Showing papers by "University of Vermont published in 2017"

The Hierarchical Taxonomy of Psychopathology (HiTOP): A Dimensional Alternative to Traditional Nosologies

Abstract: The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures. (PsycINFO Database Record

Natural climate solutions

Abstract: Better stewardship of land is needed to achieve the Paris Climate Agreement goal of holding warming to below 2 °C; however, confusion persists about the specific set of land stewardship options available and their mitigation potential. To address this, we identify and quantify "natural climate solutions" (NCS): 20 conservation, restoration, and improved land management actions that increase carbon storage and/or avoid greenhouse gas emissions across global forests, wetlands, grasslands, and agricultural lands. We find that the maximum potential of NCS-when constrained by food security, fiber security, and biodiversity conservation-is 23.8 petagrams of CO2 equivalent (PgCO2e) y-1 (95% CI 20.3-37.4). This is ≥30% higher than prior estimates, which did not include the full range of options and safeguards considered here. About half of this maximum (11.3 PgCO2e y-1) represents cost-effective climate mitigation, assuming the social cost of CO2 pollution is ≥100 USD MgCO2e-1 by 2030. Natural climate solutions can provide 37% of cost-effective CO2 mitigation needed through 2030 for a >66% chance of holding warming to below 2 °C. One-third of this cost-effective NCS mitigation can be delivered at or below 10 USD MgCO2-1 Most NCS actions-if effectively implemented-also offer water filtration, flood buffering, soil health, biodiversity habitat, and enhanced climate resilience. Work remains to better constrain uncertainty of NCS mitigation estimates. Nevertheless, existing knowledge reported here provides a robust basis for immediate global action to improve ecosystem stewardship as a major solution to climate change.

Influence of diet on the gut microbiome and implications for human health.

Abstract: Recent studies have suggested that the intestinal microbiome plays an important role in modulating risk of several chronic diseases, including inflammatory bowel disease, obesity, type 2 diabetes, cardiovascular disease, and cancer. At the same time, it is now understood that diet plays a significant role in shaping the microbiome, with experiments showing that dietary alterations can induce large, temporary microbial shifts within 24 h. Given this association, there may be significant therapeutic utility in altering microbial composition through diet. This review systematically evaluates current data regarding the effects of several common dietary components on intestinal microbiota. We show that consumption of particular types of food produces predictable shifts in existing host bacterial genera. Furthermore, the identity of these bacteria affects host immune and metabolic parameters, with broad implications for human health. Familiarity with these associations will be of tremendous use to the practitioner as well as the patient.

Breast Cancer—Major changes in the American Joint Committee on Cancer eighth edition cancer staging manual

Abstract: Answer questions and earn CME/CNE The revision of the eighth edition of the primary tumor, lymph node, and metastasis (TNM) classification of the American Joint Commission of Cancer (AJCC) for breast cancer was determined by a multidisciplinary team of breast cancer experts. The panel recognized the need to incorporate biologic factors, such as tumor grade, proliferation rate, estrogen and progesterone receptor expression, human epidermal growth factor 2 (HER2) expression, and gene expression prognostic panels into the staging system. AJCC levels of evidence and guidelines for all tumor types were followed as much as possible. The panel felt that, to maintain worldwide value, the tumor staging system should remain based on TNM anatomic factors. However, the recognition of the prognostic influence of grade, hormone receptor expression, and HER2 amplification mandated their inclusion into the staging system. The value of commercially available, gene-based assays was acknowledged and prognostic input added. Tumor biomarkers and low Oncotype DX recurrence scores can alter prognosis and stage. These updates are expected to provide additional precision and flexibility to the staging system and were based on the extent of published information and analysis of large, as yet unpublished databases. The eighth edition of the AJCC TNM staging system, thus, provides a flexible platform for prognostic classification based on traditional anatomic factors, which can be modified and enhanced using patient biomarkers and multifactorial prognostic panel data. The eighth edition remains the worldwide basis for breast cancer staging and will incorporate future online updates to remain timely and relevant. CA Cancer J Clin 2017;67:290-303. © 2017 American Cancer Society.

Radiation with or without Antiandrogen Therapy in Recurrent Prostate Cancer

Abstract: BackgroundSalvage radiation therapy is often necessary in men who have undergone radical prostatectomy and have evidence of prostate-cancer recurrence signaled by a persistently or recurrently elevated prostate-specific antigen (PSA) level. Whether antiandrogen therapy with radiation therapy will further improve cancer control and prolong overall survival is unknown. MethodsIn a double-blind, placebo-controlled trial conducted from 1998 through 2003, we assigned 760 eligible patients who had undergone prostatectomy with a lymphadenectomy and had disease, as assessed on pathological testing, with a tumor stage of T2 (confined to the prostate but with a positive surgical margin) or T3 (with histologic extension beyond the prostatic capsule), no nodal involvement, and a detectable PSA level of 0.2 to 4.0 ng per milliliter to undergo radiation therapy and receive either antiandrogen therapy (24 months of bicalutamide at a dose of 150 mg daily) or daily placebo tablets during and after radiation therapy. The p...

National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium

Abstract: Data from a large, diverse set of breast imaging facilities in the Breast Cancer Surveillance Consortium, linked to state cancer registries, provide performance benchmarks for diagnostic mammography in the era of digital mammography.

Mineral supply for sustainable development requires resource governance

Abstract: Successful delivery of the United Nations sustainable development goals and implementation of the Paris Agreement requires technologies that utilize a wide range of minerals in vast quantities. Metal recycling and technological change will contribute to sustaining supply, but mining must continue and grow for the foreseeable future to ensure that such minerals remain available to industry. New links are needed between existing institutional frameworks to oversee responsible sourcing of minerals, trajectories for mineral exploration, environmental practices, and consumer awareness of the effects of consumption. Here we present, through analysis of a comprehensive set of data and demand forecasts, an interdisciplinary perspective on how best to ensure ecologically viable continuity of global mineral supply over the coming decades.

Identification of diverse astrocyte populations and their malignant analogs.

Abstract: Astrocytes are the most abundant cell type in the brain, where they perform a wide array of functions, yet the nature of their cellular heterogeneity and how it oversees these diverse roles remains shrouded in mystery. Using an intersectional fluorescence-activated cell sorting-based strategy, we identified five distinct astrocyte subpopulations present across three brain regions that show extensive molecular diversity. Application of this molecular insight toward function revealed that these populations differentially support synaptogenesis between neurons. We identified correlative populations in mouse and human glioma and found that the emergence of specific subpopulations during tumor progression corresponded with the onset of seizures and tumor invasion. In sum, we have identified subpopulations of astrocytes in the adult brain and their correlates in glioma that are endowed with diverse cellular, molecular and functional properties. These populations selectively contribute to synaptogenesis and tumor pathophysiology, providing a blueprint for understanding diverse astrocyte contributions to neurological disease.

Instagram photos reveal predictive markers of depression

Abstract: Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression. Statistical features were computationally extracted from 43,950 participant Instagram photos, using color analysis, metadata components, and algorithmic face detection. Resulting models outperformed general practitioners’ average unassisted diagnostic success rate for depression. These results held even when the analysis was restricted to posts made before depressed individuals were first diagnosed. Human ratings of photo attributes (happy, sad, etc.) were weaker predictors of depression, and were uncorrelated with computationally-generated features. These results suggest new avenues for early screening and detection of mental illness.

Capillary K+-sensing initiates retrograde hyperpolarization to increase local cerebral blood flow

Abstract: Blood flow into the brain is dynamically regulated to satisfy the changing metabolic requirements of neurons, but how this is accomplished has remained unclear. Here we demonstrate a central role for capillary endothelial cells in sensing neural activity and communicating it to upstream arterioles in the form of an electrical vasodilatory signal. We further demonstrate that this signal is initiated by extracellular K+ -a byproduct of neural activity-which activates capillary endothelial cell inward-rectifier K+ (KIR2.1) channels to produce a rapidly propagating retrograde hyperpolarization that causes upstream arteriolar dilation, increasing blood flow into the capillary bed. Our results establish brain capillaries as an active sensory web that converts changes in external K+ into rapid, 'inside-out' electrical signaling to direct blood flow to active brain regions.

Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection

Abstract: In this paper, we propose a new unsupervised spectral feature selection model by embedding a graph regularizer into the framework of joint sparse regression for preserving the local structures of data. To do this, we first extract the bases of training data by previous dictionary learning methods and, then, map original data into the basis space to generate their new representations, by proposing a novel joint graph sparse coding (JGSC) model. In JGSC, we first formulate its objective function by simultaneously taking subspace learning and joint sparse regression into account, then, design a new optimization solution to solve the resulting objective function, and further prove the convergence of the proposed solution. Furthermore, we extend JGSC to a robust JGSC (RJGSC) via replacing the least square loss function with a robust loss function, for achieving the same goals and also avoiding the impact of outliers. Finally, experimental results on real data sets showed that both JGSC and RJGSC outperformed the state-of-the-art algorithms in terms of ${k}$ -nearest neighbor classification performance.

Determining Risk of Falls in Community Dwelling Older Adults: A Systematic Review and Meta-analysis Using Posttest Probability.

Abstract: BACKGROUND: Falls and their consequences are significant concerns for older adults, caregivers, and health care providers. Identification of fall risk is crucial for appropriate referral to preventive interventions. Falls are multifactorial; no single measure is an accurate diagnostic tool. There is limited information on which history question, self-report measure, or performance-based measure, or combination of measures, best predicts future falls. Purpose: First, to evaluate the predictive ability of history questions, self-report measures, and performance-based measures for assessing fall risk of community-dwelling older adults by calculating and comparing posttest probability (PoTP) values for individual test/measures. Second, to evaluate usefulness of cumulative PoTP for measures in combination. Data Sources: To be included, a study must have used fall status as an outcome or classification variable, have a sample size of at least 30 ambulatory community-living older adults (>=65 years), and track falls occurrence for a minimum of 6 months. Studies in acute or long-term care settings, as well as those including participants with significant cognitive or neuromuscular conditions related to increased fall risk, were excluded. Searches of Medline/PubMED and Cumulative Index of Nursing and Allied Health (CINAHL) from January 1990 through September 2013 identified 2294 abstracts concerned with fall risk assessment in community-dwelling older adults. Study Selection: Because the number of prospective studies of fall risk assessment was limited, retrospective studies that classified participants (faller/nonfallers) were also included. Ninety-five full-text articles met inclusion criteria; 59 contained necessary data for calculation of PoTP. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) was used to assess each study's methodological quality. Data Extraction: Study design and QUADAS score determined the level of evidence. Data for calculation of sensitivity (Sn), specificity (Sp), likelihood ratios (LR), and PoTP values were available for 21 of 46 measures used as search terms. An additional 73 history questions, self-report measures, and performance-based measures were used in included articles; PoTP values could be calculated for 35. Data Synthesis: Evidence tables including PoTP values were constructed for 15 history questions, 15 self-report measures, and 26 performance-based measures. Recommendations for clinical practice were based on consensus. Limitations: Variations in study quality, procedures, and statistical analyses challenged data extraction, interpretation, and synthesis. There was insufficient data for calculation of PoTP values for 63 of 119 tests. Conclusions: No single test/measure demonstrated strong PoTP values. Five history questions, 2 self-report measures, and 5 performance-based measures may have clinical usefulness in assessing risk of falling on the basis of cumulative PoTP. Berg Balance Scale score (=12 seconds), and 5 times sit-to-stand times (>=12) seconds are currently the most evidence-supported functional measures to determine individual risk of future falls. Shortfalls identified during review will direct researchers to address knowledge gaps. Copyright (C) 2016 the Section on Geriatrics of the American Physical Therapy Association Language: en

Ecology under lake ice

Abstract: Winter conditions are rapidly changing in temperate ecosystems, particularly for those that experience periods of snow and ice cover. Relatively little is known of winter ecology in these systems, due to a historical research focus on summer ‘growing seasons’. We executed the first global quantitative synthesis on under-ice lake ecology, including 36 abiotic and biotic variables from 42 research groups and 101 lakes, examining seasonal differences and connections as well as how seasonal differences vary with geophysical factors. Plankton were more abundant under ice than expected; mean winter values were 43.2% of summer values for chlorophyll a, 15.8% of summer phytoplankton biovolume and 25.3% of summer zooplankton density. Dissolved nitrogen concentrations were typically higher during winter, and these differences were exaggerated in smaller lakes. Lake size also influenced winter-summer patterns for dissolved organic carbon (DOC), with higher winter DOC in smaller lakes. At coarse levels of taxonomic aggregation, phytoplankton and zooplankton community composition showed few systematic differences between seasons, although literature suggests that seasonal differences are frequently lake-specific, species-specific, or occur at the level of functional group. Within the subset of lakes that had longer time series, winter influenced the subsequent summer for some nutrient variables and zooplankton biomass.

Effect of Oral Iron Repletion on Exercise Capacity in Patients With Heart Failure With Reduced Ejection Fraction and Iron Deficiency: The IRONOUT HF Randomized Clinical Trial.

Abstract: Importance Iron deficiency is present in approximately 50% of patients with heart failure with reduced left ventricular ejection fraction (HFrEF) and is an independent predictor of reduced functional capacity and mortality. However, the efficacy of inexpensive readily available oral iron supplementation in heart failure is unknown. Objective To test whether therapy with oral iron improves peak exercise capacity in patients with HFrEF and iron deficiency. Design, Setting, and Participants Phase 2, double-blind, placebo-controlled randomized clinical trial of patients with HFrEF ( Interventions Oral iron polysaccharide (n = 111) or placebo (n = 114), 150 mg twice daily for 16 weeks. Main Outcomes and Measures The primary end point was a change in peak oxygen uptake (Vo 2 ) from baseline to 16 weeks. Secondary end points were change in 6-minute walk distance, plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels, and health status as assessed by Kansas City Cardiomyopathy Questionnaire (KCCQ, range 0-100, higher scores reflect better quality of life). Results Among 225 randomized participants (median age, 63 years; 36% women) 203 completed the study. The median baseline peak Vo 2 was 1196 mL/min (interquartile range [IQR], 887-1448 mL/min) in the oral iron group and 1167 mL/min (IQR, 887-1449 mL/min) in the placebo group. The primary end point, change in peak Vo 2 at 16 weeks, did not significantly differ between the oral iron and placebo groups (+23 mL/min vs −2 mL/min; difference, 21 mL/min [95% CI, −34 to +76 mL/min]; P = .46). Similarly, at 16 weeks, there were no significant differences between treatment groups in changes in 6-minute walk distance (−13 m; 95% CI, −32 to 6 m), NT-proBNP levels (159; 95% CI, −280 to 599 pg/mL), or KCCQ score (1; 95% CI, −2.4 to 4.4), all P > .05. Conclusions and Relevance Among participants with HFrEF with iron deficiency, high-dose oral iron did not improve exercise capacity over 16 weeks. These results do not support use of oral iron supplementation in patients with HFrEF. Trial Registration clinicaltrials.govIdentifier:NCT02188784

Forecasting the onset and course of mental illness with Twitter data

Abstract: We developed computational models to predict the emergence of depression and Post-Traumatic Stress Disorder in Twitter users. Twitter data and details of depression history were collected from 204 individuals (105 depressed, 99 healthy). We extracted predictive features measuring affect, linguistic style, and context from participant tweets (N = 279,951) and built models using these features with supervised learning algorithms. Resulting models successfully discriminated between depressed and healthy content, and compared favorably to general practitioners’ average success rates in diagnosing depression, albeit in a separate population. Results held even when the analysis was restricted to content posted before first depression diagnosis. State-space temporal analysis suggests that onset of depression may be detectable from Twitter data several months prior to diagnosis. Predictive results were replicated with a separate sample of individuals diagnosed with PTSD (Nusers = 174, Ntweets = 243,775). A state-space time series model revealed indicators of PTSD almost immediately post-trauma, often many months prior to clinical diagnosis. These methods suggest a data-driven, predictive approach for early screening and detection of mental illness.

Increasing Cardiac Rehabilitation Participation From 20% to 70%: A Road Map From the Million Hearts Cardiac Rehabilitation Collaborative

Abstract: The primary aim of the Million Hearts initiative is to prevent 1 million cardiovascular events over 5 years. Concordant with the Million Hearts' focus on achieving more than 70% performance in the "ABCS" of aspirin for those at risk, blood pressure control, cholesterol management, and smoking cessation, we outline the cardiovascular events that would be prevented and a road map to achieve more than 70% participation in cardiac rehabilitation (CR)/secondary prevention programs by the year 2022. Cardiac rehabilitation is a class Ia recommendation of the American Heart Association and the American College of Cardiology after myocardial infarction or coronary revascularization, promotes the ABCS along with lifestyle counseling and exercise, and is associated with decreased total mortality, cardiac mortality, and rehospitalizations. However, current participation rates for CR in the United States generally range from only 20% to 30%. This road map focuses on interventions, such as electronic medical record-based prompts and staffing liaisons that increase referrals of appropriate patients to CR, increase enrollment of appropriate individuals into CR, and increase adherence to longer-term CR. We also calculate that increasing CR participation from 20% to 70% would save 25,000 lives and prevent 180,000 hospitalizations annually in the United States.

International Expert Consensus on Switching Platelet P2Y12 Receptor-Inhibiting Therapies

Abstract: Dual antiplatelet therapy with aspirin and a P2Y12 inhibitor is the treatment of choice for the prevention of atherothrombotic events in patients with acute coronary syndromes and for those undergoing percutaneous coronary interventions. The availability of different oral P2Y12 inhibitors (clopidogrel, prasugrel, ticagrelor) has enabled physicians to contemplate switching among therapies because of specific clinical scenarios. The recent introduction of an intravenous P2Y12 inhibitor (cangrelor) further adds to the multitude of modalities and settings in which switching therapies may occur. In clinical practice, it is not uncommon to switch P2Y12 inhibitor, and switching may be attributed to a variety of factors. However, concerns about the safety of switching between these agents have emerged. Practice guidelines have not fully elaborated on how to switch therapies, leaving clinicians with limited guidance on when and how to switch therapies when needed. This prompted the development of this expert consensus document by key leaders from North America and Europe with expertise in basic, translational, and clinical sciences in the field of antiplatelet therapy. This expert consensus provides an overview of the pharmacology of P2Y12 inhibitors, different modalities and definitions of switching, and available literature and recommendations for switching between P2Y12 inhibitors.

Variation in Performance of Neonatal Intensive Care Units in the United States.

Abstract: Importance Hospitals use rates from the best quartile or decile as benchmarks for quality improvement aims, but to what extent these aims are achievable is uncertain. Objective To determine the proportion of neonatal intensive care units (NICUs) in 2014 that achieved rates for death and major morbidities as low as the shrunken adjusted rates from the best quartile and decile in 2005 and the time it took to achieve those rates. Design, Setting, and Participants A total of 408 164 infants with a birth weight of 501 to 1500 g born from January 1, 2005, to December 31, 2014, and cared for at 756 Vermont Oxford Network member NICUs in the United States were evaluated. Logistic regression models with empirical Bayes factors were used to estimate standardized morbidity ratios for each NICU. Each ratio was multiplied by the overall network rate to calculate the 10th, 25th, 50th, 75th, and 90th percentiles of the shrunken adjusted rates for each year. The proportion in 2014 that achieved the 10th and 25th percentile rates from 2005 and the number of years it took for 75% of NICUs to achieve the 2005 rates from the best quartile were estimated. Main Outcomes and Measures Death prior to hospital discharge, infection more than 3 days after birth, severe retinopathy of prematurity, severe intraventricular hemorrhage, necrotizing enterocolitis, and chronic lung disease among infants less than 33 weeks’ gestational age at birth. Results Of the 756 hospitals, 695 provided data for 2014. The mean unadjusted infant-level rate of death before hospital discharge decreased from 14.0% in 2005 to 10.9% in 2014. In 2014, 689 of 695 NICUs (99.1%; 95% CI, 97.4%-100.0%) achieved the 2005 shrunken adjusted rates from the best quartile for death prior to discharge, 678 of 695 (97.6%; 95% CI, 95.8%-99.6%) for late-onset infection, 558 of 681 (81.9%; 95% CI, 77.2%-86.6%) for severe retinopathy of prematurity, 611 of 693 (88.2%; 95% CI, 81.7%-97.0%) for severe intraventricular hemorrhage, 529 of 696 (76.0%; 95% CI, 71.8%-81.2%) for necrotizing enterocolitis, and 286 of 693 (41.3%; 95% CI, 36.1%-45.6%) for chronic lung disease. It took 3 years before 445 NICUs (75.0%) achieved the 2005 shrunken adjusted rate from the best quartile for death prior to discharge, 5 years to achieve the rate from the best quartile for late-onset infection, 6 years to achieve the rate from the best quartile for severe retinopathy of prematurity and severe intraventricular hemorrhage, and 8 years to achieve the rate from the best quartile for necrotizing enterocolitis. Conclusions and Relevance From 2005 to 2014, rates of death prior to discharge and serious morbidities decreased among the NICUs in this study. Within 8 years, 75% of NICUs achieved rates of performance from the best quartile of the 2005 benchmark for all outcomes except chronic lung disease. These findings provide a novel way to quantify the magnitude and pace of improvement in neonatology.

Suppression of Kasha's rule as a mechanism for fluorescent molecular rotors and aggregation-induced emission

Abstract: Although there are some proposed explanations for aggregation-induced emission, a phenomenon with applications that range from biosensors to organic light-emitting diodes, current understanding of the quantum-mechanical origin of this photophysical behaviour is limited. To address this issue, we assessed the emission properties of a series of BF2-hydrazone-based dyes as a function of solvent viscosity. These molecules turned out to be highly efficient fluorescent molecular rotors. This property, in addition to them being aggregation-induced emission luminogens, enabled us to probe deeper into their emission mechanism. Time-dependent density functional theory calculations and experimental results showed that the emission is not from the S1 state, as predicted from Kasha's rule, but from a higher energy (>S1) state. Furthermore, we found that suppression of internal conversion to the dark S1 state by restricting the rotor rotation enhances fluorescence, which leads to the proposal that suppression of Kasha's rule is the photophysical mechanism responsible for emission in both viscous solution and the solid state.

Limb Symmetry Indexes Can Overestimate Knee Function After Anterior Cruciate Ligament Injury

Abstract: Study Design Prospective cohort. Background The high risk of second anterior cruciate ligament (ACL) injuries after return to sport highlights the importance of return-to-sport decision making. Objective return-to-sport criteria frequently use limb symmetry indexes (LSIs) to quantify quadriceps strength and hop scores. Whether using the uninvolved limb in LSIs is optimal is unknown. Objectives To evaluate the uninvolved limb as a reference standard for LSIs utilized in return-to-sport testing and its relationship with second ACL injury rates. Methods Seventy athletes completed quadriceps strength and 4 single-leg hop tests before anterior cruciate ligament reconstruction (ACLR) and 6 months after ACLR. Limb symmetry indexes for each test compared involved-limb measures at 6 months to uninvolved-limb measures at 6 months. Estimated preinjury capacity (EPIC) levels for each test compared involved-limb measures at 6 months to uninvolved-limb measures before ACLR. Second ACL injuries were tracked for a minimum follow-up of 2 years after ACLR. Results Forty (57.1%) patients achieved 90% LSIs for quadriceps strength and all hop tests. Only 20 (28.6%) patients met 90% EPIC levels (comparing the involved limb at 6 months after ACLR to the uninvolved limb before ACLR) for quadriceps strength and all hop tests. Twenty-four (34.3%) patients who achieved 90% LSIs for all measures 6 months after ACLR did not achieve 90% EPIC levels for all measures. Estimated preinjury capacity levels were more sensitive than LSIs in predicting second ACL injuries (LSIs, 0.273; 95% confidence interval [CI]: 0.010, 0.566 and EPIC, 0.818; 95% CI: 0.523, 0.949). Conclusion Limb symmetry indexes frequently overestimate knee function after ACLR and may be related to second ACL injury risk. These findings raise concern about whether the variable ACL return-to-sport criteria utilized in current clinical practice are stringent enough to achieve safe and successful return to sport. Level of Evidence Prognosis, 2b. J Orthop Sports Phys Ther 2017;47(5):334-338. Epub 29 Mar 2017. doi:10.2519/jospt.2017.7285.

On Deep Learning for Trust-Aware Recommendations in Social Networks

Abstract: With the emergence of online social networks, the social network-based recommendation approach is popularly used. The major benefit of this approach is the ability of dealing with the problems with cold-start users. In addition to social networks, user trust information also plays an important role to obtain reliable recommendations. Although matrix factorization (MF) becomes dominant in recommender systems, the recommendation largely relies on the initialization of the user and item latent feature vectors. Aiming at addressing these challenges, we develop a novel trust-based approach for recommendation in social networks. In particular, we attempt to leverage deep learning to determinate the initialization in MF for trust-aware social recommendations and to differentiate the community effect in user’s trusted friendships. A two-phase recommendation process is proposed to utilize deep learning in initialization and to synthesize the users’ interests and their trusted friends’ interests together with the impact of community effect for recommendations. We perform extensive experiments on real-world social network data to demonstrate the accuracy and effectiveness of our proposed approach in comparison with other state-of-the-art methods.

Mining drives extensive deforestation in the Brazilian Amazon

Abstract: Mining poses significant and potentially underestimated risks to tropical forests worldwide. In Brazil’s Amazon, mining drives deforestation far beyond operational lease boundaries, yet the full extent of these impacts is unknown and thus neglected in environmental licensing. Here we quantify mining-induced deforestation and investigate the aspects of mining operations, which most likely contribute. We find mining significantly increased Amazon forest loss up to 70 km beyond mining lease boundaries, causing 11,670 km2 of deforestation between 2005 and 2015. This extent represents 9% of all Amazon forest loss during this time and 12 times more deforestation than occurred within mining leases alone. Pathways leading to such impacts include mining infrastructure establishment, urban expansion to support a growing workforce, and development of mineral commodity supply chains. Mining-induced deforestation is not unique to Brazil; to mitigate adverse impacts of mining and conserve tropical forests globally, environmental assessments and licensing must considered both on- and off-lease sources of deforestation.

Evaluation of a proposal for reliable low-cost grid power with 100% wind, water, and solar

Abstract: A number of analyses, meta-analyses, and assessments, including those performed by the Intergovernmental Panel on Climate Change, the National Oceanic and Atmospheric Administration, the National Renewable Energy Laboratory, and the International Energy Agency, have concluded that deployment of a diverse portfolio of clean energy technologies makes a transition to a low-carbon-emission energy system both more feasible and less costly than other pathways. In contrast, Jacobson et al. [Jacobson MZ, Delucchi MA, Cameron MA, Frew BA (2015) Proc Natl Acad Sci USA 112(49):15060-15065] argue that it is feasible to provide "low-cost solutions to the grid reliability problem with 100% penetration of WWS [wind, water and solar power] across all energy sectors in the continental United States between 2050 and 2055", with only electricity and hydrogen as energy carriers. In this paper, we evaluate that study and find significant shortcomings in the analysis. In particular, we point out that this work used invalid modeling tools, contained modeling errors, and made implausible and inadequately supported assumptions. Policy makers should treat with caution any visions of a rapid, reliable, and low-cost transition to entire energy systems that relies almost exclusively on wind, solar, and hydroelectric power.

Comprehensive benchmarking and ensemble approaches for metagenomic classifiers.

Abstract: One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited. In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can differ by over three orders of magnitude on the same datasets. Various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species. Overall, pairing tools with different classification strategies (k-mer, alignment, marker) can combine their respective advantages. This study provides positive and negative controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision, accuracy, and recall. We show that proper experimental design and analysis parameters can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.