Interferon-γ Induces Interleukin-6 Production and Alpha-smooth Muscle Actin Expression in Systemic Sclerosis Fibroblasts.

Systemic sclerosis (SSc) is an autoimmune systemic disease that is characterized by immune dysregulation, inflammation, vasculopathy, and fibrosis. Tissue fibrosis plays an important role in SSc and can affect several organs such as the dermis, lungs, and heart. Dysregulation of interferon (IFN) signaling contributes to the SSc pathogenesis and interferon regulatory factor 1 (IRF1) has been indicated as the main regulator of type I IFN. This study aimed to clarify the effect of IFN-gamma (-γ) and dexamethasone (DEX) on the IRF1, extracellular signal-regulated kinase 1/2 (ERK1/2), and the expression of alpha-smooth muscle actin (α-SMA) in myofibroblasts and genes involved in the inflammation and fibrosis processes in early diffuse cutaneous systemic sclerosis (dcSSc). A total of 10 early dcSSc patients (diffuse cutaneous form) and 10 unaffected control dermis biopsies were obtained to determine IFNγ and DEX effects on inflammation and fibrosis. Fibroblasts were treated with IFNγ and DEX at optimum time and dose. The expression level of genes and proteins involved in the fibrosis and inflammation processes have been quantified by quantitative real-time PCR (RT-qPCR) and western blot, respectively. IFNγ could up-regulate some of the inflammation-related genes (Interleukin-6; IL6) and down-regulate some of the fibrosis-related genes (COL1A1) in cultured fibroblasts of patients with early dcSSc compared to the untreated group. Besides, it has been revealed that IFNγ can induce fibroblast differentiation to the myofibroblast that expresses α-SMA. Concerning the inhibitory effect of IFNγ on some fibrotic genes and its positive effect on the inflammatory genes and myofibroblast differentiation, it seems that IFNγ may play a dual role in SSc.

Associations between epigenetic aging and diabetes mellitus in a Swedish longitudinal study.

Diabetes mellitus type 2 (T2D) is associated with accelerated biological aging and the increased risk of onset of other age-related diseases. Epigenetic changes in DNA methylation levels have been found to serve as reliable biomarkers for biological aging. This study explores the relationship between various epigenetic biomarkers of aging and diabetes risk using longitudinal data. Data from the Swedish Adoption/Twin Study of Aging (SATSA) was collected from 1984 to 2014 and included 536 individuals with at least one epigenetic measurement. The following epigenetic biomarkers of aging were employed: DNAm PAI-1, DNAmTL, DunedinPACE, PCHorvath1, PCHorvath2, PCHannum, PCPhenoAge, and PCGrimAge. Firstly, longitudinal analysis of biomarker trajectories was done. Secondly, linear correlations between the biomarkers and time to diabetes were studied within individuals developing diabetes. Thirdly, Cox proportional hazards (PH) models were used to assess the associations between these biomarkers and time of diabetes diagnosis, with adjustments for chronological age, sex, education, smoking, blood glucose, and BMI. The longitudinal trajectories of the biomarkers revealed differences between individuals with and without diabetes. Smoothened average curves for DunedinPACE and DNAm PAI-1 were higher for individuals with diabetes around the age 60-70, compared to controls. Likewise, DunedinPACE and DNAm PAI-1 were higher closer to diabetes onset. However, no significant associations were found between the epigenetic biomarkers of aging and risk of diabetes in Cox PH models. Our findings suggest the potential value of developing epigenetic biomarkers specifically tailored to T2D, should we wish to model and explore the potential for predicting the disease.

COVID-19 Pandemic and Stroke Care in Patients with Dementia Compared to Other Stroke Patients.

OBJECTIVES: The primary objective of this study was to examine the impact of the COVID-19 pandemic on the quality of stroke care for patients with preexisting dementia, compared with patients who had only stroke. The secondary aim was to investigate how the quality of stroke care changed during the pandemic and post-pandemic periods compared with the pre-pandemic period in patients with preexisting dementia. DESIGN: A registry-based, nationwide cohort study in Sweden. SETTING AND PARTICIPANTS: We included patients with a first stroke between 2019 and 2022, both with and without dementia. The study periods were defined as follows: pre-pandemic (January 1, 2019, to February 29, 2020), COVID-19 pandemic (March 1, 2020, to February 24, 2022), and post-COVID-19 pandemic period (February 25, 2022, to September 19, 2022). The outcomes examined were the following quality indicators of stroke care, suggested by the national guideline of stroke care in Sweden: stroke admission site, performance of swallowing assessment, reperfusion treatment, assessment for rehabilitation, and early supported discharge. METHODS: The associations were studied through group comparisons and binary logistic regressions. RESULTS: Of the 21,795 patients with strokes, 1357 had documented preexisting dementia, and 20,438 had stroke without a dementia diagnosis. Throughout all study periods, a significantly lower proportion of patients with stroke with preexisting dementia, compared with stroke-only patients, received reperfusion treatment, assessments for rehabilitation, and early supported discharge from stroke units. In the subgroup of stroke patients with preexisting dementia, no significant associations were found regarding the quality indicators of stroke care before, during, and after the pandemic. CONCLUSIONS AND IMPLICATIONS: Disparities in quality of stroke care were observed between stroke patients with preexisting dementia and those with only stroke during the COVID-19 pandemic. However, there were no statistically significant differences in stroke care for patients with dementia across the pandemic.

The effect of cervical pessary on increasing gestational age at delivery in twin pregnancies with asymptomatic short cervix: a systematic review and meta-analysis of randomized controlled trials.

Objective: The incidence of preterm delivery is much higher in twin pregnancies than in singletons and even higher if a short cervical length is detected in the second trimester. Studies are contradictory regarding the efficacy of a cervical pessary to decrease preterm birth in twin pregnancies and short cervical length. To conduct a systematic review and meta-analysis investigating the efficacy of cervical pessary in prolonging gestation, preventing preterm birth, and reducing adverse neonatal outcomes in twin pregnancies with an asymptomatic short cervix. Data sources: PubMed, Scopus, Web of Science, and ClinicalTrials.org were searched for randomized controlled trials from inception to June 2023. Study eligibility criteria: In this study, randomized controlled trials comparing the cervical pessary to expectant management in the pregnant population with twin gestations and asymptomatic short cervix were included. Methods: The Cochrane risk-of-bias-2 tool for randomized controlled trials was used for the evaluation of the risk of bias in included studies. A meta-analysis was performed by calculating risk ratio and mean difference with their 95% confidence interval using the random effects model or fixed effect model on the basis of heterogeneity and accounting for potential covariates among the included randomized controlled trials. Results: A total of 6 randomized controlled trials were included in the analysis. Cervical pessary did not significantly increase the gestational age at delivery in twin pregnancies with asymptomatic patients (mean difference, 0.36 weeks [-0.27 to 0.99]; P=.270; I2=72.0%). Moreover, the cervical pessary use did not result in a reduction of spontaneous or all-preterm birth before 37 weeks of gestation (risk ratio, 0.88 [0.77-1.00]; P=.061; I2=0.0%). There was no statistically significant difference in the composite neonatal adverse outcomes (risk ratio, 1.001 [0.86-1.16]; P=.981; I2=20.9%), including early respiratory morbidity, intraventricular hemorrhage, necrotizing enterocolitis, and confirmed sepsis. Conclusion: The use of cervical pessary in twin pregnancies with asymptomatic short cervix does not seem to be effective in increasing the gestational age at delivery, preventing preterm birth, or reducing adverse neonatal outcomes. This indicates that alternative interventions should be sought for the management of this patient population.

Tocilizumab Failed to Reduce Mortality in Severe COVID-19 Patients: Results from a Randomized Controlled Clinical Trial.

