Machine learning-based evaluation of prognostic factors for mortality and relapse in patients with acute lymphoblastic leukemia: a comparative simulation study.

BACKGROUND: Predicting mortality and relapse in children with acute lymphoblastic leukemia (ALL) is crucial for effective treatment and follow-up management. ALL is a common and deadly childhood cancer that often relapses after remission. In this study, we aimed to apply and evaluate machine learning-based models for predicting mortality and relapse in pediatric ALL patients. METHODS: This retrospective cohort study was conducted on 161 children aged less than 16 years with ALL. Survival status (dead/alive) and patient experience of relapse (yes/no) were considered as the outcome variables. Ten machine learning (ML) algorithms were used to predict mortality and relapse. The performance of the algorithms was evaluated by cross-validation and reported as mean sensitivity, specificity, accuracy and area under the curve (AUC). Finally, prognostic factors were identified based on the best algorithms. RESULTS: The mean accuracy of the ML algorithms for prediction of patient mortality ranged from 64 to 74% and for prediction of relapse, it varied from 64 to 84% on test data sets. The mean AUC of the ML algorithms for mortality and relapse was above 64%. The most important prognostic factors for predicting both mortality and relapse were identified as age at diagnosis, hemoglobin and platelets. In addition, significant prognostic factors for predicting mortality included clinical side effects such as splenomegaly, hepatomegaly and lymphadenopathy. CONCLUSIONS: Our results showed that artificial neural networks and bagging algorithms outperformed other algorithms in predicting mortality, while boosting and random forest algorithms excelled in predicting relapse in ALL patients across all criteria. These results offer significant clinical insights into the prognostic factors for children with ALL, which can inform treatment decisions and improve patient outcomes.

Risk factors for the time to development of retinopathy of prematurity in premature infants in Iran: a machine learning approach.

BACKGROUND: Retinopathy of prematurity (ROP), is a preventable leading cause of blindness in infants and is a condition in which the immature retina experiences abnormal blood vessel growth. The development of ROP is multifactorial; nevertheless, the risk factors are controversial. This study aimed to identify risk factors of time to development of ROP in Iran. METHODS: This historical cohort study utilized data from the hospital records of all newborns referred to the ROP department of Farabi Hospital (from 2017 to 2021) and the NICU records of infants referred from Mahdieh Hospital to Farabi Hospital. Preterm infants with birth weight (BW) ≤ 2000 g or gestational age (GA) < 34 wk, as well as selected infants with an unstable clinical course, as determined by their pediatricians or neonatologists, with BW > 2000 g or GA ≥ 34 wk. The outcome variable was the time to development of ROP (in weeks). Random survival forest was used to analyze the data. RESULTS: A total of 338 cases, including 676 eyes, were evaluated. The mean GA and BW of the study group were 31.59 ± 2.39 weeks and 1656.72 ± 453.80 g, respectively. According to the criteria of minimal depth and variable importance, the most significant predictors of the time to development of ROP were duration of ventilation, GA, duration of oxygen supplementation, bilirubin levels, duration of antibiotic administration, duration of Total Parenteral Nutrition (TPN), mother age, birth order, number of surfactant administration, and on time screening. The concordance index for predicting survival of the fitted model was 0.878. CONCLUSION: Our findings indicated that the duration of ventilation, GA, duration of oxygen supplementation, bilirubin levels, duration of antibiotic administration, duration of TPN, mother age, birth order, number of surfactant administrations, and on time screening are potential risk factors of prognosis of ROP. The associations between identified risk factors were mostly nonlinear. Therefore, it is recommended to consider the nature of these relationships in managing treatment and designing early interventions.

Unraveling the interplay between mental workload, occupational fatigue, physiological responses and cognitive performance in office workers.

