Search

Individuals 65 years or older will comprise an estimated 20.0% of the U.S. population by 2030. This study investigated the association between food insecurity and health-related quality of life (HRQoL) among an older adult population (n = 234). HRQoL was measured using Healthy Days, a validated survey tool developed by the Centers of Disease Control and Prevention. Food-insecure individuals were more likely to report ≥14 physically unhealthy days (OR = 1.49, 95% CI 0.47-4.78) and ≥14 days with activity limitations (OR = 4.07, 95% CI 0.68-24.1). Although nonsignificant, the findings highlight food insecurity as a potentially important social determinant of health throughout the life course, including at an older age. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) preserved in marine sediments is increasingly being used to study past ecosystems. However, little is known about how accurately marine biodiversity is recorded in sediment eDNA archives, especially planktonic taxa. Here, we address this question by comparing eukaryotic diversity in 273 eDNA samples from three water depths and the surface sediments of 24 stations in the Nordic Seas. Analysis of 18S-V9 metabarcoding data reveals distinct eukaryotic assemblages between water and sediment eDNA. Only 40% of Amplicon Sequence Variants (ASVs) detected in water were also found in sediment eDNA. Remarkably, the ASVs shared between water and sediment accounted for 80% of total sequence reads suggesting that a large amount of plankton DNA is transported to the seafloor, predominantly from abundant phytoplankton taxa. However, not all plankton taxa were equally archived on the seafloor. The plankton DNA deposited in the sediments was dominated by diatoms and showed an underrepresentation of certain nano- and picoplankton taxa (Picozoa or Prymnesiophyceae). Our study offers the first insights into the patterns of plankton diversity recorded in sediment in relation to seasonality and spatial variability of environmental conditions in the Nordic Seas. Our results suggest that the genetic composition and structure of the plankton community vary considerably throughout the water column and differ from what accumulates in the sediment. Hence, the interpretation of sedimentary eDNA archives should take into account potential taxonomic and abundance biases when reconstructing past changes in marine biodiversity., (© 2024 John Wiley & Sons Ltd.)

The nature and extent of diversity in the plankton has fascinated scientists for over a century. Initially, the discovery of many new species in the remarkably uniform and unstructured pelagic environment appeared to challenge the concept of ecological niches. Later, it became obvious that only a fraction of plankton diversity had been formally described, because plankton assemblages are dominated by understudied eukaryotic lineages with small size that lack clearly distinguishable morphological features. The high diversity of the plankton has been confirmed by comprehensive metabarcoding surveys, but interpretation of the underlying molecular taxonomies is hindered by insufficient integration of genetic diversity with morphological taxonomy and ecological observations. Here we use planktonic foraminifera as a study model and reveal the full extent of their genetic diversity and investigate geographical and ecological patterns in their distribution. To this end, we assembled a global data set of ~7600 ribosomal DNA sequences obtained from morphologically characterised individual foraminifera, established a robust molecular taxonomic framework for the observed diversity, and used it to query a global metabarcoding data set covering ~1700 samples with ~2.48 billion reads. This allowed us to extract and assign 1 million reads, enabling characterisation of the structure of the genetic diversity of the group across ~1100 oceanic stations worldwide. Our sampling revealed the existence of, at most, 94 distinct molecular operational taxonomic units (MOTUs) at a level of divergence indicative of biological species. The genetic diversity only doubles the number of formally described species identified by morphological features. Furthermore, we observed that the allocation of genetic diversity to morphospecies is uneven. Only 16 morphospecies disguise evolutionarily significant genetic diversity, and the proportion of morphospecies that show genetic diversity increases poleward. Finally, we observe that MOTUs have a narrower geographic distribution than morphospecies and that in some cases the MOTUs belonging to the same morphospecies (cryptic species) have different environmental preferences. Overall, our analysis reveals that even in the light of global genetic sampling, planktonic foraminifera diversity is modest and finite. However, the extent and structure of the cryptic diversity reveals that genetic diversification is decoupled from morphological diversification, hinting at different mechanisms acting at different levels of divergence., (© 2024 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.)

Efficient and robust analytical methods are needed to improve the identification and subsequent regulation of new psychoactive substances (NPS). NMR spectroscopy is a unique method able to determine the structure of small molecules such as NPS even in mixtures. However, high-field NMR analysis is associated with expensive purchase and maintenance costs. For more than a decade, compact NMR spectrometers have changed this paradigm. It was recently shown that a dedicated analytical workflow combining compact NMR and databases could identify the molecular structure of NPS, in spite of the lower spectral dispersion and sensitivity of compact spectrometers. This approach relies on 1 H- 13 C HSQC to both recognize NPS and elucidate the structure of unknown substances. Still, its performance is limited by the need to compromise between resolution and experiment time. Here, we show that this strategy can be significantly improved by implementing non-uniform sampling (NUS) to improve spectral resolution in the 13 C dimension of HSQC at no cost in terms of experiment time. Gains in the range of 3 to 4 in resolution are achieved for pure NPS and for a mixture. Finally, 2D HSQC with NUS was applied to improve the identification of NPS with the assistance of databases. The resulting method appears as a useful tool for the characterization of NPS in mixtures, which is essential for forensic laboratories., (© 2023 The Authors. Magnetic Resonance in Chemistry published by John Wiley & Sons Ltd.)

