. P  < 0.05 was considered as significant. Participants’ mean age and BMI were 21.4 years and 22.8 kg/m 2 , respectively. In this study, after adjusting for a wide range of possible confounding variables, individuals who were in the highest quartile of DIL had 45% significantly lower odds for depression than those in the lowest quartile (95%CI: 0.31, 0.99). However, there was no statistically significant association between DII and depression (95%CI: 0.4, 1.28). No other statistically significant relationship was observed between DII, DIL, and anxiety and stress in university students ( P  < 0.05). In conclusion, DIL may be associated with depression in university students. Higher DIL is associated with higher accessibility for tryptophan in brain cells, which could be related to a better mood. Further studies with a larger sample size and stronger designs, such as cohort studies or clinical trials, are needed to confirm our results.

The Cox proportional hazards model is a widely used statistical method for the censored data that model the hazard rate rather than survival time. To overcome complexity of interpreting hazard ratio, quantile regression was introduced for censored data with more straightforward interpretation. Different methods for analyzing censored data using quantile regression model, have been introduced. The quantile regression approach models the quantile function of failure time and investigates the covariate effects in different quantiles. In this model, the covariate effects can be changed for patients with different risk and is a flexible model for controlling the heterogeneity of covariate effects. We illustrated and compared five methods in quantile regression for right censored data included Portnoy, Wang and Wang, Bottai and Zhang, Yang and De Backer methods. The comparison was made through the use of these methods in modeling the survival time of breast cancer. According to the results of quantile regression models, tumor grade and stage of the disease were identified as significant factors affecting 20th percentile of survival time. In Bottai and Zhang method, 20th percentile of survival time for a case with higher unit of stage decreased about 14 months and 20th percentile of survival time for a case with higher grade decreased about 13 months. The quantile regression models acted the same to determine prognostic factors of breast cancer survival in most of the time. The estimated coefficients of five methods were close to each other for quantiles lower than 0.1 and they were different from quantiles upper than 0.1.

Background Common and complex traits are the consequence of the interaction and regulation of multiple genes simultaneously, therefore characterizing the interconnectivity of genes is essential to unravel the underlying biological networks. However, the focus of many studies is on the differential expression of individual genes or on co-expression analysis. Methods Going beyond analysis of one gene at a time, we systematically integrated transcriptomics, genotypes and Hi-C data to identify interconnectivities among individual genes as a causal network. We utilized different machine learning techniques to extract information from the network and identify differential regulatory pattern between cases and controls. We used data from the Allen Brain Atlas for replication. Results Employing the integrative systems approach on the data from CommonMind Consortium showed that gene transcription is controlled by genetic variants proximal to the gene (cis-regulatory factors), and transcribed distal genes (trans-regulatory factors). We identified differential gene regulatory patterns in SCZ-cases versus controls and novel SCZ-associated genes that may play roles in the disorder since some of them are primary expressed in human brain. In addition, we observed genes known associated with SCZ are not likely (OR = 0.59) to have high impacts (degree > 3) on the network. Conclusions Causal networks could reveal underlying patterns and the role of genes individually and as a group. Establishing principles that govern relationships between genes provides a mechanistic understanding of the dysregulated gene transcription patterns in SCZ and creates more efficient experimental designs for further studies. This information cannot be obtained by studying a single gene at the time.

One of the common concerns of healthcare systems is the potential for re-admission of COVID-19 patients. In addition to adding costs to the healthcare system, re-admissions also endanger patient safety. Recognizing the factors that influence re-admission, can help provide appropriate and optimal health care. The aim of this study was to assess comorbidities that affect re-admission and survival in COVID-19 patients using a joint frailty model. This historical cohort study was done using data of patients with COVID-19 who were re-hospitalized more than twice in a referral hospital in North of Iran. We used the joint frailty model to investigate prognostic factors of survival and recurrence, simultaneously using R version 3.5.1 (library \"frailtypack\"). P-values less than 0.05 were considered as statistically significant. A total of 112 patients with mean (SD) age of 63.76 (14.58) years old were recruited into the study. Forty-eight (42.9%) patients died in which 53.83% of them were re-admitted for a second time. Using adjusted joint model, the hazard of re-admission increased with cancer (Hazard ratio (HR) = 1.92) and hyperlipidemia (HR = 1.22). Furthermore, the hazard of death increased with hyperlipidemia (HR = 4.05) followed by age (HR = 1.76) and cancer (HR = 1.64). It Also decreased with lung disease (HR = 0.11), hypothyroidism (HR = 0.32), and hypertension (HR = 0.97). Considering the correlation between re-admission and mortality in the joint frailty model, malignancy and hyperlipidemia increased the risk of both re-admission and mortality. Moreover, lung disease probably due to the use of corticosteroids, was a protective factor against both mortality and re-admission.