Recently, cognitive demands in workplaces have surged significantly. This study explored the intricate relationship among mental workload (MWL), occupational fatigue, physiological responses, and cognitive performance in office workers by using collective semi-parametric models. One hundred office workers were selected from twenty offices involved in cognitive performance. MWL was assessed through the NASA Task Load Index (NASA-TLX), and occupational fatigue was measured using the Persian version of the Swedish Occupational Fatigue Inventory. Physiological responses, including respiratory rate, the electrical conductivity of the skin (ECS), Heart Rate (HR), and other heart-related parameters, were recorded from the participants during a work shift. Selective and Divided Attention tests were chosen to evaluate workers' cognitive function based on cognitive task analysis. The mean of MWL and occupational fatigue scores were 66.28 ± 11.76 and 1.62 ± 1.07, respectively. There was a significant moderate correlation between two dimensions, mental demand (0.429) and frustration (0.409), with functional fatigue. Also, Significant and, of course, nonlinear relationships were observed between MWL and HR (R2 = 0.44, P-value < 0.001) and ECS (R2 = 0.45, P-value < 0.001) and reaction time in selected (R2 = 0.34, P-value < 0.001) and divided test (R2 = 0.48, P-value < 0.001). Similarly, nonlinear relationships were observed between physiological responses and cognitive performance with fatigue among participants who had experienced higher levels of occupational fatigue. The MWL and fatigue seem to have a significant and non-linear effect on physiological parameters such as HR and ECS and cognitive parameters such as reaction time. Moreover, MWL can influence the dimension of functional fatigue of workers.

Identification of Risk Factors for Relapse in Childhood Leukemia Using Penalized Semi-parametric Mixture Cure Competing Risks Model.

BACKGROUND: Leukemia is the most common childhood malignancy. Identifying prognostic factors of patient survival and relapse using more reliable statistical models instead of traditional variable selection methods such as stepwise regression is of great importance. The present study aimed to apply a penalized semi-parametric mixture cure model to identify the prognostic factors affecting short-term and long-term survival of childhood leukemia in the presence of competing risks. The outcome of interest in this study was time to relapse. Study Design: A retrospective cohort study. METHODS: A total of 178 patients (0‒15 years old) with leukemia participated in this study (September 1997 to September 2016, followed up to June 2021) at Golestan University of Medical Sciences, Iran. Demographic, clinical, and laboratory data were collected, and then a penalized semi-parametric mixture cure competing risk model with smoothly clipped absolute deviation (SCAD) and least absolute shrinkage and selection operator (LASSO) regularizations was used to analyze the data. RESULTS: Important prognostic factors of relapse patients selected by the SCAD regularization method were platelets (150000‒400000 vs.>400000; odds ratio=0.31) in the cure part and type of leukemia (ALL vs. AML, hazard ratio (HR)=0.08), mediastinal tumor (yes vs. no, HR=16.28), splenomegaly (yes vs. no; HR=2.94), in the latency part. In addition, significant prognostic factors of death identified by the SCAD regularization method included white blood cells (<4000 vs.>11000, HR=0.25) and rheumatoid arthritis signs (yes vs. no, HR=5.75) in the latency part. CONCLUSION: Several laboratory factors and clinical side effects were associated with relapse and death, which can be beneficial in treating the disease and predicting relapse and death time.

Eye movements desensitization and reprocessing with finger movements and Elite mobile health software on guilt feeling of parents of children with autism: A randomized trial.