New psychoactive substances (NPS) have become a serious threat for public health due to their ability to be sold in the street or on internet. NPS are either derived from commercial drugs which are misused (recreational rather than medical use) or whose structure is slightly modified. To regulate NPS, it is essential to accurately characterize them, either to recognize molecules that were previously identified or to quickly elucidate the structure of unknown ones. Most approaches rely on the determination of the exact mass obtained by high-resolution mass spectrometry requiring expensive equipment. This motivated us to develop a workflow in which the elucidation is assisted with databases and does not need the exact mass. This workflow combines 1D and 2D NMR measurements performed on a benchtop spectrometer with IR spectroscopy, for creating a multi-technique database to characterize pure and mixed NPS. The experimental database was created with 57 entries mostly coming from seizures, mainly cathinones, cannabinoids, amphetamines, arylcyclohexylamines, and fentanyl. A blind validation of the workflow was carried out on a set of six unknown seizures. In the first three cases, AF, AB-FUBINACA, and a mixture of 2C-I and 2C-E could be straightforwardly identified with the help of their reference spectra in the database. The two next samples were elucidated for the first time with the help of the database to reveal NEK and MPHP substances. Finally, a precise quantification of each characterized NPS was obtained in order to track NPS trafficking networks., (© 2022 The Authors. Drug Testing and Analysis published by John Wiley & Sons Ltd.)

Deep-sea biodiversity, a source of critical ecological functions and ecosystem services, is increasingly subject to the threat of disturbance from existing practices (e.g., fishing, waste disposal, oil and gas extraction) as well as emerging industries such as deep-seabed mining. Current scientific tools may not be adequate for monitoring and assessing subsequent changes to biodiversity. In this paper, we evaluate the scientific and budgetary trade-offs associated with morphology-based taxonomy and metabarcoding approaches to biodiversity surveys in the context of nascent deep-seabed mining for polymetallic nodules in the Clarion-Clipperton Zone, the area of most intense interest. For the dominant taxa of benthic meiofauna, we discuss the types of information produced by these methods and use cost-effectiveness analysis to compare their abilities to yield biological and ecological data for use in environmental assessment and management. On the basis of our evaluation, morphology-based taxonomy is less cost-effective than metabarcoding but offers scientific advantages, such as the generation of density, biomass, and size structure data. Approaches that combine the two methods during the environmental assessment phase of commercial activities may facilitate future biodiversity monitoring and assessment for deep-seabed mining and for other activities in remote deep-sea habitats, for which taxonomic data and expertise are limited. Integr Environ Assess Manag 2022;18:655-663. © 2021 SETAC., (© 2021 SETAC.)

Since 2010, considerable efforts have been undertaken to monitor the environmental status of European marine waters and ensuring the development of methodological standards for the evaluation of this status. However, the current routine biomonitoring implicates time-consuming and costly manual sorting and morphological identification of benthic macrofauna. Environmental DNA (eDNA) metabarcoding represents an alternative to the traditional monitoring method with very promising results. Here, we tested it further by performing eDNA metabarcoding of benthic eukaryotic communities in the vicinity of two offshore oil and gas platforms in the North Sea. Three different genetic markers (18S V1V2, 18S V9 and COI) were used to assess the environmental pressures induced by the platforms. All markers showed patterns of alpha and beta diversity consistent with morphology-based macrofauna analyses. In particular, the communities' structure inferred from metabarcoding and morphological data significantly changed along distance gradients from the platforms. The impact of the operational discharges was also detected by the variation of biotic index values, AMBI index showing the best correlation between morphological and eDNA data sets. Finally, the sediment physicochemical parameters were used to build a local de novo pressure index that served as benchmark to test the potential of a taxonomy-free approach. Our study demonstrates that metabarcoding approach outperforms morphology-based approach and can be used as a cost and time-saving alternative solution to the traditional morphology-based monitoring in order to monitor more efficiently the impact of industrial activities on marine biodiversity., (© 2020 John Wiley & Sons Ltd.)

Recently, several studies demonstrated the usefulness of diatom eDNA metabarcoding as an alternative to assess the ecological quality of rivers and streams. However, the choice of the taxonomic marker as well as the methodology for data analysis differ between these studies, hampering the comparison of their results and effectiveness. The aim of this study was to compare two taxonomic markers commonly used in diatom metabarcoding and three distinct analytical approaches to infer a molecular diatom index. We used the values of classical morphological diatom index as a benchmark for this comparison. We amplified and sequenced both a fragment of the rbcL gene and the V4 region of the 18S rRNA gene for 112 epilithic samples from Swiss and French rivers. We inferred index values using three analytical approaches: by computing it directly from taxonomically assigned sequences, by calibrating de novo the ecovalues of all metabarcodes, and by using a supervised machine learning algorithm to train predictive models. In general, the values of index obtained using the two "taxonomy-free" approaches, encompassing molecular assignment and machine learning, were closer correlated to the values of the morphological index than the values based on taxonomically assigned sequences. The correlations of the three analytical approaches were higher in the case of rbcL compared to the 18S marker, highlighting the importance of the reference database which is more complete for the rbcL marker. Our study confirms the effectiveness of diatom metabarcoding as an operational tool for rivers ecological quality assessment and shows that the analytical approaches by-passing the taxonomic assignments are particularly efficient when reference databases are incomplete., (© 2020 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

