The Wound Healing Effect of Plantago Major Leaf Extract in a Rat Model: An Experimental Confirmation of a Traditional Belief in Persian Medicine

Background and Aim: Plantago major leaf has been traditionally used in Iran and many other countries for wound healing. This study presents a brief report about the depiction of the effects of Plantago major on wound healing in the major texts of Persian medicine. Moreover, the effect of Plantago major’s leaf extract on wound healing duration has been experimentally assessed in male rats. Materials and Methods: In experimental studies, the methanolic extract of Plantago major's leaf was used as an ointment. To make a wound model, a circular ulcer was made on the back of animals. Adult male Wistar rats were divided into two groups: animals in the control group were treated once a day only with the ointment's eucerin base, and the rats in Plantago major's group were treated with the ointment containing the plant extract. Ulcerous areas were measured on days 0 and 14. The durations of complete wound healing processes were determined too. Results: The difference between the mean duration of wound healing was statistically significant using independent samples t-test (20.7±0.4 days in control vs 19.1±0.4 in plant extract group, p=0.022). Furthermore, there was a significant difference in the mean wound surface area on the fourteenth day (p=0.014) despite the fact that there were no significant differences in day 0 (p=0.69). Conclusion: There is a long history of using Plantago major's leaf for wound healing in Persian medicine text books. It was determined, in the experimental studies conducted on rats, that P. major's leaf extract could accelerate wound healing process. This capability justifies its application not only in Persian medicine but also in some other traditional medicines

Breast cancer and dietary fat quality indices in Iranian women: A case–control study

BackgroundThe association between breast cancer (BC) and different indices of dietary fats has not been well-studied. Thus, this study aimed to investigate the association between BC and dietary fat quality (DFQ) indices in Iranian women.MethodsThis case–control study was conducted on 120 women with breast cancer and 240 healthy women in Tehran, Iran. Food Frequency Questionnaire and nutritionist IV software were used to assess the intake of dietary fats and to calculate the DFQ indices.ResultsThe patients with BC had a higher total fat (TF) (P < 0.01) and a lower ratio of polyunsaturated fatty acids (PUFAs) omega-3 to PUFAs omega-6 (ω-3/ω-6) compared with the controls (P < 0.001). TF had a significant association with BC risk (OR: 1.16; 95% CI: 1.01–1.33, P < 0.001). No significant association was found between BC and PUFA/saturated fatty acid ratio or the ω-3/ω-6 ratio.ConclusionThe patients with BC had a lower ω-3/ω-6 ratio and a higher total dietary fat intake than the healthy women. Total dietary fat intake was also directly associated with the risk of BC. Thus, low-fat diets may have beneficial effects for BC prevention. Further longitudinal studies are warranted

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Evaluation of the effect of adherence to treatment regimen program on quality of life in atrial fibrillation patients hospitalized in Shahid Chamran Hospital in Isfahan in 2017

Background and objective: Atrial fibrillation is the mostcommon cardiac arrhythmia, which is associated with reducedquality of life due to prolonged treatment and itsrecurrence. One of the key goals in the care of patientswith atrial fibrillation is increasing adherence to treatmentregimen program and the recommendations providedby the treatment group. Thus, the present study was designedand carried out with the aim of determining theeffect of treatment regimen program on quality of life inatrial fibrillation patients hospitalized in Shahid ChamranHospital in Isfahan in 2017.Methodology: This clinical trial study was conducted onpatients with atrial fibrillation arrhythmia in the CardiacCare Unit (CCU) and Post CCU Unit and Internal HeartSurgery Unit of Shahid Chamran Hospital in Isfahan. Atotal of 50 people were randomly selected as sample ofstudy and assigned to two groups of test and control. Thetest group received two 45-minute sessions of adherenceand educational booklet and they were followed-up forone month through phone call. The control group also receivedone session of usual care training individually withregard to the illness. Demographic data and quality of lifedata were collected through Atrial Fibrillation Effects onQuality of Life (AFEQT) before intervention, and one andthree month after the intervention. Data were analyzed bydescriptive and inferential statistics.Results: There was no significant difference between twogroups in terms of quality of life and demographic informationbefore the intervention. However, significant differencewas seen between the two groups in terms of qualityof life one month and three months after the intervention.Conclusion: The results suggest the positive effects ofadherence to treatment regimen program and follow-upof the patients by experienced nurses on quality of life inthese patients one and three months after discharge

Evaluation of the effect of adherence to treatment regimen program on quality of life in atrial fibrillation patients hospitalized in Shahid Chamran Hospital in Isfahan in 2017

Background and objective: Atrial fibrillation is the mostcommon cardiac arrhythmia, which is associated with reducedquality of life due to prolonged treatment and itsrecurrence. One of the key goals in the care of patientswith atrial fibrillation is increasing adherence to treatmentregimen program and the recommendations providedby the treatment group. Thus, the present study was designedand carried out with the aim of determining theeffect of treatment regimen program on quality of life inatrial fibrillation patients hospitalized in Shahid ChamranHospital in Isfahan in 2017.Methodology: This clinical trial study was conducted onpatients with atrial fibrillation arrhythmia in the CardiacCare Unit (CCU) and Post CCU Unit and Internal HeartSurgery Unit of Shahid Chamran Hospital in Isfahan. Atotal of 50 people were randomly selected as sample ofstudy and assigned to two groups of test and control. Thetest group received two 45-minute sessions of adherenceand educational booklet and they were followed-up forone month through phone call. The control group also receivedone session of usual care training individually withregard to the illness. Demographic data and quality of lifedata were collected through Atrial Fibrillation Effects onQuality of Life (AFEQT) before intervention, and one andthree month after the intervention. Data were analyzed bydescriptive and inferential statistics.Results: There was no significant difference between twogroups in terms of quality of life and demographic informationbefore the intervention. However, significant differencewas seen between the two groups in terms of qualityof life one month and three months after the intervention.Conclusion: The results suggest the positive effects ofadherence to treatment regimen program and follow-upof the patients by experienced nurses on quality of life inthese patients one and three months after discharge