IntroductionPremenstrual syndrome (PMS) includes a range of physical, behavioural and psychological symptoms and decreases women’s health-related quality of life (HRQoL). It has been proposed that increased body mass index (BMI) is associated with menstrual problems and decreased HRQoL. The body fat amount plays a role in menstrual cycles by altering the oestrogen/progesterone ratio. Alternate day fasting as an unusual diet results in the improvement of anthropometric indices and reduction of body weight. This study aims to investigate the effect of a daily calorie restriction diet and a modified alternate day fasting diet on PMS and HRQoL.Methods and analysisThis 8-week open-label parallel randomised controlled trial examines the impact of a modified alternate-day fasting diet and daily caloric restriction on the severity of PMS and HRQoL in obese or overweight women. Using simple random sampling, women between the ages of 18 years and 50 years and 25 ≤ BMI ˂ 40 who meet the inclusion and exclusion criteria will be chosen from the Kashan University of Medical Sciences Centre. Patients will be randomised, based on BMI and age through stratified randomisation. Then by the random numbers table, they are allocated to fasting (intervention) or daily calorie restriction (control) groups. Outcomes are chosen for the trial: the difference in the severity of PMS, HRQoL, BMI, body fat mass, fat-free mass, waist-to-hip ratio, waist circumference, hip circumference, per cent body fat, skeletal muscle mass and visceral fat area from baseline to 8 weeks.Ethics and disseminationThe Kashan University of Medical Sciences Ethics Committee has approved the trial (IR.KAUMS.MEDNT.REC.1401.003) (17 April 2022). Results will be published in peer-reviewed academic journals and the participants will be informed via phone calls.Trial registration numberIRCT20220522054958N1.

Background: The analysis of disease-free survival and related factors leads to a better understanding of the patient’s condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors on disease-free survival in breast cancer with a quantile regression model. Methods: This retrospective study was conducted by reviewing data obtained from 2056 breast cancer patients. Age at diagnosis and education status, tumor size, lymph node ratio, tumor grade, estrogen receptor and progesterone receptor, type of surgery, use of radiotherapy, chemotherapy, and hormone therapy were the prognosis factors considered in this study. A quantile regression model was used to investigate prognostic factors of disease-free survival in breast cancer. Results: Disease recurrence was verified in 251 (13.9%) women, and 39 (0.02%) women died before experience recurrence. The 10th percentile of disease-free survival for patients with the hormone therapy was 23.85 months greater than patients who did not receive this treatment (P value < .001). In the examination of the tumor size, the 10th and 20th percentiles of disease-free survival for patients with tumor size > 5 cm were 31.06 and 27 months less than patients with the tumor size < 2 cm, respectively (P value = .006 and .021, respectively). Compared with grade 1 tumors, the 10th and 20th percentiles of disease-free survival for patients with grade 3 tumors decreased 30.11 and 38.32 months, respectively (P value < .001 and .038, respectively). The 10th and 20th percentiles of disease-free survival decreased 28.16 and 45.32 months with a 1 unit increase in lymph node ratio, respectively (P value = .032 and .032, respectively). Conclusions: Among the prognostic factors, tumor size, grade, and lymph node ratio showed a close relationship with disease-free survival in breast cancer. The findings indicated that developing public screening and educational programs through the health care system with more emphasis on low-educated women is needed among Iranian women.

Background Sleep disturbances are common in nearly one-third of adults. Both low quality of sleep and sleep time could be related to increased obesity. An increase in visceral adipose tissue can result in the secretion of inflammatory cytokines. Inflammatory cytokines can lead to a disturbance of the sleep-wake rhythm. Therefore, weight loss may improve sleep quality and duration. Intermittent fasting diet as a popular diet reduces body weight and improves anthropometric indices. This study is performed to further investigate the effect of a modified intermittent fasting diet on sleep quality and anthropometric indices. Methods This is an open-label randomized controlled trial to evaluate the effect of daily calorie restriction (control) and modified intermittent fasting (intervention) on sleep quality, anthropometric data, and body composition in women with obesity or overweight for 8 weeks. Fifty-six participants will be classified using stratified randomization based on body mass index (BMI) and age. Then, participants will be assigned to one of the two groups of intervention or control using the random numbers table. The sleep quality, daytime sleepiness, and insomnia will be evaluated by using the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), and the Insomnia Severity Index respectively. The primary outcomes chosen for the study were as follows: the difference in sleep quality, daytime sleepiness, insomnia, BMI, fat-free mass (FFM), body fat mass, waist circumference, and waist-to-hip ratio from baseline to 8 weeks. Secondary outcomes chosen for the study were as follows: the difference in hip circumference, the visceral fat area, percent body fat, soft lean mass, skeletal muscle mass, extracellular water ratio, and total body water from baseline to 8 weeks. Discussion This study will investigate the effect of intermittent fasting intervention compared with daily calorie restriction on sleep quality and anthropometric indices. The information gained will enhance our understanding of fasting interventions, which can be used to improve clinical dietary recommendations. The findings will help to disclose as yet the unknown relationship between diet and sleep quality. Trial registration Iranian Registry of Clinical Trials IRCT20220522054958N3. Registered on 8 July 2022. https://www.irct.ir/trial/64510 .