WHAT IS KNOWN ON THE SUBJECT?: Taking care of an autistic child at home can be tough for parents. They struggle to balance caring for their child and other tasks. This can affect their emotional well-being and cause guilt and other psychological problems. WHAT DOES THE PAPER ADD TO EXISTING KNOWLEDGE?: Eye movement desensitization and reprocessing with finger movements can reduce guilt in parents of autistic children. Eye movement desensitization and reprocessing with Elite mobile health software movements can reduce guilt in parents of autistic children. The bilateral eye stimulation method using finger movements has a more sustained impact than the Elite app's bilateral stimulation method. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Healthcare providers are encouraged to learn Eye Movements Desensitization and Reprocessing. Healthcare providers are encouraged to use these methods to help with psychological issues in children with autism. Psychiatric nurses are encouraged to utilize this treatment approach for parents of children with autism, as well as to help alleviate feelings of guilt more broadly. ABSTRACT: INTRODUCTION: Caring for an autistic child at home can be challenging for parents, as it can make it difficult to balance their responsibilities. This imbalance can negatively affect the emotional well-being of the caregiver and lead to feelings of guilt. While this is a known issue, there may be gaps in knowledge specific to Iran. In this study, a new method was introduced to address this issue. AIM: This study aimed to examine the impact of desensitization with eye movements and reprocessing (EMDR) on reducing parental guilt among autistic children's families. We aim to examine the effectiveness of two different treatment methods. METHODS: This study involved 90 parents (60 mothers, 30 fathers) of autistic children randomly assigned to either an experimental or control group. The two experimental groups received a 45-min intervention session once a week for 3 weeks, while the control group did not receive any intervention. Data on feelings of guilt was collected using a questionnaire. After 30 days, both groups took a follow-up test. The data were analysed using statistical software. RESULTS: This study found that there were significant differences in guilt feelings among different groups of EMDR therapy and a control group. Specifically, no significant differences were observed in the mean guilt scores between the experimental and control groups at the pre-intervention stage (p > .05). However, the experimental groups exhibited significantly lower mean guilt scores immediately after the intervention and 1 month later than the control group (p < .05). Immediately after the intervention and 1 month later, no significant differences were observed between the two experimental groups (p > .05). CONCLUSIONS: The findings of this study demonstrate the efficacy of desensitization treatment using eye movements and reprocessing in reducing feelings of guilt among autistic children's parents. In the follow-up phase, it seems that the two-way stimulation method with finger movements is more effective than Elite software in terms of the continuity of the effect. Healthcare providers are encouraged to learn and use these methods to help prevent and treat psychological issues in autistic children.

Comparison of the effect of licorice and chlorhexidine mouthwash on the oral health of intubated patients in the intensive care unit.

BACKGROUND: Chlorhexidine mouthwash is a common oral hygiene product used in intensive care units, but it may have some adverse effects. Licorice, a natural herb, could be a potential alternative to chlorhexidine. However, the effect of licorice mouthwash on the oral health of intubated patients has not been studied yet. Therefore, this study aimed to compare the effects of licorice and chlorhexidine mouthwash on the oral health of intubated patients. METHODS: This was a triple-blind clinical trial. The sample included 130 intubated patients admitted to an intensive care unit in Iran. The samples were selected by convenience sampling and randomly assigned to two groups: A and B. In group A, the main researcher applied 15 ml of 0.2% chlorhexidine mouthwash after each brushing (twice a day for 5.5 days) and suctioned it after 30 s. In group B, 20% licorice mouthwash was used instead of chlorhexidine. The demographic information questionnaire and the Beck Oral Assessment Scale (BOAS) were completed by one of the nurses before and on the sixth day of the study. RESULTS: Finally, 60 patients in each group completed the study. There was no significant difference between the groups in terms of demographic variables or oral health before the intervention (P > 0.05). The oral health of patients in both the chlorhexidine and liquorice mouthwash groups improved significantly after the intervention (P < 0.05). However, there was no significant difference in oral health between the two groups at postintervention (P = 0.06). CONCLUSION: The results demonstrated that both mouthwashes exerted a comparable effect on dental and oral health. However, the chlorhexidine mouthwash showed a greater impact on the reduction of dental plaque and the thinning of saliva compared to licorice mouthwash. In essential cases, licorice mouthwash can be employed as an alternative to chlorhexidine.

In-depth analysis to develop a social marketing model to promote women's participation in waste segregation behaviour: A qualitative study.

Waste separation is one of the key factors in managing solid waste and creating a healthy environment. Waste separation at source has always been associated with challenges. Therefore, this study was conducted to determine the perceptions of housewives and related parties regarding the factors that influence waste separation behaviour and to identify approaches to improve behaviour based on the social marketing framework. This study was conducted as a qualitative content analysis in Amol City in 2022. The data was collected through semi-structured individual interviews. A total of 25 housewives were selected as main participants and 5 stakeholders through purposive selection. The results of the study included lack of awareness of recyclable materials (product), personal, family and environmental barriers (price), lack of doorstep collection of dry waste (place), and lack of use of appropriate technology (promotion). The lack of financial resources, inappropriate political measures and the coronavirus pandemic were also the causes of this challenge. Most participants cited environmental and educational deficits as the main reason for not separating waste. It is possible to improve waste sorting behaviour at source through appropriate behavioural interventions at the individual, social and environmental levels. Researchers can use the results of this study to design, implement and evaluate waste segregation intervention programmes for housewives.

Evaluation of the Correlation Between the Structural Parameters of Trabecular Bone in CBCT and the Primary Stability of Dental Implants.

PURPOSE: To investigate the relationship between the structural parameters of trabecular bone obtained from CBCT imaging and the primary stability of dental implants. MATERIALS AND METHODS: Sixty patients underwent implant placement followed by primary stability evaluation via measurement of the insertion torque (IT) and the implant stability quotient (ISQ). Gray values (GV) and the fractal dimension (FD) were also measured using pretreatment CBCT images. RESULTS: FD values showed a positive and significant relationship with ISQ and IT values (P = .017 and P = .004, respectively). Additionally, there was a positive and significant correlation between GV and IT (P = .004) as well as between GV and ISQ (P = .010). FD and GV showed a considerable difference between the maxillary and mandibular jaws and were higher in the mandible. Only FD was significantly different between men and women and was higher in men. In the two age groups (older and younger than 45 years), only GV was considerably higher in people older than 45 (P < .05). CONCLUSIONS: Both fractal dimension and gray values obtained from CBCT are efficient methods for predicting the primary stability of the implant due to their relationship with ISQ and IT values.

The Effect of Melatonin on Increasing the Health Related Quality of Life in Non-Metastatic Breast Cancer Patients: Three-Year Follow up a Clinical Trial.

INTRODUCTION: Although breast cancer is common worldwide, if diagnosed early and treated on time, the probability of recovery is high and patients often experience a long life. Reducing the quality of life is a common side effect in patients. Melatonin may have an important role in fatigue, sleep disorders and, as a result, the health-related quality of life (HRQoL) in people. About 184 patients with breast cancer were enrolled in 2 groups: intervention with daily melatonin intake of 18 mg for 3 years (93 patients) and the control group with placebo intake (91 patients). Health-related quality of life and the effect of melatonin on increasing that were evaluated with the EORTC QLQ-C30 questionnaire, third edition at the beginning, 2 months later and 3 years after the beginning of the study. RESULTS: The general score of the HRQoL was significantly different both in the passage of time and in the comparative study of the 2 groups, and it was better in the melatonin group (P < .05). CONCLUSION: Long-term use of 18 mg of melatonin for 3 years in patients with non-metastatic breast cancer can lead to an increase in the patients' quality of life.

Relationship between workplace spirituality with organization-based self-esteem and workplace deviant behaviors among Iranian nurses.

