Factors associated with reporting multiple causes of death

BACKGROUND: There is analytical potential for multiple cause of death data collected from death certificates. This study examines relationships of multiple causes of death as a function of factors available on the death certificate (demographics of decedent, place of death, type of certifier, disposal method, whether an autopsy was performed, and year of death). METHODS: Data from 326,332 Minnesota death certificates from 1990–1998 are examined. Underlying and non-underlying causes of death are examined (based on record axis codes) as well as demographic and death-related covariates. Associations between covariates and prevalence of multiple causes of death and conditional probability of underlying compared to non-underlying causes of death are examined. The occurrence of ischemic heart disease or diabetes as underlying causes are specifically examined. RESULTS: Both the probability of multiple causes of death and the proportion of underlying cause compared to non-underlying cause of death are associated with demographic characteristics of the deceased and other non-medical conditions related to filing death certificate such as place of death. CONCLUSIONS: Multiple cause of death data provide a potentially useful way of looking for inaccuracies in reporting of causes of death. Differences across demographics in the proportion of time a cause is selected as underlying compared to non-underlying exist and can potentially provide useful information about the overall impact of causes of death in different populations

Pharmacokinetics and Dosing of Levofloxacin in Children Treated for Active or Latent Multidrug-resistant Tuberculosis, Federated States of Micronesia and Republic of the Marshall Islands

In the Federated States of Micronesia (FSM) and then the Republic of the Marshall Islands (RMI), levofloxacin pharmacokinetics (PK) were studied in children receiving directly observed once-daily regimens (10 mg/kg, age >5 years; 15–20 mg/kg, age ≤5 years) for either multidrug-resistant tuberculosis (MDR TB) disease or latent infection after MDR TB exposure, to inform future dosing strategies

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 2.3 million people, killed over 160,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven clinical efficacy, nor are there vaccines for its prevention, and these efforts are hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. To address this, we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), identifying 332 high-confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Screening a subset of these in multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the Sigma1 and Sigma2 receptors. Further studies of these host factor targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19

Cell-associated heparin-like molecules modulate the ability of LDL to regulate PCSK9 uptake.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) targets the LDL receptor (LDLR) for degradation, increasing plasma LDL and, consequently, cardiovascular risk. Uptake of secreted PCSK9 is required for its effect on the LDLR, and LDL itself inhibits this uptake, though how it does so remains unclear. In this study, we investigated the relationship between LDL, the PCSK9:LDLR interaction, and PCSK9 uptake. We show that LDL inhibits binding of PCSK9 to the LDLR in vitro more impressively than it inhibits PCSK9 uptake in cells. Furthermore, cell-surface heparin-like molecules (HLMs) can partly explain this difference, consistent with heparan sulfate proteoglycans (HSPGs) acting as coreceptors for PCSK9. We also show that HLMs can interact with either PCSK9 or LDL to modulate the inhibitory activity of LDL on PCSK9 uptake, with such inhibition rescued by competition with the entire PCSK9 prodomain, but not its truncated variants. Additionally, we show that the gain-of-function PCSK9 variant, S127R, located in the prodomain near the HSPG binding site, exhibits increased affinity for HLMs, potentially explaining its phenotype. Overall, our findings suggest a model where LDL acts as a negative regulator of PCSK9 function by decreasing its uptake via direct interactions with either the LDLR or HLMs

A High-Throughput Luciferase Assay to Evaluate Proteolysis of the Single-Turnover Protease PCSK9.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a single-turnover protease which regulates serum low-density lipoprotein (LDL) levels and, consequently, cardiovascular disease. Although PCSK9 proteolysis is required for its full hypercholesterolemic effect, the evaluation of its proteolytic function is challenging: PCSK9 is only known to cleave itself, undergoes only a single turnover, and after proteolysis, retains its substrate in its active site as an auto-inhibitor. The methods presented here describe an assay which overcomes these challenges. The assay focuses on intermolecular proteolysis in a cell-based context and links successful cleavage to the secreted luciferase activity, which can be easily read out in the conditioned medium. Via sequential steps of mutagenesis, transient transfection, and a luciferase readout, the assay can probe PCSK9 proteolysis under conditions of either genetic or molecular perturbation in a high-throughput manner. This system is well suited for both the biochemical evaluation of clinically discovered missense single-nucleotide polymorphisms (SNPs), as well as for the screening of small-molecule inhibitors of PCSK9 proteolysis