15 research outputs found
Machine learning for determining lateral flow device results for testing of SARS-CoV-2 infection in asymptomatic populations
Rapid antigen tests, in the form of lateral flow devices (LFD) allow testing of a large population for SARS-CoV-2. To reduce the variability seen in device interpretation, we show the design and testing of an AI algorithm based on machine learning. The machine learning (ML) algorithm is trained on a combination of artificially hybridised LFDs and LFD data linked to RT-qPCR result. Participants are recruited from assisted test sites (ATS) and health care workers undertaking self-testing and images analysed using the ML algorithm. A panel of trained clinicians are used to resolve discrepancies. In total, 115,316 images are returned. In the ATS sub study, sensitivity increased from 92.08% to 97.6% and specificity from 99.85% to 99.99%. In the self-read sub-study, sensitivity increased from 16.00% to 100%, and specificity from 99.15% to 99.40%. An ML-based classifier of LFD results outperforms human reads in asymptomatic testing sites and self-reading
A black mould death: A case of fatal cerebral phaeohyphomycosis caused by Cladophialophora bantiana
Cladophialophora bantiana is a neurotropic mould and primary cause of cerebral phaeohyphomycoses, which presents with brain abscesses in both immunocompromised and immunocompetent individuals. It is associated with high mortality due to delay in diagnosis and absence of standardised therapy. We present a case of fatal cerebral phaeohyphomycosis in a 67-year-old Caucasian man. Diagnosis was achieved by histopathological examination of brain tissue followed by conventional culture and molecular identification. We highlight diagnostic and treatment challenges involved. Keywords: Cerebral phaeohyphomycoses, Dematiaceous fungi, Gene sequencing, Cladophialophora bantian
Unusual behaviour of lithium tetraborate Li2B4O7 at low temperatures: An X-ray diffraction study
Perceptions of Graduating General Surgery Chief Residents: Are They Confident in Their Training?
Host Factors in Enterovirus 71 Replication â–¿
Enterovirus 71 (EV71) infections continue to remain an important public health problem around the world, especially in the Asia-Pacific region. There is a significant mortality rate following such infections, and there is neither any proven therapy nor a vaccine for EV71. This has spurred much fundamental research into the replication of the virus. In this review, we discuss recent work identifying host cell factors which regulate the synthesis of EV71 RNA and proteins. Three of these proteins, heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1), far-upstream element-binding protein 2 (FBP2), and FBP1 are nuclear proteins which in EV71-infected cells are relocalized to the cytoplasm, and they influence EV71 internal ribosome entry site (IRES) activity. hnRNP A1 stimulates IRES activity but can be replaced by hnRNP A2. FBP2 is a negative regulatory factor with respect to EV71 IRES activity, whereas FBP1 has the opposite effect. Two other proteins, hnRNP K and reticulon 3, are required for the efficient synthesis of viral RNA. The cleavage stimulation factor 64K subunit (CstF-64) is a host protein that is involved in the 3′ polyadenylation of cellular pre-mRNAs, and recent work suggests that in EV71-infected cells, it may be cleaved by the EV71 3C protease. Such a cleavage would impair the processing of pre-mRNA to mature mRNAs. Host cell proteins play an important role in the replication of EV71, but much work remains to be done in order to understand how they act
A conceptual framework for nomenclatural stability and validity of medically important fungi: a proposed global consensus guideline for fungal name changes supported by ABP, ASM, CLSI, ECMM, ESCMID-EFISG, EUCAST-AFST, FDLC, IDSA, ISHAM, MMSA, and MSGERC.
The rapid pace of name changes of medically important fungi is creating challenges for clinical laboratories and clinicians involved in patient care. We describe two sources of name change which have different drivers, at the species versus the genus level. Some suggestions are made here to reduce the number of name changes. We urge taxonomists to provide diagnostic markers of taxonomic novelties. Given the instability of phylogenetic trees due to variable taxon sampling, we advocate to maintain genera at the largest possible size. Reporting of identified species in complexes or series should where possible comprise both the name of the overarching species and that of the molecular sibling, often cryptic species. Because the use of different names for the same species will be unavoidable for many years to come, an open access online database of the names of all medically important fungi, with proper nomenclatural designation and synonymy, is essential. We further recommend that while taxonomic discovery continues, the adaptation of new name changes by clinical laboratories and clinicians be reviewed routinely by a standing committee for validation and stability over time, with reference to an open access database, wherein reasons for changes are listed in a transparent way
The Nuremberg Code subverts human health and safety by requiring animal modeling
<p>Abstract</p> <p>Background</p> <p>The requirement that animals be used in research and testing in order to protect humans was formalized in the Nuremberg Code and subsequent national and international laws, codes, and declarations.</p> <p>Discussion</p> <p>We review the history of these requirements and contrast what was known via science about animal models then with what is known now. We further analyze the predictive value of animal models when used as test subjects for human response to drugs and disease. We explore the use of animals for models in toxicity testing as an example of the problem with using animal models.</p> <p>Summary</p> <p>We conclude that the requirements for animal testing found in the Nuremberg Code were based on scientifically outdated principles, compromised by people with a vested interest in animal experimentation, serve no useful function, increase the cost of drug development, and prevent otherwise safe and efficacious drugs and therapies from being implemented.</p