BACKGROUND: Despite the numerous studies conducted on workplace spirituality, there is still lack of studies that have explored the relationship between workplace spirituality with organization-based self-esteem and workplace deviant behaviors. This study aims to examine the relationship between workplace spirituality with organization-based self-esteem and workplace deviant behaviors among Iranian nurses. METHODS: 236 nurses from 5 hospitals participated in this descriptive, analytical, and cross-sectional study from August to December 2022. Data was gathered by four questionnaires: demographic information, workplace spirituality, organization-based self-steam, and workplace deviant behaviors. The data were analyzed by SPSS 26 based on descriptive and inferential statistics (Independent Two-sample t Test, Pearson correlation coefficient and multiple regression). RESULTS: Based on the findings, nurses had a moderate level of perception of workplace spirituality and organization-based self-esteem while having a low level of perception regarding the occurrence of workplace deviate behaviors. Results of Pearson correlation coefficient test showed a positive and statistically significant relationship between workplace spirituality and organization-based self-esteem. Additionally, there was an inverse and significant relationship between workplace spirituality and organization-based self-esteem with workplace deviant behaviors. Results of multiple regression analyses indicate that by controlling the demographic characteristics of nurses, the meaningful work and sense of community have a significant relationship with organization-based self-esteem. Furthermore, by controlling the demographic characteristics of nurses, permanent employment status, sense of community, alignment with the organization's values, and organization-based self-esteem have a significant relationship with workplace deviant behavior. CONCLUSIONS: The study suggests that organizations must prioritize promoting workplace spirituality and organization-based self-esteem to ensure a healthy work environment and prevent workplace deviant behaviors.

Modeling heart rate of individual and team manual handling with one hand using generalized additive mixed models.

OBJECTIVES: Despite the fact that team manual handling is common in different working environments, the previous studies in this regard, particularly those with a physiological approach are quite limited. The present study is an attempt to model the heart rate (HR) of individual and team manual handling with one hand. METHODS: Twenty-five young men (aged 21.24±1.42 year) volunteered for this study. The experiments included individual and two-person handling of the load with three different weights with and without height difference. The participants' HR was registered at the end of the route by a chest-strap pulse monitor and a polar watch according to the manufacturer's recommendation. A multivariate Generalized Additive Mixed Model (MGAMM) was used for modeling heart rate based on explanatory variables of workload, carry method, HRrest, body weight, height, knee height, shoulder height, elbow height, and hand height. The significance level of the tests was considered as <0.05. RESULTS: Based on the MGAMM, the average HR (bpm) of participants increased as the workload increased (P<0.001). Handling the load with a taller person increased the HR compared to shorter partner (P<0.001). Moreover, the nonlinear associations of the resting HR (P<0.001), body weight (P<0.001), height (P<0.001), and the height of elbow, hand and knee (P<0.001) were statistically significant. The adjusted R2 of the model was 0.89 indicating that about 90 percent of the variations observed in HR could be explained by the variables in the model. This was greater than the model considering only linear effects (R2 =0.60). CONCLUSION: The model obtained in this study can predict the heart rate of individual and team one-handed handling with high validity. The MGAMM can be used in modeling heart rate in manual handling.

Effects of wearing medical gowns at different temperatures on the physiological responses of female healthcare workers during the COVID-19 pandemic.

BACKGROUND: Using medical gowns with high protection against COVID-19 among healthcare workers (HCWs) may limit heat exchange, resulting in physiological challenges. OBJECTIVE: This study aimed to compare the physiological and neurophysiological responses of female HCWs when using two typical medical gowns at different temperatures during the COVID-19 pandemic. METHODS: Twenty healthy female HCWs participated in this study. Participants wore two types of medical gowns: Spunbond gown (SG) and laminate gown (LG). They walked on a treadmill in a controlled climate chamber for 30 minutes at three different temperatures (24, 28, and 32°C). Heart rate (HR), skin surface temperature (ST), clothing surface temperature (CT), ear temperature (ET), blood oxygen percentage (SaO2), galvanic skin response (GSR), and blood pressure were measured before and after walking on a treadmill. The study's results were analyzed using SPSS26. RESULTS: The study found that LG led to an average increase of 0.575°C in CT compared to SG at the same temperatures (P < 0.03). The average HR increased by 6.5 bpm in LG at 28°C compared to SG at a comfortable temperature (P = 0.01). The average ET in SG and GSR in LG at 32°C increased by 0.39°C and 0.25µS, respectively, compared to the comfortable temperature (P < 0.02). CONCLUSION: The study recommends maintaining a comfortable temperature range in hospitals to prevent physiological challenges among HCWs wearing medical gowns with high protection against COVID-19. This is important because using LG, compared to SG, at high temperatures can increase HR, ET, CT, and GSR.

