Deep learning in ophthalmology: The technical and clinical considerations

The advent of computer graphic processing units, improvement in mathematical models and availability of big data has allowed artificial intelligence (AI) using machine learning (ML) and deep learning (DL) techniques to achieve robust performance for broad applications in social-media, the internet of things, the automotive industry and healthcare. DL systems in particular provide improved capability in image, speech and motion recognition as well as in natural language processing. In medicine, significant progress of AI and DL systems has been demonstrated in image-centric specialties such as radiology, dermatology, pathology and ophthalmology. New studies, including pre-registered prospective clinical trials, have shown DL systems are accurate and effective in detecting diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD), retinopathy of prematurity, refractive error and in identifying cardiovascular risk factors and diseases, from digital fundus photographs. There is also increasing attention on the use of AI and DL systems in identifying disease features, progression and treatment response for retinal diseases such as neovascular AMD and diabetic macular edema using optical coherence tomography (OCT). Additionally, the application of ML to visual fields may be useful in detecting glaucoma progression. There are limited studies that incorporate clinical data including electronic health records, in AL and DL algorithms, and no prospective studies to demonstrate that AI and DL algorithms can predict the development of clinical eye disease. This article describes global eye disease burden, unmet needs and common conditions of public health importance for which AI and DL systems may be applicable. Technical and clinical aspects to build a DL system to address those needs, and the potential challenges for clinical adoption are discussed. AI, ML and DL will likely play a crucial role in clinical ophthalmology practice, with implications for screening, diagnosis and follow up of the major causes of vision impairment in the setting of ageing populations globally

Identifying chemokines as therapeutic targets in renal disease: Lessons from antagonist studies and knockout mice

Chemokines, in concert with cytokines and adhesion molecules, play multiple roles in local and systemic immune responses. In the kidney, the temporal and spatial expression of chemokines correlates with local renal damage and accumulation of chemokine receptor-bearing leukocytes. Chemokines play important roles in leukocyte trafficking and blocking chemokines can effectively reduce renal leukocyte recruitment and subsequent renal damage. However, recent data indicate that blocking chemokine or chemokine receptor activity in renal disease may also exacerbate renal inflammation under certain conditions. An increasing amount of data indicates additional roles of chemokines in the regulation of innate and adaptive immune responses, which may adversively affect the outcome of interventional studies. This review summarizes available in vivo studies on the blockade of chemokines and chemokine receptors in kidney diseases, with a special focus on the therapeutic potential of anti-chemokine strategies, including potential side effects, in renal disease. Copyright (C) 2004 S. Karger AG, Basel

Implications of improved representation of convection for the East Africa water budget using a convection-permitting model

The precipitation and diabatic heating resulting from moist convection make it a key component of the atmospheric water budget in the tropics. With convective parametrisation being a known source of uncertainty in global models, convection-permitting (CP) models are increasingly being used to improve understanding of regional climate. Here, a new 10-year CP simulation is used to study the characteristics of rainfall and atmospheric water budget for East Africa and the Lake Victoria basin. The explicit representation of convection leads to a widespread improvement in the intensities and diurnal cycle of rainfall when compared with a parametrised simulation. Differences in large-scale moisture fluxes lead to a shift in the mean rainfall pattern from the Congo to Lake Victoria basin in the CP simulation - highlighting the important connection between local changes in the representation of convection and larger scale dynamics and rainfall. Stronger lake-land contrasts in buoyancy in the CP model lead to a stronger nocturnal land breeze over Lake Victoria, increasing evaporation and moisture flux convergence (MFC), and likely unrealistically high rainfall. However, for the mountains east of the lake, the CP model produces a diurnal rainfall cycle much more similar to satellite estimates, which is related to differences in the timing of MFC. Results here demonstrate that, whilst care is needed regarding lake forcings, a CP approach offers a more realistic representation of several rainfall characteristics through a more physically-based realisation of the atmospheric dynamics around the complex topography of East Africa

The selective phosphodiesterase 4 inhibitor roflumilast and phosphodiesterase 3/4 inhibitor pumafentrine reduce clinical score and TNF expression in experimental colitis in mice.

The specific inhibition of phosphodiesterase (PDE)4 and dual inhibition of PDE3 and PDE4 has been shown to decrease inflammation by suppression of pro-inflammatory cytokine synthesis. We examined the effect of roflumilast, a selective PDE4 inhibitor marketed for severe COPD, and the investigational compound pumafentrine, a dual PDE3/PDE4 inhibitor, in the preventive dextran sodium sulfate (DSS)-induced colitis model. The clinical score, colon length, histologic score and colon cytokine production from mice with DSS-induced colitis (3.5% DSS in drinking water for 11 days) receiving either roflumilast (1 or 5 mg/kg body weight/d p.o.) or pumafentrine (1.5 or 5 mg/kg/d p.o.) were determined and compared to vehicle treated control mice. In the pumafentrine-treated animals, splenocytes were analyzed for interferon-γ (IFNγ) production and CD69 expression. Roflumilast treatment resulted in dose-dependent improvements of clinical score (weight loss, stool consistency and bleeding), colon length, and local tumor necrosis factor-α (TNFα) production in the colonic tissue. These findings, however, were not associated with an improvement of the histologic score. Administration of pumafentrine at 5 mg/kg/d alleviated the clinical score, the colon length shortening, and local TNFα production. In vitro stimulated splenocytes after in vivo treatment with pumafentrine showed a significantly lower state of activation and production of IFNγ compared to no treatment in vivo. These series of experiments document the ameliorating effect of roflumilast and pumafentrine on the clinical score and TNF expression of experimental colitis in mice

