Iranian Journal of Medical Sciences
Volume:46 Issue: 6, Nov 2021

Coronavirus disease 2019 (COVID-19) is a recently emerging disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Notably, the safety of immunosuppressive medications is a major concern during an infectious disease pandemic. Rituximab (RTX), as a monoclonal antibody against CD20 molecule, is widely used for the treatment of various diseases, mostly autoimmune diseases and some malignancies. Previous studies indicated that RTX, as an immunosuppressive medication, may be associated with the increased risk of infections. Moreover, given the wide use of RTX, a necessity of determining the different aspects of RTX use in the COVID-19 era is strongly felt. We reviewed current studies on the clinical courses of patients with SARS-CoV-2 infection. It appears that the use of RTX does not increase morbidity and mortality in most patients. However, underlying diseases and other concomitant medications may play a role in the disease course, while the concerns of vaccine efficacy in patients receiving RTX still need to be addressed. Therefore, more controlled studies are needed for a better conclusion.

Chest computed tomography (CT) plays an essential role in diagnosing coronavirus disease 2019 (COVID-19). However, CT findings are often nonspecific among different viral pneumonia conditions. The differentiation between COVID-19 and influenza can be challenging when seasonal influenza concurs with the COVID-19 pandemic. This study was conducted to test the ability of radiomics-artificial intelligence (AI) to perform this task. In this retrospective study, chest CT images from 47 patients with COVID-19 (after February 2020) and 19 patients with H1N1 influenza (before September 2019) pneumonia were collected from three hospitals affiliated with Arak University of Medical Sciences, Arak, Iran. All pulmonary lesions were segmented on CT images. Multiple radiomics features were extracted from the lesions and used to develop support-vector machine (SVM), k-nearest neighbor (k-NN), decision tree, neural network, adaptive boosting (AdaBoost), and random forest. The patients with COVID-19 and H1N1 influenza were not significantly different in age and sex (P=0.13 and 0.99, respectively). Nonetheless, the average time between initial symptoms/hospitalization and chest CT was shorter in the patients with COVID-19 (P=0.001 and 0.01, respectively). After the implementation of the inclusion and exclusion criteria, 453 pulmonary lesions were included in this study. On the harmonized features, random forest yielded the highest performance (area under the curve=0.97, sensitivity=89%, precision=90%, F1 score=89%, and classification accuracy=89%). In our preliminary study, radiomics feature extraction, conjoined with AI, especially random forest and neural network, appeared to yield very promising results in the differentiation between COVID-19 and H1N1 influenza on chest CT.

Recently, people have recognized the post-acute phase symptoms of the COVID-19. We investigated the long-term symptoms associated with COVID-19, (Long COVID Syndrome), and the risk factors associated with it.

This was a retrospective observational study. All the consecutive adult patients referred to the healthcare facilities anywhere in Fars province from 19 February 2020 until 20 November 2020 were included. All the patients had a confirmed COVID-19 diagnosis. In a phone call to the patients, at least three months after their discharge from the hospital, we obtained their current information. The IBM SPSS Statistics (version 25.0) was used. Pearson Chi square, Fisher’s exact test, t test, and binary logistic regression analysis model were employed. A P value of less than 0.05 was considered to be significant.

In total, 4,681 patients were studied, 2915 of whom (62.3%) reported symptoms. The most common symptoms of long COVID syndrome were fatigue, exercise intolerance, walking intolerance, muscle pain, and shortness of breath. Women were more likely to experience long-term COVID syndrome than men (Odds Ratio: 1,268; 95% Confidence Interval: 1,122-1,432; P=0.0001), which was significant. Presentation with respiratory problems at the onset of illness was also significantly associated with long COVID syndrome (Odds Ratio: 1.425; 95% Confidence Interval: 1.177-1.724; P=0.0001). A shorter length of hospital stay was inversely associated with long COVID syndrome (Odds Ratio: 0.953; 95% Confidence Interval: 0.941-0.965; P=0.0001).

Long COVID syndrome is a frequent and disabling condition and has significant associations with sex (female), respiratory symptoms at the onset, and the severity of the illness.

