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The rough guide to the Lake District
\"The Rough Guide to the Lake District is the best all-purpose guide to the English Lake District, beautifully illustrated with colour photos and full-colour maps. Comprehensive, lively reviews outline the finest places to stay and eat for every budget, based on personal inspection by a long-time Lakes expert. Whether you're looking for a walker's hostel or boutique hotel, simple cafe or swanky gastro-pub, farmhouse B&B or country-house hotel, The Rough Guide to the Lake District has the lowdown on all the best deals, detailed information on the best way to get around by public transport, while special features on the great outdoors focus on local walks, classic hikes, mountain climbs, lake cruises and family adventures. The Things Not to Miss section pinpoints some of the absolute must-sees, while author picks throughout The Rough Guide to the Lake District highlight personal favourites and special places that are less well known. Whether you're on a walking holiday or family break, you can discover all the facts you need - from full opening times and admission prices to festival dates and walking routes, plus history, culture, nature, and wildlife of the English lakes to help you make the most of your time in the Lake District.\" -- Provided by publisher.
Book
Antibiotic resistance breakers: can repurposed drugs fill the antibiotic discovery void?
Key Points
Concern over antibiotic resistance is growing. Resistance of up to 50% has been reported in some regions, including resistance to carbapenems, our current last line of defence.
New classes of antibiotics are needed, particularly against Gram-negative bacteria. However, even if the scientific hurdles can be overcome, it could take decades before sufficient numbers of such antibiotics become available.
As an interim solution, antibiotic resistance could be 'broken' by co-administering appropriate non-antibiotic drugs with failing antibiotics.
Several marketed drugs that do not currently have antibacterial indications can directly kill bacteria, reduce the antibiotic minimum inhibitory concentration when used in combination with existing antibiotics, modulate host defence through effects on host innate immunity, particularly inflammation and autophagy, or a combination of these three.
This article discusses how such 'antibiotic resistance breakers' (ARBs) could contribute to reducing the antibiotic resistance problem, and analyses a priority list of candidates for further investigation.
Drug resistance is threatening to sideline the currently available antibiotics, and new antibiotics are unlikely to become available before the current arsenal becomes ineffective. Brown proposes the use of approved drugs or neutraceuticals as antibiotic resistance breakers — compounds that could be administered alongside current antibiotics to prolong their useful lifespan — to bridge the gap.
Concern over antibiotic resistance is growing, and new classes of antibiotics, particularly against Gram-negative bacteria, are needed. However, even if the scientific hurdles can be overcome, it could take decades for sufficient numbers of such antibiotics to become available. As an interim solution, antibiotic resistance could be 'broken' by co-administering appropriate non-antibiotic drugs with failing antibiotics. Several marketed drugs that do not currently have antibacterial indications can either directly kill bacteria, reduce the antibiotic minimum inhibitory concentration when used in combination with existing antibiotics and/or modulate host defence through effects on host innate immunity, in particular by altering inflammation and autophagy. This article discusses how such 'antibiotic resistance breakers' could contribute to reducing the antibiotic resistance problem, and analyses a priority list of candidates for further investigation.
Journal Article
Emergency department triage prediction of clinical outcomes using machine learning models
Background
Development of emergency department (ED) triage systems that accurately differentiate and prioritize critically ill from stable patients remains challenging. We used machine learning models to predict clinical outcomes, and then compared their performance with that of a conventional approach—the Emergency Severity Index (ESI).
Methods
Using National Hospital and Ambulatory Medical Care Survey (NHAMCS) ED data, from 2007 through 2015, we identified all adult patients (aged ≥ 18 years). In the randomly sampled training set (70%), using
routinely
available triage data as predictors (e.g., demographics, triage vital signs, chief complaints, comorbidities), we developed four machine learning models: Lasso regression, random forest, gradient boosted decision tree, and deep neural network. As the reference model, we constructed a logistic regression model using the five-level ESI data. The clinical outcomes were critical care (admission to intensive care unit or in-hospital death) and hospitalization (direct hospital admission or transfer). In the test set (the remaining 30%), we measured the predictive performance, including area under the receiver-operating-characteristics curve (AUC) and net benefit (decision curves) for each model.