Impact of shortened crop rotation of oilseed rape on soil and rhizosphere microbial diversity in relation to yield decline

Oilseed rape (OSR) grown in monoculture shows a decline in yield relative to virgin OSR of up to 25%, but the mechanisms responsible are unknown. A long term field experiment of OSR grown in a range of rotations with wheat was used to determine whether shifts in fungal and bacterial populations of the rhizosphere and bulk soil were associated with the development of OSR yield decline. The communities of fungi and bacteria in the rhizosphere and bulk soil from the field experiment were profiled using terminal restriction fragment length polymorphism (TRFLP) and sequencing of cloned internal transcribed spacer regions and 16S rRNA genes, respectively. OSR cropping frequency had no effect on rhizosphere bacterial communities. However, the rhizosphere fungal communities from continuously grown OSR were significantly different to those from other rotations. This was due primarily to an increase in abundance of two fungi which showed 100% and 95% DNA identity to the plant pathogens Olpidium brassicae and Pyrenochaeta lycopersici, respectively. Real-time PCR confirmed that there was significantly more of these fungi in the continuously grown OSR than the other rotations. These two fungi were isolated from the field and used to inoculate OSR and Brassica oleracea grown under controlled conditions in a glasshouse to determine their effect on yield. At high doses, Olpidium brassicae reduced top growth and root biomass in seedlings and reduced branching and subsequent pod and seed production. Pyrenochaeta sp. formed lesions on the roots of seedlings, and at high doses delayed flowering and had a negative impact on seed quantity and quality

Monitoring one-electron photo-oxidation of guanine in DNA crystals using ultrafast infrared spectroscopy

To understand the molecular origins of diseases caused by ultraviolet and visible light, and also to develop photodynamic therapy, it is important to resolve the mechanism of photoinduced DNA damage. Damage to DNA bound to a photosensitizer molecule frequently proceeds by one-electron photo-oxidation of guanine, but the precise dynamics of this process are sensitive to the location and the orientation of the photosensitizer, which are very difficult to define in solution. To overcome this, ultrafast time-resolved infrared (TRIR) spectroscopy was performed on photoexcited ruthenium polypyridyl–DNA crystals, the atomic structure of which was determined by X-ray crystallography. By combining the X-ray and TRIR data we are able to define both the geometry of the reaction site and the rates of individual steps in a reversible photoinduced electron-transfer process. This allows us to propose an individual guanine as the reaction site and, intriguingly, reveals that the dynamics in the crystal state are quite similar to those observed in the solvent medium

Interactions between Naïve and Infected Macrophages Reduce Mycobacterium tuberculosis Viability

A high intracellular bacillary load of Mycobacterium tuberculosis in macrophages induces an atypical lysosomal cell death with early features of apoptosis that progress to necrosis within hours. Unlike classical apoptosis, this cell death mode does not appear to diminish M. tuberculosis viability. We previously reported that culturing heavily infected macrophages with naïve macrophages produced an antimicrobial effect, but only if naïve macrophages were added during the pre-necrotic phase of M. tuberculosis-induced cell death. In the present study we investigated the mechanism of antimicrobial activity in co-cultures, anticipating that efferocytosis of bacilli in apoptotic bodies would be required. Confocal microscopy revealed frustrated phagocytosis of M. tuberculosis-infected macrophages with no evidence that significant numbers of bacilli were transferred to the naïve macrophages. The antimicrobial effect of naïve macrophages was retained when they were separated from infected macrophages in transwells, and conditioned co-culture supernatants transferred antimicrobial activity to cultures of infected macrophages alone. Antimicrobial activity in macrophage co-cultures was abrogated when the naïve population was deficient in IL-1 receptor or when the infected population was deficient in inducible nitric oxide synthase. The participation of nitric oxide suggested a conventional antimicrobial mechanism requiring delivery of bacilli to a late endosomal compartment. Using macrophages expressing GFP-LC3 we observed the induction of autophagy specifically by a high intracellular load of M. tuberculosis. Bacilli were identified in LC3-positive compartments and LC3-positive compartments were confirmed to be acidified and LAMP1 positive. Thus, the antimicrobial effect of naïve macrophages acting on M. tuberculosis in heavily-infected macrophages is contact-independent. Interleukin-1 provides an afferent signal that induces an as yet unidentified small molecule which promotes nitric oxide-dependent antimicrobial activity against bacilli in autolysosomes of heavily infected macrophages. This cooperative, innate antimicrobial interaction may limit the maximal growth rate of M. tuberculosis prior to the expression of adaptive immunity in pulmonary tuberculosis

