Obesity as an independent risk factor for COVID-19 severity and mortality.

BACKGROUND: Since December 2019, the world has struggled with the COVID-19 pandemic. Even after the introduction of various vaccines, this disease still takes a considerable toll. In order to improve the optimal allocation of resources and communication of prognosis, healthcare providers and patients need an accurate understanding of factors (such as obesity) that are associated with a higher risk of adverse outcomes from the COVID-19 infection. OBJECTIVES: To evaluate obesity as an independent prognostic factor for COVID-19 severity and mortality among adult patients in whom infection with the COVID-19 virus is confirmed. SEARCH METHODS: MEDLINE, Embase, two COVID-19 reference collections, and four Chinese biomedical databases were searched up to April 2021. SELECTION CRITERIA: We included case-control, case-series, prospective and retrospective cohort studies, and secondary analyses of randomised controlled trials if they evaluated associations between obesity and COVID-19 adverse outcomes including mortality, mechanical ventilation, intensive care unit (ICU) admission, hospitalisation, severe COVID, and COVID pneumonia. Given our interest in ascertaining the independent association between obesity and these outcomes, we selected studies that adjusted for at least one factor other than obesity. Studies were evaluated for inclusion by two independent reviewers working in duplicate.  DATA COLLECTION AND ANALYSIS: Using standardised data extraction forms, we extracted relevant information from the included studies. When appropriate, we pooled the estimates of association across studies with the use of random-effects meta-analyses. The Quality in Prognostic Studies (QUIPS) tool provided the platform for assessing the risk of bias across each included study. In our main comparison, we conducted meta-analyses for each obesity class separately. We also meta-analysed unclassified obesity and obesity as a continuous variable (5 kg/m2 increase in BMI (body mass index)). We used the GRADE framework to rate our certainty in the importance of the association observed between obesity and each outcome. As obesity is closely associated with other comorbidities, we decided to prespecify the minimum adjustment set of variables including age, sex, diabetes, hypertension, and cardiovascular disease for subgroup analysis.  MAIN RESULTS: We identified 171 studies, 149 of which were included in meta-analyses.  As compared to 'normal' BMI (18.5 to 24.9 kg/m2) or patients without obesity, those with obesity classes I (BMI 30 to 35 kg/m2), and II (BMI 35 to 40 kg/m2) were not at increased odds for mortality (Class I: odds ratio [OR] 1.04, 95% confidence interval [CI] 0.94 to 1.16, high certainty (15 studies, 335,209 participants); Class II: OR 1.16, 95% CI 0.99 to 1.36, high certainty (11 studies, 317,925 participants)). However, those with class III obesity (BMI 40 kg/m2 and above) may be at increased odds for mortality (Class III: OR 1.67, 95% CI 1.39 to 2.00, low certainty, (19 studies, 354,967 participants)) compared to normal BMI or patients without obesity. For mechanical ventilation, we observed increasing odds with higher classes of obesity in comparison to normal BMI or patients without obesity (class I: OR 1.38, 95% CI 1.20 to 1.59, 10 studies, 187,895 participants, moderate certainty; class II: OR 1.67, 95% CI 1.42 to 1.96, 6 studies, 171,149 participants, high certainty; class III: OR 2.17, 95% CI 1.59 to 2.97, 12 studies, 174,520 participants, high certainty). However, we did not observe a dose-response relationship across increasing obesity classifications for ICU admission and hospitalisation. AUTHORS' CONCLUSIONS: Our findings suggest that obesity is an important independent prognostic factor in the setting of COVID-19. Consideration of obesity may inform the optimal management and allocation of limited resources in the care of COVID-19 patients.

The effect of the polycystic ovary syndrome and hypothyroidism on the risk of fibrocystic breast changes: a meta-analysis.