Spatial inequalities and non-linear association of continuous variables with mortality risk of liver transplantation in Iran: a retrospective cohort study.

Liver transplantation is the second most common solid organ transplant and the best option for liver failure. Of course, patient survival after transplantation depends on many risk factors. The aim of this study was to investigate the spatial and non-linear effects of continuous risk factors on patient survival after liver transplantation. This retrospective cohort study (n = 3148) used data on liver transplantation in Iran (2004-2019). A generalized additive model with spatial effects and non-linear effects of age and Model for End-Stage Liver Disease (MELD) score variables by penalized spline was used. The majority of patients were male (63.3%), with a mean (SD) age of 42.65 (13.31) and a mean (SD) MELD score of 24.43 (6.72). The 1, 5, and 10-year survival rates were 88.2%, 84.6%, and 82.5% respectively. The non-linear effect showed a steeper slope of the age effect on the hazard of death after the age of 50 (p < 0.05), and the MELD score had a direct but non-linear relationship with the hazard of death (p < 0.05). In the spatial pattern, the provinces with a greater distance from the transplant center had significantly fewer old patients than other provinces. Also, more distant provinces with an older transplant age had higher post-transplant mortality rates. Our study showed that it is better to take age and MELD score into account in postoperative care. The spatial pattern of mortality risk reflects inequalities in access to transplantation and public health services after transplantation.

Using machine learning approach for screening metastatic biomarkers in colorectal cancer and predictive modeling with experimental validation.

Colorectal cancer (CRC) liver metastasis accounts for the majority of fatalities associated with CRC. Early detection of metastasis is crucial for improving patient outcomes but can be delayed due to a lack of symptoms. In this research, we aimed to investigate CRC metastasis-related biomarkers by employing a machine learning (ML) approach and experimental validation. The gene expression profile of CRC patients with liver metastasis was obtained using the GSE41568 dataset, and the differentially expressed genes between primary and metastatic samples were screened. Subsequently, we carried out feature selection to identify the most relevant DEGs using LASSO and Penalized-SVM methods. DEGs commonly selected by these methods were selected for further analysis. Finally, the experimental validation was done through qRT-PCR. 11 genes were commonly selected by LASSO and P-SVM algorithms, among which seven had prognostic value in colorectal cancer. It was found that the expression of the MMP3 gene decreases in stage IV of colorectal cancer compared to other stages (P value < 0.01). Also, the expression level of the WNT11 gene was observed to increase significantly in this stage (P value < 0.001). It was also found that the expression of WNT5a, TNFSF11, and MMP3 is significantly lower, and the expression level of WNT11 is significantly higher in liver metastasis samples compared to primary tumors. In summary, this study has identified a set of potential biomarkers for CRC metastasis using ML algorithms. The findings of this research may provide new insights into identifying biomarkers for CRC metastasis and may potentially lay the groundwork for innovative therapeutic strategies for treatment of this disease.

Self-Management and Its Predictors in adult Patients with Epilepsy: A Cross-Sectional Study.

