Nix Pro Color Sensor provides comparable color measurements to HunterLab colorimeter for fresh beef.

The HunterLab MiniScan (HunterLab) colorimeter is used in meat quality research worldwide for measuring meat color; however, the Nix Pro Color Sensor (Nix) could be a less expensive alternative that is easier to operate. Therefore, the objective of this study was to compare the two colorimeters to objectively evaluate fresh beef color. Longissimus thoracis muscle from one side of A maturity beef carcasses (n = 200) was evaluated using both the HunterLab (3 technical replicate scans) and Nix (3, 5, 7, and 9 technical replicate scans) colorimeters. The correlation between the HunterLab and Nix for L* (lightness), a* (redness), and b* (yellowness) values ranged between r = 0.80 to 0.85 and the Bland Altman Limits of Agreement analysis indicated good agreement between the Nix and HunterLab colorimeters for all the color parameters. These results indicated that the Nix colorimeter could be a viable alternative for HunterLab colorimeters.

Provider Consensus on Candidate Protective and Risk Factors for Adverse Psychosocial Outcomes Following Discharge From a PICU: A Modified Delphi Study.

OBJECTIVES: Pediatric palliative care promotes interdisciplinary, family-centered care when children are faced with diagnoses threatening length and/or quality of life. A significant knowledge gap remains in how to best match pediatric palliative care resources to palliate the psychosocial impact of a PICU admission. This study was designed to identify drivers of adverse post-PICU psychosocial outcomes related to social determinants of health to inform pediatric palliative care services and improve post-PICU psychosocial outcomes. DESIGN: Modified Delphi technique to develop consensus regarding social determinants of health and clinical factors affecting post-ICU psychosocial outcomes. SETTING: All Delphi rounds were via an electronically mailed survey link. SUBJECTS: First-round participants were PICU and pediatric palliative care clinicians at the study institution. Subsequent rounds invited participants from national PICU and pediatric palliative care professional online listserves. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Consensus was defined a priori as items assigned a score greater than or equal to 4 (5-point scale) by greater than75% of respondents. One-hundred twenty-six surveys were returned and scored. Social determinants of health risk factors included child protective services involvement (91%), caregiver with intellectual disability (87%), lack of friend or family support (82%), caregiver with behavioral health diagnosis (81%), teenage caregiver (79%), transportation challenges (79%), and language/cultural barrier (76%). Clinical risk factors included new home ventilator (94%), new tracheostomy (90%), greater than or equal to 3 hospitalizations in the prior 6 months (88%), and greater than or equal to 3 hospitalizations in the prior 12 months (82%). Social determinants of health protective factors included extended family support (91%), caregivers in a committed relationship (79%), and caregiver optimism (78%). Respondents reported that pediatric palliative care services had the greatest impact on caregiver satisfaction with the healthcare system (90%) and increased family involvement with state social services programs (80%). CONCLUSIONS: Consensus on candidate risk and protective factors for post-ICU psychosocial challenges and candidate pediatric palliative care-sensitive variables were identified. Further research is needed to operationalize and optimize a screening tool based on these consensus items and test it prospectively.

The spectrum of cutaneous adverse events during encorafenib and binimetinib treatment in B-rapidly accelerated fibrosarcoma-mutated advanced melanoma.