This meta-analysis aimed to determine the pooled association between polycystic ovary syndrome (PCOS), hypothyroidism, and fibrocystic breast changes. We searched important databases, including PubMed (Medline), Scopus, Web of Science, and Embase to retrieve all relevant studies published from 1990 to April 2021. The bias risk of selected articles was assessed based on the JBI checklist. Our search strategy yielded a total of 487 articles from the international databases. After screening their full-texts, 6 articles met the inclusion criteria and were considered for meta-analysis. The effect of PCOS on the incidence of fibrocystic breast changes was 2.49 (95% CI 1.85-3.34). Also, the effect of hypothyroidism on the incidence of fibrocystic breast changes was 1.90 (95% CI 0.92-3.93). The results showed that women with PCOS were at higher risks to develop fibrocystic breast changes.

Seroconversion following the first, second, and third dose of SARS-CoV-2 vaccines in immunocompromised population: a systematic review and meta-analysis.

BACKGROUND: Immunocompromised (IC) patients are at higher risk of more severe COVID-19 infections than the general population. Special considerations should be dedicated to such patients. We aimed to investigate the efficacy of COVID-19 vaccines based on the vaccine type and etiology as well as the necessity of booster dose in this high-risk population. MATERIALS AND METHODS: We searched PubMed, Web of Science, and Scopus databases for observational studies published between June 1st, 2020, and September 1st, 2021, which investigated the seroconversion after COVID-19 vaccine administration in adult patients with IC conditions. For investigation of sources of heterogeneity, subgroup analysis and sensitivity analysis were conducted. Statistical analysis was performed using R software. RESULTS: According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, we included 81 articles in the meta-analysis. The overall crude prevalence of seroconversion after the first (n: 7460), second (n: 13,181), and third (n: 909, all population were transplant patients with mRNA vaccine administration) dose administration was 26.17% (95% CI 19.01%, 33.99%, I2 = 97.1%), 57.11% (95% CI: 49.22%, 64.83%, I2 = 98.4%), and 48.65% (95% CI: 34.63%, 62.79%, I2 = 94.4%). Despite the relatively same immunogenicity of mRNA and vector-based vaccines after the first dose, the mRNA vaccines induced higher immunity after the second dose. Regarding the etiologic factor, transplant patients were less likely to develop immunity after both first and second dose rather than patients with malignancy (17.0% vs 37.0% after first dose, P = 0.02; 38.3% vs 72.1% after second dose, P < 0.001) or autoimmune disease (17.0% vs 36.4%, P = 0.04; 38.3% vs 80.2%, P < 0.001). To evaluate the efficacy of the third dose, we observed an increasing trend in transplant patients after the first (17.0%), second (38.3%), and third (48.6%) dose. CONCLUSION: The rising pattern of seroconversion after boosting tends to be promising. In this case, more attention should be devoted to transplant patients who possess the lowest response rate.

Socio-demographic correlates of diabetes self-reporting validity: a study on the adult Kurdish population.

BACKGROUND: In this research, data of the DehPCS study were used to assess the validity of self-reported diabetes based on the reference criteria, including the history of taking oral anti-diabetic drugs, insulin injection, or high fasting blood sugar. METHODS: A cross-sectional analytical study was performed on 4400 participants of the DehPCS study, aged 35-70 years. The reference criteria were oral hypoglycemic drug consumption, insulin injection, and/ or fasting blood sugar ≥126 (mg/dl). The self-reporting diabetes was investigated by well-trained interviewers before the diabetes diagnosis based on the reference criteria. The validity of self-reporting diabetes was assessed using sensitivity, specificity, as well as positive and negative predictive values. Socio-demographic correlates of self-reported agreement were examined by multinomial logistic regression. RESULTS: Three thousand nine hundred ninety-six people participated in this study, and the participation rate was equal to 90.8%. The diabetes prevalence among the study population was 13.1% based on self-reports and 9.7% based on the reference criteria. Five hundred twenty-three participants reported diabetes, 213 (41.28%) of whom did not have it. We found a good agreement of 92.3% with an acceptable kappa value of 65.1% between self-reporting diabetes and the reference criteria. Diabetes self-reporting also guaranteed sensitivity of 78.5%, specificity of 93.9%, as well as the positive and negative predictive values of 58.7% and of 98.0%, respectively. Being female, the higher economic class, the higher body mass index (BMI), and the positive family history of diabetes increased the chance of false positive. Being male, older ages and the moderate economic class increased the chance of false positive. CONCLUSION: Self-reporting diabetes is identified as a relatively valid tool which could fairly determine the diabetes prevalence in epidemiological studies. It should be noted that its validity is influenced by some socio-demographic characteristics.