Background: Appropriate self-management (SM) is crucial in controlling epilepsy and improving self-efficacy, medication adherence and avoidance of seizure triggers in patients with epilepsy (PWE. The aim of this study was to evaluate SM and its predictors among adult PWE in Iran. Methods: This cross-sectional study was conducted in 2021. The participants were 335 adult PWEs that were selected from healthcare settings in Hamadan, Iran. Epilepsy Self-Management Scale (ESMS) was used to measure patients' self-management behaviors. Data were analyzed using the independent samples t-test, Pearson's and Spearman's correlation analyses and multiple linear regression analysis. Results: The mean score of SM was 114.37±11, indicating moderate level of SM, and the mean scores of SM in the medication management, seizure management, and safety management subscales were significantly more than the mean scores of the other subscales (P < 0.05). Age, place of residence, marital status, seizure type, seizure frequency, and epilepsy duration significantly predicted 53% of the variance of SM (adjusted R square = 0.532). Conclusion: PWEs have moderate SM and need SM-related education, particularly about lifestyle management and information management. Predictors of SM should be considered to boost SM practice.

Psoriasis Associated Hub Genes Revealed by Weighted Gene Co-Expression Network Analysis.

OBJECTIVE: Psoriasis, an immune-mediated disorder, is a multifactorial disease with unidentified cause(s). This study aimed to discover possible biomarkers of this papulosquamous skin disease. MATERIALS AND METHODS: The gene chip GSE55201, resulted from an experimental study, including 44 Psoriasis patients and 30 healthy controls was downloaded from GEO and weighted gene co-expression network analysis was utilized to identify hub genes. Key modules were determined using the module eigenvalues. We used biological functions (BFs), cellular components, and molecular functions in the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis in the gene metabolic pathway were used for enrichment analysis. RESULTS: Adjacency matrix was built by using power adjacency function and the power to turn the correlation to adjacency matrix was four with a topology fit index of 0.92. Using the weighted gene co-expression network analysis, 11 modules were identified. The green-yellow module eigenvalues were significantly associated with Psoriasis (Pearson correlation=0.53, P<0.001). Candidate hub genes were determined by their higher connectivity and relationship with module eigenvalue. The genes including SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 were recorded as the hub genes. CONCLUSION: We can conclude that SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 have an important role in the immune response regulation and they could be considered as a potential diagnostic biomarker and therapeutic target for Psoriasis.

A deep learning-based framework for predicting survival-associated groups in colon cancer by integrating multi-omics and clinical data.

Precise prognostic classification of patients and identifying survival subgroups and their associated genes can be important clinical references when designing treatment strategies for cancer patients. Multi-omics and data integration techniques are powerful tools to achieve this goal. This study aimed to introduce a machine learning method to integrate three types of biological data, and investigate the performance of two other methods, in identifying the survival dependency of patients. The data included TCGA RNA-seq gene expression, DNA methylation, and clinical data from 368 patients with colon cancer also we use an independent external validation data set, containing 232 samples. Three methods including, hyper-parameter optimized autoencoders (HPOAE), normal autoencoder, and penalized principal component analysis (PPCA) were used for simultaneous data integration and estimation under a COX hazards model. The HPOAE was thought to outperform other methods. The HPOAE had the Log Rank Mantel-Cox value of 14.27 ± 2, and a Breslow-Generalized Wilcoxon value of 13.13 ± 1. Ten miRNA, 11 methylated genes, and 28 mRNA all by (importance of marginal cutoff > 0.95) were identified. The study demonstrated that hsa-miR-485-5p targets both ZMYM1 and tp53, the latter of which has been previously associated with cancer in numerous studies. Furthermore, compared to other methods, the HPOAE exhibited a greater capacity for identifying survival subgroups and the genes associated with them in patients with colon cancer. However, all of the results were obtained by computational methods, and clinical and experimental studies are needed to validate these results.

A Randomized, Controlled, Parallel-Group, Trial on the Long-term Effects of Melatonin on Fatigue Associated With Breast Cancer and Its Adjuvant Treatments.