The severe coronavirus disease 2019 (COVID-19) is associated with increased levels of blood interleukin (IL)-6. Therefore, it is hypothesized that modulating the levels or effects of IL-6  could diminish airway inflammation and alter the course of COVID-19. We conducted a controlled, randomized, double-blind clinical trial on hospitalized patients with severe COVID-19 in Iran. The patients were randomly distributed by block randomization to take either standard-of-care (SOC) plus 1 or 2 doses of tocilizumab 8 mg/kg or SOC alone. The endpoint was defined by clinical improvement and discharge. We enrolled 40 patients (20 patients in each group) from 10 July to 10 December 2020. After randomization, 1 patient in the SOC arm and 3 patients in the tocilizumab arm refused to participate and were eliminated from the study. The mean age of participants was 59.62±15.80 in the tocilizumab group (8 women and 9 men) and 63.52±12.83 years old in the SOC group (9 women and 10 men) groups. The number of patients who recovered did not differ significantly between the tocilizumab and SOC groups (12 [70.6%][70.6%] vs. 15 [78.9%]), respectively). Hospitalization rates were also similar between the groups (Log-rank test, p=0.615; hazard ratio, 0.83; 95% C I [0. 39-1.78]). The results show that tocilizumab could not be a beneficial agent for treating severe cases of COVID-19 patients and would not significantly improve clinical outcomes.

Investigating efficacy of colchicine plus phenolic monoterpenes fraction as a potential treatment for patients diagnosed with COVID-19: A randomized controlled parallel clinical trial.

Background: COVID-19 now is a serious concern for the world healthcare system. This study aimed to investigate possible therapeutic effect of colchicine and phenolic monoterpenes accompanied by standard care of treatment (SCT) in patients diagnosed with COVID-19. Methods: In this randomized controlled parallel clinical trial, a total number of 179 (of 200) patients with confirmed COVID-19 were enrolled according to the inclusion and exclusion criteria. The patients were allocated by simple randomization method into two groups control (receiving SCT with 71 patients) and intervention (receiving SCT plus colchicine and phenolic monoterpenes with 107 patients). The mortality ratio during hospitalization as well as a 2-week follow-up, ICU admission rate, and hospitalization duration were assessed as main outcomes. Results: The mortality ratio was 0.9% (1/108) and 8.45% (6/71) in the intervention and the control groups (p-value = 0.035) respectively, these ratios after a 14-day follow-up were 1.85% (2/108), and 9.85 (7/71) respectively (p-value = 0.031). Also, the ICU admission was significantly lower (p-value = 0.006) in the intervention group 2/108 (1.85%) compared with controls 10/71 (14.08%). Moreover, the duration of hospitalization followed a similar pattern to ICU admission with 4.17 ± 1.34 vs. 6.39 ± 2.59 days in the intervention and control groups respectively (p-value< 0.001). Furthermore, no significant side effect was found between the groups. Conclusion: According to the results, the combination of colchicine plus phenolic monoterpenes could be an additive treatment for the SCT. The authors strongly recommend further trials on this combination with other SCTs.

Social, economic, and health indexes affecting epidemiology of preterm birth: A cross-sectional study.

Background and Aim: Preterm birth (PTB) accompanies with morbidities and mortality among newborns. This study aimed to show that different factors such as economic (adjusted net national income and gross domestic product [GDP] per capita), human developmental (human developmental index), and health (overall health performance, pregnancy prenatal care rate, and modeled estimated maternal mortality rate) indexes might influence the prevalence of PTB. Methods: To this, the top 10 countries with the highest and lowest prevalence of PTB were extracted from the Global Burden of Disease report for PTB. Then, we have gathered some common indexes for economic (adjusted net national income and GDP per capita), health-related (overall health performance, pregnancy prenatal care rate, and modeled estimated maternal mortality rate), and combined developmental (human developmental index) factors from different resources including World Bank and United Nations for those countries. The truncated Bayesian linear regression model, decision tree, and k-means clustering algorithms were used for data analysis. Results: The results showed Pregnancy Prenatal Care Rate index has a significant effect on the PTB rate in the top 10 countries with the highest prevalence of PTB. Also, for the top 10 less prevalent countries for PTB, it was shown that modeled estimated maternal mortality rate, human developmental index rank, and pregnancy prenatal care rate have significant effects on PTB rate. In addition, the clustering based on the similarities in socioeconomic, human developmental, and health indexes were approximately like with the clustering of the countries based on the PTB rates (Rand index = 0.823). Conclusion: The results showed studies on the epidemiology of PTB (either worldwide or nation-based) should consider these confounder factors to obtain accurate results.

Statins and cognitive decline in patients with Alzheimer's and mixed dementia: a longitudinal registry-based cohort study.

