The Readiness for and Current Status of E-Government in China

E-government is important for China’s economic and social development. A measurement is developed and applied to assess the readiness of local Chinese governments for e-government. E-government development status of local Chinese governments is assessed through evaluation of their websites. Relationships between e-government readiness and the actual progress on e-government are discussed

Prevalence and incidence of diagnosed hypertension in Alberta, Canada

Introduction The prevalence of diagnosed hypertension in Canada is projected to increase despite the incidence rate decreasing. Previous work around the world has utilized survey data to provide estimates of prevalence and incidence. Administrative data is population-level, and may provide more reliable estimates of provincial prevalence and incidence than could be achieved using survey data.  Objectives and Approach • To produce age and sex-specific prevalence and incidence estimates of diagnosed hypertension in Alberta from 2007 to 2015, • To project estimates to the fiscal year of 2019/2020. Data from the Discharge Abstract Database, physician claims database, National Ambulatory Care Reporting System, and provincial health insurance registry will be linked using unique anonymous personal identifier and gender. A validated case definition of diagnosed hypertension for use in administrative datasets will be used to identify annual prevalent and incident cases from claims data. Obstetric cases will be excluded. The provincial health insurance registry will be used to estimate denominator values. Results Results of this analysis are not available for the time of abstract submission as the timeline for this analysis projects completion in April 2018. Conclusion/Implications Maintained surveillance of diagnosed hypertension is important to inform health policy and spending decisions, to monitor efficacy of public health interventions, and to inform patient care. Furthermore, diagnosis guidelines have been updated since 2017. Providing estimates for the prevalence of diagnosed hypertension in Alberta five years into the future to compare to actual prevalence estimates may indicate whether changes in prevalence are due to actual changes in health status or to changes in diagnosis guidelines

Improving the Coding Completeness of Hypertension in Inpatient Administrative Health Data Using Machine Learning Methods

Introduction The Discharge Abstract Database (DAD) associates ICD-10-CA diagnosis codes with inpatient care episodes at acute-care facilities. Codes are assigned by human coders, based on chart review. Coding guidelines stipulate mandatory coding of major and fatal conditions but only optional coding of secondary conditions, which results in undercoding for many conditions. Objectives and Approach This research evaluates machine learning approaches for identifying and completing records with missing codes, to improve data quality. The Alberta Hospital DAD for 2013-14 was used in this study. We assumed that the existing ICD-10-CA codes in the DAD are correct, and used them as training examples. Several ML classifiers, including logistic regression and random forest, were used to develop models to assess the coding probability, using existing codes and demographic information. 3300 chart-review records were used as the reference standard. We focused on hypertension-related codes. Validity of raw diagnosis codes in the DAD was used as the baseline. Results A record is deemed to have a missing hypertension diagnosis code if the predicted probability is high, but without the diagnosis codes having been assigned by the coders. In the baseline, the original hypertension codes have high PPV (ranging from 0.902 for the age group 35-54 to 1.000 for the age group 18-34) but low sensitivity (ranging from 0.200 for the age group 18-34 to 0.565 for the age group 75+). The most successful models that we have tested so far have provided improvements of 2-6% in the sensitivity, while maintaining the PPV. More improvement is generally seen for the younger age groups. Initial experiments indicate greater improvements in sensitivity may be possible for other conditions, such as peptic ulcer disease and cerebrovascular disease. Conclusion/Implications Machine learning approaches can be useful and cost-effective for improving data quality in DAD. While the improvements in sensitivity relative to the baseline are modest at present, further experiments with different models and feature sets are warranted. Experiments with other conditions may also be fruitful

Patient-Reported Outcomes Improves the Prediction of In-patient and Emergency Department Readmission Risks in Coronary Artery Disease

Introduction Coronary Artery Disease (CAD) patients are known to report higher healthcare resource use, such as inpatient [IP] and emergency department [ED] readmissions, than the general population. We investigate if the patient reported outcome measures (PROMs) improve the accuracy of readmissions risk prediction models in CAD. Objectives and Approach Patients enrolled in the Alberta Provincial Project for Outcomes Assessment in Coronary Heart Disease (APPROACH) registry between 1995 and 2014 who received catheterization (CATH) and completed baseline PROMs were linked to discharge abstract data and national ambulatory data. Logistic regression (LR) was used to develop 30-day and 1-year readmissions risk prediction models adjusting for patients’ demographic, clinical, and self-reported characteristics. PROM was measured using the 19-item Seattle Angina Questionnaire (SAQ). The discriminatory performance of each prediction model was assessed using the Harrel’s c-statistic for LR. Results Of the 13,264 patients who completed baseline SAQ, 59 (0.3%) had IP readmissions or ED visits within 30 days, and up to 356 (1.9%) within 1 year of baseline survey. The C-statistics for one-year readmissions risk prediction models that only adjusted for demographic and clinical variables only ranged between 56.4% and 61.2%. The prognostic improvement in the discrimination of these models ranged between 2% to 10% when patient-reported SAQ was included as predictor. The addition of SAQ improves the model discrimination in all types of admission. Conclusion/Implications The addition of PROMs improves the moderate accuracy of readmissions risk prediction models. These findings highlight the need for routine collection of PROMs in clinical settings and their potential use for aiding clinical and policy decision-making and post-discharge outcomes monitoring in the management of cardiovascular diseases

