Muscleblind-like 1 interacts with RNA hairpins in splicing target and pathogenic RNAs

The MBNL and CELF proteins act antagonistically to control the alternative splicing of specific exons during mammalian postnatal development. This process is dysregulated in myotonic dystrophy because MBNL proteins are sequestered by (CUG)n and (CCUG)n RNAs expressed from mutant DMPK and ZNF9 genes, respectively. While these observations predict that MBNL proteins have a higher affinity for these pathogenic RNAs versus their normal splicing targets, we demonstrate that MBNL1 possesses comparably high affinities for (CUG)n and (CAG)n RNAs as well as a splicing target, Tnnt3. Mapping of a MBNL1-binding site upstream of the Tnnt3 fetal exon indicates that a preferred binding site for this protein is a GC-rich RNA hairpin containing a pyrimidine mismatch. To investigate how pathogenic RNAs sequester MBNL1 in DM1 cells, we used a combination of chemical/enzymatic structure probing and electron microscopy to determine that MBNL1 forms a ring-like structure which binds to the dsCUG helix. While the MBNL1 N-terminal region is required for RNA binding, the C-terminal region mediates homotypic interactions which may stabilize intra- and/or inter-ring interactions. Our results provide a mechanistic basis for dsCUG-induced MBNL1 sequestration and highlight a striking similarity in the binding sites for MBNL proteins on splicing precursor and pathogenic RNAs

SARS Clinical Features, United States, 2003

We compared the clinical features of 8 U.S. case-patients with laboratory-confirmed severe acute respiratory syndrome (SARS) to 65 controls who tested negative for SARS coronavirus (SARS-CoV) infection. Shortness of breath, vomiting, diarrhea, progressive bilateral infiltrates on chest radiograph, and need for supplemental oxygen were significantly associated with confirmed SARS-CoV infection

Timing of seasonal influenza epidemics for 25 countries in Africa during 2010-19: a retrospective analysis.

BACKGROUND: Using country-specific surveillance data to describe influenza epidemic activity could inform decisions on the timing of influenza vaccination. We analysed surveillance data from African countries to characterise the timing of seasonal influenza epidemics to inform national vaccination strategies. METHODS: We used publicly available sentinel data from African countries reporting to the WHO Global Influenza Surveillance and Response FluNet platform that had 3-10 years of data collected during 2010-19. We calculated a 3-week moving proportion of samples positive for influenza virus and assessed epidemic timing using an aggregate average method. The start and end of each epidemic were defined as the first week when the proportion of positive samples exceeded or went below the annual mean, respectively, for at least 3 consecutive weeks. We categorised countries into five epidemic patterns: northern hemisphere-dominant, with epidemics occurring in October-March; southern hemisphere-dominant, with epidemics occurring in April-September; primarily northern hemisphere with some epidemic activity in southern hemisphere months; primarily southern hemisphere with some epidemic activity in northern hemisphere months; and year-round influenza transmission without a discernible northern hemisphere or southern hemisphere predominance (no clear pattern). FINDINGS: Of the 34 countries reporting data to FluNet, 25 had at least 3 years of data, representing 46% of the countries in Africa and 89% of Africa's population. Study countries reported RT-PCR respiratory virus results for a total of 503 609 specimens (median 12 971 [IQR 9607-20 960] per country-year), of which 74 001 (15%; median 2078 [IQR 1087-3008] per country-year) were positive for influenza viruses. 248 epidemics occurred across 236 country-years of data (median 10 [range 7-10] per country). Six (24%) countries had a northern hemisphere pattern (Algeria, Burkina Faso, Egypt, Morocco, Niger, and Tunisia). Eight (32%) had a primarily northern hemisphere pattern with some southern hemisphere epidemics (Cameroon, Ethiopia, Mali, Mozambique, Nigeria, Senegal, Tanzania, and Togo). Three (12%) had a primarily southern hemisphere pattern with some northern hemisphere epidemics (Ghana, Kenya, and Uganda). Three (12%) had a southern hemisphere pattern (Central African Republic, South Africa, and Zambia). Five (20%) had no clear pattern (Côte d'Ivoire, DR Congo, Madagascar, Mauritius, and Rwanda). INTERPRETATION: Most countries had identifiable influenza epidemic periods that could be used to inform authorities of non-seasonal and seasonal influenza activity, guide vaccine timing, and promote timely interventions. FUNDING: None. TRANSLATIONS: For the Berber, Luganda, Xhosa, Chewa, Yoruba, Igbo, Hausa and Afan Oromo translations of the abstract see Supplementary Materials section

Leveraging International Influenza Surveillance Systems and Programs during the COVID-19 Pandemic.

A network of global respiratory disease surveillance systems and partnerships has been built over decades as a direct response to the persistent threat of seasonal, zoonotic, and pandemic influenza. These efforts have been spearheaded by the World Health Organization, country ministries of health, the US Centers for Disease Control and Prevention, nongovernmental organizations, academic groups, and others. During the COVID-19 pandemic, the US Centers for Disease Control and Prevention worked closely with ministries of health in partner countries and the World Health Organization to leverage influenza surveillance systems and programs to respond to SARS-CoV-2 transmission. Countries used existing surveillance systems for severe acute respiratory infection and influenza-like illness, respiratory virus laboratory resources, pandemic influenza preparedness plans, and ongoing population-based influenza studies to track, study, and respond to SARS-CoV-2 infections. The incorporation of COVID-19 surveillance into existing influenza sentinel surveillance systems can support continued global surveillance for respiratory viruses with pandemic potential

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A Comparative Risk Assessment Of Burden Of Disease And Injury Attributable To 67 Risk Factors And Risk Factor Clusters In 21 Regions, 1990–2010: A Systematic Analysis For The Global Burden Of Disease Study 2010

Background Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time

A Novel Strategy To Identify Placebo Responders: Prediction Index Of Clinical And Biological Markers In The Embarc Trial

Background: One-in-three clinical trial patients with Major Depressive Disorder report symptomatic improvement with placebo. Strategies to mitigate the effect of placebo response have focused on modifying study design with variable success. Identifying and excluding or controlling for individuals with high likelihood of responding to placebo may improve clinical trial efficiency and avoid unnecessary medication trials. Methods: Participants included those assigned to the placebo arm (n=141) of the Establishing Moderators and Biosignatures for Antidepressant Response in Clinical Care (EMBARC) trial. The elastic net was used to evaluate 283 baseline clinical, behavioral, imaging, and electrophysiological variables to identify the most robust yet parsimonious features that predicted depression severity at the end of the double-blind 8-week trial. Variables retained in at least 50% of the 100 imputed datasets were used ina Bayesian multiple linear regression model to simultaneously predict the probabilities of response and remission. Results: Lower baseline depression severity, younger age, absence of melancholic features or history of physical abuse, less anxious arousal, less anhedonia, less neuroticism, and higher average theta current density in the rostral anterior cingulate predicted higher likelihood of improvement with placebo. The Bayesian model predicted remission and response with a actionable degree of accuracy (both AUC> 0.73). An interactive calculator was developed predicting likelihood of placebo response at the individual level. Conclusion: Easy-to-measure clinical, behavioral and electrophysiological assessments can be used to identify placebo responders with a high degree of accuracy. Development of this calculator based on these findings can be used to identify potential placebo responders