Circulating amino acids and acylcarnitines correlated with different CAC score ranges in diabetic postmenopausal women using LC-MS/MS based metabolomics approach.

BACKGROUND: Diabetes mellitus (DM) and its cardiovascular disease (CVD) complication are among the most frequent causes of death worldwide. However, the metabolites linking up diabetes and CVD are less understood. In this study, we aimed to evaluate serum acylcarnitines and amino acids in postmenopausal women suffering from diabetes with different severity of CVD and compared them with healthy controls. METHODS: Through a cross-sectional study, samples were collected from postmenopausal women without diabetes and CVD as controls (n = 20), patients with diabetes and without CVD (n = 16), diabetes with low risk of CVD (n = 11), and diabetes with a high risk of CVD (n = 21) referred for CT angiography for any reason. Metabolites were detected by a targeted approach using LC-MS/MS and metabolic -alterations were assessed by applying multivariate statistical analysis. The diagnostic ability of discovered metabolites based on multivariate statistical analysis was evaluated by ROC curve analysis. RESULTS: The study included women aged from 50-80 years with 5-30 years of menopause. The relative concentration of C14:1, C14:2, C16:1, C18:1, and C18:2OH acylcarnitines decreased and C18 acylcarnitine and serine increased in diabetic patients compared to control. Besides, C16:1 and C18:2OH acylcarnitines increased in high-risk CVD diabetic patients compared to no CVD risk diabetic patients. CONCLUSION: Dysregulation of serum acylcarnitines and amino acids profile correlated with different CAC score ranges in diabetic postmenopausal women. (Ethic approval No: IR.TUMS.EMRI.REC.1399.062).

Metabolic signatures of insulin resistance in non-diabetic individuals.

BACKGROUND: Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, we have measured a wide array of metabolites (30 acylcarnitines and 20 amino acids) with the MS/MS and investigated the association of metabolic profile with insulin resistance. METHODS: The study population (n = 403) was randomly chosen from non-diabetic participants of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS 2016). STEPS 2016 is a population-based cross-sectional study conducted periodically on adults aged 18-75 years in 30 provinces of Iran. Participants were divided into two groups according to the optimal cut-off point determined by the Youden index of HOMA-IR for the diagnosis of metabolic syndrome. Associations were investigated using regression models adjusted for age, sex, and body mass index (BMI). RESULTS: People with high IR were significantly younger, and had higher education level, BMI, waist circumference, FPG, HbA1c, ALT, triglyceride, cholesterol, non-HDL cholesterol, uric acid, and a lower HDL-C level. We observed a strong positive association of serum BCAA (valine and leucine), AAA (tyrosine, tryptophan, and phenylalanine), alanine, and C0 (free carnitine) with IR (HOMA-IR); while C18:1 (oleoyl L-carnitine) was inversely correlated with IR. CONCLUSIONS: In the present study, we identified specific metabolites linked to HOMA-IR that improved IR prediction. In summary, our study adds more evidence that a particular metabolomic profile perturbation is associated with metabolic disease and reemphasizes the significance of understanding the biochemistry and physiology which lead to these associations.

The Effect of HIV/AIDS Infection on the Clinical Outcomes of COVID-19: A Meta-Analysis.

PURPOSE: Patients with HIV may be more likely to become severely ill from COVID-19. The present meta-analysis aims to determine the impact of HIV/AIDS infection on the clinical outcomes of COVID-19. METHODS: A comprehensive literature search was performed to identify relevant cohort studies to evaluate the association of HIV/AIDS infection with clinical outcomes of COVID-19. International databases, including PubMed (Medline), Web of Sciences, Scopus, and Embase, were searched from the emergence of the COVID-19 pandemic until January 2022. We utilized the risk ratio (RR) with its 95% confidence interval (95% CI) to quantify the effect of cohort studies. RESULTS: Twelve cohort studies were included in this meta-analysis, which examined a total number of 17,786,384 patients. Among them, 40,386 were identified to be HIV positive, and 17,745,998 were HIV negative. The pooled analyses showed HIV positive patients who were co-infected with SARS-CoV-2 were 58% more likely to develop a fever (RR=1.58; 95% CI: 1.42, 1.75), 24% more likely to have dyspnea (RR=1.24; 95% CI: 1.08, 1.41), 45% more likely to be admitted to ICU (RR=1.45; 95% CI: 1.26, 1.67), and 37% more likely to die from to COVID-19 (RR=1.37; 95% CI: 1.30, 1.45) than HIV negative patients. CONCLUSION: HIV/AIDS coinfection with COVID 19 increased the risk of fever, dyspnea, ICU admission, and mortality.

Systematic review and meta-analysis of randomized clinical trials comparing efficacy, safety, and satisfaction between ablative and non-ablative lasers in facial and hand rejuvenation/resurfacing.

Skin aging inevitably begins from the very early days of life. The lasers used in skin rejuvenation are mainly of two types: ablative and non-ablative. This meta-analysis aimed at comparing ablative with non-ablative lasers in terms of their efficacy and safety in skin rejuvenation. Articles published by March 15, 2020 in Embase, Medline (PubMed), Scopus, Cochrane, and clinicalTrials.gov were searched. The inclusion criteria included randomized controlled clinical trials (RCTs) in English using ablative and non-ablative lasers and comparing their safety and efficiency in wrinkle improvement and photoaging therapy. Out of 1353 extracted articles, 11 were selected for qualitative synthesis and of these, 4 were quantitatively analyzed. Different modes of various lasers were implemented; the ablative lasers included Erbium: yttrium-aluminium-garnet (Er:YAG) and CO2, besides the non-ablative lasers, comprised Ytterbium/Erbium, Erbium: Glass, neodymium: yttrium-aluminum-garnet (Nd:YAG), and alexandrite. Pooled analyses on 124 participants showed insignificant differences between ablative and non-ablative lasers in the likelihood of excellent improvement with an odds ratio of 0.83 (95% CI: 0.24, 2.83). The analyses also showed good improvement with an odds ratio of 0.88 (95% CI: 0.44, 1.78), fair improvement with an odds ratio of 1.13 (95% CI: 0.56, 2.26) and side effects with an odds ratio of 0.82 (95% CI: 0.43, 1.56). The efficacy and safety of ablative laser were not higher than those of non-ablative laser in skin rejuvenation. Given the small samples of the included articles, it is recommended that further high-quality RCTs be conducted using larger samples to confirm this conclusion.

WT1 and ACE mRNAs of blood extracellular vesicle as biomarkers of diabetic nephropathy.

BACKGROUND: Diabetic nephropathy (DN) has an increasing global prevalence with excessive health expenditure and burden. Exosomal mRNAs regulate intercellular communications and participate in the pathogenesis of various disorders like DN. This study aimed to assess the expression levels of ACE, ELMO1, and WT1 mRNAs in the blood extracellular vesicles (EVs) of DN patients and diabetic patients without nephropathy (DM group) in comparison to healthy controls and investigate their correlations with the severity of DN. METHODS: The performed investigation is a cross-sectional study of 256 participants including 103 DN patients, 100 DM patients, and 53 healthy controls. The quantification of WT1, ACE, and ELMO1 mRNAs in the blood EVs were executed using qRT-PCR. The ROC analysis was performed to determine the diagnostic accuracy of mRNAs. RESULTS: DN patients had significantly higher expressed WT1 mRNA (1.70-fold change) and lower expressed ACE mRNA (0.55-fold change) in the blood EVs compared to DM patients and controls. ELMO1 mRNA was not expressed in EVs of any groups. A positive correlation between WT1 mRNA level and urine Alb/Cr ratio (r = 0.602, p < 0.001) and a negative correlation between ACE mRNA expression and urine Alb/Cr ratio within DN patients (r = - 0.474, p < 0.001) was identified. The accuracy of WT1 mRNA and 1/ACE mRNA for predicting incipient DN was 0.63 (95% CI 0.55, 0.72) and 0.62 (95% CI 0.54, 0.71), and for predicting overt DN was 0.83 (95% CI 0.74, 0.92) and 0.75 (95% CI 0.66, 0.83), respectively. CONCLUSIONS: WT1 and ACE mRNAs level in blood EVs were predictors for early diagnosis of DN therefore their quantifications might be used to determine the severity of albuminuria and glomerular injuries.