Increasing anthropogenic impact and global change effects on natural ecosystems has prompted the development of less expensive and more efficient bioassessments methodologies. One promising approach is the integration of DNA metabarcoding in environmental monitoring. A critical step in this process is the inference of ecological quality (EQ) status from identified molecular bioindicator signatures that mirror environmental classification based on standard macroinvertebrate surveys. The most promising approaches to infer EQ from biotic indices (BI) are supervised machine learning (SML) and the calculation of indicator values (IndVal). In this study we compared the performance of both approaches using DNA metabarcodes of bacteria and ciliates as bioindicators obtained from 152 samples collected from seven Norwegian salmon farms. Results from standard macroinvertebrate-monitoring of the same samples were used as reference to compare the accuracy of both approaches. First, SML outperformed the IndVal approach to infer EQ from eDNA metabarcodes. The Random Forest (RF) algorithm appeared to be less sensitive to noisy data (a typical feature of massive environmental sequence data sets) and uneven data coverage across EQ classes (a typical feature of environmental compliance monitoring scheme) compared to a widely used method to infer IndVals for the calculation of a BI. Second, bacteria allowed for a more accurate EQ assessment than ciliate eDNA metabarcodes. For the implementation of DNA metabarcoding into routine monitoring programmes to assess EQ around salmon aquaculture cages, we therefore recommend bacterial DNA metabarcodes in combination with SML to classify EQ categories based on molecular signatures., (© 2020 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs., (© 2020 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

The microbial community composition in aquatic ecosystems have received increased attention. However, the knowledge gap relative to the responses of bacterial, archaeal and fungal communities in co-contaminated river sediments remain poorly studied. Here, we investigated the changes of tetrabromobisphenol A (TBBPA) and copper (Cu) concentrations and the responses of microbial communities in co-contaminated sediments during long-term incubation. TBBPA concentrations significantly decreased over time, whereas Cu concentrations remained relatively stable over the 60-day incubation. Abundances of the bacterial 16S rRNA, archaeal 16S rRNA and fungal ITS genes ranged from 6.53 × 10 6 to 1.26 × 10 9 copies g -1 , 1.12 × 10 6 to 5.47 × 10 6 copies g -1 and 5.33 × 10 3 to 7.51 × 10 4 copies g -1 in the samples, respectively. A total of 11, 6 and 5 bacterial, archaeal and fungal phyla were identified across all samples. Bacterial, archaeal and fungal communities mainly consisted of members from the phyla Proteobacteria and Acidobacteria, Methanomicrobia and Woesearchaeia as well as Agaricales and Helotiales, respectively. Fungal communities showed a stronger response to pollutant addition after a long incubation compared with bacterial and archaeal communities. The variance analysis results revealed that the bacterial, archaeal and fungal microbial communities of all treatments were distinctly distributed into two separated clusters according to incubation time. However, the three microbial communities did not significantly change in response to pollutant types, which was consistent with variation in relative abundances of the three microbial communities. These findings improve our understanding of the ecotoxicological effects of co-exposure on sediment microbial communities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

New psychoactive substances (NPS) have become a serious threat to public health in Europe due to their ability to be sold in the street or on the darknet. Regulating NPS is an urgent priority but comes with a number of analytical challenges since they are structurally similar to legal products. A number of analytical techniques can be used for identifying NPS, among which NMR spectroscopy is a gold standard. High field NMR is typically used for structural elucidation in combination with others techniques like GC-MS, Infrared spectroscopy, together with databases. In addition to their strong ability to elucidate molecular structures, high field NMR techniques are the gold standard for quantification without any physical isolation procedure and with a single internal standard. However, high field NMR remains expensive and emerging "benchtop" NMR apparatus which are cheaper and transportable can be considered as valuable alternatives to high field NMR. Indeed, benchtop NMR, which emerged about ten years ago, makes it possible to carry out structural elucidation and quantification of NPS despite the gap in resolution and sensitivity as compared to high field NMR. This review describes recent advances in the field of NMR applied to the characterization of NPS. High-field NMR methods are first described in view of their complementarity with other analytical methods, focusing on both structural and quantitative aspects. The second part of the review highlights how emerging benchtop NMR approaches could act as a game changer in the field of forensics., Competing Interests: Declarations of interest None., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Ruptures of the Extensor pollicis longus tendon are commonly treated by Extensor indicis transfer using Pulvertaft suture technique. Current literature does not yet give evidence for a preferable post-operative therapy protocol. A side-to-side suture technique is significantly stronger than the Pulvertaft repair technique and therefore allows an immediate active postoperative treatment. We present a new postoperative protocol, which is simple, fast and safe, and should make treatment easier for patients and therapists., Patients and Methods: We treated 10 patients with a transfer of the extensor indicis tendon between 07/2016 and 08/2017 according to the new active protocol. Patients were seen for follow-up at 2, 4 and 8 weeks. Thumb range of motion, pinch and grip strength as well as subjective parameters like pain and general satisfaction were measured., Results: All patients regained full function of their thumbs with retropulsion over the level of the palm at 4 weeks. Median pinch strength was 89 % and grip strength 74 % of the contralateral side at week 4. There was no secondary rupture of the reconstructed tendon over a one-year period. All patients were satisfied with the result of the operation and the protocol., Conclusion: Our new active postoperative protocol for extensor indicis transfer using a side-to-side suture has proven to be safe and less strenuous for patients and therapists and has been established as standard treatment in our clinic., Competing Interests: Die Autoren geben an, dass kein Interessenkonflikt besteht., (Thieme. All rights reserved.)

This study examined the effects of a digital diabetes prevention program (DPP) on health care costs and utilization among Medicare Advantage participants. Patients (n = 501) received access to a plan-sponsored, digitally-delivered DPP accessible through computer, tablet, or smartphone. Prior research demonstrated a 7.5% reduction in body weight at 12 months. A comparison group who did not participate in the DPP was constructed by matching on demographic, health plan, health status, and health care costs and utilization. The authors assessed effects on cost and utilization outcomes using difference-in-differences regressions, controlling for propensities to participate and engage in the DPP, in the 12 months prior to DPP enrollment and 24 months after. Though post-enrollment data showed trends in decreased drug spending and emergency department use, increased inpatient utilization, and no change in total nondrug costs or outpatient utilization, the findings did not reach statistical significance, potentially because of sample size. The population had low costs and utilization at baseline, which may be responsible for the lack of observed effects in the short time frame. This study demonstrates the challenges of studying the effectiveness of preventive programs in a population with low baseline costs and the importance of using a large enough sample and follow-up period, but remains an important contribution to exploring the effects of digital DPPs in a real-world sample of individuals who were eligible and willing to participate.

