Fractal dimension analysis of grey matter in multiple sclerosis

The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of a complex object. Among other applications, FD has been used to identify abnormalities of the human brain in conventional magnetic resonance imaging (MRI), including white matter abnormalities in patients with Multiple Sclerosis (MS). Extensive grey matter (GM) pathology has been recently identified in MS and it appears to be a key factor in long-term disability. The aim of the present work was to assess whether FD measurement of GM in T1 MRI sequences can identify GM abnormalities in patients with MS in the early phase of the disease. A voxel-based morphometry approach optimized for MS was used to obtain the segmented brain, where we later calculated the three-dimensional FD of the GM in MS patients and healthy controls.We found that patients with MS had a significant increase in the FD of the GM compared to controls. Such differences were present even in patients with short disease durations, including patients with first attacks of MS. In addition, the FD of the GM correlated with T1 and T2 lesion load, but not with GM atrophy or disability. The FD abnormalities of the GM here detected differed from the previously published FD of the white matter in MS, suggesting that different pathological processes were taking place in each structure. These results indicate that GM morphology is abnormal in patients with MS and that this alteration appears early in the course of the disease

Predicting relapsing-remitting dynamics in multiple sclerosis using discrete distribution models: a population approach

Background: Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI) as contrast enhancing lesions (CEL). CEL dynamics are considered unpredictable and are characterized by high intra- and inter-patient variability. Here, a population approach (nonlinear mixed-effects models) was applied to analyse of CEL progression, aiming to propose a model that adequately captures CEL dynamics. Methods and Findings: We explored several discrete distribution models to CEL counts observed in nine MS patients undergoing a monthly MRI for 48 months. All patients were enrolled in the study free of immunosuppressive drugs, except for intravenous methylprednisolone or oral prednisone taper for a clinical relapse. Analyses were performed with the nonlinear mixed-effect modelling software NONMEM 7.2. Although several models were able to adequately characterize the observed CEL dynamics, the negative binomial distribution model had the best predictive ability. Significant improvements in fitting were observed when the CEL counts from previous months were incorporated to predict the current month's CEL count. The predictive capacity of the model was validated using a second cohort of fourteen patients who underwent monthly MRIs during 6-months. This analysis also identified and quantified the effect of steroids for the relapse treatment. Conclusions: The model was able to characterize the observed relapsing-remitting CEL dynamic and to quantify the inter-patient variability. Moreover, the nature of the effect of steroid treatment suggested that this therapy helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could be used for design of future longitudinal studies and clinical trials, as well as for the evaluation of new therapies

Soluble and Cell-Associated Insulin Receptor Dysfunction Correlates with Severity of HAND in HIV-Infected Women

Blood sugar metabolism abnormalities have been identified in HIV-infected individuals and associated with HIV-associated neurocognitive disorders (HAND). These abnormalities may occur as a result of chronic HIV infection, long-term use of combined antiretroviral treatment (CART), aging, genetic predisposition, or a combination of these factors, and may increase morbidity and mortality in this population.To determine if changes in soluble and cell-associated insulin receptor (IR) levels, IR substrate-1 (IRS-1) levels, and IRS-1 tyrosine phosphorylation are associated with the presence and severity of HAND in a cohort of HIV-seropositive women.This is a retrospective cross-sectional study using patient database information and stored samples from 34 HIV-seropositive women and 10 controls without history of diabetes from the Hispanic-Latino Longitudinal Cohort of Women. Soluble IR subunits [sIR, ectodomain (α) and full-length or intact (αβ)] were assayed in plasma and CSF samples by ELISA. Membrane IR levels, IRS-1 levels, and IRS-1 tyrosine phosphorylation were analyzed in CSF white cell pellets (WCP) using flow cytometry. HIV-seropositive women had significantly increased levels of intact or full-length sIR in plasma (p<0.001) and CSF (p<0.005) relative to controls. Stratified by HAND, increased levels of full-length sIR in plasma were associated with the presence (p<0.001) and severity (p<0.005) of HAND. A significant decrease in IRS-1 tyrosine-phosphorylation in the WCP was also associated with the presence (p<0.02) and severity (p<0.02) of HAND.This study provides evidence that IR secretion is increased in HIV-seropositive women, and increased IR secretion is associated with cognitive impairment in these women. Thus, IR dysfunction may have a role in the progression of HAND and could represent a biomarker for the presence and severity of HAND

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Pharmacokinetic/Pharmacodynamic modelling during development of novel drugs for the treatment of sleep disorders