OBJECTIVE: Cancer related fatigue is a distressing condition and correlated with decrease in quality of life of patients with malignant conditions. In continuation of our previous research, we assessed long term anti-fatigue effects of melatonin in patients with the breast cancer. MATERIAL AND METHODS: In this clinical trial, 92 breast cancer patients were randomly assigned to receive either melatonin (18 mg/day) or placebo from 1 week before the adjuvant treatments until 2 years after their completion. The levels of fatigue were assessed before and after intervention using Brief Fatigue Inventory (BFI) and were compared at a significance level of P ≤ .05. RESULTS: The BFI scores were similar between the 2 groups at the baseline (placebo group: 5.56 ± 1.59 and melatonin group: 5.72 ± 1.68, P = .67). After the intervention, not only the mean fatigue score was significantly lower in melatonin group (2.93 ± 1.04 vs 1.99 ± 1.02, P < .001, P ≤ .05), but also a greater reduction in fatigue score in intervention group was evident over time (P ≤ .001). CONCLUSION: Long-term usage of melatonin even after completion of adjuvant therapies in women with breast cancer decreased the levels of fatigue associated with the malignant condition and its treatments. THE TRIAL REGISTRY NAME AND URL, AND REGISTRATION NUMBER: Iranian Registry of Clinical Trials, https://en.irct.ir/trial/62267, IRCT20180426039421N3.

Treatment adherence and associated factors in older people with type 2 diabetes: A qualitative study.

PATIENT CONTRIBUTION: Older people with T2D participated in this study to achieve the objective of the study. AIM: Treatment adherence is an important indicator for evaluating successful diabetes control and overall disease management. It is necessary to identify the hidden themes of the concept of treatment adherence and related factors based on the experiences of older people with T2D. Therefore, the present study was conducted to identify the concept of treatment adherence and its associated factors in older people with type 2 diabetes (T2D). DESIGN: The study was conducted as a qualitative study using a content analysis approach. METHODS: Semi-structured interviews were conducted with 20 older people with T2D, between May and September 2021. Data were organized using MAXQDA-10 software and analysed using the Elo and Kyngas qualitative content analysis method. We followed the COREQ Checklist to ensure rigour in our study. RESULTS: Three themes emerged from the analysis of the data, including: 'Health literacy', 'Support umbrella' and 'responsibility'.

Relationship between moral sensitivity of nurses and quality of nursing care for patients with COVID-19.

AIM: This study aimed to: (1) assess the level of moral sensitivity of nurses and the quality of nursing care for patients with COVID-19 in Iran; and (2) identify the relationship between the moral sensitivity of nurses and the quality of nursing care for patients with COVID-19 in Iran. DESIGN: This study was designed as a descriptive, cross-sectional, and correlational research. METHOD: A total of 211 nurses working in four hospitals affiliated with the Hamadan University of Medical Sciences in Iran from December 2021 to April 2022 were selected via the stratified proportional random sampling method. Demographic information, a moral sensitivity questionnaire, and the Good Nursing Care Scale were used for data collection. The data were analysed by SPSS 24 based on descriptive and inferential statistics (Pearson correlation coefficient and multiple regression). RESULTS: Results revealed that 188 of the nurses (89.1%) had a moderate level of moral sensitivity. Furthermore, 160 of the participants (75.8%) reported a relatively low level of the quality of nursing care. The results of the Pearson correlation coefficient test indicated that there was an inverse and significant relationship between the moral sensitivity of nurses and the quality of nursing care (r = -0.528, p < 0.001). The results of multiple regression indicated that the model of moral sensitivity components explained 27.9% of the variance in the quality of nursing care. The components of moral sensitivity, including relation (ß = -0.246, p < 0.001), meaning (ß = -0.188, p = 0.003), conflict (ß = -0.170, p = 0.008), benevolence (ß = -0.153, p = 0.012), and rules (ß = -0.144, p = 0.019) had inverse and significant effects on the quality of nursing care. CONCLUSION: Since higher mean scores of moral sensitivity reflect lower moral sensitivity, it can be stated that with the increase in moral sensitivity of nurses, the quality of nursing care for patients with COVID-19 grows.