Rapid genotype imputation from sequence without reference panels

Inexpensive genotyping methods are essential for genetic studies requiring large sample sizes. In human studies, array-based microarrays and high-density haplotype reference panels allow efficient genotype imputation for this purpose. However, these resources are typically unavailable in non-human settings. Here we describe a method (STITCH) for imputation based only on sequencing read data, without requiring additional reference panels or array data. We demonstrate its applicability even in settings of extremely low sequencing coverage, by accurately imputing 5.7 million SNPs at a mean r(2) value of 0.98 in 2,073 outbred laboratory mice (0.15× sequencing coverage). In a sample of 11,670 Han Chinese (1.7× coverage), we achieve accuracy similar to that of alternative approaches that require a reference panel, demonstrating that our approach can work for genetically diverse populations. Our method enables straightforward progression from low-coverage sequence to imputed genotypes, overcoming barriers that at present restrict the application of genome-wide association study technology outside humans

Superoxide dismutase A antigens derived from molecular analysis of sarcoidosis granulomas elicit systemic Th-1 immune responses

<p>Abstract</p> <p>Background</p> <p>Sarcoidosis is an idiopathic granulomatous disease with pathologic and immunologic features similar to tuberculosis. Routine histologic staining and culture fail to identify infectious agents. An alternative means for investigating a role of infectious agents in human pathogenesis involves molecular analysis of pathologic tissues for microbial nucleic acids, as well as recognition of microbial antigens by the host immune system. Molecular analysis for superoxide dismutase A (sodA) allows speciation of mycobacteria. SodA is an abundantly secreted virulence factor that generates cellular immune responses in infected hosts. The purpose of this study is to investigate if target antigens of the sarcoidosis immune response can be identified by molecular analysis of sarcoidosis granulomas.</p> <p>Methods</p> <p>We detected sodA amplicons in 12 of 17 sarcoidosis specimens, compared to 2 of 16 controls (p = 0.001, two-tailed Fisher's exact test), and 3 of 3 tuberculosis specimens (p = 0.54). Analysis of the amplicons revealed sequences identical to <it>M. tuberculosis </it>(MTB) complex, as well as sequences which were genetically divergent. Using peripheral blood mononuclear cells (PBMC) from 12 of the 17 sarcoidosis subjects, we performed enzyme-linked immunospot assay (ELISPOT) to assess for immune recognition of MTB sodA peptides, along with PBMC from 26 PPD- healthy volunteers, and 11 latent tuberculosis subjects.</p> <p>Results</p> <p>Six of 12 sarcoidosis subjects recognized the sodA peptides, compared to one of 26 PPD- controls (p = 0.002), and 6/11 PPD+ subjects (p = .68). Overall, 10 of the 12 sarcoidosis subjects from whom we obtained PBMC and archival tissue possessed molecular or immunologic evidence for sodA.</p> <p>Conclusion</p> <p>Dual molecular and immunologic analysis increases the ability to find infectious antigens. The detection of Th-1 immune responses to sodA peptides derived from molecular analysis of sarcoidosis granulomas reveals that these are among the target antigens contributing to sarcoidosis granulomatous inflammation.</p

Probabilistic fire spread forecast as a management tool in an operational setting

Background: An approach to predict fire growth in an operational setting, with the potential to be used as a decision-support tool for fire management, is described and evaluated. The operational use of fire behaviour models has mostly followed a deterministic approach, however, the uncertainty associated with model predictions needs to be quantified and included in wildfire planning and decision-making process during fire suppression activities. We use FARSITE to simulate the growth of a large wildfire. Probabilistic simulations of fire spread are performed, accounting for the uncertainty of some model inputs and parameters. Deterministic simulations were performed for comparison. We also assess the degree to which fire spread modelling and satellite active fire data can be combined, to forecast fire spread during large wildfires events. Results: Uncertainty was propagated through the FARSITE fire spread modelling system by randomly defining 100 different combinations of the independent input variables and parameters, and running the correspondent fire spread simulations in order to produce fire spread probability maps. Simulations were initialized with the reported ignition location and with satellite active fires. The probabilistic fire spread predictions show great potential to be used as a fire management tool in an operational setting, providing valuable information regarding the spatial–temporal distribution of burn probabilities. The advantage of probabilistic over deterministic simulations is clear when both are compared. Re-initializing simulations with satellite active fires did not improve simulations as expected. Conclusion: This information can be useful to anticipate the growth of wildfires through the landscape with an associated probability of occurrence. The additional information regarding when, where and with what probability the fire might be in the next few hours can ultimately help minimize the negative environmental, social and economic impacts of these firesinfo:eu-repo/semantics/publishedVersio