The clinical features of the piriformis syndrome: a systematic review

Piriformis syndrome, sciatica caused by compression of the sciatic nerve by the piriformis muscle, has been described for over 70 years; yet, it remains controversial. The literature consists mainly of case series and narrative reviews. The objectives of the study were: first, to make the best use of existing evidence to estimate the frequencies of clinical features in patients reported to have PS; second, to identify future research questions. A systematic review was conducted of any study type that reported extractable data relevant to diagnosis. The search included all studies up to 1 March 2008 in four databases: AMED, CINAHL, Embase and Medline. Screening, data extraction and analysis were all performed independently by two reviewers. A total of 55 studies were included: 51 individual and 3 aggregated data studies, and 1 combined study. The most common features found were: buttock pain, external tenderness over the greater sciatic notch, aggravation of the pain through sitting and augmentation of the pain with manoeuvres that increase piriformis muscle tension. Future research could start with comparing the frequencies of these features in sciatica patients with and without disc herniation or spinal stenosis

Can incontinence be cured? A systematic review of cure rates

Background Incontinence constitutes a major health problem affecting millions of people worldwide. The present study aims to assess cure rates from treating urinary (UI) or fecal incontinence (FI) and the number of people who may remain dependent on containment strategies. Methods Medline, Embase, PsycINFO, Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL, and PEDro were searched from January 2005 to June 2015. Supplementary searches included conference abstracts and trials registers (2013–2015). Included studies had patients ≥ 18 years with UI or FI, reported treatment cure or success rates, had ≥ 50 patients treated with any intervention recognized in international guideline algorithms, a follow-up ≥ 3 months, and were published from 2005 onwards. Title and abstract screening, full paper screening, data extraction and risk-of-bias assessment were performed independently by two reviewers. Disagreements were resolved through discussion or referral to a third reviewer where necessary. A narrative summary of included studies is presented. Results Most evidence was found for UI: Surgical interventions for stress UI showed a median cure rate of 82.3% (interquartile range (IQR), 72–89.5%); people with urgency UI were mostly treated using medications (median cure rate for antimuscarinics = 49%; IQR, 35.6–58%). Pelvic floor muscle training and bulking agents showed lower cure rates for UI. Sacral neuromodulation for FI had a median cure rate of 38.6% (IQR, 35.6–40.6%). Conclusions Many individuals were not cured and hence may continue to rely on containment. No studies were found assessing success of containment strategies. There was a lack of data in the disabled and in those with neurological diseases, in the elderly and those with cognitive impairment. Surgical interventions were effective for stress UI. Other interventions for UI and FI showed lower cure rates. Many individuals are likely to be reliant on containment strategies

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Conformations and three-dimensional structures of selected SARS-CoV-2 drug candidates

Quantum mechanical theories are used to search and optimized the conformations of proposed small molecule candidates for treatment of SARS-CoV-2. These candidate compounds are taken from what is reported in the news and in other pre-peer-reviewed literature (e.g. ChemRxiv, bioRxiv). The goal herein is to provided predicted structures and relative conformational stabilities for selected drug and ligand candidates, in the hopes that other research groups can make use of them for developing a treatment

Mathematics Meets Chemistry - Workflow-guided Evolving Software for Molecular Modelling

Computational chemistry began with the birth of computers in the mid 1900s, and its growth has been directly coupled to the technological advances made in computer science and high-performance computing. A popular goal within the field, be it Newtonian or quantum based methods, is the accurate modelling of physical forces and energetics through mathematics and algorithm design. Through reliable modelling of the underlying forces, molecular simulations frequently provide atomistic insights into macroscopic experimental observations

Principal component and clustering analysis on molecular dynamics data of the ribosomal L11·23S subdomain

With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria’s L11·23S ribosomal subdomain, which is a target of thiopeptide antibiotics. Clustering was performed, using K-means and average-linkage algorithms, on data involving the first two to the first five PC subspace dimensions. For the average-linkage algorithm we found that data-point membership, cluster shape, and cluster size depended on the selected PC subspace data. In contrast, K-means provided very consistent results regardless of the selected subspace. Since we present results on a single model system, generalization concerning the clustering of different PC subspaces of other molecular systems is currently premature. However, our hope is that this study illustrates a) the complexities in selecting the appropriate clustering algorithm, b) the complexities in interpreting and validating their results, and c) by combining PC analysis with subsequent clustering valuable dynamic and conformational information can be obtained. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00894-012-1563-4) contains supplementary material, which is available to authorized users

A modern workflow for force-field development – Bridging quantum mechanics and atomistic computational models

In this article we present our recent efforts in designing a comprehensive consistent scientific workflow, nicknamed Wolf2 Pack, for force-field optimization in the field of computational chemistry. Atomistic force fields represent a multiscale bridge that connects high-resolution quantum mechanics knowledge to coarser molecular mechanics-based models. Force-field optimization has so far been a time-consuming and error-prone process, and is a topic where the use of a scientific workflow can provide obvious great benefits. As a case study we generate a gas-phase force field for methanol using Wolf2 Pack, with special attention given toward deriving partial atomic charges