Inferring causal molecular networks: empirical assessment through a community-based effort.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Sexual side effects of 5-α-reductase inhibitors finasteride and dutasteride: A comprehensive review

The 5-α-reductase inhibitors finasteride and dutasteride are frequently used in the treatment of androgenetic alopecia and benign prostatichyperplasia. These drugs are effective at reducing levels of dihydrotestosterone, the primary androgen responsible for the pathogenesis of both these conditions. However, finasteride and dutasteride have also been shown to produce an increase in the incidence of sexual dysfunction, namely, impotence, decreased libido, and ejaculation disorder. The purpose of this study is to review the existing medical literature with regard to the sexual side effects of 5-α-reductase inhibitor therapy. This review is an extensive look at the sexual effects of 5-α-reductase inhibitors and compares outcomes for finasteride versus dutasteride in addition to comparing sexualside effects for each of the different dosages prescribed of finasteride and dutasteride

Healthcare utilization and cost outcomes for a multicenter first seizure and new onset epilepsy clinic.

RATIONALE: A First Seizure/New Onset Epilepsy (FS/NOE) protocol was implemented to ensure proper evaluation by an epileptologist and improve overall care for patients. We compared healthcare utilization and cost incurred by patients pre and post protocol implementation. METHODS: Clinical data were retrospectively collected from the EMR and cost data from the financial database. Patients were identified by FS event and grouped into either the pre-implementation (pre-FSC) or post-implementation cohort (post-FSC). Pre-FSC patients were seen between January 2014-December 2015 and post-FSC between March 2016-January 2018. Utilization outcomes include time from FS to neurology appointment, MRI, and electroencephalogram (EEG). Cost outcomes included the annualized median difference in pre versus post costs for ER, inpatient, outpatient or ambulatory, and total hospital services. Cost and utilization outcomes were collected within 90 days or 6 months post first-seizure event. Pre and post cohorts were compared using Kaplan-Meier analysis and Cox proportional hazard models for time-to-event outcomes, multivariable median regression models for cost differences and negative binomial regression models for utilization analyses. Models were adjusted for age, sex, health insurance, and comorbidities. RESULTS: One-hundred and fifty six patients were included with 84 (53.8%) pre- and 72 (46.2%) post-FSC patients. Kaplan-Meier and Cox regression results indicated post-FSC patients had significantly faster time-to-first neurology appointment (5.0 vs. 20.9 days, p \u3c .001; Adjusted Hazard Ratio (HR) = 5.98, p \u3c .001), time-to-MRI (9.0 vs. 27.0 days; p = 0.005; HR = 1.88, p = .021) and EEG (3.6 vs. 48.6 days, p \u3c .001; HR = 9.01, p \u3c .001). A total of 138 patients had at least one cost in the financial database. For 6-month follow-up period, post-FSC patients had higher adjusted all-cause total median costs (+$830, p = 0.009) and outpatient costs (+$1203, p \u3c .001) but lower ED costs (-245, p = 0.073), not significant. Results were similar for seizure-related costs. Similarly, Post-FSC patients had a significantly higher likelihood of all-cause (Adjusted Rate Ratio (ARR) = 1.41, p = .029) and outpatient utilization (ARR = 1.72, p = .008) but lower ED utilization (ARR = 0.54, p \u3c .001). CONCLUSIONS: Implementation of the FSC decreased time to evaluation by a neurologist and time to diagnostic workup. Ultimately, total healthcare costs and ambulatory costs increased but ED costs and utilization were reduced. It is our hypothesis that faster access to initial care and diagnosis would result in better control of seizures and reduce long-term costs and utilization. Further research over a longer duration of time across a broader population is needed to evaluate the full implications of an epilepsy specialist-populated FSC

Alopecia Areata: Review of Epidemiology, Clinical Features, Pathogenesis, and New Treatment Options

Alopecia areata (AA) is a complex autoimmune condition that causes nonscarring hair loss. It typically presents with sharply demarcated round patches of hair loss and may present at any age. In this article, we review the epidemiology, clinical features, pathogenesis, and new treatment options of AA, with a focus on the immunologic mechanism underlying the treatment. While traditional treatment options such as corticosteroids are moderately effective, a better understanding of the disease pathogenesis may lead to the development of new treatments that are more directed and effective against AA. Sources were gathered from PubMed, Embase, and the Cochrane database using the keywords: alopecia, alopecia areata, hair loss, trichoscopy, treatments, pathogenesis, and epidemiology

Generalized periodic discharges and 'triphasic waves': A blinded evaluation of inter-rater agreement and clinical significance

Objectives: Generalized periodic discharges (GPDs) are associated with nonconvulsive seizures. Triphasic waves (TWs), a subtype of GPDs, have been described in relation to metabolic encephalopathy and not felt to be associated with seizures. We sought to establish the consistency of use of this descriptive term and its association with seizures. Methods: 11 experts in continuous EEG monitoring scored 20 cEEG samples containing GPDs using Standardized Critical Care EEG Terminology. In the absence of patient information, the inter-rater agreement (IRA) for EEG descriptors including TWs was assessed along with raters' clinical EEG interpretation and compared with actual patient information. Results: The IRA for 'generalized' and 'periodic' was near-perfect (kappa = 0.81), but fair for 'triphasic' (kappa = 0.33). Patients with TWs were as likely to develop seizures as those without (25% vs 26%, N.S.) and surprisingly, patients with TWs were less likely to have toxic-metabolic encephalopathy than those without TWs (55% vs 79%, p < 0.01). Conclusions: While IRA for the terms "generalized" and "periodic" is high, it is only fair for TWs. EEG interpreted as TWs presents similar risk for seizures as GPDs without triphasic appearance. GPDs are commonly associated with metabolic encephalopathy, but 'triphasic' appearance is not predictive. Significance: Conventional association of 'triphasic waves' with specific clinical conditions may lead to inaccurate EEG interpretation.SCOPUS: ar.jinfo:eu-repo/semantics/publishe