With the growing rate of cesarean sections, rising morbidity and mortality thereafter is an important health issue. Predictive models can identify individuals with a higher probability of cesarean section, and help them make better decisions. This study aimed to investigate the biopsychosocial factors associated with the method of childbirth and designed a predictive model using the decision tree C4.5 algorithm. In this cohort study, the sample included 170 pregnant women in the third trimester of pregnancy referring to Shahroud Health Care Centers (Semnan, Iran), from 2018 to 2019. Blood samples were taken from mothers to measure the estrogen hormone at baseline. Birth information was recorded at the follow-up time per 30-42 days postpartum. Chi square, independent samples t test, and Mann-Whitney were used for comparisons between the two groups. Modeling was performed with the help of MATLAB software and C4.5 decision tree algorithm using input variables and target variable (childbirth method). The data were divided into training and testing datasets using the 70-30% method. In both stages, sensitivity, specificity, and accuracy were evaluated by the decision tree algorithm. Previous method of childbirth, maternal body mass index at childbirth, maternal age, and estrogen were the most significant factors predicting the childbirth method. The decision tree model’s sensitivity, specificity, and accuracy were 85.48%, 94.34%, and 89.57% in the training stage, and 82.35%, 83.87%, and 83.33% in the testing stage, respectively. The decision tree model was designed with high accuracy successfully predicted the method of childbirth. By recognizing the contributing factors, policymakers can take preventive action. It should be noted that this article was published in preprint form on the website of research square (https://www.researchsquare.com/article/rs-34770/v1).

Glucocorticoids are pivotal components of immunosuppressive regimens in solid organ transplantations. This study aimed to assess the possible association between the ER22/23EK, N363S, and Bcl1 polymorphisms, and short-term clinical outcomes, including acute rejection and delayed graft function (DGF), in kidney transplantation recipients.

A case-control study was conducted in a two-year period on adults with transplanted kidneys, comprised of subjects without rejection (n=50, control) and those with documented rejection within one year after transplantation (n=50, case), between April 2017 and September 2018, in Shiraz, Iran. Demographic characteristics and clinical and paraclinical findings were gathered. The genotyping of the ER22/23EK, N363S, and Bcl1 polymorphisms was carried out via polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). The association between the genotypes and DGF as well as rejection types was evaluated using either the Chi square test or Fisher exact test. A stepwise logistic regression analysis was conducted to determine the independent factors of acute rejection within the first year after transplantation.

The study population consisted of 64 men and 36 women. The frequency of mutated alleles was 0.32 for G (Bcl1), 0.02 for S (N363S), and 0.065 for A (ER22/23EK). There was no significant association either between the studied polymorphisms and acute rejection or between the Bcl1 (P=0.17), N363S (P=0.99), and ER22/23EK (P=0.99) genotypes and DGF. The length of hospital stay after kidney transplantation was slightly more in N363N and ER22/23EK wild allele carriers. However, this difference was not statistically significant.

Our data suggested no statistically significant association between the genotypes of the studied polymorphisms and early clinical outcomes after kidney transplantation.

Ocriplasmin has been developed for the induction of posterior vitreous detachment in patients with vitreomacular adhesion. At physiological pH, ocriplasmin is susceptible to autolytic and proteolytic degradation, limiting its activity duration. These undesirable properties of ocriplasmin can be reduced by site-directed mutagenesis, so that its enzymatic activities can be augmented. This study aimed to design ocriplasmin variants with improved biological/physicochemical characteristics via bioinformatics tools. This study was performed in Tabriz University of Medical Sciences, Tabriz, Iran, 2019. Through site-directed mutagenesis, three ocriplasmin variants were designed. Structural analysis was performed on the wild-type variant and the mutant variants using the Protein Interactions Calculator (PIC) server. The interactions between the S-2403 substrate and the ocriplasmin variants were studied by molecular docking simulations, and binding capability was evaluated by the calculation of free binding energy. The conformational features of protein-substrate complex systems for all the variants were evaluated using molecular dynamic simulations at 100 nanoseconds. The structural analysis of ocriplasmin revealed that the substitution of threonine for alanine 59 significantly reduced proteolytic activity, while the substitution of glutamic acid for lysine 156 influenced autolytic function. The molecular docking simulation results indicated the appropriate binding of the substrate to the ocriplasmin variants with high-to-low affinities. The binding affinity of the wild-type variant for the substrate was higher than that between the mutant variants and the substrate. Simulation analyses, consisting of the root-mean-square deviation, the root-mean-square fluctuation, and the center-of-mass average distance showed a higher affinity of the substrate for the wild type than for the mutant variants. The mutational analysis of ocriplasmin revealed that A59T and K156E mutagenesis could be used for the development of a new variant with higher therapeutic efficacy.