Hematopoietic stem cell transplantation (HSCT) emerged over sixty years ago as a groundbreaking and potentially curative treatment for patients with acute myeloid leukemia (AML) who were not responding to chemotherapy. In this study, we aimed to investigate prognostic factors for survival after allo-HSCT in AML patients. This retrospective cohort study was carried out using data from 742 adult AML patients underwent allo-HSCT. we analysis prognostic factors for survival after allo-HSCT with censored quantile regression model. The 5-year OS, DFS and GRFS rates were 58, 53, and 30%, respectively. OS for recipients older than 35 years was 0.95 and 1.12 years lower than that for recipients under 35 years in the 25th and 40th percentiles, respectively. Compared to patients in their CRІ, those with CRІІІ disease experienced a decrease in OS at the 25th and 40th percentiles by 1.72 and 3.72 years, respectively. Moreover, OS for ABO matched patients was 0.92 and 1.29 years longer than that of patients with an ABO major mismatch. This study could assist oncologists and hematologists in understanding the prognostic factors affecting patient survival across various survival ranges, thereby potentially extending patients’ lifespans.

Hypertension is a common toxicity induced by bevacizumab and other antiangiogenic drugs. There are no biomarkers to predict the risk of bevacizumab-induced hypertension. This study aimed to identify plasma proteins related to the function of the vasculature to predict the risk of severe bevacizumab-induced hypertension. Using pretreated plasma samples from 398 bevacizumab-treated patients in two clinical trials (CALGB 80303 and 90401), the levels of 17 proteins were measured via ELISA. The association between proteins and grade 3 bevacizumab-induced hypertension was performed by calculating the odds ratio (OR) from logistic regression adjusting for age, sex, and clinical trial. Using the optimal cut-point of each protein, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for hypertension were estimated. Five proteins showed no difference in levels between clinical trials and were used for analyses. Lower levels of angiopoietin-2 (p = 0.0013, OR 3.41, 95% CI 1.67–7.55), VEGF-A (p = 0.0008, OR 4.25, 95% CI 1.93–10.72), and VCAM-1 (p = 0.0067, OR 2.68, 95% CI 1.34–5.63) were associated with an increased risk of grade 3 hypertension. The multivariable model suggests independent effects of angiopoietin-2 (p = 0.0111, OR 2.71, 95% CI 1.29–6.10), VEGF-A (p = 0.0051, OR 3.66, 95% CI 1.54–9.73), and VCAM-1 (p = 0.0308, OR 2.27, 95% CI 1.10–4.92). The presence of low levels of 2–3 proteins had an OR of 10.06 (95% CI 3.92–34.18, p = 1.80 × 10–5) for the risk of hypertension, with sensitivity of 89.7%, specificity of 53.5%, PPV of 17.3%, and NPV of 97.9%. This is the first study providing evidence of plasma proteins with potential value to predict patients at risk of developing bevacizumab-induced hypertension.Clinical trial registration: ClinicalTrials.gov Identifier: NCT00088894 (CALGB 80303); and NCT00110214 (CALGB 90401).

Background Many genome-wide association studies have detected genomic regions associated with traits, yet understanding the functional causes of association often remains elusive. Utilizing systems approaches and focusing on intermediate molecular phenotypes might facilitate biologic understanding. Results The availability of exome sequencing of two populations of African-Americans and European-Americans from the Atherosclerosis Risk in Communities study allowed us to investigate the effects of annotated loss-of-function (LoF) mutations on 122 serum metabolites. To assess the findings, we built metabolomic causal networks for each population separately and utilized structural equation modeling. We then validated our findings with a set of independent samples. By use of methods based on concepts of Mendelian randomization of genetic variants, we showed that some of the affected metabolites are risk predictors in the causal pathway of disease. For example, LoF mutations in the gene KIAA1755 were identified to elevate the levels of eicosapentaenoate ( p -value = 5E-14), an essential fatty acid clinically identified to increase essential hypertension. We showed that this gene is in the pathway to triglycerides, where both triglycerides and essential hypertension are risk factors of metabolomic disorder and heart attack. We also identified that the gene CLDN17, harboring loss-of-function mutations, had pleiotropic actions on metabolites from amino acid and lipid pathways. Conclusion Using systems biology approaches for the analysis of metabolomics and genetic data, we integrated several biological processes, which lead to findings that may functionally connect genetic variants with complex diseases.