BACKGROUND: Disturbances in brain cholesterol homeostasis may be involved in the pathogenesis of Alzheimer's disease (AD). Lipid-lowering medications could interfere with neurodegenerative processes in AD through cholesterol metabolism or other mechanisms. OBJECTIVE: To explore the association between the use of lipid-lowering medications and cognitive decline over time in a cohort of patients with AD or mixed dementia with indication for lipid-lowering treatment. METHODS: A longitudinal cohort study using the Swedish Registry for Cognitive/Dementia Disorders, linked with other Swedish national registries. Cognitive trajectories evaluated with mini-mental state examination (MMSE) were compared between statin users and non-users, individual statin users, groups of statins and non-statin lipid-lowering medications using mixed-effect regression models with inverse probability of drop out weighting. A dose-response analysis included statin users compared to non-users. RESULTS: Our cohort consisted of 15,586 patients with mean age of 79.5 years at diagnosis and a majority of women (59.2 %). A dose-response effect was demonstrated: taking one defined daily dose of statins on average was associated with 0.63 more MMSE points after 3 years compared to no use of statins (95% CI: 0.33;0.94). Simvastatin users showed 1.01 more MMSE points (95% CI: 0.06;1.97) after 3 years compared to atorvastatin users. Younger (< 79.5 years at index date) simvastatin users had 0.80 more MMSE points compared to younger atorvastatin users (95% CI: 0.05;1.55) after 3 years. Simvastatin users had 1.03 more MMSE points (95% CI: 0.26;1.80) compared to rosuvastatin users after 3 years. No differences regarding statin lipophilicity were observed. The results of sensitivity analysis restricted to incident users were not consistent. CONCLUSIONS: Some patients with AD or mixed dementia with indication for lipid-lowering medication may benefit cognitively from statin treatment; however, further research is needed to clarify the findings of sensitivity analyses.

Psychiatric Disorders Before and After Dementia Diagnosis.

Importance: Little is known about the specific timing and sequence of incident psychiatric comorbidities at different stages of dementia diagnosis. Objectives: To examine the temporal risk patterns of psychiatric disorders, including depression, anxiety, stress-related disorders, substance use disorders, sleep disorders, somatoform/conversion disorders, and psychotic disorders, among patients with dementia before, at the time of, and after receipt of a diagnosis. Design, Setting, and Participants: This population-based, nationwide cohort study analyzed data from 796 505 participants obtained from 6 registers between January 1, 2000, and December 31, 2017, including the Swedish registry for cognitive/dementia disorders. Patients with dementia were matched on year of birth (±3 years), sex, and region of residence with up to 4 controls. Data were analyzed between March 1, 2023, and August 31, 2023. Exposures: Any cause of dementia and dementia subtypes. Main Outcomes and Measures: Flexible parametric survival models to determine the time-dependent risk of initial diagnosis of psychiatric disorders, from 7 years prior to dementia diagnosis to 10 years after diagnosis. Subgroup analysis was conducted for psychiatric drug use among persons receiving a diagnosis of dementia from January 1, 2011, to December 31, 2012. Results: Of 796 505 patients included in the study (mean [SD] age at diagnosis, 80.2 [8.3] years; 448 869 (56.4%) female), 209 245 had dementia, whereas 587 260 did not, across 7 824 616 person-years. The relative risk of psychiatric disorders was consistently higher among patients with dementia compared with control participants and began to increase from 3 years before diagnosis (hazard ratio, [HR], 1.72; 95% CI, 1.67-1.76), peaked during the week after diagnosis (HR, 4.74; 95% CI, 4.21-5.34), and decreased rapidly thereafter. Decreased risk relative to controls was observed from 5 years after diagnosis (HR, 0.93; 95% CI, 0.87-0.98). The results were similar for Alzheimer disease, mixed dementia, vascular dementia and unspecified dementia. Among patients with dementia, markedly elevated use of psychiatric medications was observed in the year leading up to the dementia diagnosis and peaked 6 months after diagnosis. For example, antidepressant use was persistently higher among patients with dementia compared with controls, and the difference increased from 2 years before dementia diagnosis (15.9% vs 7.9%, P < .001), peaked approximately 6 months after dementia diagnosis (29.1% vs 9.7%, P < .001), and then decreased slowly from 3 years after diagnosis but remained higher than controls 5 years after diagnosis (16.4% vs 6.9%, P < .001). Conclusions and Relevance: The findings of this cohort study that patients with dementia had markedly increased risks of psychiatric disorders both before and after dementia diagnosis highlight the significance of incorporating psychiatric preventative and management interventions for individuals with dementia across various diagnostic stages.

