Laplacian Spectral Characterization of Signed Sun Graphs

A sun $SG_{n}$ is a graph of order $2n$ consisting of a cycle $C_{n}$, $n\geq 3$, to each vertex of it a pendant edge is attached. In this paper, we prove that unbalanced signed sun graphs are determined by their Laplacian spectra. Also we show that a balanced signed sun graph is determined by its Laplacian spectrum if and only if $n$ is odd

Does the repeat dose of gonadotropin-releasing hormone agonist trigger in polycystic ovarian syndrome improve in vitro fertilization cycles outcome? A clinical trial study

Background: A repeat dose of Gonadotropin-releasing Hormone (GnRH) agonist could provide long duration of luteinizing hormone (LH) surge and amplitude appropriately. Objective: Improvement in oocyte maturity could be obtained by a repeat dose of GnRH agonist. Materials and Methods: In this randomized double-blinded study, 120 women with polycystic ovarian syndrome and serum estradiol level (E2) > 3000 who were candidate for in vitro fertilization with Antagonist protocol were enrolled between July 2018 and July 2019. Participants were randomized in two groups - and final oocyte maturation was triggered with two doses: In group A, a repeat dose of 0.1 mg, 12 hr. after the first dose and in group B, 0.2 mg SC triptorelin (decapeptyl) 35 hr. prior to oocyte retrieval. Serum Estradiol, LH, and progesterone concentration were measured on the trigger day. Serum LH measurement was done three times in both groups. The outcomes were oocyte yield, meiosis (M) I, MII, Maturity rate, germinal vesicle (GV) rate, 2 pronuclear, embryo yield, ovarian hyper stimulation syndrome rates. Results: Maturity rate (p = 0.89), MI (p = 0.38), MII (p = 0.89), and GV oocytes (p = 0.38) were not statistically different between the two study groups. LH levels measured at 12 hr post-trigger did not relate statistically significant with maturity rate in our participants (p = 0.96). No empty follicular syndrome was reported. Conclusion: Although the second dose of GnRH agonist after 12 hr since the first dose could provide duration of LH surge and amplitude and as a result no empty follicular syndrome was seen, the maturity rate, MI, MII, and GV oocytes were not different between the two study groups. Key words: Polycystic ovarian syndrome, Treatment, In vitro fertilization, Gonadotropin-Releasing hormone

Correction to “Does the repeat dose of gonadotropin-releasing hormone agonist trigger in polycystic ovarian syndrome improve in vitro fertilization cycles outcome? A clinical trial study” [Int J Reprod BioMed 2020; 18: 485-490]

This is a corrigendum to “Does the repeat dose of gonadotropin-releasing hormone agonist trigger in polycystic ovarian syndrome improve in vitro fertilization cycles outcome? A clinical trial study” [Int J Reprod BioMed 2020; 18: 485-490] and does not have an abstract. Please download the PDF or view the article HTML

Applying GMDH artificial neural network to predict dynamic viscosity of an antimicrobial nanofluid

Objective (s): Artificial Neural Networks (ANN) are widely used for predicting systems’ behavior. GMDH is a type of ANNs which has remarkable ability in pattern recognition. The aim the current study is proposing a model to predict dynamic viscosity of silver/water nanofluid which can be used as antimicrobial fluid in several medical purposes.Materials and Methods: In order to have precise model, it is necessary to consider all influential factors. Temperature, concentration and size of nano particles are used as input variables of the model. In addition, GMDH artificial neural network is applied to design a proper model. Data for modeling are extracted from conducted experimental studies published in valuable journals. Results: The dynamic viscosity of Ag/water nanofluid is precisely modeled by using GMDH. The obtained values for R-squared is equal to 0.9996 which indicates perfect precision of the proposed model. In addition, the highest relative deviation for the model is 2.2%. Based on the values of these statistical criteria, the model is acceptable and very accurate. Conclusion: GMDH artificial neural network is reliable approach to predict dynamic viscosity of Ag/water nanofluid by using temperature, concentration and size of particles as input data

A Novel Analytical Framework for Dissecting the Genetic Architecture of Behavioral Symptoms in Neuropsychiatric Disorders

