Data-driven malaria prevalence prediction in large densely populated urban holoendemic sub-Saharan West Africa

Over 200 million malaria cases globally lead to half-million deaths annually. The development of malaria prevalence prediction systems to support malaria care pathways has been hindered by lack of data, a tendency towards universal "monolithic" models (one-size-fits-all-regions) and a focus on long lead time predictions. Current systems do not provide short-term local predictions at an accuracy suitable for deployment in clinical practice. Here we show a data-driven approach that reliably produces one-month-ahead prevalence prediction within a densely populated all-year-round malaria metropolis of over 3.5 million inhabitants situated in Nigeria which has one of the largest global burdens of P. falciparum malaria. We estimate one-month-ahead prevalence in a unique 22-years prospective regional dataset of > 9 × 10^{4} participants attending our healthcare services. Our system agrees with both magnitude and direction of the prediction on validation data achieving MAE ≤ 6 × 10^{-2}, MSE ≤ 7 × 10^{-3}, PCC (median 0.63, IQR 0.3) and with more than 80% of estimates within a (+ 0.1 to - 0.05) error-tolerance range which is clinically relevant for decision-support in our holoendemic setting. Our data-driven approach could facilitate healthcare systems to harness their own data to support local malaria care pathways

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

<p>Abstract</p> <p>Background</p> <p>Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing α-helices, β-strands, and non-regular structures) from primary sequence data which makes use of Parallel Cascade Identification (PCI), a powerful technique from the field of nonlinear system identification.</p> <p>Results</p> <p>Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs) are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at <url>http://bioinf.sce.carleton.ca/PCISS</url>. In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP) interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input protein sequence data and also to encode the resulting structure prediction in a machine-readable format. To our knowledge, this represents the only publicly available SOAP-interface for a protein secondary structure prediction service with published WSDL interface definition.</p> <p>Conclusion</p> <p>Relative to the 9 contemporary methods included in the comparison cascaded PCI classifiers perform well, however PCI finds greatest application as a consensus classifier. When PCI is used to combine a sequence-to-structure PCI-based classifier with the current leading ANN-based method, PSIPRED, the overall error rate (Q3) is maintained while the rate of occurrence of a particularly detrimental error is reduced by up to 25%. This improvement in BAD score, combined with the machine-readable SOAP web service interface makes PCI-SS particularly useful for inclusion in a tertiary structure prediction pipeline.</p

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Candidate role for toll-like receptor 3 L412F polymorphism and infection in acute exacerbation of idiopathic pulmonary fibrosis

Rationale: The Toll-like receptor 3 Leu412Phe (TLR3 L412F) polymorphism attenuates cellular anti-viral responses and is associated with accelerated disease progression in IPF. The role of TLR3 L412F in bacterial infection in IPF or in acute exacerbations (AE) has not been reported. Objective: To characterize the association between TLR3 L412F and AE-related death in IPF. To determine the effect of TLR3 L412F on the lung microbiome and on anti-bacterial TLR-responses of primary lung fibroblasts from IPF patients. Methods: TLR-mediated anti-bacterial and anti-viral responses were quantitated in L412F-wild-type and 412F-heterozygous primary lung fibroblasts from IPF patients using ELISA, western blot analysis and qPCR. Hierarchical heatmap analysis was employed to establish bacterial and viral clustering in nasopharyngeal lavage (NPL) samples from AE-IPF patients. 16S rRNA qPCR and pyrosequencing were used to determine the effect of TLR3 L412F on the IPF lung microbiome. Measurements and Main Results: A significant increase in AE-related death in 412F-variant IPF patients was reported. We established that 412F-heterozygous IPF lung fibroblasts have reduced anti-bacterial TLR responses to LPS (TLR4), Pam3CYSK4 (TLR1/2), flagellin (TLR5) and FSL-1 (TLR6/1) and have reduced responses to live Pseudomonas aeruginosa infection. Using 16S rRNA sequencing, we demonstrated that 412F-heterozygous IPF patients have a dysregulated lung microbiome with increased frequencies of Streptococcus and Staphylococcus spp. Conclusions: This study reveals that TLR3 L412F dysregulates the IPF lung microbiome and reduces the responses of IPF lung fibroblasts to bacterial TLR-agonists and live bacterial infection. These findings identify a candidate role for TLR3 L412F in viral- and bacterial-mediated AE-death

Spinal glioblastoma with brain relapse in a child: clinical considerations

STUDY DESIGN: Case report. OBJECTIVES: To describe a child with intramedullary glioblastoma at T9-T10-T11, and to discuss the clinical features of this rare pathology. SETTING: Department of Neurological Sciences, Italy. CASE REPORT: Spinal cord glioblastoma in children has only rarely been reported. It most frequently involves the thoracic region with a predilection for the second and third decades of life. This report describes one case of thoracic glioblastoma multiforme in a 6-year-old child and reviews other cases reported in the literature. RESULTS: Laminectomy and excision of the tumour were performed. Postoperative radiotherapy and chemotherapy were given, but 4 months later the patient presented with a brain relapse of the tumour. At 9 months after diagnosis the patient died from cerebral tumour regrowth. CONCLUSIONS: Full neuraxis MRI is always recommended in order to detect possible metastases. The prognosis after multimodality therapy (surgery, radiotherapy, chemotherapy) remains poor. From the literature, only four cases of paediatric patients with long-term survival have been reported