BACKGROUND: B-rapidly accelerated fibrosarcoma (BRAF) inhibitor encorafenib alone and in combination with MEK inhibitor binimetinib improves survival in BRAF-mutated melanoma patients. So far, the range of cutaneous adverse events has been characterized only for established BRAF inhibitors (vemurafenib, dabrafenib) and MEK inhibitors (trametinib, cobimetinib). OBJECTIVE: The aim of this study was to investigate cutaneous adverse events emerging in melanoma patients treated with encorafenib and binimetinib. METHODS: Patients treated with BRAF and MEK inhibitors in clinical trials at the University Hospital of Zurich were identified. Frequency and features of cutaneous adverse events as well as their management were assessed based on the prospectively collected clinical and histopathological data. The events emerging during encorafenib and/or binimetinib therapy were compared to other BRAF and MEK inhibitors at the institution and in the literature. RESULTS: The most frequent cutaneous adverse events observed in patients treated with encorafenib alone (n = 24) were palmoplantar hyperkeratosis (54%), palmoplantar erythrodysesthesia (58%) and alopecia (46%). Drug-induced papulopustular eruptions prevailed in patients with binimetinib monotherapy (n = 25). The most frequent cutaneous adverse events in patients treated with encorafenib/binimetinib (n = 49) were palmoplantar hyperkeratosis (10%). CONCLUSION: Compared to data published for established BRAFi, encorafenib monotherapy showed less hyperproliferative cutaneous adverse events. In contrast, palmoplantar hyperkeratosis and palmoplantar erythrodysesthesia seem to occur more often. The combination of encorafenib and binimetinib is well tolerated and induces few cutaneous adverse events.

Epiphyseal fusion and dental development in Pan paniscus with comparisons with Pan troglodytes.

OBJECTIVES: Compared with frequent studies of skeletal development in chimpanzees, relatively little is known about bonobo skeletal development. This study seeks to explore the relationship between skeletal and dental development in both species of Pan. New data are presented for fusion sites not previously observed in bonobos. MATERIALS AND METHODS: In a sample of 34 Pan paniscus and 168 Pan troglodytes subadults, state of fusion was recorded for 30 epiphyseal fusion sites using a three-stage system of unfused, midfusion, and complete fusion based on Wintheiser, Clauser, and Tappen. Stage of dental development for permanent mandibular dentition was assessed using the Demrijian, Goldstein, and Tanner method. These data allowed for comparisons of both species of Pan and the two subspecies of P. troglodytes. RESULTS: The sequence of fusion events was generally consistent between the two species, but some exceptions may exist for the knee and ankle. The number of fusion events that occurred after complete dental mineralization was similar in both species. No statistically significant differences were found in the fusion timing for the subspecies of P. troglodytes. DISCUSSION: Bolter and Zihlman suggested that fusion at the acetabulum occurs earlier in Pan paniscus, while fusion of epiphyses at the knee are delayed, compared with P. troglodytes. Our data do not indicate earlier fusion of the acetabulum, but fusion events at the knee may complete later relative to dental mineralization in Pan pansicus. Compared with Homo sapiens, both P. troglodytes and Pan paniscus demonstrate later completion of epiphyseal fusion relative to dental mineralization.

Standard Setting for Clinical Performance of Basic Perioperative Transesophageal Echocardiography: Moving beyond the Written Test.

BACKGROUND: Credible methods for assessing competency in basic perioperative transesophageal echocardiography examinations have not been reported. The authors' objective was to demonstrate the collection of real-world basic perioperative transesophageal examination performance data and establish passing scores for each component of the basic perioperative transesophageal examination, as well as a global passing score for clinical performance of the basic perioperative transesophageal examination using the Angoff method. METHODS: National Board of Echocardiography (Raleigh, North Carolina) advanced perioperative transesophageal echocardiography-certified anesthesiologists (n = 7) served as subject matter experts for two Angoff standard-setting sessions. The first session was held before data analysis, and the second session for calibration of passing scores was held 9 months later. The performance of 12 anesthesiology residents was assessed via the new passing score grading system. RESULTS: The first standard-setting procedure resulted in a global passing score of 63 ± 13% on a basic perioperative transesophageal examination. The global passing score from the second standard-setting session was 73 ± 9%. Three hundred seventy-one basic perioperative transesophageal examinations from 12 anesthesiology residents were included in the analysis and used to guide the second standard-setting session. All residents scored higher than the global passing score from both standard-setting sessions. CONCLUSIONS: To the authors' knowledge, this is the first demonstration that the collection of real-world anesthesia resident basic perioperative transesophageal examination clinical performance data is possible and that automated grading for competency assessment is feasible. The authors' findings demonstrate at least minimal basic perioperative transesophageal examination clinical competency of the 12 residents.

