Generating SQL queries from visual specifications

Abstract: Structured Query Language (SQL) is the most widely used declarative language for accessing relational databases, and an essential topic in introductory database courses in higher learning institutions. Despite the intuitiveness of SQL, formulating and comprehending written queries can be confusing, especially for undergraduate students. One major reason for this is that the simple syntax of SQL is often misleading and hard to comprehend. A number of tools have been developed to aid the comprehension of queries and improve the mental models of students concerning the underlying logic of SQL. Some of these tools employed visualisation and animation in their approach to aid the comprehension of SQL. This paper presents an interactive comprehension aid based on visualisation, specifically designed to support the SQL SELECT statement, an area identified in the literature as problematic for students. The visualisation tool uses visual specifications depicting SQL operations to build queries. This is expected to reduce the cognitive load of a student who is learning SQL. We have shown with an online survey that adopting visual specifications in teaching systems assist students in attaining a richer learning experience in introductory database courses

Association of SARS-CoV-2 clades with clinical, inflammatory and virologic outcomes: An observational study

BACKGROUND: Host determinants of severe coronavirus disease 2019 include advanced age, comorbidities and male sex. Virologic factors may also be important in determining clinical outcome and transmission rates, but limited patient-level data is available. METHODS: We conducted an observational cohort study at seven public hospitals in Singapore. Clinical and laboratory data were collected and compared between individuals infected with different SARS-CoV-2 clades. Firth's logistic regression was used to examine the association between SARS-CoV-2 clade and development of hypoxia, and quasi-Poisson regression to compare transmission rates. Plasma samples were tested for immune mediator levels and the kinetics of viral replication in cell culture were compared. FINDINGS: 319 patients with PCR-confirmed SARS-CoV-2 infection had clinical and virologic data available for analysis. 29 (9%) were infected with clade S, 90 (28%) with clade L/V, 96 (30%) with clade G (containing D614G variant), and 104 (33%) with other clades 'O' were assigned to lineage B.6. After adjusting for age and other covariates, infections with clade S (adjusted odds ratio (aOR) 0·030 (95% confidence intervals (CI): 0·0002-0·29)) or clade O (B·6) (aOR 0·26 (95% CI 0·064-0·93)) were associated with lower odds of developing hypoxia requiring supplemental oxygen compared with clade L/V. Patients infected with clade L/V had more pronounced systemic inflammation with higher concentrations of pro-inflammatory cytokines, chemokines and growth factors. No significant difference in the severity of clade G infections was observed (aOR 0·95 (95% CI: 0·35-2·52). Though viral loads were significantly higher, there was no evidence of increased transmissibility of clade G, and replicative fitness in cell culture was similar for all clades. INTERPRETATION: Infection with clades L/V was associated with increased severity and more systemic release of pro-inflammatory cytokines. Infection with clade G was not associated with changes in severity, and despite higher viral loads there was no evidence of increased transmissibility

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Antibiotic utilisation and resistance over the first decade of nationally funded antimicrobial stewardship programmes in Singapore acute-care hospitals

10.1186/s13756-023-01289-xAntimicrobial Resistance and Infection Control12182

Virological and serological kinetics of SARS-CoV-2 Delta variant vaccine breakthrough infections: a multicentre cohort study

10.1016/j.cmi.2021.11.010Clinical Microbiology and Infection284612.e1-612.e

Digital technologies and numeracy—synergy or discord?

Engaging young learners in STEM practices such as robotics and coding gives students the opportunity to use new and emerging technologies to solve problems while extending their own knowledge and understanding of mathematics. In Australia, a digital technologies curriculum was introduced in 2014 to assist with making connections between Technology and areas such as mathematics. Drawing on examples from Australia, British Columbia, the United Kingdom and New Zealand, this chapter examines how the introduction of a new curriculum intersects with existing curricula. As an example of an authentic activity that successfully combines elements of both curricula to support STEM learning, findings of a research project that has been conducted with Year 2 students (n = 153) from two Australian primary schools are presented. It appears as young students engage in robotics and coding (Technology) to learn mathematics concepts, they demonstrate learning that moves beyond their curriculum year level, creating a possible conflict between the digital technologies and mathematics curricula with their tightly prescribed sequence of content