Artificial Intelligence-Driven Single-Shot PET Image Artifact Detection and Disentanglement: Toward Routine Clinical Image Quality Assurance.

PURPOSE: Medical imaging artifacts compromise image quality and quantitative analysis and might confound interpretation and misguide clinical decision-making. The present work envisions and demonstrates a new paradigm PET image Quality Assurance NETwork (PET-QA-NET) in which various image artifacts are detected and disentangled from images without prior knowledge of a standard of reference or ground truth for routine PET image quality assurance. METHODS: The network was trained and evaluated using training/validation/testing data sets consisting of 669/100/100 artifact-free oncological 18 F-FDG PET/CT images and subsequently fine-tuned and evaluated on 384 (20% for fine-tuning) scans from 8 different PET centers. The developed DL model was quantitatively assessed using various image quality metrics calculated for 22 volumes of interest defined on each scan. In addition, 200 additional 18 F-FDG PET/CT scans (this time with artifacts), generated using both CT-based attenuation and scatter correction (routine PET) and PET-QA-NET, were blindly evaluated by 2 nuclear medicine physicians for the presence of artifacts, diagnostic confidence, image quality, and the number of lesions detected in different body regions. RESULTS: Across the volumes of interest of 100 patients, SUV MAE values of 0.13 ± 0.04, 0.24 ± 0.1, and 0.21 ± 0.06 were reached for SUV mean , SUV max , and SUV peak , respectively (no statistically significant difference). Qualitative assessment showed a general trend of improved image quality and diagnostic confidence and reduced image artifacts for PET-QA-NET compared with routine CT-based attenuation and scatter correction. CONCLUSION: We developed a highly effective and reliable quality assurance tool that can be embedded routinely to detect and correct for 18 F-FDG PET image artifacts in clinical setting with notably improved PET image quality and quantitative capabilities.

Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement.

PURPOSE: Image artefacts continue to pose challenges in clinical molecular imaging, resulting in misdiagnoses, additional radiation doses to patients and financial costs. Mismatch and halo artefacts occur frequently in gallium-68 (68Ga)-labelled compounds whole-body PET/CT imaging. Correcting for these artefacts is not straightforward and requires algorithmic developments, given that conventional techniques have failed to address them adequately. In the current study, we employed differential privacy-preserving federated transfer learning (FTL) to manage clinical data sharing and tackle privacy issues for building centre-specific models that detect and correct artefacts present in PET images. METHODS: Altogether, 1413 patients with 68Ga prostate-specific membrane antigen (PSMA)/DOTA-TATE (TOC) PET/CT scans from 3 countries, including 8 different centres, were enrolled in this study. CT-based attenuation and scatter correction (CT-ASC) was used in all centres for quantitative PET reconstruction. Prior to model training, an experienced nuclear medicine physician reviewed all images to ensure the use of high-quality, artefact-free PET images (421 patients' images). A deep neural network (modified U2Net) was trained on 80% of the artefact-free PET images to utilize centre-based (CeBa), centralized (CeZe) and the proposed differential privacy FTL frameworks. Quantitative analysis was performed in 20% of the clean data (with no artefacts) in each centre. A panel of two nuclear medicine physicians conducted qualitative assessment of image quality, diagnostic confidence and image artefacts in 128 patients with artefacts (256 images for CT-ASC and FTL-ASC). RESULTS: The three approaches investigated in this study for 68Ga-PET imaging (CeBa, CeZe and FTL) resulted in a mean absolute error (MAE) of 0.42 ± 0.21 (CI 95%: 0.38 to 0.47), 0.32 ± 0.23 (CI 95%: 0.27 to 0.37) and 0.28 ± 0.15 (CI 95%: 0.25 to 0.31), respectively. Statistical analysis using the Wilcoxon test revealed significant differences between the three approaches, with FTL outperforming CeBa and CeZe (p-value < 0.05) in the clean test set. The qualitative assessment demonstrated that FTL-ASC significantly improved image quality and diagnostic confidence and decreased image artefacts, compared to CT-ASC in 68Ga-PET imaging. In addition, mismatch and halo artefacts were successfully detected and disentangled in the chest, abdomen and pelvic regions in 68Ga-PET imaging. CONCLUSION: The proposed approach benefits from using large datasets from multiple centres while preserving patient privacy. Qualitative assessment by nuclear medicine physicians showed that the proposed model correctly addressed two main challenging artefacts in 68Ga-PET imaging. This technique could be integrated in the clinic for 68Ga-PET imaging artefact detection and disentanglement using multicentric heterogeneous datasets.