Environmental DNA (eDNA) metabarcoding of marine sediments has revealed large amounts of sequences assigned to planktonic taxa. How this planktonic eDNA is delivered on the seafloor and preserved in the sediment is not well understood. We address these questions by comparing metabarcoding and microfossil foraminifera assemblages in sediment cores taken off Newfoundland across a strong ecological gradient. We detected planktonic foraminifera eDNA down to 30 cm and observed that the planktonic/benthic amplicon ratio changed with depth. The relative proportion of planktonic foraminiferal amplicons remained low from the surface down to 10 cm, likely due to the presence of DNA from living benthic foraminifera. Below 10 cm, the relative proportion of planktonic foraminifera amplicons rocketed, likely reflecting the higher proportion of planktonic eDNA in the DNA burial flux. In addition, the microfossil and metabarcoding assemblages showed a congruent pattern indicating that planktonic foraminifera eDNA is deposited without substantial lateral advection and preserves regional biogeographical patterns, indicating deposition by a similar mechanism as the foraminiferal shells. Our study shows that the planktonic eDNA preserved in marine sediments has the potential to record climatic and biotic changes in the pelagic community with the same spatial and temporal resolution as microfossils.

Since the 1960 s, there has been a rapid expansion of drilling activities in the central and northern Adriatic Sea to meet the increasing global energy demand. The discharges of organic and inorganic pollutants, as well as the alteration of the sediment substrate, are among the main impacts associated with these activities. In the present study, we evaluate the response of benthic foraminifera to the activities of three gas platforms in the northwestern Adriatic Sea, with a special focus on the Armida A platform for which extensive geochemical data (organic matter, trace elements, polycyclic aromatic hydrocarbons, other hydrocarbons, and volatile organic compounds) are available. The response to disturbance is assessed by analyzing the foraminiferal diversity using the traditional morphology-based approach and by 18S rDNA-based metabarcoding. The two methods give congruent results, showing relatively lower foraminiferal diversity and higher dominance values at stations closer to the platforms (<50 m). The taxonomic compositions of the morphological and metabarcoding datasets are very different, the latter being dominated by monothalamous, mainly soft-walled species. However, compositional changes consistently occur at 50 m from the platform and can be related to variations in sediment grain-size variation and higher concentrations of Ni, Zn, Ba, hydrocarbons and total organic carbon. Additionally, several morphospecies and Molecular Operational Taxonomic Units (MOTUs) show strong correlations with distance from the platform and with environmental parameters extracted from BIOENV analysis. Some of these MOTUs have the potential to become new bioindicators, complementing the assemblage of hard-shelled foraminiferal species detected through microscopic analyses. The congruence and complementarity between metabarcoding and morphological approaches support the application of foraminiferal metabarcoding in routine biomonitoring surveys as a reliable, time- and cost-effective methodology to assess the environmental impacts of marine industries., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: Primary care provider encounters are associated with health and well-being; however, limited evidence guides optimal primary care provider rate of visit, referred to as encounter cadence. This study measures associations between primary care provider encounter cadence and diabetes outcomes among individuals newly diagnosed with type 2 diabetes mellitus., Methods: In this retrospective cohort study, 7,106 people enrolled in Medicare Advantage and newly diagnosed with type 2 diabetes mellitus between July 1, 2012 and June 30, 2013 were identified and followed for 36 months. Two methods measured primary care provider encounter cadence: total primary care provider encounters (frequency) and quarters with primary care provider encounter (regularity). Logistic regression measured relationships between primary care provider encounter cadence and non-insulin diabetes medication adherence, HbA1c control, emergency department visits, and inpatient admissions. Non-insulin diabetes medication adherence was defined according to the National Committee for Quality Assurance, Healthcare Effectiveness Data and Information Set specifications and measured using healthcare claims data. Post-hoc models examined adherence and diabetes control among those nonadherent (n=5,212) and with noncontrolled HbA1c (n=326) during the encounter/cadence period. Data were extracted and analyzed in 2017., Results: Adjusted models indicated that both frequency (AOR=1.08, 95% CI=1.06, 1.10) and regularity (AOR=1.18, 95% CI=1.13, 1.22) of primary care provider encounters were associated with increased odds of adherence. Post-hoc analyses indicated that more frequent (AOR=1.12, 95% CI=1.10, 1.15) and regular (AOR=1.27, 95% CI=1.22, 1.33) primary care provider encounters were associated significantly with adherence and were associated directionally with HbA1c control., Conclusions: More frequent and regular primary care provider encounters are associated with an increased likelihood of non-insulin diabetes medication adherence. These findings contribute to data needed to establish evidence-based guidelines for primary care provider encounter cadence for those newly diagnosed with type 2 diabetes mellitus., (Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: The original Charlson Comorbidity Index (CCI) encompassed 19 categories of medical conditions that were identifiable in medical records. Subsequent publications provided scoring algorithms based on International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD-9-CM ) codes. The recent adoption of International Classification of Diseases, Tenth Revision, Clinical Modification ( ICD-10-CM ) codes in the United States created a need for a new scoring scheme. In addition, a review of existing claims-based scoring systems suggested 3 areas for improvement: the lack of explicit identification of secondary diabetes, the lack of differentiation between HIV infection and AIDS, and insufficient guidance on scoring hierarchy. In addition, addressing the third need raised the issue of disease severity in renal disease., Objectives: This initiative aimed to create an expanded and refined ICD-9 scoring system for CCI, addressing the classification of issues noted above, create a corresponding ICD-10 system, assess the comparability of ICD-9 - and ICD-10 -based scores, and validate the new scoring scheme., Methods: We created ICD-9 and ICD-10 code tables for 19 CCI medical conditions. The new scoring scheme was labeled CDMF CCI and was tested using claims-based data for individuals aged ≥65 years who participated in a Humana Medicare Advantage plan during at least 1 of 3 consecutive 12-month periods. Two 12-month periods were during the ICD-9 era and the third 12-month period was during the ICD-10 era. Because many individuals were counted in more than one 12-month period, we described the study population as comprising 3 panels. We used regression models to analyze the association between the CCI score and same-year inpatient admissions and near-term (90-day) mortality. Additional testing was done by comparing the mean CCI score or disease prevalence in the 3 subpopulations of people with HIV/AIDS, renal disease, or diabetes. Finally, we calculated area under the receiver operating characteristics (AUC-ROC) curve values by applying the Deyo system and our ICD-9 and ICD-10 scoring systems., Results: The CDMF ICD-9 and ICD-10 scoring scheme yielded comparable scores across the 3 panels, and inpatient admissions and mortality rates consistently increased in each panel as the CCI score increased. Comparisons of the performance of the Deyo system and our proposed CDMF ICD-9 system in the 3 key subpopulations showed that the CDMF ICD-9 system produced a lower CCI score in the presence of HIV infection without AIDS, achieved similar detection ability of diabetes, and allowed good differentiation between mild-to-moderate and severe renal disease. AUC-ROC values were similar between the CDMF ICD-9 coding system and the Deyo system., Conclusion: Our results support the implementation of the CDMF CCI scoring instrument to triage individual patients for disease- and care-management programs. In addition, the CDMF scheme allows for a more precise understanding of chronic disease at a population level, thus allowing health systems and plans to design services and benefits to meet multifactorial clinical needs. Preliminary validation sets the stage for further testing using long-term follow-up data and for the adaptation of this coding scheme to a chart review instrument.