Paricalcitol has been proposed for the treatment of secondary hyperparathyroidism in patients with renal failure and vitamin D deficiency (VDD); however, VDD is related to a range of clinical complaints. We aimed to investigate the effects of paricalcitol on body composition in VDD rats. Thirty adult male rats aged 10 weeks were randomly divided into three groups of 10, comprising control, VDD, and VDD plus paricalcitol (32 ng/rat intraperitoneal injection) (VDD+P), at the Animal Lab of the Endocrinology and Metabolism Research Center, Shiraz, Iran, in 2020. Body composition was assessed after three weeks via serum biochemical tests and dual-energy X-ray absorptiometry. Finally, the data were analyzed by using the paired-sample t test, the one-way ANOVA, and the Tukey post hoc test. Global lean mass and fat mass were lower in the VDD and VDD+P groups than in the controls (P<0.001). Global fat percentage was reduced significantly in the VDD+P group (P=0.029). Paricalcitol reduced global fat mass and fat percentage in a rat model with VDD. Evaluation of insulin and adiponectin levels is suggested to clarify the physiology of paricalcitol in VDD states.

Silibinin (SBN), a major active constituent of milk thistle seeds, exhibits numerous pharmacological activities. However, its oral bioavailability is low due to poor water solubility. This study aimed to develop a new synthetic approach for tuning the pore characteristics of mesoporous silica nanoparticles (MSNs) intended for the oral delivery of SBN. In addition, the effects of the pore diameter of MSNs on the loading capacity and the release profile of SBN were investigated. The present study was performed at Shiraz University of Medical Sciences, Shiraz, Iran, in 2019. This synthesis method shares the features of the simultaneous free-radical polymerization of methyl methacrylate and the sol-gel reaction of the silica precursor at the n-heptane/water interface. SBN was loaded onto MSNs, the in vitro release was determined, and the radical scavenging activities were compared between various pH values using the analysis of variance. According to the Brunauer–Emmett–Teller protocol, the pore sizes were well-tuned in the range of 2 to 7 nm with a large specific surface area (600–1200 m2/g). Dynamic light scattering results showed that different volume ratios of n-heptane/water resulted in different sizes, ranging from 25 to 100 nm. Interestingly, high SBN loading (13% w/w) and the sustained release of the total drug over 12 hours were achieved in the phosphate buffer (pH=6.8). Moreover, the antioxidant activity of SBN was well preserved in acidic gastric pH. Well-tuned pores of MSNs provided a proper substrate, and thus, enhanced SBN loading and oral dissolution and preserved its antioxidant activity. Nevertheless, further in vitro and in vivo investigations are needed.

The cumulative rate of death of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has necessitated better recognizing the risk factors of the disease and the COVID-19-induced mortality. This cross-sectional study aimed to determine the potential risk factors that predict COVID-19-related mortality concentrating on the initial recorded laboratory tests. We extracted admission’s medical records of a total of 136 deaths related to COVID-19 and 272 discharged adult inpatients (≥18 years old) related to four referral centers from February 24th to April 12th, 2020, in Isfahan, Iran, to figure out the relationship between the laboratory findings and mortality beyond demographic and clinical findings. We applied the independent sample t test and a chichi square test with SPSS software to compare the differences between the survivor and non-survivor patients. A P value of less than 0.05 was considered significant. Our results showed that greater length of hospitalization (P≤0.001), pre-existing chronic obstructive pulmonary disease (P≤0.001), high pulse rate, hypoxia (P≤0.001), and high computed tomography scan score (P<0.001), in addition to high values of some laboratory parameters, increase the risk of mortality. Moreover, high neutrophil/lymphocyte ratio (OR, 1.890; 95% CI, 1.074-3.325, P=0.027), increased creatinine levels (OR, 15.488; 95% CI, 0.801-299.479, P=0.07), and elevated potassium levels (OR, 13.400; 95% CI, 1.084-165.618, P=0.043) independently predicted in-hospital death related to COVID-19 infection. These results emphasized the potential role of impaired laboratory parameters for the prognosis of fatal outcomes in adult inpatients.