The goal of the present work was to describe the sleep effects of the hypnotic drug zolpidem in rats using a semi-mechanistic pharmacokinetic-pharmacodynamic (PK/PD) Markov-chain model. Data were obtained from healthy Sprague-Dawley rats in which EEG was continuously recorded for at least two days of alternating dark/light cycles. For each 10 second interval, EEG data were converted into AWAKE, REM or NREM stages. After a baseline period, methylcellulose (MC), zolpidem at doses of 10, 20 or 30 mg/kg was administered orally. The time course of the nine possible transition probabilities was described using a non-homogeneous Markov chain model based on piecewise multinomial logistic functions. Model building was performed in three steps: (i) baseline data was described first, then (ii) the model accounting for the MC effects was built, finally (iii) the PK/PD model describing zolpidem effects was developed. Exploration of the time course of raw transition probabilities revealed that zolpidem elicited an initial time dependent decrease in the transition probability from NREM to awake, and an increase at later times which is interpreted as a rebound effect. Drug effects including the rebound phenomena were described with a turnover feedback model. The current analysis shows an application of the multinomial logistic approach applied to Markov chain models. The model presented here represents an integrated model including baseline, saline, and drug effect models. This type of approach supports the identification and the quantitative description of feedback mechanisms, and represents a promise approach to extract pharmacodynamic characteristics of different classes of sleep drugs

Predicting relapsing-remitting dynamics in multiple sclerosis using discrete distribution models: a population approach

Background: Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI) as contrast enhancing lesions (CEL). CEL dynamics are considered unpredictable and are characterized by high intra- and inter-patient variability. Here, a population approach (nonlinear mixed-effects models) was applied to analyse of CEL progression, aiming to propose a model that adequately captures CEL dynamics. Methods and Findings: We explored several discrete distribution models to CEL counts observed in nine MS patients undergoing a monthly MRI for 48 months. All patients were enrolled in the study free of immunosuppressive drugs, except for intravenous methylprednisolone or oral prednisone taper for a clinical relapse. Analyses were performed with the nonlinear mixed-effect modelling software NONMEM 7.2. Although several models were able to adequately characterize the observed CEL dynamics, the negative binomial distribution model had the best predictive ability. Significant improvements in fitting were observed when the CEL counts from previous months were incorporated to predict the current month's CEL count. The predictive capacity of the model was validated using a second cohort of fourteen patients who underwent monthly MRIs during 6-months. This analysis also identified and quantified the effect of steroids for the relapse treatment. Conclusions: The model was able to characterize the observed relapsing-remitting CEL dynamic and to quantify the inter-patient variability. Moreover, the nature of the effect of steroid treatment suggested that this therapy helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could be used for design of future longitudinal studies and clinical trials, as well as for the evaluation of new therapies

Gender Associated with the Intention to Choose a Medical Specialty in Medical Students: A Cross-Sectional Study in 11 Countries in Latin America

INTRODUCTION:The selection of a medical specialty has been associated with multiple factors, such as personal preferences, academic exposure, motivational factors and sociodemographic factors, such as gender. The number of women in the medical field has increased in recent years. In Latin America, we have not found any studies that explore this relationship. OBJECTIVE:To determine whether there is an association between gender and the intention to choose a medical specialty in medical students from 11 countries in Latin America. METHODS:Secondary analysis of the Collaborative Working Group for the Research of Human Resources for Health (Red-LIRHUS) data; a multi-country project of students in their first year and fifth year of study, from 63 medical schools in 11 Latin American countries. All students who referred intention to choose a certain medical specialty were considered as participants. RESULTS:Of the 11073 surveyed students, 9235 indicated the name of a specific specialty. The specialties chosen most often in the fifth year were General Surgery (13.0%), Pediatrics (11.0%), Internal Medicine (10.3%) and Obstetrics/Gynecology (9.0%). For women, the top choices were Pediatrics (15.8%), Obstetrics/Gynecology (11.0%), Cardiology (8.7%), General Surgery (8.6%), and Oncology (6.4%). In the adjusted analysis, the female gender was associated with the choice of Obstetrics/Gynecology (RP: 2.75; IC95%: 2.24-3.39); Pediatric Surgery (RP: 2.19; IC95%: 1.19-4.00), Dermatology (RP: 1.91; IC95%:1.24-2.93), Pediatrics (RP: 1.83; IC95%: 1.56-2.17), and Oncology (RP: 1.37; IC95%: 1.10-1.71). CONCLUSIONS:There is an association between the female gender and the intention to choose Obstetrics/Gynecology, Pediatrics, Pediatric Surgery, Dermatology, and Oncology. We recommend conducting studies that consider other factors that can influence the choice of a medical specialty

Impact of COVID-19 on Cardiovascular Testing in the United States Versus the Rest of the World

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-U.S. institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p &lt; 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection