Abstract: The aim was to update the 2009 European League against Rheumatism (EULAR) recommendations for the treatment of systemic sclerosis (SSc), with attention to new therapeutic questions. Update of the previous treatment recommendations was performed according to EULAR standard operating procedures. The task force consisted of 32 SSc clinical experts from Europe and the USA, 2 patients nominated by the pan-European patient association for SSc (Federation of European Scleroderma Associations (FESCA)), a clinical epidemiologist and 2 research fellows. All centres from the EULAR Scleroderma Trials and Research group were invited to submit and select clinical questions concerning SSc treatment using a Delphi approach. Accordingly, 46 clinical questions addressing 26 different interventions were selected for systematic literature review. The new recommendations were based on the available evidence and developed in a consensus meeting with clinical experts and patients. The procedure resulted in 16 recommendations being developed (instead of 14 in 2009) that address treatment of several SSc-related organ complications: Raynaud's phenomenon (RP), digital ulcers (DUs), pulmonary arterial hypertension (PAH), skin and lung disease, scleroderma renal crisis and gastrointestinal involvement. Compared with the 2009 recommendations, the 2016 recommendations include phosphodiesterase type 5 (PDE-5) inhibitors for the treatment of SSc-related RP and DUs, riociguat, new aspects for endothelin receptor antagonists, prostacyclin analogues and PDE-5 inhibitors for SSc-related PAH. New recommendations regarding the use of fluoxetine for SSc-related RP and haematopoietic stem cell transplantation for selected patients with rapidly progressive SSc were also added. In addition, several comments regarding other treatments addressed in clinical questions and suggestions for the SSc research agenda were formulated. These updated data-derived and consensus-derived recommendations will help rheumatologists to manage patients with SSc in an evidence-based way. These recommendations also give directions for future clinical research in SSc.

Abstract: Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few labeled samples are available. As deep neural networks (DNNs) tend to overfit using a few samples only, meta-learning typically uses shallow neural networks (SNNs), thus limiting its effectiveness. In this paper we propose a novel few-shot learning method called meta-transfer learning (MTL) which learns to adapt a deep NN for few shot learning tasks. Specifically, "meta" refers to training multiple tasks, and "transfer" is achieved by learning scaling and shifting functions of DNN weights for each task. In addition, we introduce the hard task (HT) meta-batch scheme as an effective learning curriculum for MTL. We conduct experiments using (5-class, 1-shot) and (5-class, 5-shot) recognition tasks on two challenging few-shot learning benchmarks: miniImageNet and Fewshot-CIFAR100. Extensive comparisons to related works validate that our meta-transfer learning approach trained with the proposed HT meta-batch scheme achieves top performance. An ablation study also shows that both components contribute to fast convergence and high accuracy.

Abstract: Poststroke depression (PSD) has been recognized by psychiatrists for more than 100 years, but controlled systematic studies did not begin until the 1970s. Meta-analyses addressing almost all major clinical issues in the field have emerged because of the relatively small number of patients included in some stroke studies. In order to build large databases, these meta-analyses have merged patients with rigorously assessed mood disorders with major depressive features with patients scoring above arbitrary cutoff points on depression rating scales, thus missing important findings such as cognitive impairment associated with major but not minor depression. Nevertheless, PSD occurs in a significant number of patients and constitutes an important complication of stroke, leading to greater disability as well as increased mortality. The most clinically important advances, however, have been in the treatment and prevention of PSD. Recent meta-analyses of randomized controlled trials for the treatment of PSD have demonstrated the efficacy of antidepressants. Similarly, randomized controlled trials for prevention of PSD have shown that antidepressants significantly decrease the incidence of PSD compared with placebo. Early antidepressant treatment of PSD appears to enhance both physical and cognitive recovery from stroke and might increase survival up to 10 years following stroke. There has also been progress in understanding the pathophysiology of PSD. Inflammatory processes might be associated with the onset of at least some depressive symptoms. In addition, genetic and epigenetic variations, white matter disease, cerebrovascular deregulation, altered neuroplasticity, and changes in glutamate neurotransmission might be relevant etiological factors. Further elucidation of the mechanism of PSD may ultimately lead to specific targeted treatments.