An unsupervised machine learning model for discovering latent infectious diseases using social media data.

INTRODUCTION: The authors of this work propose an unsupervised machine learning model that has the ability to identify real-world latent infectious diseases by mining social media data. In this study, a latent infectious disease is defined as a communicable disease that has not yet been formalized by national public health institutes and explicitly communicated to the general public. Most existing approaches to modeling infectious-disease-related knowledge discovery through social media networks are top-down approaches that are based on already known information, such as the names of diseases and their symptoms. In existing top-down approaches, necessary but unknown information, such as disease names and symptoms, is mostly unidentified in social media data until national public health institutes have formalized that disease. Most of the formalizing processes for latent infectious diseases are time consuming. Therefore, this study presents a bottom-up approach for latent infectious disease discovery in a given location without prior information, such as disease names and related symptoms. METHODS: Social media messages with user and temporal information are extracted during the data preprocessing stage. An unsupervised sentiment analysis model is then presented. Users' expressions about symptoms, body parts, and pain locations are also identified from social media data. Then, symptom weighting vectors for each individual and time period are created, based on their sentiment and social media expressions. Finally, latent-infectious-disease-related information is retrieved from individuals' symptom weighting vectors. DATASETS AND RESULTS: Twitter data from August 2012 to May 2013 are used to validate this study. Real electronic medical records for 104 individuals, who were diagnosed with influenza in the same period, are used to serve as ground truth validation. The results are promising, with the highest precision, recall, and F1 score values of 0.773, 0.680, and 0.724, respectively. CONCLUSION: This work uses individuals' social media messages to identify latent infectious diseases, without prior information, quicker than when the disease(s) is formalized by national public health institutes. In particular, the unsupervised machine learning model using user, textual, and temporal information in social media data, along with sentiment analysis, identifies latent infectious diseases in a given location.

How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information.

It is believed that anomalous mental states such as stress and anxiety not only cause suffering for the individuals, but also lead to tragedies in some extreme cases. The ability to predict the mental state of an individual at both current and future time periods could prove critical to healthcare practitioners. Currently, the practical way to predict an individual's mental state is through mental examinations that involve psychological experts performing the evaluations. However, such methods can be time and resource consuming, mitigating their broad applicability to a wide population. Furthermore, some individuals may also be unaware of their mental states or may feel uncomfortable to express themselves during the evaluations. Hence, their anomalous mental states could remain undetected for a prolonged period of time. The objective of this work is to demonstrate the ability of using advanced machine learning based approaches to generate mathematical models that predict current and future mental states of an individual. The problem of mental state prediction is transformed into the time series forecasting problem, where an individual is represented as a multivariate time series stream of monitored physical and behavioral attributes. A personalized mathematical model is then automatically generated to capture the dependencies among these attributes, which is used for prediction of mental states for each individual. In particular, we first illustrate the drawbacks of traditional multivariate time series forecasting methodologies such as vector autoregression. Then, we show that such issues could be mitigated by using machine learning regression techniques which are modified for capturing temporal dependencies in time series data. A case study using the data from 150 human participants illustrates that the proposed machine learning based forecasting methods are more suitable for high-dimensional psychological data than the traditional vector autoregressive model in terms of both magnitude of error and directional accuracy. These results not only present a successful usage of machine learning techniques in psychological studies, but also serve as a building block for multiple medical applications that could rely on an automated system to gauge individuals' mental states.

Epiphyseal fusion in Pan troglodytes relative to dental age.