Genomics is fast becoming a routine tool in medical diagnostics and cutting-edge biotechnologies. Yet, its use for environmental biomonitoring is still considered a futuristic ideal. Until now, environmental genomics was mainly used as a replacement of the burdensome morphological identification, to screen known morphologically distinguishable bioindicator taxa. While prokaryotic and eukaryotic microbial diversity is of key importance in ecosystem functioning, its implementation in biomonitoring programs is still largely unappreciated, mainly because of difficulties in identifying microbes and limited knowledge of their ecological functions. Here, we argue that the combination of massive environmental genomics microbial data with machine learning algorithms can be extremely powerful for biomonitoring programs and pave the way to fill important gaps in our understanding of microbial ecology., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The environmental DNA (eDNA) metabarcoding represents a new promising tool for biomonitoring and environmental impact assessment. One of the main advantages of eDNA metabarcoding, compared to the traditional morphotaxonomy-based methods, is to provide a more holistic biodiversity information that includes inconspicuous morphologically non-identifiable taxa. Here, we use eDNA metabarcoding to survey marine biodiversity in the vicinity of the three offshore gas platforms in North Adriatic Sea (Italy). We isolated eDNA from 576 water and sediment samples collected at 32 sampling sites situated along four axes at increasing distances from the gas platforms. We obtained about 46 million eDNA sequences for 5 markers from nuclear 18S V1V2, 18S V4, 18S 37F and mitochondrial 16S and COI genes that cover a wide diversity of benthic and planktonic eukaryotes. Our results showed some impact of platform activities on benthic and pelagic communities at very close distance (<50 m), while communities for intermediate (125 m, 250 m, 500 m) and reference (1000 m, 2000 m) sites did not show any particular biodiversity changes that could be related to platforms activities. The most significant community change along the distance gradient was obtained with the 18S V1V2 marker targeting benthic eukaryotes, even though other markers showed similar trends, but to a lesser extent. These results were congruent with the AMBI index inferred from the eDNA sequences assigned to benthic macrofauna. We finally explored the relation between various physicochemical parameters, including hydrocarbons, on benthic community in the case of one of the platforms. Our results showed that these communities were not significantly impacted by most of hydrocarbons, but rather by macro-elements and sediment texture., (Copyright © 2019. Published by Elsevier Ltd.)