Inclusive Multiple Model Using Hybrid Artificial Neural Networks for Predicting Evaporation

Predicting evaporation is essential for managing water resources in basins. Improvement of the prediction accuracy is essential to identify adequate inputs on evaporation. In this study, artificial neural network (ANN) is coupled with several evolutionary algorithms, i.e., capuchin search algorithm (CSA), firefly algorithm (FFA), sine cosine algorithm (SCA), and genetic algorithm (GA) for robust training to predict daily evaporation of seven synoptic stations with different climates. The inclusive multiple model (IMM) is then used to predict evaporation based on established hybrid ANN models. The adjusting model parameters of the current study is a major challenge. Also, another challenge is the selection of the best inputs to the models. The IMM model had significantly improved the root mean square error (RMSE) and Nash Sutcliffe efficiency (NSE) values of all the proposed models. The results for all stations indicated that the IMM model and ANN-CSA could outperform other models. The RMSE of the IMM was 18, 21, 22, 30, and 43% lower than those of the ANNCSA, ANN-SCA, ANN-FFA, ANN-GA, and ANN models in the Sharekord station. The MAE of the IMM was 0.112 mm/day, while it was 0.189 mm/day, 0.267 mm/day, 0.267 mm/day, 0.389 mm/day, 0.456 mm/day, and 0.512 mm/day for the ANN-CSA, ANN-SCA, and ANN-FFA, ANN-GA, and ANN models, respectively, in the Tehran station. The current study proved that the inclusive multiple models based on improved ANN models considering the fuzzy reasoning had the high ability to predict evaporation

Mean length of utterance (MLU) in typically-developing 2.5-5.5 year-old Persian-speaking children in Iran

Introduction: Mean length of utterance in morphemes (MLU) is widely used as a general index of language development in pre-school children. Because of insufficient data on Persian language development in Iran, this study examined the MLU of Persian-speaking children and its relation to their in an attempt to help improving clinical decision making. Materials and Methods: This cross-sectional study was conducted on 171 typically-developing children 2.5-5.5 years of age who were recruited from nursery settings of Isfahan, Iran. The sample was selected using a mixed method of sampling and divided into six age groups. After an informal conversation with each child to gauge whether the child appeared to be typically developing in terms of language and cognitive levels, speech therapists played with and tape-recorded them. Each child's MLU was calculated for 75 complete and intelligible utterances longer than one word. The mean and standard deviation of MLU were computed for each age group within six-month intervals. The correlation between age and MLU was also investigated. Results: The children’s mean MLU increased between 37-42 and 43-48 months and also between 43-48 and 49-54 months of age. The increase in MLU from the first age group onward was statistically significant. The correlation between age in months and MLU in morphemes was significant, r(171) = 0.47, P < 0.005. Conclusion: The average MLU of the children in this study-and similar studies of Persian-speaking children is much higher than that reported for English-speaking children, and the correlation with age lower; mainly because of morpho-syntactic differences between languages. Age sensitivity of MLU in Persian, however, indicates its capability as a developmental scale for monitoring syntax development in Persian-speaking children which needs to be deeply investigated in relation to Persian language-specific features, either. Keywords: Mean length of utterance, Syntax development, Language development, Pre-school children, Speech therap

Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy

Power supply is a key issue for decision-makers. The reservoir operation of multi-reservoir systems is an important aspect to consider in efforts to increase power generation. This research studies a multi-reservoir system comprising of the Khersan-I (KHI), Karoon-III (KAIII) and Karoon-IV (KAIV) with the intent being to increase power generation. To achieve this, the Two-Point Heading Rule was integrated with a new optimization algorithm, namely the Seagull Optimization Algorithm (SEOA). The Two-Point Heading Rule was used based on four distinct scenarios, namely Two-Point Heading Rule (1), Two-Point Heading Rule (2), Two-Point Heading Rule (3) and Two-Point Heading Rule (4). The Seagull Optimization Algorithm was then used to find two heading parameters of the TPHRs. The Seagull Optimization Algorithm was subsequently benchmarked against the Salp Swarm Algorithm (SSA), Bat Algorithm (BA) and the Shark Optimization Algorithm (SOA). Various inflow scenarios consisting of the first inflow scenario (dry condition), the second inflow scenario (normal) and the third inflow scenario (wet condition) were considered for the optimal operation of this multi-reservoir system. The results indicated that the global solution of the MSOO based on NLP for Two-Point Heading Rule (1) under the first inflow scenario and was 3.22 while the average solution of Seagull Optimization Algorithm, Salp Swarm Algorithm, Shark Optimization Algorithm, and Bat Algorithm in respective order was 3.25, 3.93, 4.87 and 6.03. The results indicated that the global solution of the MSOO based on NLP for Two-Point Heading Rule (1) under the second inflow scenario was 2.14 while the average best solution of Seagull Optimization Algorithm, Salp Swarm Algorithm, Shark Optimization Algorithm, and Bat Algorithm in respective order was 2.16, 2.98, 3.96, and 4.89. It can be concluded that the SEOA outperformed all of the other algorithms. It was also found that the SEOA based on the Two-Point Heading Rule (3) under the third inflow scenario provided the most power generation for the KHI and KAIV systems. A multi-criteria decision was utilized to choose the best algorithm and heading policy. The ensuing results indicate that the SEOA had the best performance out of all the algorithms based on Two-Point Heading Rule (3) and the third inflow scenario