Fetoscopic laser photocoagulation versus expectant management for stage I twin-to-twin transfusion syndrome: A systematic review and meta-analysis.

To investigate the outcomes of asymptomatic stage I twin-to-twin transfusion syndrome (stage I TTTS) among patients treated with fetoscopic laser photocoagulation (FLP) versus expectant management. Databases such as PubMed, Web of Science and Scopus were systematically searched from inception up to March 1st, 2022. The primary outcome was at least one fetal survival at birth and secondary outcomes included gestational age at delivery, preterm premature rupture of membranes < 32 weeks, preterm birth < 32 weeks, and single and dual fetal survival. Five studies were included in the meta-analysis. There was no significant difference in terms of at least one survival (odds ratio (OR) = 1.40, 95%CI= (0.26, 7.43), P = 0.70), single survival (OR = 0.87, 95%CI= (0.51, 1.48), P = 0.60) and dual survival (OR = 1.63, 95%CI= (0.74, 3.62), P = 0.23) among FLP and expectant groups. Gestational age at delivery (mean difference = 1.19, 95%CI= (-0.25, 2.63), P = 0.10), the risk of PTB<32 weeks (OR = 0.88, 95%CI= (0.50, 1.54), P = 0.65), and pPROM<32 weeks (OR = 1.80, 95% CI= (0.41, 7.98), P = 0.44) were also comparable between the groups. Routine FLP of the placental anastomoses before 26 weeks of gestation is unlikely to be beneficial among asymptomatic stable stage I TTTS patients without cervical shortening as the procedure does not offer a survival advantage compared with expectant management.

Association of angiotensin-converting enzyme (ACE) I/D variation with biochemical parameters and oxidative stress markers in systemic lupus erythematosus patients in west of Iran.

PURPOSE: We aimed to study insertion/deletion (I/D) variation (rs4646994) of ACE gene in a group of SLE patients in west of Iran and its possible relationship with oxidative stress. METHOD AND RESULTS: Genotypes and allele frequencies related to ACE (I/D) variation were determined in 108 SLE patients and 110 gender and age-matched healthy controls using PCR. Neopterin, malondialdehyde (MDA), and serum lipid concentrations were determined by HPLC and enzyme assay respectively. The overall distribution of ACE I/D genotypes in SLE patients was different from that of the control group (P = 0.005). DD genotype compared to ID genotype increased the risk of SLE (OR = 2.57, 95% CI 1.4-4.8, P = 0.003). ID genotype compared to the II genotype decreased the risk of disease (OR = 0.45, 95% CI 0.2-0.99, p = 0.042). SLE patients with DD, ID, and II genotypes had lower paraoxonase (PON) activity and higher serum levels of MDA and neopterin versus control patients. We also detected a significant protective effect against SLE in presence of ACE I alleles and lack of angiotensin II receptor, type 1 (AGTR1) A1166C (NCBI reference SNP id: rs5186), C alleles in this study (OR = 0.31, 95% CI 0.14-0.68, P = 0.002). CONCLUSIONS: Carriers of the DD genotype of ACE gene with higher serum concentrations of neopterin and MDA, and lower PON activity had a high risk to develop SLE, while ID genotype decreased the risk of disease development by 2.22 times compared to II genotype.

Association between dietary inflammatory index and infertility of women; Results from RaNCD Cohort Study.