Abstract: In this paper, we propose a novel 3D object detector that can exploit both LIDAR as well as cameras to perform very accurate localization. Towards this goal, we design an end-to-end learnable architecture that exploits continuous convolutions to fuse image and LIDAR feature maps at different levels of resolution. Our proposed continuous fusion layer encode both discrete-state image features as well as continuous geometric information. This enables us to design a novel, reliable and efficient end-to-end learnable 3D object detector based on multiple sensors. Our experimental evaluation on both KITTI as well as a large scale 3D object detection benchmark shows significant improvements over the state of the art.

Abstract: BackgroundThe excess risks of death from any cause and death from cardiovascular causes among persons with type 2 diabetes and various levels of glycemic control and renal complications are unknown. In this registry-based study, we assessed these risks according to glycemic control and renal complications among persons with type 2 diabetes. MethodsWe included patients with type 2 diabetes who were registered in the Swedish National Diabetes Register on or after January 1, 1998. For each patient, five controls were randomly selected from the general population and matched according to age, sex, and county. All the participants were followed until December 31, 2011, in the Swedish Registry for Cause-Specific Mortality. ResultsThe mean follow-up was 4.6 years in the diabetes group and 4.8 years in the control group. Overall, 77,117 of 435,369 patients with diabetes (17.7%) died, as compared with 306,097 of 2,117,483 controls (14.5%) (adjusted hazard ratio, 1.15; 95% confidence interval [CI], 1.14 to 1.16). T...

Abstract: COVID-19 (the new strain of coronavirus) has been declared a global pandemic. Measures announced over recent weeks to tackle it have seen people's day-to-day life drastically altered. These changes are essential to beat coronavirus and protect health systems (UK Home Office 2020). However, there are unintended, negative consequences. As the virus continues to spread across the world, it brings with it multiple new stresses, including physical and psychological health risks, isolation and loneliness, the closure of many schools and businesses, economic vulnerability and job losses. Through all of that, children (and their mothers) are particularly vulnerable (End Violence against Children, 2020) to the risk of domestic violence. Domestic violence refers to a range of violations that happen within a domestic space. It is a broad term that encompasses intimate partner violence (IPV), a form of abuse that is perpetrated by a current or ex-partner.

Abstract: In this paper we argue for the fundamental importance of the value distribution: the distribution of the random return received by a reinforcement learning agent. This is in contrast to the common approach to reinforcement learning which models the expectation of this return, or value. Although there is an established body of literature studying the value distribution, thus far it has always been used for a specific purpose such as implementing risk-aware behaviour. We begin with theoretical results in both the policy evaluation and control settings, exposing a significant distributional instability in the latter. We then use the distributional perspective to design a new algorithm which applies Bellman's equation to the learning of approximate value distributions. We evaluate our algorithm using the suite of games from the Arcade Learning Environment. We obtain both state-of-the-art results and anecdotal evidence demonstrating the importance of the value distribution in approximate reinforcement learning. Finally, we combine theoretical and empirical evidence to highlight the ways in which the value distribution impacts learning in the approximate setting.

Abstract: Summary Background We previously found that dual HER2 blockade with trastuzumab and lapatinib led to inhibition of tumour growth in patient-derived xenografts of HER2 -amplified metastatic colorectal cancer. In this study, we aimed to assess the antitumour activity of trastuzumab and lapatinib in patients with HER2-positive colorectal cancer. Methods HERACLES was a proof-of-concept, multicentre, open-label, phase 2 trial done at four Italian academic cancer centres. We enrolled adult patients with KRAS exon 2 (codons 12 and 13) wild-type and HER2-positive metastatic colorectal cancer refractory to standard of care (including cetuximab or panitumumab), an Eastern Cooperative Oncology Group performance status of 0 or 1, and at least one measurable lesion. We defined HER2 positivity in tumour samples by use of immunohistochemistry and fluorescence in-situ hybridisation in accordance with our previously validated colorectal cancer-specific diagnostic criteria. Eligible patients received intravenous trastuzumab at 4 mg/kg loading dose followed by 2 mg/kg once per week, and oral lapatinib at 1000 mg per day until evidence of disease progression. The primary endpoint was the proportion of patients achieving an objective response (defined as complete response or partial response), which was assessed by independent central review in the intention-to-treat population. This trial is registered with EudraCT, number 2012-002128-33. Findings Between Aug 27, 2012, and May 15, 2015, we screened 914 patients with KRAS exon 2 (codons 12 and 13) wild-type metastatic colorectal cancer and identified 48 (5%) patients with HER2-positive tumours, although two died before enrolment. Of these patients, 27 were eligible for the trial. All were evaluable for response. At the time of data cutoff on Oct 15, 2015, with a median follow-up of 94 weeks (IQR 51–127), eight (30%, 95% CI 14–50) of 27 patients had achieved an objective response, with one patient (4%, 95% CI −3 to 11) achieving a complete response, and seven (26%, 95% CI 9–43) achieving partial responses; 12 (44%, 95% CI 25–63) patients had stable disease. Six (22%) of 27 patients had grade 3 adverse events, which consisted of fatigue in four patients, skin rash in one patient, and increased bilirubin concentration in one patient. No grade 4 or 5 adverse events were reported. We detected no drug-related serious adverse events. Interpretation The combination of trastuzumab and lapatinib is active and well tolerated in treatment-refractory patients with HER2-positive metastatic colorectal cancer. Funding Associazione Italiana Ricerca Cancro (AIRC), Fondazione Oncologia Niguarda Onlus, and Roche.

Abstract: We introduce a new class of scalar-tensor theories of gravity that extend Horndeski, or " generalized galileon " , models. Despite possessing equations of motion of higher order in derivatives, we show that the true propagating degrees of freedom obey well-behaved second-order equations and are thus free from Ostrogradski instabilities, in contrast to standard lore. Remarkably, the covariant versions of the original galileon Lagrangians—obtained by direct replacement of derivatives with covariant derivatives—belong to this class of theories. These extensions of Horndeski theories exhibit an uncommon, interesting phenomenology: The scalar degree of freedom affects the speed of sound of matter, even when the latter is minimally coupled to gravity. The discovery of the present cosmological acceleration has spurred the exploration of gravitational theories that could account for this effect. Many extensions of general relativity (GR) are based on the inclusion of a scalar degree of freedom (DOF) in addition to the two ten-sor propagating modes of GR (see e.g. [1] for a review). In this context, a recent important proposal is the so-called galileon models [2], with Lagrangians that involve second-order derivatives of the scalar field and lead, nevertheless , to equations of motions of second order. Such a property guarantees the avoidance of Ostrogradski in-stabilities, i.e. of the ghost-like DOF that are usually associated with higher time derivatives (see e.g. [3]). Initially introduced in Minkowski spacetime, galileons have then been generalized to curved spacetimes [4–6], where they turn out to be equivalent to a class of theories originally constructed by Horndeski forty years ago [7]. Today, Horndeski theories, which include quintessence, k-essence and f (R) models, constitute the main theoretical framework for scalar-tensor theories, in which cosmologi-cal observations are interpreted. The purpose of this Letter is to show that this framework is not as exhaustive as generally believed, and can in fact be extended to include new Lagrangians. Indeed, having equations of motion of second order in derivatives—while indeed sufficient—is not necessary to avoid Ostrogradski instabilities, as already pointed out in e.g. [8, 9]. The theories beyond Horndeski that we propose lead to distinct observational effects and are thus fully relevant for an extensive comparison of scalar-tensor theories with observations.

Abstract: What determines what we see? In contrast to the traditional "modular" understanding of perception, according to which visual processing is encapsulated from higher-level cognition, a tidal wave of recent research alleges that states such as beliefs, desires, emotions, motivations, intentions, and linguistic representations exert direct top-down influences on what we see. There is a growing consensus that such effects are ubiquitous, and that the distinction between perception and cognition may itself be unsustainable. We argue otherwise: none of these hundreds of studies - either individually or collectively - provide compelling evidence for true top-down effects on perception, or "cognitive penetrability". In particular, and despite their variety, we suggest that these studies all fall prey to only a handful of pitfalls. And whereas abstract theoretical challenges have failed to resolve this debate in the past, our presentation of these pitfalls is empirically anchored: in each case, we show not only how certain studies could be susceptible to the pitfall (in principle), but how several alleged top-down effects actually are explained by the pitfall (in practice). Moreover, these pitfalls are perfectly general, with each applying to dozens of other top-down effects. We conclude by extracting the lessons provided by these pitfalls into a checklist that future work could use to convincingly demonstrate top-down effects on visual perception. The discovery of substantive top-down effects of cognition on perception would revolutionize our understanding of how the mind is organized; but without addressing these pitfalls, no such empirical report will license such exciting conclusions. Language: en

Abstract: When T cells from a bone marrow donor begin to attack the host within 3 months after hematopoietic-cell transplantation, acute graft-versus-host disease results. The disease mainly affects the skin, liver, and gastrointestinal tract and is treated with immunosuppressive drugs.

Abstract: Assume that a multi-user multiple-input multiple-output (MIMO) system is designed from scratch to uniformly cover a given area with maximal energy efficiency (EE). What are the optimal number of antennas, active users, and transmit power? The aim of this paper is to answer this fundamental question. We consider jointly the uplink and downlink with different processing schemes at the base station and propose a new realistic power consumption model that reveals how the above parameters affect the EE. Closed-form expressions for the EE-optimal value of each parameter, when the other two are fixed, are provided for zero-forcing (ZF) processing in single-cell scenarios. These expressions prove how the parameters interact. For example, in sharp contrast to common belief, the transmit power is found to increase (not to decrease) with the number of antennas. This implies that energy-efficient systems can operate in high signal-to-noise ratio regimes in which interference-suppressing signal processing is mandatory. Numerical and analytical results show that the maximal EE is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve a relatively large number of users using ZF processing. The numerical results show the same behavior under imperfect channel state information and in symmetric multi-cell scenarios.

Abstract: In this article we use Hirsch and Levin’s (1999) notion of ‘umbrella concepts’ as an analytical lens, in order to articulate the valuable catalytic function the circular economy concept could perform in the waste and resource management debate. We realize this goal by anchoring the circular economy concept in this broader debate through a narrative approach. This leads to the insight that while the various resource strategies grouped under circular economy’s banner are not new individually, the concept offers a new framing of these strategies by drawing attention to their capacity of prolonging resource use as well as to the relationship between these strategies. As such, circular economy offers a new perspective on waste and resource management and provides a new cognitive unit and discursive space for debate. We conclude by discussing research opportunities for the IE community relating to the concept’s theoretical development and its implementation. Specifically, we pose that reinvigorating and growing the social science aspects of IE is required for both. After all, it is the wide adoption and collective implementation of an idea that shapes our material future.

Abstract: Estimates vary regarding the number of G protein-coupled receptors (GPCRs), the largest family of membrane receptors that are targeted by approved drugs, and the number of such drugs that target GPCRs. We review current knowledge regarding GPCRs as drug targets by integrating data from public databases (ChEMBL, Guide to PHARMACOLOGY, and DrugBank) and from the Broad Institute Drug Repurposing Hub. To account for discrepancies among these sources, we curated a list of GPCRs currently targeted by approved drugs. As of November 2017, 134 GPCRs are targets for drugs approved in the United States or European Union; 128 GPCRs are targets for drugs listed in the Food and Drug Administration Orange Book. We estimate that ∼700 approved drugs target GPCRs, implying that approximately 35% of approved drugs target GPCRs. GPCRs and GPCR-related proteins, i.e., those upstream of or downstream from GPCRs, represent ∼17% of all protein targets for approved drugs, with GPCRs themselves accounting for ∼12%. As such, GPCRs constitute the largest family of proteins targeted by approved drugs. Drugs that currently target GPCRs and GPCR-related proteins are primarily small molecules and peptides. Since ∼100 of the ∼360 human endo-GPCRs (other than olfactory, taste, and visual GPCRs) are orphan receptors (lacking known physiologic agonists), the number of GPCR targets, the number of GPCR-targeted drugs, and perhaps the types of drugs will likely increase, thus further expanding this GPCR repertoire and the many roles of GPCR drugs in therapeutics.

Abstract: Student feedback literacy denotes the understandings, capacities and dispositions needed to make sense of information and use it to enhance work or learning strategies. In this conceptual paper, student responses to feedback are reviewed and a number of barriers to student uptake of feedback are discussed. Four inter-related features are proposed as a framework underpinning students’ feedback literacy: appreciating feedback; making judgments; managing affect; and taking action. Two well-established learning activities, peer feedback and analysing exemplars, are discussed to illustrate how this framework can be operationalized. Some ways in which these two enabling activities can be re-focused more explicitly towards developing students’ feedback literacy are elaborated. Teachers are identified as playing important facilitating roles in promoting student feedback literacy through curriculum design, guidance and coaching. The implications and conclusion summarise recommendations for teaching and set...

Abstract: Immunotherapy has demonstrated impressive outcomes for some patients with cancer. However, selecting patients who are most likely to respond to immunotherapy remains a clinical challenge. Here, we discuss immune escape mechanisms exploited by cancer and present strategies for applying this knowledge to improving the efficacy of cancer immunotherapy.

Abstract: CD44, a non-kinase transmembrane glycoprotein, is overexpressed in several cell types including cancer stem cells and frequently shows alternative spliced variants that are thought to play a role in cancer development and progression. Hyaluronan, the main ligand for CD44, binds to and activates CD44 resulting in activation of cell signaling pathways that induces cell proliferation, increases cell survival, modulates cytoskeletal changes, and enhances cellular motility. The different functional roles of CD44 standard (CD44s) and specific CD44 variant (CD44v) isoforms are not fully understood. CD44v contain additional peptide motifs that can interact with and sequester growth factors and cytokines at the cell surface thereby functioning as coreceptors to facilitate cell signaling. Moreover, CD44v were expressed in metastasized tumors, whereas switching between CD44v and CD44s may play a role in regulating epithelial to mesenchymal transition (EMT) and in the adaptive plasticity of cancer cells. Here, we review current data on the structural and functional properties of CD44, the known roles for CD44 in tumorigencity, the regulation of CD44 expression, and the potential for targeting CD44 for cancer therapy.

Abstract: BACKGROUND Despite growing evidence that bariatric/metabolic surgery powerfully improves type 2 diabetes (T2D), existing diabetes treatment algorithms do not include surgical options. AIM The 2nd Diabetes Surgery Summit (DSS-II), an international consensus conference, was convened in collaboration with leading diabetes organizations to develop global guidelines to inform clinicians and policymakers about benefits and limitations of metabolic surgery for T2D. METHODS A multidisciplinary group of 48 international clinicians/scholars (75% nonsurgeons), including representatives of leading diabetes organizations, participated in DSS-II. After evidence appraisal (MEDLINE [1 January 2005–30 September 2015]), three rounds of Delphi-like questionnaires were used to measure consensus for 32 data-based conclusions. These drafts were presented at the combined DSS-II and 3rd World Congress on Interventional Therapies for Type 2 Diabetes (London, U.K., 28–30 September 2015), where they were open to public comment by other professionals and amended face-to-face by the Expert Committee. RESULTS Given its role in metabolic regulation, the gastrointestinal tract constitutes a meaningful target to manage T2D. Numerous randomized clinical trials, albeit mostly short/midterm, demonstrate that metabolic surgery achieves excellent glycemic control and reduces cardiovascular risk factors. On the basis of such evidence, metabolic surgery should be recommended to treat T2D in patients with class III obesity (BMI ≥40 kg/m2) and in those with class II obesity (BMI 35.0–39.9 kg/m2) when hyperglycemia is inadequately controlled by lifestyle and optimal medical therapy. Surgery should also be considered for patients with T2D and BMI 30.0–34.9 kg/m2 if hyperglycemia is inadequately controlled despite optimal treatment with either oral or injectable medications. These BMI thresholds should be reduced by 2.5 kg/m2 for Asian patients. CONCLUSIONS Although additional studies are needed to further demonstrate long-term benefits, there is sufficient clinical and mechanistic evidence to support inclusion of metabolic surgery among antidiabetes interventions for people with T2D and obesity. To date, the DSS-II guidelines have been formally endorsed by 45 worldwide medical and scientific societies. Health care regulators should introduce appropriate reimbursement policies.

Abstract: Topological semimetals can support one-dimensional Fermi lines or zero-dimensional Weyl points in momentum space, where the valence and conduction bands touch. While the degeneracy points in Weyl semimetals are robust against any perturbation that preserves translational symmetry, nodal lines require protection by additional crystalline symmetries such as mirror reflection. Here we report, based on a systematic theoretical study and a detailed experimental characterization, the existence of topological nodal-line states in the non-centrosymmetric compound PbTaSe2 with strong spin-orbit coupling. Remarkably, the spin-orbit nodal lines in PbTaSe2 are not only protected by the reflection symmetry but also characterized by an integer topological invariant. Our detailed angle-resolved photoemission measurements, first-principles simulations and theoretical topological analysis illustrate the physical mechanism underlying the formation of the topological nodal-line states and associated surface states for the first time, thus paving the way towards exploring the exotic properties of the topological nodal-line fermions in condensed matter systems.

Abstract: We demonstrate first room temperature, and ultrabright single photon emission from a color center in two-dimensional multilayer hexagonal boron nitride. Density Functional Theory calculations indicate that vacancy-related centers are a likely source of the emission.

Abstract: Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and 'enhancer hijacking' events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.

Abstract: Many machine learning algorithms are vulnerable to almost imperceptible perturbations of their inputs. So far it was unclear how much risk adversarial perturbations carry for the safety of real-world machine learning applications because most methods used to generate such perturbations rely either on detailed model information (gradient-based attacks) or on confidence scores such as class probabilities (score-based attacks), neither of which are available in most real-world scenarios. In many such cases one currently needs to retreat to transfer-based attacks which rely on cumbersome substitute models, need access to the training data and can be defended against. Here we emphasise the importance of attacks which solely rely on the final model decision. Such decision-based attacks are (1) applicable to real-world black-box models such as autonomous cars, (2) need less knowledge and are easier to apply than transfer-based attacks and (3) are more robust to simple defences than gradient- or score-based attacks. Previous attacks in this category were limited to simple models or simple datasets. Here we introduce the Boundary Attack, a decision-based attack that starts from a large adversarial perturbation and then seeks to reduce the perturbation while staying adversarial. The attack is conceptually simple, requires close to no hyperparameter tuning, does not rely on substitute models and is competitive with the best gradient-based attacks in standard computer vision tasks like ImageNet. We apply the attack on two black-box algorithms from this http URL. The Boundary Attack in particular and the class of decision-based attacks in general open new avenues to study the robustness of machine learning models and raise new questions regarding the safety of deployed machine learning systems. An implementation of the attack is available as part of Foolbox at this https URL .

Abstract: We propose and characterize a new Z2 class of topological semimetals with a vanishing spin-orbit interaction. The proposed topological semimetals are characterized by the presence of bulk one-dimensional (1D) Dirac line nodes (DLNs) and two-dimensional (2D) nearly flat surface states, protected by inversion and time-reversal symmetries. We develop the Z2 invariants dictating the presence of DLNs based on parity eigenvalues at the parity-invariant points in reciprocal space. Moreover, using first-principles calculations, we predict DLNs to occur in Cu_{3}N near the Fermi energy by doping nonmagnetic transition metal atoms, such as Zn and Pd, with the 2D surface states emerging in the projected interior of the DLNs. This Letter includes a brief discussion of the effects of spin-orbit interactions and symmetry breaking as well as comments on experimental implications.

Abstract: BackgroundThe Hospital Readmissions Reduction Program, which is included in the Affordable Care Act (ACA), applies financial penalties to hospitals that have higher-than-expected readmission rates for targeted conditions. Some policy analysts worry that reductions in readmissions are being achieved by keeping returning patients in observation units instead of formally readmitting them to the hospital. We examined the changes in readmission rates and stays in observation units over time for targeted and nontargeted conditions and assessed whether hospitals that had greater increases in observation-service use had greater reductions in readmissions. MethodsWe compared monthly, hospital-level rates of readmission and observation-service use within 30 days after hospital discharge among Medicare elderly beneficiaries from October 2007 through May 2015. We used an interrupted time-series model to determine when trends changed and whether changes differed between targeted and nontargeted conditions. We assessed...

Abstract: For millions of years, our resident microbes have coevolved and coexisted with us in a mostly harmonious symbiotic relationship. We are not distinct entities from our microbiome, but together we form a 'superorganism' or holobiont, with the microbiome playing a significant role in our physiology and health. The mouth houses the second most diverse microbial community in the body, harbouring over 700 species of bacteria that colonise the hard surfaces of teeth and the soft tissues of the oral mucosa. Through recent advances in technology, we have started to unravel the complexities of the oral microbiome and gained new insights into its role during both health and disease. Perturbations of the oral microbiome through modern-day lifestyles can have detrimental consequences for our general and oral health. In dysbiosis, the finely-tuned equilibrium of the oral ecosystem is disrupted, allowing disease-promoting bacteria to manifest and cause conditions such as caries, gingivitis and periodontitis. For practitioners and patients alike, promoting a balanced microbiome is therefore important to effectively maintain or restore oral health. This article aims to give an update on our current knowledge of the oral microbiome in health and disease and to discuss implications for modern-day oral healthcare.