Benchtop NMR spectrometers experience a great success for a wide range of applications. However, their performance is highly limited by peak overlaps. Emerging "pure-shift NMR" (PS NMR) methods have been intensively used at high field to enhance the resolution by homodecoupling strategies. Here, different PS methods have been implemented on a compact NMR spectrometer operating at 43 MHz. Among the PS methods, the recent PSYCHE scheme appears more sensitive than Zangger-Sterk (ZS) experiments and offers a substantial resolution improvement as compared to 1D 1 H. On the other hand, despite their slightly lower sensitivity, ZS methods are more efficient to reduce broad signals and are more immune to strong couplings. Finally, the classical J-resolved pulse sequence is more efficient to reduce larger signals for bigger-sized molecules. The three approaches appear relevant for benchtop NMR and their combination forms an efficient toolbox to analyze a great diversity of samples., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Ciliates are powerful indicators for monitoring the impact of aquaculture and other industrial activities in the marine environment. Here, we tested the efficiency of four different genetic markers (V4 and V9 regions of the SSU rRNA gene, D1 and D2 regions of the LSU rRNA gene, obtained from environmental (e)DNA and environmental (e)RNA) of benthic ciliate communities for environmental monitoring. We obtained these genetic metabarcodes from sediment samples collected along a transect extending from below salmon cages toward the open sea. These data were compared to benchmark data from traditional macrofauna surveys of the same samples. In beta diversity analyses of ciliate community structures, the V4 and V9 markers had a higher resolution power for sampling sites with different degrees of organic enrichment compared to the D1 and D2 markers. The eDNA and eRNA V4 markers had a higher discriminatory power than the V9 markers. However, results obtained with the eDNA V9 marker corroborated better with the traditional macrofauna monitoring. This allows for a more direct comparison of ciliate metabarcoding with the traditional monitoring. We conclude that the ciliate eDNA V9 marker is the best choice for implementation in routine monitoring programs in marine aquaculture., (© 2018 International Society of Protistologists.)

Background: Tibial plateau fracture classifications are based on anteroposterior radiographs. Precontoured locking plates are commonly used to treat such fractures. The aims of this study are to: (1) describe tibial plateau fracture anatomy in the axial plane and (2) assess whether current plating systems allow screws to be placed suitably., Materials and Methods: A graphical tibial plateau template was developed. One hundred twenty-five tibial plateau fractures (four bilateral) were reviewed (80 men, 41 women; average age 45.5 years, range 21-77.7 years). The axial computed tomography (CT) slice 0.3-0.5 mm below the medial articular surface was reviewed in all cases. Fracture lines were drawn on the template. Four lateral locking plates were placed against a cadaveric adult tibia. Based on the projected screw directions, suitable fracture patterns were identified. Fractures were considered "suitable" if the screws passed 90 ± 22° to the fracture line., Results: Two hundred sixty-one different fracture lines were identified. One hundred thirty-four fractures involved the lateral plateau; 96 were suitable for lateral plating. Ninety fractures involved the medial plateau, 82 were treatable using the various plate positions on medial-posterior aspect of the medial plateau. Thirty-seven fractures were bicondylar; 20 were treatable with a posteromedial plate., Conclusions: Tibial plateau fractures follow consistent patterns, with most lateral and medial plateau fracture lines being in the sagittal plane, although there is greater variation medially. Positioning of modern locking plates will deal effectively with 72 % of all lateral plateau fractures and 91 % of medial plateau fractures., Level of Evidence: Level 3.

Background: High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) has become a routine tool for biodiversity survey and ecological studies. By including sample-specific tags in the primers prior PCR amplification, it is possible to multiplex hundreds of samples in a single sequencing run. The analysis of millions of sequences spread into hundreds to thousands of samples prompts for efficient, automated yet flexible analysis pipelines. Various algorithms and software have been developed to perform one or multiple processing steps, such as paired-end reads assembly, chimera filtering, Operational Taxonomic Unit (OTU) clustering and taxonomic assignment. Some of these software are now well established and widely used by scientists as part of their workflow. Wrappers that are capable to process metabarcoding data from raw sequencing data to annotated OTU-to-sample matrix were also developed to facilitate the analysis for non-specialist users. Yet, most of them require basic bioinformatic or command-line knowledge, which can limit the accessibility to such integrative toolkits. Furthermore, for flexibility reasons, these tools have adopted a step-by-step approach, which can prevent an easy automation of the workflow, and hence hamper the analysis reproducibility., Results: We introduce SLIM, an open-source web application that simplifies the creation and execution of metabarcoding data processing pipelines through an intuitive Graphic User Interface (GUI). The GUI interact with well-established software and their associated parameters, so that the processing steps are performed seamlessly from the raw sequencing data to an annotated OTU-to-sample matrix. Thanks to a module-centered organization, SLIM can be used for a wide range of metabarcoding cases, and can also be extended by developers for custom needs or for the integration of new software. The pipeline configuration (i.e. the modules chaining and all their parameters) is stored in a file that can be used for reproducing the same analysis., Conclusion: This web application has been designed to be user-friendly for non-specialists yet flexible with advanced settings and extensibility for advanced users and bioinformaticians. The source code along with full documentation is available on the GitHub repository ( https://github.com/yoann-dufresne/SLIM ) and a demonstration server is accessible through the application website ( https://trtcrd.github.io/SLIM/ ).

The effectiveness of environmental protection measures is based on the early identification and diagnosis of anthropogenic pressures. Similarly, restoration actions require precise monitoring of changes in the ecological quality of ecosystems, in order to highlight their effectiveness. Monitoring the ecological quality relies on bioindicators, which are organisms revealing the pressures exerted on the environment through the composition of their communities. Their implementation, based on the morphological identification of species, is expensive because it requires time and experts in taxonomy. Recent genomic tools should provide access to reliable and high-throughput environmental monitoring by directly inferring the composition of bioindicators' communities from their DNA (metabarcoding). The French-Swiss program SYNAQUA (INTERREG France-Switzerland 2017-2019) proposes to use and validate the tools of environmental genomic for biomonitoring and aims ultimately at their implementation in the regulatory bio-surveillance. SYNAQUA will test the metabarcoding approach focusing on two bioindicators, diatoms, and aquatic oligochaetes, which are used in freshwater biomonitoring in France and Switzerland. To go towards the renewal of current biomonitoring practices, SYNAQUA will (1) bring together different actors: scientists, environmental managers, consulting firms, and biotechnological companies, (2) apply this approach on a large scale to demonstrate its relevance, (3) propose robust and reliable tools, and (4) raise public awareness and train the various actors likely to use these new tools. Biomonitoring approaches based on such environmental genomic tools should address the European need for reliable, higher-throughput monitoring to improve the protection of aquatic environments under multiple pressures, guide their restoration, and follow their evolution.