Previous studies on different aspects of chimpanzee growth and development have documented dental eruption and development, long bone and somatic growth, and to a lesser extent, skeletal fusion. Such data are useful in comparative and evolutionary studies of growth and some aspects of life history evolution in apes and early hominids. However, few studies have integrated dental development and other aspects of skeletal development, and none of these have been able to incorporate a large study sample. This study documents dental mineralization and skeletal epiphyseal fusion in a mixed-sex sample of 155 Pan troglodytes skeletons, and aims to: a) document the pattern of dental and skeletal developmental in chimpanzees; b) compare male and female developmental patterns in chimpanzees; and c) compare these chimpanzee developmental patterns to general patterns of dental and skeletal development in published human studies. The analysis of both dental and skeletal development in this sample demonstrates clearly that dental development is complete before the fusion of the many skeletal epiphyses, in contrast to the pattern observed in humans. Age estimates for individuals were calculated using previously published regression equations for dental development and used to estimate fusion ages. These appear to be accurate in that our estimates are similar to published ranges. These data improve our understanding about chimpanzee dental and skeletal development and provide a basis for further comparison between extant apes and humans, as well as those extinct species represented by fossil partial skeletons.

An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages.

OBJECTIVES: The role of social media as a source of timely and massive information has become more apparent since the era of Web 2.0.Multiple studies illustrated the use of information in social media to discover biomedical and health-related knowledge.Most methods proposed in the literature employ traditional document classification techniques that represent a document as a bag of words.These techniques work well when documents are rich in text and conform to standard English; however, they are not optimal for social media data where sparsity and noise are norms.This paper aims to address the limitations posed by the traditional bag-of-word based methods and propose to use heterogeneous features in combination with ensemble machine learning techniques to discover health-related information, which could prove to be useful to multiple biomedical applications, especially those needing to discover health-related knowledge in large scale social media data.Furthermore, the proposed methodology could be generalized to discover different types of information in various kinds of textual data. METHODOLOGY: Social media data is characterized by an abundance of short social-oriented messages that do not conform to standard languages, both grammatically and syntactically.The problem of discovering health-related knowledge in social media data streams is then transformed into a text classification problem, where a text is identified as positive if it is health-related and negative otherwise.We first identify the limitations of the traditional methods which train machines with N-gram word features, then propose to overcome such limitations by utilizing the collaboration of machine learning based classifiers, each of which is trained to learn a semantically different aspect of the data.The parameter analysis for tuning each classifier is also reported. DATA SETS: Three data sets are used in this research.The first data set comprises of approximately 5000 hand-labeled tweets, and is used for cross validation of the classification models in the small scale experiment, and for training the classifiers in the real-world large scale experiment.The second data set is a random sample of real-world Twitter data in the US.The third data set is a random sample of real-world Facebook Timeline posts. EVALUATIONS: Two sets of evaluations are conducted to investigate the proposed model's ability to discover health-related information in the social media domain: small scale and large scale evaluations.The small scale evaluation employs 10-fold cross validation on the labeled data, and aims to tune parameters of the proposed models, and to compare with the stage-of-the-art method.The large scale evaluation tests the trained classification models on the native, real-world data sets, and is needed to verify the ability of the proposed model to handle the massive heterogeneity in real-world social media. FINDINGS: The small scale experiment reveals that the proposed method is able to mitigate the limitations in the well established techniques existing in the literature, resulting in performance improvement of 18.61% (F-measure).The large scale experiment further reveals that the baseline fails to perform well on larger data with higher degrees of heterogeneity, while the proposed method is able to yield reasonably good performance and outperform the baseline by 46.62% (F-Measure) on average.

3D-printed digital pneumatic logic for the control of soft robotic actuators.

Soft robots are paving their way to catch up with the application range of metal-based machines and to occupy fields that are challenging for traditional machines. Pneumatic actuators play an important role in this development, allowing the construction of bioinspired motion systems. Pneumatic logic gates provide a powerful alternative for controlling pressure-activated soft robots, which are often controlled by metallic valves and electric circuits. Many existing approaches for fully compliant pneumatic control logic suffer from high manual effort and low pressure tolerance. In our work, we invented three-dimensional (3D) printable, pneumatic logic gates that perform Boolean operations and imitate electric circuits. Within 7 hours, a filament printer is able to produce a module that serves as an OR, AND, or NOT gate; the logic function is defined by the assigned input signals. The gate contains two alternately acting pneumatic valves, whose work principle is based on the interaction of pressurized chambers and a 3D-printed 1-millimeter tube inside. The gate design does not require any kind of support material for its hollow parts, which makes the modules ready to use directly after printing. Depending on the chosen material, the modules can operate on a pressure supply between 80 and more than 750 kilopascals. The capabilities of the invented gates were verified by implementing an electronics-free drink dispenser based on a pneumatic ring oscillator and a 1-bit memory. Their high compliance is demonstrated by driving a car over a fully flexible, 3D-printed robotic walker controlled by an integrated circuit.