Background: For diagnosis of neuropsychiatric disorders, a categorical classification system is often utilized as a simple way for conceptualizing an often complex clinical picture. This approach provides an unsatisfactory model of mental illness, since in practice patients do not conform to these prototypical diagnostic categories. Family studies show notable familial co-aggregation between schizophrenia and bipolar illness and between schizoaffective disorders and both bipolar disorder and schizophrenia, revealing that mental illness does not conform to such categorical models and is likely to follow a continuum encompassing a spectrum of behavioral symptoms. Results and Methodology: We introduce an analytic framework to dissect the phenotypic heterogeneity present in complex psychiatric disorders based on the conceptual paradigm of a continuum of psychosis. The approach identifies subgroups of behavioral symptoms that are likely to be phenotypically and genetically homogenous. We have evaluated this approach through analysis of simulated data with simulated behavioral traits and predisposing genetic factors. We also apply this approach to a psychiatric dataset of a genome scan for schizophrenia for which extensive behavioral information was collected for each individual patient and their families. With this approach, we identified significant evidence for linkage among depressed individuals with two distinct symptom profiles, that is individuals with sleep disturbance symptoms with linkage on chromosome 2q13 and also a mutually exclusive group of individuals with symptoms of concentration problems with linkage on chromosome 2q35. In addition we identified a subset of individuals with schizophrenia defined by language disturbances with linkage to chromosome 2p25.1 and a group of patients with a phenotype intermediate between those of schizophrenia and schizoaffective disorder with linkage to chromosome 2p21. Conclusions: The findings presented are novel and demonstrate the efficacy of this approach in detection of genes underlying such complex human disorders as schizophrenia and depression

Association of interleukin-6 with suicidal ideation in veterans: a longitudinal perspective

IntroductionStudies showing associations between inflammation in suicide are typically cross-sectional. Present study investigated how cytokine levels track with suicidal ideation and severity longitudinally.MethodsVeterans with a diagnosis of major depressive disorder (MDD) with or without suicide attempt history (MDD/SA n = 38, MDD/NS n = 41) and non-psychiatric non-attempter controls (HC n = 33) were recruited, MDD/SA and HC groups were followed longitudinally at 3 months and 6 months. Blood plasma was collected and processed using Luminex Immunology Multiplex technology.ResultsSignificant differences in depression severity (BDI) and suicidal ideation severity (SSI) were observed across all groups at study entry, wherein MDD/SA group had the highest scores followed by MDD/NS and HC, respectively. Cytokines IL-1β, IL-4, TNF-α, IFN-γ, and IL-6 were examined at study entry and longitudinally, with IL6 levels differing significantly across the groups (p = 0.0123) at study entry. Significant differences in changes in cytokine levels between depressed attempters and the control group were detected for IL-6 (interaction F1,91.77 = 5.58, p = 0.0203) and TNF-α (F1,101.73 = 4.69, p = 0.0327). However, only depressed attempters showed a significant change, in IL-6 and TNF-α levels, decreasing over time [IL-6: b = −0.04, 95% CI = (−0.08, −0.01), p = 0.0245 and TNF-α: b = −0.02, 95% CI = (−0.04, −0.01), p = 0.0196]. Although IL-6 levels were not predictive of suicidal ideation presence [OR = 1.34, 95% CI = (0.77, 2.33), p = 0.3067], IL-6 levels were significantly associated with suicidal ideation severity (b = 0.19, p = 0.0422).DiscussionIL-6 was not associated with presence of suicidal ideation. IL-6 however, was associated with severity of ideation, suggesting that IL-6 may be useful in clinical practice, as an objective marker of heightened suicide risk

Self-supervised Learning for Segmentation and Quantification of Dopamine Neurons in Parkinson's Disease

Parkinson's Disease (PD) is the second most common neurodegenerative disease in humans. PD is characterized by the gradual loss of dopaminergic neurons in the Substantia Nigra (SN). Counting the number of dopaminergic neurons in the SN is one of the most important indexes in evaluating drug efficacy in PD animal models. Currently, analyzing and quantifying dopaminergic neurons is conducted manually by experts through analysis of digital pathology images which is laborious, time-consuming, and highly subjective. As such, a reliable and unbiased automated system is demanded for the quantification of dopaminergic neurons in digital pathology images. Recent years have seen a surge in adopting deep learning solutions in medical image processing. However, developing high-performing deep learning models hinges on the availability of large-scale, high-quality annotated data, which can be expensive to acquire, especially in applications like digital pathology image analysis. To this end, we propose an end-to-end deep learning framework based on self-supervised learning for the segmentation and quantification of dopaminergic neurons in PD animal models. To the best of our knowledge, this is the first deep learning model that detects the cell body of dopaminergic neurons, counts the number of dopaminergic neurons, and provides characteristics of individual dopaminergic neurons as a numerical output. Extensive experiments demonstrate the effectiveness of our model in quantifying neurons with high precision, which can provide a faster turnaround for drug efficacy studies, better understanding of dopaminergic neuronal health status, and unbiased results in PD pre-clinical research. As part of our contributions, we also provide the first publicly available dataset of histology digital images along with expert annotations for the segmentation of TH-positive DA neuronal soma