Biodiversity monitoring is the standard for environmental impact assessment of anthropogenic activities. Several recent studies showed that high-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) could overcome many limitations of the traditional morphotaxonomy-based bioassessment. Recently, we demonstrated that supervised machine learning (SML) can be used to predict accurate biotic indices values from eDNA metabarcoding data, regardless of the taxonomic affiliation of the sequences. However, it is unknown to which extent the accuracy of such models depends on taxonomic resolution of molecular markers or how SML compares with metabarcoding approaches targeting well-established bioindicator species. In this study, we address these issues by training predictive models upon five different ribosomal bacterial and eukaryotic markers and measuring their performance to assess the environmental impact of marine aquaculture on independent data sets. Our results show that all tested markers are yielding accurate predictive models and that they all outperform the assessment relying solely on taxonomically assigned sequences. Remarkably, we did not find any significant difference in the performance of the models built using universal eukaryotic or prokaryotic markers. Using any molecular marker with a taxonomic range broad enough to comprise different potential bioindicator taxa, SML approach can overcome the limits of taxonomy-based eDNA bioassessment., (© 2018 John Wiley & Sons Ltd.)

The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties in morphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper, we review the structure of conventional biotic indices, and we present the results of pilot metabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices. We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring programs., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: Recipients of ICD are likely to have several risk factors that could interfere with successful use of implantable cardioverter defibrillators (ICDs)., Hypothesis: Age, sex, and factors indicated in claims are associated with one-year mortality and complications after ICD placement., Methods: Adult Medicare Advantage patients who underwent outpatient ICD implantation from January 2014 to September 2015 were included. Age, sex, Charlson Comorbidity Index (CCI), prior year hospitalization and emergency department (ED) visit, diabetes, heart failure, ischemic heart disease, and indicators of the need for pacing were evaluated as risk factors. Mortality and device-related complications (lead and nonlead) were assessed at one-year post-procedure using Kaplan-Meier and Cox Proportional Hazard analysis., Results: Among 8450 patients who underwent implantation, 1-year event-free survival was 80.1%, based on an overall composite measure of complications and mortality. Adjusted survival analysis showed that age ≥ 65, male sex, incremental increase in CCI, heart failure, prior year hospitalization, ED visit, and prior year pacing procedure were significant predictors of mortality. Age ≥ 65, male sex, and prior year hospitalization were significant predictors of a composite measure of device-related complications. CCI and prior hospitalization were significant predictors of a composite measure of any adverse outcome., Conclusions: Results suggest most patients in an older population do not experience adverse outcomes in the year following ICD implantation. The risk of mortality may be greater in men, patients over the age of 65, and patients with greater general morbidity, heart failure, or a history of a pacing procedure., (© 2018 Wiley Periodicals, Inc.)

Humana, a large health care company, has set a goal of 20% improvement in health in the communities it serves by 2020. The metric chosen for the Bold Goal initiative was the HRQOL-4 version of the Centers for Disease Control and Prevention (CDC) Healthy Days survey. This paper presents the methods for measuring progress, reports results for the first year of tracking, and describes Humana's community-based interventions. Across 7 specially designated "Bold Goal" communities, mean unhealthy days declined from 10.98 in 2015 to 10.64 in 2016, which represented a 3.1% relative, or 0.34 absolute, decline. This compares with a 0.17 absolute unhealthy days decline in Humana's national population overall. The paper also describes how additional work identifying associations between social determinants of health (SDOH) and Healthy Days is influencing Humana's strategy. Lastly, a strategy of community engagement is illustrated through 2 case examples: San Antonio and Knoxville. In the San Antonio area, the community in which Humana has been involved the longest, unhealthy days dropped by 9.0% (-0.95 absolute) from a mean 10.52 to 9.57 unhealthy days. In Knoxville, one of the newer areas of engagement, mean unhealthy days declined by 4.8% (-0.61 absolute), representing declines in both physically and mentally unhealthy days. Overall, results are encouraging, and Humana expects declines to accelerate over time as initiatives are launched and scaled in Bold Goal communities.

Background: The impact of messaging campaigns on influencing urgent care- and emergent care-seeking behaviors, including the use of in-network providers, is not well-understood. Although out-of-network healthcare utilization can have negative financial consequences for patients in narrow network Affordable Care Act plans, individuals with time-sensitive medical conditions, and especially patients visiting the emergency department, may not think about out-of-network issues. Inappropriate or avoidable emergency department visits can also create unnecessary costs for patients., Objective: To evaluate the impact of 5 messaging strategies to educate individuals about the use of in-network providers and when care should be sought in the emergency department, urgent care center, or other sites of care., Methods: Using a retrospective analysis, individuals aged ≥18 years who were enrolled in an individually purchased Affordable Care Act-compliant Humana plan as of July 1, 2015, were randomized to 1 of 5 messaging arms (e-mail, magnet mailer with or without e-mail, and key-tag mailer with or without e-mail) or to a control group. The outreach was implemented and evaluated in 2 distinct, geographically defined populations of Orlando, Palm Beach, and Tampa, Florida (Population 1); and Atlanta, Georgia, and San Antonio and Austin, Texas (Population 2). The relative number of each emergency department, urgent care, and out-of-network visits during follow-up was modeled using negative binomial regression. Cox proportional hazard models were used to calculate the risk for ≥1 of each visit type (assessed separately) and high emergency department utilization (defined as ≥3 visits during follow-up) relative to the control, while accounting for variable follow-up time., Results: The relative numbers of each visit type assessed were not significantly different for any message group compared with the control in either population. The risk for an emergency department visit was 4% lower in the e-mail arm of Population 2 (hazard ratio [HR], 0.96; 95% confidence interval [CI], 0.94-0.99; P = .005) and 7% lower in the e-mail/key-tag arm of Population 1 (HR, 0.93; 95% CI, 0.89-0.97; P = .001). The risk for high emergency department utilization was significantly reduced by the key-tag, magnet, and e-mail/key-tag strategies in Population 1, but no impact was found in Population 2., Conclusion: Despite the mixed results, the study provides new insights into how different messaging strategies could be used to educate patients and influence healthcare utilization decisions by people with health insurance.

We evaluated benthic bacterial communities as bioindicators in environmental impact assessments of salmon aquaculture, a rapidly growing sector of seafood industry. Sediment samples (n=72) were collected from below salmon cages towards distant reference sites. Bacterial community profiles inferred from DNA metabarcodes were compared to reference data from standard macrofauna biomonitoring surveys of the same samples. Deltaproteobacteria were predominant in immediate vicinity of the salmon cages. Along the transect, significant shifts in bacterial community structures were observed with Gammaproteobacteria dominating the less-impacted sites. Alpha- and beta-diversity measures of bacterial communities correlated significantly with macrofauna diversity metrics and with five ecological status indices. Benthic bacterial communities mirror the reaction of macrofauna bioindicators to environmental disturbances caused by salmon farming. The implementation of bacterial eDNA metabarcoding in future Strategic Framework Directives is an alternative cost-effective high-throughput biomonitoring solution, providing a basis for management strategies in a matter of days rather than months., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objectives: To investigate whether self-reported unhealthy days are related to 6 chronic conditions and other health indicators by using administrative claims., Study Design: Cross-sectional study using Healthy Days survey data linked to administrative claims., Methods: Survey respondents 65 years or older with Medicare Advantage coverage in November or December 2014 and 12 months continuous presurvey enrollment were identified. Mean physically and mentally unhealthy days were reported by chronic condition subgroups. Mean incremental unhealthy days were calculated for individuals in chronic condition subgroups and those exhibiting noncompliance with 2014 quality measures after adjusting for age, gender, provider/insurer contractual relationship, dual Medicaid/Medicare eligibility, and sum of chronic conditions. The relationship between the unhealthy days category and adjusted mean resource utilization (inpatient and outpatient visits) and total healthcare costs for the year prior to the survey was also described., Results: The population averages for physically and mentally unhealthy days were 7.24 and 4.05, respectively. After adjustment, all 6 chronic conditions were associated with significantly more physically unhealthy days, and chronic obstructive pulmonary disease, depression, and diabetes were associated with significantly more mentally unhealthy days (P <.001 vs not having the condition). After adjustment, quality measure noncompliance was generally associated with incremental increases in unhealthy days. Utilization and cost generally increased with increasing unhealthy days., Conclusions: This is the first study to use administrative claims to demonstrate a relationship between Healthy Days and chronic conditions, related healthcare quality measures, utilization, and costs. Our findings underscore the validity of using Healthy Days to supplement traditional health measures in assessing health status in this population.

Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which is time-consuming and taxonomic-expertise demanding. High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) represents a promising alternative for benthic monitoring. However, an important fraction of eDNA sequences remains unassigned or belong to taxa of unknown ecology, which prevent their use for assessing the ecological quality status. Here, we show that supervised machine learning (SML) can be used to build robust predictive models for benthic monitoring, regardless of the taxonomic assignment of eDNA sequences. We tested three SML approaches to assess the environmental impact of marine aquaculture using benthic foraminifera eDNA, a group of unicellular eukaryotes known to be good bioindicators, as features to infer macro-invertebrates based biotic indices. We found similar ecological status as obtained from macro-invertebrates inventories. We argue that SML approaches could overcome and even bypass the cost and time-demanding morpho-taxonomic approaches in future biomonitoring.

Introduction: Arthritis is related to poor health-related quality of life (HRQoL) in adults aged 18 years or older. We sought to determine whether this relationship persisted in an older population using claims-based arthritis diagnoses and whether people who also had arthritis and at least 1 of 5 other chronic conditions had lower HRQoL., Methods: We identified adults aged 65 years or older with Medicare Advantage coverage in November or December 2014 who responded to an HRQoL survey (Healthy Days). For respondents with and without arthritis, we used linear regression to compare mean physically, mentally, and total unhealthy days, overall and in 5 comorbidity subgroups (coronary artery disease, congestive heart failure, chronic obstructive pulmonary disease, diabetes, and hypertension), accounting for age, sex, dual Medicaid/Medicare eligibility, rural/urban commuting area, and Charlson Comorbidity Index., Results: Of the 58,975 survey respondents, 44% had arthritis diagnosed through claims. Respondents with arthritis reported significantly more adjusted mean physically, mentally, and total unhealthy days than those without arthritis (P < .001). Older adults with arthritis and either congestive heart failure, chronic obstructive pulmonary disease, diabetes, or hypertension reported significantly more adjusted physically, mentally, and total unhealthy days than older adults without arthritis but with the same chronic conditions., Conclusions: In older adults, having arthritis is associated with lower HRQoL and even lower HRQoL among those with at least 1 of 5 other common chronic conditions. Because arthritis is so common among older adults, improving HRQoL depends on managing both underlying chronic conditions and any accompanying arthritis.