The association between ATM variants and risk of breast cancer: a systematic review and meta-analysis.

BACKGROUND: Ataxia telangiectasia-mutated (ATM) gene contributes to repair damaged DNA and to regulate cell cycle; therefore, ATM variants seem to increase breast cancer risk; however, the results are controversial. So we conducted a systematic review and meta-analysis to clarify the pooled association between various ATM variants and the risk of breast cancer. METHODS: The relevant studies were searched through Scopus, Web of Science, PubMed and Cochrane. Stratified and subgroup analyses were performed to explore heterogeneity between studies and assess effects of study quality. The pooled estimates logarithm with standard error logarithm of odds ratio and relative risk with confidence interval were calculated. RESULTS: This study revealed that there is association between ATM variants and the risk of breast cancer; according to the seven adjusted case-control studies, OR of this association was estimated as 1.67 (95%CI: 0.73-3.82), according to nine unadjusted case-control studies, the crude OR was 2.27 (95% CI: 1.17-4.40) and according to two cohorts, the RR was estimated as 1.68 (95% CI: 1.17-2.40). CONCLUSIONS: The ATM variants are associated with an increased risk of breast cancer that ATM V2424G mutation is detected as the most predisposing factor while ATM D1853V, L546V, and S707P variants have the least predictive ability.

Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with rising incidence and with 5-years overall survival of less than 8%. PDAC creates an immune-suppressive tumor microenvironment to escape immune-mediated eradication. Regulatory T (Treg) cells and myeloid-derived suppressor cells (MDSC) are critical components of the immune-suppressive tumor microenvironment. Shifting from tumor escape or tolerance to elimination is the major challenge in the treatment of PDAC. RESULTS: In a mathematical model, we combine distinct treatment modalities for PDAC, including 5-FU chemotherapy and anti- CD25 immunotherapy to improve clinical outcome and therapeutic efficacy. To address and optimize 5-FU and anti- CD25 treatment (to suppress MDSCs and Tregs, respectively) schedule in-silico and simultaneously unravel the processes driving therapeutic responses, we designed an in vivo calibrated mathematical model of tumor-immune system (TIS) interactions. We designed a user-friendly graphical user interface (GUI) unit which is configurable for treatment timings to implement an in-silico clinical trial to test different timings of both 5-FU and anti- CD25 therapies. By optimizing combination regimens, we improved treatment efficacy. In-silico assessment of 5-FU and anti- CD25 combination therapy for PDAC significantly showed better treatment outcomes when compared to 5-FU and anti- CD25 therapies separately. Due to imprecise, missing, or incomplete experimental data, the kinetic parameters of the TIS model are uncertain that this can be captured by the fuzzy theorem. We have predicted the uncertainty band of cell/cytokines dynamics based on the parametric uncertainty, and we have shown the effect of the treatments on the displacement of the uncertainty band of the cells/cytokines. We performed global sensitivity analysis methods to identify the most influential kinetic parameters and simulate the effect of the perturbation on kinetic parameters on the dynamics of cells/cytokines. CONCLUSION: Our findings outline a rational approach to therapy optimization with meaningful consequences for how we effectively design treatment schedules (timing) to maximize their success, and how we treat PDAC with combined 5-FU and anti- CD25 therapies. Our data revealed that a synergistic combinatorial regimen targeting the Tregs and MDSCs in both crisp and fuzzy settings of model parameters can lead to tumor eradication.