Pelizaeus-Merzbacher-Like Disease 1 is a genetic disorder affecting the central nervous system with an autosomal recessive inheritance pattern. It is a rare genetic disorder that affects the central nervous system. In this report, we demonstrated the clinical and paraclinical features of an Iranian consanguine pedigree with suspected hypomyelinating leukodystrophy, without any defined diagnosis. The proband, a 15-month-old girl, visited the Razi pathobiology and medical genetic laboratory of Karaj, where the study was conducted in 2020. Following whole-exome sequencing analysis of the proband and segregation analysis, a novel pathogenic mutation was discovered. GJC2 (NM_020435.4):c.1096dupG was found to be homozygous in the proband and heterozygous in both parents. This mutation was in the coding region of the protein, which results in D366Gfs*126 (p.Asp366GlyfsTer126). The site of mutation was at the 3’ region of the connexin superfamily domain. The frameshift results in a different peptide sequence of the C-terminal and extended protein. Our findings led to the diagnosis of the proband’s disease as Pelizaeus-Merzbacher-Like Disease 1 and led to the end of the diagnostic odyssey. We provided effective genetic counseling through the identification of a novel pathogenic mutation in gap junction protein C2 in this family and suggested preimplantation genetic diagnosis for the next pregnancy. Furthermore, our findings confirmed the association of GJC2 mutations with PMLD1. This discovery added to the repertoire of genetic mutations of Pelizaeus-Merzbacher-Like Disease 1. This knowledge could be applied for expanded carrier screening of other families, especially for Iranian consanguine marriages.

Medical trainees’ lifestyle has been changed particularly in the recent decade because of a group of health-related, social, and educational, variables. The emergence of COVID-19 and its effects on a wide variety of areas are such current cases. According to the published reports, the orientation of some changes has NOT been in support of healthier lifestyles (e.g., reduced interpersonal relationships, decrease in physical activity and so on).1, 2 Surely, as a warning and a matter of concern, such changes could affect our trainees’ qualifications regarding their professional performance. Academia provides an opportunity for performing developmental and/or preventive strategies that could help foster and maintain such qualifications in line with our social responsibility. Now, it seems that we require wise and in-time interventions- including but not limited to educational ones- for mediating side effects of the issue in the future. Despite its various dimensions, academic settings could responsibly approach this ongoing event through formal/informal curricula.

The surge in fast food consumption in recent years is considered a threat to human health. This change in the life habit has raised serious concerns among health policy-makers and medical nutrition researchers. Environmental stress, multitasking, low physical activity, and low academic achievement have been shown to influence the predilection for consuming fast food.1 We have now faced with one similarly threatening phenomenon among university students and academics, which can be termed “fast research”.

Since late 2019, the world and since early 2020, Iran has been experiencing a catastrophic pandemic of the coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).1 This fatal virus has a high potential for person-to-person transmission; therefore, this deadly outbreak has caused massive job losses, various psychiatric problems, and increasing difficulties for all businesses worldwide.2-5 Production of scientific data and its timely dissemination are the essential elements of an effective response to any crisis including the current pandemic. The current study aimed to determine the early contributions of the Iranian Journal of Medical Sciences (IJMS) during the COVID-19 pandemic in 2020. We retrieved all the IJMS publications in 2020 and divided the published articles into three main categories: clinical sciences, basic sciences, and editorials. We also identified and highlighted the studies related to COVID-19.