BACKGROUND: In recent decades, more and more attention has been paid to the influence of nutrition on reproductive health. Nevertheless, the imminent association between diet-related inflammation and the risk of infertility has not yet been established. The aim of the current study was to investigate the ability of the Dietary Inflammatory Index (DII) to estimate infertility incidence in women. METHODS: This cross-sectional study was conducted using data from Ravansar non-communicable diseases (RaNCD) cohort study on 4437 participants. The DII was calculated based on the reported consumption of up to 31 food parameters measured via a validated and reproducible 118-item food-frequency questionnaire (FFQ). Multiple logistic regression analysis was applied to estimate the multivariable odds ratio (OR) adjusted for potential confounding variables. RESULTS: Out of all participants, 411 women (9.26%) were infertile. The mean ± SD age and weight of infertile women were 43.67 ± 7.47 years and 72.86 ± 13.02 kg, respectively. Statistical analyses showed the odds ratio of infertility in the fourth quartile (pro-inflammatory diet) was 1.76 times higher than in the first quartile (anti-inflammatory diet) of DII (95% CI: 1.57-2.02). CONCLUSIONS: The findings of this study provide compelling evidence about the association between infertility and the quality of diet in women. Therefore, interventions and programs aimed at promoting a healthy lifestyle and using healthy diets can be considered as one of the effective approaches in the prevention and treatment of infertility in women.

External Causes of Death From Death Certificates in Patients With Dementia.

OBJECTIVES: We aim to analyze the risk of death from specific external causes, including falls, complications of medical and surgical care, unintentional injuries, and suicide, in dementia patients. DESIGN: Swedish nationwide cohort study integrating 6 registers from May 1, 2007, through December 31, 2018, including the Swedish Registry for Cognitive/Dementia Disorders (SveDem). SETTING AND PARTICIPANTS: Population-based study. Patients diagnosed with dementia from 2007 to 2018 and up to 4 controls matched on year of birth (±3 years), sex, and region of residence. METHODS: The exposures of this study were diagnosis of dementia and dementia subtypes. Number of deaths and causes of mortality were obtained from death certificates compiled into the Cause of Death Register. Hazard ratios (HRs) and 95% CIs were estimated using Cox and flexible models, adjusted for sociodemographics, medical and psychiatric disorders. RESULTS: The study population included 235,085 patients with dementia [96,760 men (41.2%); mean age 81.5 (SD 8.5) years] and 771,019 control participants [341,994 men (44.4%); mean age 79.9 (SD 8.6) years], over 3,721,687 person-years. Compared with control participants, patients with dementia presented increased risk for unintentional injuries (HR 3.30, 95% CI 3.19-3.40) and falls (HR 2.67, 95% CI 2.54-2.80) during old age (≥75 y), and suicide (HR 1.56, 95% CI 1.02-2.39) in middle age (<65 y). Suicide risk was 5.04 times higher (HR 6.04, 95% CI 4.22-8.66) in patients with both dementia and 2 or more psychiatric disorders relative to controls (incidence rate per person-years, 1.6 vs 0.3). For dementia subtypes, frontotemporal dementia had the highest risks of unintentional injuries (HR 4.28, 95% CI 2.80-6.52) and falls (HR 3.83, 95% CI 1.98-7.41), whereas subjects with mixed dementia were less likely to die from suicide (HR 0.11, 95% CI 0.03-0.46) and complications of medical and surgical care (HR 0.53, 95% CI 0.40-0.70) compared to controls. CONCLUSIONS AND IMPLICATIONS: Suicide risk screening and psychiatric disorders management in early-onset dementia and early interventions for unintentional injuries and falls prevention in older dementia patients should be provided.

A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis.

BACKGROUND: Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first time, the function of the longitudinal regression tree algorithm as a non-parametric method after imputing missing data using SI and MI was investigated using simulated and real data. METHOD: Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing longitudinal data using parametric and non-parametric longitudinal models and the performance of the methods was assessed in real data. The real data included 3,645 participants older than 18 years within six waves obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling was conducted using systolic and diastolic blood pressure (SBP/DBP) as the outcome variables and included predictor variables such as age, gender, and BMI. The efficiency of imputation approaches was compared using mean squared error (MSE), root-mean-squared error (RMSE), median absolute deviation (MAD), deviance, and Akaike information criteria (AIC). RESULTS: The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the missing at random (MAR) mechanism. Overall, based on fitting the non-parametric model, the performance of the 27 imputation approaches was nearly similar. However, the SI traj-mean method improved performance compared with other imputation approaches. CONCLUSION: Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data, we recommend that researchers use the traj-mean method for imputing missing values of longitudinal data. Choosing the imputation method with the best performance is widely dependent on the models of interest and the data structure.

