Clinical Significance of D-dimer Level and Numeric Rating Scale with Amount of Sinus Involvement in Cerebral Sinus Thrombosis Patients

Lisda Amalia, Ryan Tantri Ardo Department of Neurology, Medical Faculty, Universitas Padjadjaran/Hasan Sadikin General Hospital, Bandung, IndonesiaCorrespondence: Lisda Amalia, Department of Neurology, Medical Faculty, Universitas Padjadjaran/Hasan Sadikin General Hospital, Jl. Eykman 38, Bandung, 40161, Indonesia, Email [email protected]: Cerebral venous sinus thrombosis (CVST) is a cerebral vascular disorder that currently occurs quite often and has very varied clinical symptoms. Headache is the main symptom most commonly found in patients with CVST and multiple sinus involvement often have a more severe prognosis and poor clinical outcome. This study aimed to learn the relationship between D-dimer level, numeric rating scale (NRS), and amount of sinus involvement in CVST patients.Methods: This study was a retrospective observational analytic study with a cross-sectional approach using medical records and supporting data (D-dimer level and imaging finding) on patients diagnosed with CVST at Dr Hasan Sadikin Hospital Bandung.Results: Sixty-five CVST patients met the study criteria with mean age of 47 years and mostly female (76.9%). Patients with single sinus involvement had a median initial NRS of 4 (range 2– 6) and multiple sinus involvement was higher at 8 (range 5– 9). Statistical test results showed a significant difference between D-dimer level, NRS and amount of sinus involvement (P< 0.001).Conclusion: D-dimer level, NRS, and amount of sinus involvement are associated with amount of sinus involvement in CVST patients. Involvement of multiple sinus will cause higher NRS with higher D-dimer level.Keywords: CVST, D-dimer, NRS, sinus involvemen

Combining chemoinformatics with bioinformatics: in silico prediction of bacterial flavor-forming pathways by a chemical systems biology approach "reverse pathway engineering"

Contains fulltext : 127577.pdf (publisher's version ) (Open Access)The incompleteness of genome-scale metabolic models is a major bottleneck for systems biology approaches, which are based on large numbers of metabolites as identified and quantified by metabolomics. Many of the revealed secondary metabolites and/or their derivatives, such as flavor compounds, are non-essential in metabolism, and many of their synthesis pathways are unknown. In this study, we describe a novel approach, Reverse Pathway Engineering (RPE), which combines chemoinformatics and bioinformatics analyses, to predict the "missing links" between compounds of interest and their possible metabolic precursors by providing plausible chemical and/or enzymatic reactions. We demonstrate the added-value of the approach by using flavor-forming pathways in lactic acid bacteria (LAB) as an example. Established metabolic routes leading to the formation of flavor compounds from leucine were successfully replicated. Novel reactions involved in flavor formation, i.e. the conversion of alpha-hydroxy-isocaproate to 3-methylbutanoic acid and the synthesis of dimethyl sulfide, as well as the involved enzymes were successfully predicted. These new insights into the flavor-formation mechanisms in LAB can have a significant impact on improving the control of aroma formation in fermented food products. Since the input reaction databases and compounds are highly flexible, the RPE approach can be easily extended to a broad spectrum of applications, amongst others health/disease biomarker discovery as well as synthetic biology