Recent developments in the engineered biosynthesis of fungal meroterpenoids

Meroterpenoids are hybrid compounds that are partially derived from terpenoids. This group of natural products displays large structural diversity, and many members exhibit beneficial biological activities. This mini-review highlights recent advances in the engineered biosynthesis of meroterpenoid compounds with C15 and C20 terpenoid moieties, with the reconstruction of fungal meroterpenoid biosynthetic pathways in heterologous expression hosts and the mutagenesis of key enzymes, including terpene cyclases and α-ketoglutarate (αKG)-dependent dioxygenases, that contribute to the structural diversity. Notable progress in genome sequencing has led to the discovery of many novel genes encoding these enzymes, while continued efforts in X-ray crystallographic analyses of these enzymes and the invention of AlphaFold2 have facilitated access to their structures. Structure-based mutagenesis combined with applications of unnatural substrates has further diversified the catalytic repertoire of these enzymes. The information in this review provides useful knowledge for the design of biosynthetic machineries to produce a variety of bioactive meroterpenoids

Mechanism of the Bifunctional Multiple Product Sesterterpene Synthase AcAS from Aspergillus calidoustus

The multiproduct chimeric sesterterpene synthase AcAS from Aspergillus calidoustus yielded spirocyclic calidoustene, which exhibits a novel skeleton, besides five known sesterterpenes. The complex cyclisation mechanism to all six compounds was investigated by isotopic labelling experiments in combination with DFT calculations. Chemically synthesised 8-hydroxyfarnesyl diphosphate was converted with isopentenyl diphosphate and AcAS into four oxygenated sesterterpenoids that structurally resemble cytochrome P450 oxidation products of the sesterterpene hydrocarbons. Protein engineering of AcAS broadened the substrate scope and gave significantly improved enzyme yields

Travel before, during and after the COVID-19 pandemic: Exploring factors in essential travel using empirical data

The COVID-19 pandemic has a significant impact on daily life, leading to quarantines and essential travel restrictions worldwide in an effort to curb the virus\u27s spread. Despite the potential importance of essential travel, research on changes in travel patterns during the pandemic has been limited, and the concept of essential travel has not been fully explored. This paper aims to address this gap by using GPS data from taxis in Xi\u27an City between January and April 2020 to investigate differences in travel patterns across three periods pre, during, and post the pandemic. Spatial statistical models are used to examine the major supply and demand-oriented factors that affect spatial travel patterns in different periods, and essential and nonessential socioeconomic resources are defined based on types of services. Results indicate that the spatial distribution of travel demand was highly correlated with the location of socioeconomic resources and opportunities, regardless of the period. During the “Emergency Response” period, essential travel was found to be highly associated with facilities and businesses providing essential resources and opportunities, such as essential food provider, general hospital and daily grocery supplies. The findings suggest that local authorities may better identify essential travel destinations by referencing the empirical results, strengthening public transit connections to these locations, and ultimately promoting traffic fairness in the post-pandemic era

Molecular Basis for Stellatic Acid Biosynthesis: A Genome Mining Approach for Discovery of Sesterterpene Synthases

The search for a new sesterterpene synthase in the genome of <i>Emericella variecolor</i>, which reportedly produces diverse sesterterpenoids, is described. One gene product (a chimeric protein with prenyltransferase and terpene cyclase domains) led to the synthesis of a novel tricyclic sesterterpene, stellata-2,6,19-triene (<b>1</b>), from DMAPP and IPP, and the hydrocarbon was further transformed into stellatic acid (<b>2</b>) by cytochrome P450 monooxygenase encoded by the gene adjacent to the sesterterpene synthase gene

Identification of SIRT3 as an eraser of H4K16la

Summary: Lysine lactylation (Kla) is a novel histone post-translational modification discovered in late 2019. Later, HDAC1-3, were identified as the robust Kla erasers. While the Sirtuin family proteins showed weak eraser activities toward Kla, as reported. However, the catalytic mechanisms and physiological functions of HDACs and Sirtuins are not identical. In this study, we observed that SIRT3 exhibits a higher eraser activity against the H4K16la site than the other human Sirtuins. Crystal structures revealed the detailed binding mechanisms between lactyl-lysine peptides and SIRT3. Furthermore, a chemical probe, p-H4K16laAlk, was developed to capture potential Kla erasers from cell lysates. SIRT3 was captured by this probe and detected via proteomic analysis. And another chemical probe, p-H4K16la-NBD, was developed to detect the eraser-Kla delactylation processes directly via fluorescence indication. Our findings and chemical probes provide new directions for further investigating Kla and its roles in gene transcription regulation