Supplemental irrigation management of rainfed grapevines under drought conditions using the CropSyst model

Aim of study: To determine how much water should be used and when it should be applied in rain-fed grapevine using a cropping system simulation model (CropSyst), and also the economic analysis of supplemental irrigation for rainfed grapevine.Area of study: This study was conducted at the School of Agriculture, Shiraz University, Shiraz, Iran, in 2012, 2013 and 2014.Material and methods: The CropSyst model was calibrated to predict the rainfed yields of ‘Askari’ and ‘Yaghooti’ grapevines in different climates using four amounts of SI: 250 L (I1), 500 L (I2), 1000 L (I3) and 0 (I4), five SI times: single in March (T1), single in April (T2), single in March + single in April (T3), single in May (T4) and single in June (T5).Main results: Treatment T3 increased the average simulated yield of ‘Askari’ by 15% to 40% at regions with P/ETo>0.6, 17% to 61% at 0.2<P/ETO<0.6, and 26% to 61% at P/ETO<0.2, while in ‘Yaghooti’ it increased about 2% to 41% at regions with P/ETo>0.6, 4% to 36% at 0.2<P/ETO<0.6 and 2% to 26% at P/ETO<0.2. By increasing the water price by 30% and 50%, net benefits for the ‘Askari’ decreased by about 31% and 54%, while 6% and 18%, for ‘Yaghooti’ respectively.Research highlights: The CropSyst model can successfully predict soil water content and grapevine yields. Application of SI in May increased significantly the grapevine yield as compared to other SI times

Visual Outcomes of Adding Erythropoietin to Methylprednisolone for Treatment of Retrobulbar Optic Neuritis

Purpose: To compare the short-term visual function results and safety of erythropoietin as an add-on to the standard corticosteroid therapy in retrobulbar optic neuritis (RON). Methods: In this prospective pilot study, adult patients with isolated RON with less than 10 days of onset were enrolled. Patients were consecutively assigned to standard intravenous methylprednisolone treatment either in combination with intravenous erythropoietin (20,000 units/day for three days) (group-1) or alone (group-2). Primary outcome measure was best-corrected visual acuity (BCVA), which was assessed up to 120 days from the day the treatment was begun. Systemic evaluations were performed during and after treatment. Results: Sixty-two patients with RON (mean age = 26.6 ± 5.77 years; range = 18–40 years) were enrolled into the study (group-1, n = 35; group-2, n = 27). BCVA three months after the treatment was 0.19 ± 0.55 logMAR and 0.11 ± 0.32 logMAR in group-1 and group-2, respectively (95% CI: –0.61–0.16; P = 0.62). Change in BCVA after three months was 2.84 ± 3.49 logMAR in group-1 and 2.46 ± 1.40 logMAR in group-2 (95% CI: –0.93–1.91; P = 0.57). Pace of recovery was not significantly different between the groups. No complications were detected among patients. Conclusion: Intravenous erythropoietin as an add-on did not significantly improve the visual outcome in terms of visual acuity, visual field, and contrast sensitivity compared to traditional intravenous corticosteroid. This pilot study supports the safety profile of intravenous human recombinant erythropoietin, and it may help formulate future investigations with a larger sample size

Comparison of Physical Fitness among Smoker and Non-Smoker Men

Background: It is well documented that cigarette smoking has negative impacts on body health, as well as social health, economy, culture, etc. Nowadays, there is a large body of evidence that smoking is the cause of numerous life-threatening diseases like cardiovascular and pulmonary diseases along with different kinds of cancer. The aim of this study was to compare the physical fitness of smokers and non smokers.Methods: This cross-sectional study was conducted on 64 non-sportsmen (34 non-smokers and 30 smokers) aging 19–27 years. Both groups were matched for age, weight, height and body mass index (BMI). The smokers used cigarettes at least 5 cigarettes a day for 2 years. None of them had a musculoskeletal disease. We used a questionnaire and physical fitness tests for data gathering. The tests were used to measure muscle strength, endurance, speed, agility and flexibility in both groups.Findings: The muscle strength was significantly different in smokers and non-smokers (P = 0.012). Moreover, smokers had less agility (P = 0.004) and speed (P = 0.008) than non-smokers. However, although smokers were weaker than non- smokers, the differences in muscle endurance (P = 0.066) and flexibility (P = 0.095) were not the statistically significant.Conclusion: According to these results, the smokers were less powerful than nonsmokers. In addition, physical activity skills in young smokers were decreased. Therefore, smoking will cause a gradual loss of physical strength and active personal and social power. Keywords: Tobacco, Physical fitness, Muscle