Results
Of 135,470 eligible ED visits, 2.1% had critical care outcome and 16.2% had hospitalization outcome. In the critical care outcome prediction, all four machine learning models outperformed the reference model (e.g., AUC, 0.86 [95%CI 0.85–0.87] in the deep neural network vs 0.74 [95%CI 0.72–0.75] in the reference model), with less under-triaged patients in ESI triage levels 3 to 5 (urgent to non-urgent). Likewise, in the hospitalization outcome prediction, all machine learning models outperformed the reference model (e.g., AUC, 0.82 [95%CI 0.82–0.83] in the deep neural network vs 0.69 [95%CI 0.68–0.69] in the reference model) with less over-triages in ESI triage levels 1 to 3 (immediate to urgent). In the decision curve analysis, all machine learning models consistently achieved a greater net benefit—a larger number of appropriate triages considering a trade-off with over-triages—across the range of clinical thresholds.
Conclusions
Compared to the conventional approach, the machine learning models demonstrated a superior performance to predict critical care and hospitalization outcomes. The application of modern machine learning models may enhance clinicians’ triage decision making, thereby achieving better clinical care and optimal resource utilization.
Journal Article
Evidence for PMAT- and OCT-like biogenic amine transporters in a probiotic strain of Lactobacillus: Implications for interkingdom communication within the microbiota-gut-brain axis
The ability of prokaryotic microbes to produce and respond to neurochemicals that are more often associated with eukaryotic systems is increasingly recognized through the concept of microbial endocrinology. Most studies have described the phenomena of neurochemical production by bacteria, but there remains an incomplete understanding of the mechanisms by which microbe- or host-derived neuroactive substances can be recognized by bacteria. Based on the evolutionary origins of eukaryotic solute carrier transporters, we hypothesized that bacteria may possess an analogous uptake function for neuroactive biogenic amines. Using specific fluorescence-based assays, Lactobacillus salivarius biofilms appear to express both plasma membrane monoamine transporter (PMAT)- and organic cation transporter (OCT)-like uptake of transporter-specific fluorophores. This phenomenon is not distributed throughout the genus Lactobacillus as L. rhamnosus biofilms did not take up these fluorophores. PMAT probe uptake into L. salivarius biofilms was attenuated by the protonophore CCCP, the cation transport inhibitor decynium-22, and the natural substrates norepinephrine, serotonin and fluoxetine. These results provide the first evidence, to our knowledge, for the existence of PMAT- and OCT-like uptake systems in a bacterium. They also suggest the existence of a hitherto unrecognized mechanism by which a probiotic bacterium may interact with host signals and may provide a means to examine microbial endocrinology-based interactions in health and disease that are part of the larger microbiota-gut-brain axis.
Journal Article
The Little Golden Book of jokes and riddles
Enjoy this unique book of kids' laugh-out-loud riddles and jokes!
Book
Causes of encephalitis and differences in their clinical presentations in England: a multicentre, population-based prospective study
Encephalitis has many causes, but for most patients the cause is unknown. We aimed to establish the cause and identify the clinical differences between causes in patients with encephalitis in England.
Patients of all ages and with symptoms suggestive of encephalitis were actively recruited for 2 years (staged start between October, 2005, and November, 2006) from 24 hospitals by clinical staff. Systematic laboratory testing included PCR and antibody assays for all commonly recognised causes of infectious encephalitis, investigation for less commonly recognised causes in immunocompromised patients, and testing for travel-related causes if indicated. We also tested for non-infectious causes for acute encephalitis including autoimmunity. A multidisciplinary expert team reviewed clinical presentation and hospital tests and directed further investigations. Patients were followed up for 6 months after discharge from hospital.
We identified 203 patients with encephalitis. Median age was 30 years (range 0–87). 86 patients (42%, 95% CI 35–49) had infectious causes, including 38 (19%, 14–25) herpes simplex virus, ten (5%, 2–9) varicella zoster virus, and ten (5%, 2–9) Mycobacterium tuberculosis; 75 (37%, 30–44) had unknown causes. 42 patients (21%, 15–27) had acute immune-mediated encephalitis. 24 patients (12%, 8–17) died, with higher case fatality for infections from M tuberculosis (three patients; 30%, 7–65) and varicella zoster virus (two patients; 20%, 2–56). The 16 patients with antibody-associated encephalitis had the worst outcome of all groups—nine (56%, 30–80) either died or had severe disabilities. Patients who died were more likely to be immunocompromised than were those who survived (OR=3·44).
Early diagnosis of encephalitis is crucial to ensure that the right treatment is given on time. Extensive testing substantially reduced the proportion with unknown cause, but the proportion of cases with unknown cause was higher than that for any specific identified cause.
The Policy Research Programme, Department of Health, UK.
Journal Article
Paradise lost : a life of F. Scott Fitzgerald
Pigeonholed in popular memory as a Jazz Age epicurean, a playboy, and an emblem of the Lost Generation, F. Scott Fitzgerald was at heart a moralist struck by the nation's shifting mood and manners after World War I. In Paradise Lost, David Brown contends that Fitzgerald's deepest allegiances were to a fading antebellum world he associated with his father's Chesapeake Bay roots. Yet as a midwesterner, an Irish Catholic, and a perpetually in-debt author, he felt like an outsider in the haute bourgeoisie haunts of Lake Forest, Princeton, and Hollywood--places that left an indelible mark on his worldview. In this comprehensive biography, Brown reexamines Fitzgerald's childhood, first loves, and difficult marriage to Zelda Sayre. He looks at Fitzgerald's friendship with Hemingway, the golden years that culminated with Gatsby, and his increasing alcohol abuse and declining fortunes which coincided with Zelda's institutionalization and the nation's economic collapse. Placing Fitzgerald in the company of Progressive intellectuals such as Charles Beard, Randolph Bourne, and Thorstein Veblen, Brown reveals Fitzgerald as a writer with an encompassing historical imagination not suggested by his reputation as \"the chronicler of the Jazz Age.\" His best novels, stories, and essays take the measure of both the immediate moment and the more distant rhythms of capital accumulation, immigration, and sexual politics that were moving America further away from its Protestant agrarian moorings. Fitzgerald wrote powerfully about change in America, Brown shows, because he saw it as the dominant theme in his own family history and life.-- Provided by publisher
Book
Using Seroprevalence and Immunisation Coverage Data to Estimate the Global Burden of Congenital Rubella Syndrome, 1996-2010: A Systematic Review
The burden of Congenital Rubella Syndrome (CRS) is typically underestimated in routine surveillance. Updated estimates are needed following the recent WHO position paper on rubella and recent GAVI initiatives, funding rubella vaccination in eligible countries. Previous estimates considered the year 1996 and only 78 (developing) countries.
We reviewed the literature to identify rubella seroprevalence studies conducted before countries introduced rubella-containing vaccination (RCV). These data and the estimated vaccination coverage in the routine schedule and mass campaigns were incorporated in mathematical models to estimate the CRS incidence in 1996 and 2000-2010 for each country, region and globally.
The estimated CRS decreased in the three regions (Americas, Europe and Eastern Mediterranean) which had introduced widespread RCV by 2010, reaching <2 per 100,000 live births (the Americas and Europe) and 25 (95% CI 4-61) per 100,000 live births (the Eastern Mediterranean). The estimated incidence in 2010 ranged from 90 (95% CI: 46-195) in the Western Pacific, excluding China, to 116 (95% CI: 56-235) and 121 (95% CI: 31-238) per 100,000 live births in Africa and SE Asia respectively. Highest numbers of cases were predicted in Africa (39,000, 95% CI: 18,000-80,000) and SE Asia (49,000, 95% CI: 11,000-97,000). In 2010, 105,000 (95% CI: 54,000-158,000) CRS cases were estimated globally, compared to 119,000 (95% CI: 72,000-169,000) in 1996.
Whilst falling dramatically in the Americas, Europe and the Eastern Mediterranean after vaccination, the estimated CRS incidence remains high elsewhere. Well-conducted seroprevalence studies can help to improve the reliability of these estimates and monitor the impact of rubella vaccination.
Journal Article