Machine learning algorithms for identifying predictive variables of mortality risk following dementia diagnosis: a longitudinal cohort study.

Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to identify the most important variables associated with mortality after dementia diagnosis in the Swedish Registry for Cognitive/Dementia Disorders (SveDem). From SveDem, a longitudinal cohort of 28,023 dementia-diagnosed patients was selected for this study. Sixty variables were considered as potential predictors of mortality risk, such as age at dementia diagnosis, dementia type, sex, body mass index (BMI), mini-mental state examination (MMSE) score, time from referral to initiation of work-up, time from initiation of work-up to diagnosis, dementia medications, comorbidities, and some specific medications for chronic comorbidities (e.g., cardiovascular disease). We applied sparsity-inducing penalties for three ML algorithms and identified twenty important variables for the binary classification task in mortality risk prediction and fifteen variables to predict time to death. Area-under-ROC curve (AUC) measure was used to evaluate the classification algorithms. Then, an unsupervised clustering algorithm was applied on the set of twenty-selected variables to find two main clusters which accurately matched surviving and dead patient clusters. A support-vector-machines with an appropriate sparsity penalty provided the classification of mortality risk with accuracy = 0.7077, AUROC = 0.7375, sensitivity = 0.6436, and specificity = 0.740. Across three ML algorithms, the majority of the identified twenty variables were compatible with literature and with our previous studies on SveDem. We also found new variables which were not previously reported in literature as associated with mortality in dementia. Performance of basic dementia diagnostic work-up, time from referral to initiation of work-up, and time from initiation of work-up to diagnosis were found to be elements of the diagnostic process identified by the ML algorithms. The median follow-up time was 1053 (IQR = 516-1771) days in surviving and 1125 (IQR = 605-1770) days in dead patients. For prediction of time to death, the CoxBoost model identified 15 variables and classified them in order of importance. These highly important variables were age at diagnosis, MMSE score, sex, BMI, and Charlson Comorbidity Index with selection scores of 23%, 15%, 14%, 12% and 10%, respectively. This study demonstrates the potential of sparsity-inducing ML algorithms in improving our understanding of mortality risk factors in dementia patients and their application in clinical settings. Moreover, ML methods can be used as a complement to traditional statistical methods.

Radioproteomics modeling of metformin-enhanced radiosensitivity: an animal study.

PURPOSE: Metformin is considered as radiation modulator in both tumors and healthy tissues. Radiomics has the potential to decode biological mechanisms of radiotherapy response. The aim of this study was to apply radiomics analysis in metformin-induced radiosensitivity and finding radioproteomics associations of computed tomography (CT) imaging features and proteins involved in metformin radiosensitivity signaling pathways. MATERIALS AND METHODS: A total of 32 female BALB/c mice were used in this study and were subjected to injection of breast cancer cells. When tumors reached a mean volume of 150 mm3, mice were randomly divided into the four groups including Control, Metformin, Radiation, and Radiation + Metformin. Western blot analysis was performed after treatment to measure expression of proteins including AMPK-alpha, phospho-AMPK-alpha (Thr172), mTOR, phospho-mTOR (Ser2448), phospho-4EBP1 (Thr37/46), phospho-ACC (Ser79), and ß-actin. CT imaging was performed before treatment and at the end of treatment in all groups. Radiomics features extracted from segmented tumors were selected using Elastic-net regression and were assessed in terms of correlation with expression of the proteins. RESULTS: It was observed that proteins including phospho-mTOR, phospho-4EBP1, and mTOR had positive correlations with changes in tumor volumes in days 28, 24, 20, 16, and 12, while tumor volume changes at these days had negative correlations with AMPK-alpha, phospho-AMPK-alpha, and phospho-ACC proteins. Furthermore, median feature had a positive correlation with AMPK-alpha, phospho-ACC, and phospho-AMPK-alpha proteins. Also, Cluster shade feature had positive correlations with mTOR and p-mTOR. On the other hand, LGLZE feature had negative correlations with AMPK-alpha and phospho-AMPK-alpha. CONCLUSION: Radiomics features can decode proteins that involved in response to metformin and radiation, although further studies are warranted to investigate the optimal way to integrate radiomics into biological experiments.