Association of circulating omega 3, 6 and 9 fatty acids with gestational diabetes mellitus: a systematic review.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with increased risks of disease for mother and child during pregnancy and after that. Early diagnosis of GDM would promote both maternal and fetal health. Metabolomics can simplify and develop our understanding of the etiology, manifestation, or pathophysiology of the disease. This systematic review investigates the association of circulating omega 3, 6, and 9 fatty acids with GDM. METHODS: We conducted a systematic search of PubMed, Scopus, Web of Science, and EMBASE databases up to May 8, 2020, using the key term combinations of all types of omega fatty acids with gestational diabetes mellitus. Additional articles were identified through searching the reference lists of included studies. RESULTS: This systematic review included 15 articles. Five were cohort studies, four included nested case-control studies and four were case-control studies. The results of this study demonstrate an increasing trend in the amount of oleic acid and palmitoleic acid in the second trimester and an increase in decosahexanoic acid in the third trimester of GDM mothers. The changes in other fatty acids of interest are either not significant or if significant, their results are inconsistent with the other existing articles. CONCLUSIONS: Omega fatty acids, as potential biomarkers, are considered to be associated with GDM risk and thus provide useful information regarding the prevention and early diagnosis of GDM. Moreover, existing metabolomic studies on GDM are shown to provide conflicting results about metabolite profile characteristics. This systematic review was registered at PROSPERO ( www.crd.york.ac.uk/PROSPERO ) as CRD42020196122.

Evaluation of Reinfection in COVID-19 Patients in the World: A Narrative Review.

Background: The evaluation of reinfection and the genetic structure of all human and virus genomes could help to develop programs and protocols for providing services and ultimately to prevent the disease by producing more effective vaccines. Therefore, the aim of this study was to investigate the presence and occurrence of COVID-19 reinfection through a narrative review study. Methods: We searched the Medline (PubMed), Embase, Scopus, Web of Science, Cochrane library, Ovid, and CINHAL databases. Inclusion criteria included all studies whose main purpose was to provide information about the occurrence or presence of reinfection in patients with COVID-19. An independent samples t test was used to compare the continuous outcomes between the 2 groups. Results: The mean duration of the first episode in the group with mild or moderate COVID-19 was 24.42±1.67 days, and it was 21.80±3.79 days in the group with severe COVID-19. The mean duration of the second episode (reinfection) in patients with mild or moderate form was 15.38 ± 5.57 days, and it was 19.20±2.98 days in patients with severe form. In both episodes, the duration of the disease did not significantly differ between the 2 groups (p=0.484 in the first episode; p=0.675 in the second episode), but the interval to the occurrence of reinfection in patients with the mild or moderate form was significantly longer than those with the severe form (p<0.001). In this instance, the time interval in patients with the mild or moderate form was 36.63±5.71 days while in those with the severe form of the disease it was 29.70±5.65 days. Besides, the genomes of the viruses isolated from the first and second episode were different. Conclusion: According to the results, all patients should be very careful about the severity of the second episode because of the more need for medical interventions for saving the patients. The interval between the first end and the second episode as well as the duration of each episode is highly important for better management of the disease.

Global scientific output trend for Akkermansia muciniphila research: a bibliometric and scientometric analysis.

BACKGROUND: Akkermansia muciniphila is an anaerobic bacterium residing in the healthy intestinal tract of host and its quantity has a negative correlation with various host diseases. This study for the first time provides a holistic bibliometric aspect of Akkermansi muciniphila research in the literature and shows the hot topic terms of these articles in any period of time. METHODS: Scopus database was selected to retrieve documents relevant to Akkermansia muciniphila in any language up to 2019. The bibliometric profile of Akkermansia muciniphila articles including subject area, year distribution, citations, institutions, journals, authors, and countries was systematically characterized and the collaboration networks of authors and countries as well as the burst detection algorithm of the words in the titles, abstracts and keywords were visualized. RESULTS: There is a progressive growing trend in research on Akkermansia from 2004 to 2019 with a total of 566 articles during this period. Out of 353 original articles, there are 194 animal studies (155 studies on mice) and 112 human studies. Also, 65 various diseases were investigated in these studies. The most focused conditions are obesity (71 articles) and type2 diabetes (39 articles). The United States is the leading country on Akkermansia publications (n = 132), followed by China (n = 95). Frontiers in Microbiology is the most dominant journal with 23 Akkermansia publications. In addition, "cancer" is the hot topic of recent Akkermansia research. CONCLUSION: Akkermansia research is of progressive interest during the last decade and the studies on this subject move towards its relationship with cancer and its promising effect on health.

32-Year Scientometric analysis of the Medical Journal of the Islamic Republic of Iran.

Background: Of scientometric goals are to explore scientific productivity and trend, elicit scientific collaborations and inter/intra and cross disciplinary relations within a realm of study. This is a descriptive scientometric analysis of Medical Journal of the Islamic Republic of Iran (MJIRI) from 1987 to 2018. Methods: The data were collected from 1987 to 2018 including the MJIRI annual publication number, annual growth rate (AGR), annual citation indicators, annual degree of collaboration (DC), the most active universities, and the most co-occurred keywords being used in MJIRI articles. Results: MJIRI has published 2166 articles in the field of health and medicine between 1987 and 2018, over a third of which have been published during the last five years (2014-2018). The highest and lowest AGR were recorded in 2014 (AGR=276.190%) and 2001(AGR=-28.75%), respectively. The journal CiteScore has increased from 0.26 in 2013 to 0.94 in 2018; the SCImago Journal Rank has promoted from 0.123 in 2013 to 0.320 in 2018. The Source Normalized Impact per Paper has enhanced from 0.398 in 2013 to 0.552 in 2018. The overall degree of collaboration of MJIRI articles was 0.89. Also, the most co-occurred keywords pertaining to the specific field of medicine were "Breast cancer", "Pregnancy", "Tuberculosis", and "Hypertension". Conclusion: The current quantitative evaluation of MJIRI provides a holistic landscape of journal performance for 32 years.

Bibliometric analysis of global scientific research on Coronavirus (COVID-19).

Background: Since the outbreak of the novel coronavirus disease from Wuhan, China, in early December 2019, many scientists focused on this infection to find a way to deal with it. Due to the dramatic scientific growth in this field, we conducted a scientometric study to gain a better understanding of the scientific literature on COVID-19. Methods: We extracted all COVID-19 documents indexed in the Scopus from December 1, 2019, to April 1, 2020, without any language limitation and determined their bibliometric characteristics, including document type, open accessibility status, citation counting, H-index, top cited documents, the most productive countries, institutions and journals, international collaboration, the most frequent terms and keywords, journal bibliographic coupling and cocitations. Results: A total of 923 documents on COVID-19 were retrieved, of which 418 were original articles. All documents had received 2551 citations with an average citation of 2.76 per document and an h-index of 23. China ranked first with 348 documents, followed by the United States (n = 160). The Lancet and BMJ Clinical Research Ed published the most documents (each with 74 documents) and 2 institutions (University of Hong Kong and Huazhong University of Science and Technology) ranked first in this regard. In addition, the present study analyzed the top 25 highly-cited documents (those that had received 70% of all citations). Conclusion: This study highlighted the focused subjects on various aspects of COVID-19 literature such as pathogenesis, epidemiology, transmission, diagnosis, treatment, prevention, and its complications.

Sperm telomere length in male-factor infertility and reproduction.

The underlying reasons for male-factor infertility are often unknown. 30% of all men have unexplained semen analysis abnormalities. Moreover, 15%-40% of infertile men have normal semen analyses. There have been increasing efforts to identify causes and associations that may explain idiopathic male-factor infertility. Telomeres have become an area of considerable interest in the field because of the essential roles they have in cellular division and genome integrity. Research to date most consistently supports that men with infertility have shorter sperm telomere length (STL); however, associations between shorter STL and meaningful reproductive health outcomes are less consistent. There is a major need for additional studies to better identify the role of STL in male reproductive health and use the information to improve the counseling and treatment of couples with idiopathic male-factor infertility.

Transgenerational effects of paternal exposures: the role of germline de novo mutations.

Germline de novo mutations (DNMs) refer to spontaneous mutations arising during gametogenesis, resulting in genetic changes within germ cells that are subsequently transmitted to the next generation. While the impact of maternal exposures on germline DNMs has been extensively studied, more recent studies have begun to highlight the increasing importance of the effects of paternal factors. In this review, we have summarized the existing literature on how various exposures experienced by fathers affect the germline DNM burden in their spermatozoa, as well as their consequences for semen analysis parameters, pregnancy outcomes, and offspring health. A growing body of literature supports the conclusion that advanced paternal age (APA) correlates with a higher germline DNM rate in offspring. Furthermore, lifestyle choices, environmental toxins, assisted reproductive techniques (ART), and chemotherapy are associated with the accumulation of paternal DNMs in spermatozoa, with deleterious consequences for pregnancy outcomes and offspring health. Ultimately, our review highlights the clear importance of the germline DNM mode of inheritance, and the current understanding of how this is affected by various paternal factors. In addition, we explore conflicting reports or gaps of knowledge that should be addressed in future research.

Bibliometric analysis of publications on trabecular bone score (TBS).

Purpose: Trabecular bone score (TBS), as a texture indicator of bone microarchitecture, predicts the risk of fracture. This study aims to explore the knowledge map of TBS. Methods: We searched Scopus for "trabecular bone score" or "trabecular score" from the beginning to 2021. Our inclusion criteria were original articles and reviews that were related to TBS and our exclusion criteria were non-English articles, non-related to TBS, and document type other than original articles and reviews. and related documents were included for bibliometric analysis. Excel, VOS viewer, and Science of Science (Sci2) software were used for data synthesis. Results: From 749 retrieved articles, 652 articles were included for analysis. These documents were cited 12,153 times and had an H-index of 56. The most productivity belonged to the USA (n = 130 documents), Switzerland (n = 101), and Italy (n = 67). "Osteoporosis International" (n = 80) had the highest participation in publishing. The research topics of interest were mainly related to the applicability of TBS for fracture risk assessment in chronic endocrine disorders such as osteoporosis and diabetes mellitus. Bursting analysis of the title and abstract revealed the initial focus of the discriminative power of TBS for osteoporotic fracture and the more recent focus on comparing bone mineral density (BMD) and TBS in a variety of chronic diseases. Conclusion: The number of annual publications on TBS has increased, especially after 2016. These publications highlight the importance of in-depth knowledge of TBS in predicting fracture risk and also its strengths and limitations of treatment monitoring in different health conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01338-7.

Plasma acylcarnitines and amino acids in dyslipidemia: An integrated metabolomics and machine learning approach.

Purpose: The Discovery of underlying intermediates associated with the development of dyslipidemia results in a better understanding of pathophysiology of dyslipidemia and their modification will be a promising preventive and therapeutic strategy for the management of dyslipidemia. Methods: The entire dataset was selected from the Surveillance of Risk Factors of Noncommunicable Diseases (NCDs) in 30 provinces of Iran (STEPs 2016 Country report in Iran) that included 1200 subjects and was stratified into four binary classes with normal and abnormal cases based on their levels of triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and non-HDL-C.Plasma concentrations of 20 amino acids and 30 acylcarnitines in each class of dyslipidemia were evaluated using Tandem mass spectrometry. Then, these attributes, along with baseline characteristics data, were used to check whether machine learning (ML) algorithms could classify cases and controls. Results: Our ML framework accurately predicts TG binary classes. Among the models tested, the SVM model stood out, performing slightly better with an AUC of 0.81 and a standard deviation of test accuracy at 0.04. Consequently, it was chosen as the optimal model for TG classification. Moreover, the findings showed that alanine, phenylalanine, methionine, C3, C14:2, and C16 had great power in differentiating patients with high TG from normal TG controls. Conclusions: The comprehensive output of this work, along with sex-specific attributes, will improve our understanding of the underlying intermediates involved in dyslipidemia. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-024-01384-9.