Threat Net: A Metagenomic Surveillance Network for Biothreat Detection and Early Warning.

Early detection of novel pathogens can prevent or substantially mitigate biological incidents, including pandemics. Metagenomic next-generation sequencing (mNGS) of symptomatic clinical samples may enable detection early enough to contain outbreaks, limit international spread, and expedite countermeasure development. In this article, we propose a clinical mNGS architecture we call "Threat Net," which focuses on the hospital emergency department as a high-yield surveillance location. We develop a susceptible-exposed-infected-removed (SEIR) simulation model to estimate the effectiveness of Threat Net in detecting novel respiratory pathogen outbreaks. Our analysis serves to quantify the value of routine clinical mNGS for respiratory pandemic detection by estimating the cost and epidemiological effectiveness at differing degrees of hospital coverage across the United States. We estimate that a biological threat detection network such as Threat Net could be deployed across hospitals covering 30% of the population in the United States. Threat Net would cost between $400 million and $800 million annually and have a 95% chance of detecting a novel respiratory pathogen with traits of SARS-CoV-2 after 10 emergency department presentations and 79 infections across the United States. Our analyses suggest that implementing Threat Net could help prevent or substantially mitigate the spread of a respiratory pandemic pathogen in the United States.

Starving the Gut: A Deficit of Butyrate in the Intestinal Ecosystem of Children With Intestinal Failure.

BACKGROUND: Intestinal epithelial integrity is influenced by short-chain fatty acids (SCFAs) and is of critical importance for children with intestinal failure (IF) given the known devastating infectious and gastrointestinal complications. The composition of the microbiome in IF represents an important variable in the physiology and prognosis of this disease. AIM: We sought to compare the intestinal microbiome and SCFA concentration of children who require parenteral nutrition (PN) with that of children with short-bowel syndrome (SBS) who have discontinued PN and with age-matched controls, using high-throughput sequencing to investigate host-microbe interactions. METHODS: Fifty-three samples were submitted over 6-15 months. Six children with SBS + IF submitted 34 samples, and 6 children with SBS with discontinued PN submitted 15 samples; these were compared with samples from 5 control children. Fecal samples were analyzed by 16S ribosomal RNA partial gene sequencing using the MiSeq Illumina sequencer. SCFAs were measured in stool samples by mass spectrometry. RESULTS: Butyrate quantity was near absent in children with IF compared with that in controls (median 0.37 nmol/mg vs 10.92 nmol/mg; P < .0001). Similarly, commensal anaerobes known to produce SCFA, including Ruminococcaceae and Lachnospiraceae, were reduced in those with SBS. SBS + IF enteric samples demonstrated a 168-fold increase in the relative abundance of the Escherichia genus seemingly attributable to the species Escherichia coli. CONCLUSION: The reduced relative abundance of butyrate-producing Clostridia as well as decreased intestinal butyrate concentration in children with IF support further investigation in therapeutic options that target butyrate-producing bacterial communities or butyrate supplementation.

Toxoplasma gondii and schizophrenia: a review of published RCTs.

Over the last 60 years, accumulating evidence has suggested that acute, chronic, and maternal Toxoplasma gondii infections predispose to schizophrenia. More recent evidence suggests that chronically infected patients with schizophrenia present with more severe disease. After acute infection, parasites form walled cysts in the brain, leading to lifelong chronic infection and drug resistance to commonly used antiparasitics. Chronic infection is the most studied and closely linked with development and severity of schizophrenia. There are currently four published randomized controlled trials evaluating antiparasitic drugs, specifically azithromycin, trimethoprim, artemisinin, and artemether, in patients with schizophrenia. No trials have demonstrated a change in psychopathology with adjunctive treatment. Published trials have either selected drugs without evidence against chronic infection or used them at doses too low to reduce brain cyst burden. Furthermore, trials have failed to achieve sufficient power or account for confounders such as previous antipsychotic treatment, sex, age, or rhesus status on antiparasitic effect. There are currently no ongoing trials of anti-Toxoplasma therapy in schizophrenia despite ample evidence to justify further testing.

A program to identify prognostic and predictive gene signatures.

BACKGROUND: The advent of high-throughput technologies to profile human tumors has generated unprecedented insight into our molecular understanding of cancer. However, analysis of such high dimensional data is challenging and requires significant expertise which is not routinely available to many cancer researchers. RESULTS: To overcome this limitation, we developed a freely accessible and user friendly Program to Identify Molecular Signatures (PIMS). Importantly, such signatures allow important insight into cancer biology, as well as provide clinical tools to identify potential biomarkers that might provide means to accurately stratify patients into different risk or treatment groups. We evaluated the performance of PIMS by identifying and testing predictive and prognostic gene signatures for breast cancer, using multiple breast tumor microarray cohorts representing hundreds of patients. Importantly, PIMS identified signatures classified patients into high and low risk groups with at least similar performance to other commonly used gene signature selection techniques. CONCLUSIONS: Our program is contained entirely within a Microsoft Excel file and therefore requires no installation of any additional programs or training. Hence, PIMS provides an accessible tool for cancer researchers to identify predictive and prognostic gene signatures to advance their research.