From DNA damage to chromosome aberrations: joining the break.

Despite many years of experimental studies on radiation-induced chromosomal aberrations, and the recent progress in elucidating the molecular mechanisms of the DNA damage response, the link between DNA double-strand break repair and its expression as microscopically visible chromosomal rearrangements remains, in many ways, obscure. Some long standing controversies have partially been resolved to the satisfaction of most investigators, including the linearity of the dose-response for DNA double-strand break induction, the necessity of pairwise interaction of radiogenic damaged sites in the formation of exchange aberrations, and the importance of proximity between lesions in misrejoining. However, the contribution of different molecular DNA repair mechanisms (e.g., alternative end-joining pathways) and their impact on the kinetics of aberration formation is still unclear, as is the definition of "complex" radiogenic damaged sites - in either the chemical or spatial sense - which ostensibly lead to chromosome rearrangements. These topics have been recently debated by molecular biologists and cytogeneticists, whose opinions are summarized in this paper.

The impact of marker selection, in-line near-infrared spectroscopy (NIR), and feed mix time on the coefficient of variation (mix uniformity), body weight uniformity and broiler growth performance during the starter, grower, and finisher periods.

Most feed manufacturers in the United States use the same mixing time (and thus mix uniformity) throughout the growing period regardless of age and consumption patterns. However, research evaluating the optimum mixing time requirements and novel analysis methods, such as in-line near-infrared (NIR) spectroscopy, on the coefficient of variation (CV) and growth performance of broilers throughout the production phases is sparse. Two experiments were conducted to determine the effects of marker selection, in-line NIR, and varying mix times on mix uniformity, broiler growth performance, and body weight uniformity from 1 to 42 d of age. Feed was manufactured utilizing a 1,815-kg counterpoise ribbon mixer. In both experiments, feed was mixed for 4.5 min (3 min dry mix and 90 s of wet mix) and 30 s (0 s dry mix and 30 s wet mix) to obtain a standard mix (SM) and an abbreviated mix (AM), respectively. Experiment 1 constituted a 2 × 2 × 4 factorial arrangement of 2 mix times, (4.5 and 0.5 min), 2 batch sizes (908 and 1,815 kg), and 4 methodologies to evaluate mixer performance (sodium chloride, Microtracers (Red#40 and Blue#40), and in-line NIR). In experiment 2, broilers received different mix time combinations: 1) SM from 1 to 42 d, 2) SM from 1 to 28 d and AM from 28 to 42 d, 3) SM from 1 to 14 d and AM from 14 to 42 d, and 4) AM from 1 to 42 d. In both experiments, selecting a single source marker provided a more accurate estimation of mixer CV in SM and AM diets (P < 0.05). In experiment 2, mix time did not influence BW, feed intake (FI), FCR, or individual bird BW CV from 1 to 42 d of age (P > 0.05). These data indicated that mixer CV differed depending on total mix time and methodology used and diets with a reduced mix time may not necessarily influence growth performance and BW uniformity during the starter, grower, and finisher periods of broilers.

Video-Based Elevated Skin Temperature Detection.

In this work, we propose a non-contact video-based approach that detects when an individual's skin temperature is elevated beyond the normal range. The detection of elevated skin temperature is critical as a diagnostic tool to infer the presence of an infection or an abnormal health condition. Detection of elevated skin temperature is typically achieved using contact thermometers or non-contact infrared-based sensors. The ubiquity of video data acquisition devices such as mobile phones and computers motivates the development of a binary classification approach, the Video-based TEMPerature (V-TEMP) to classify subjects with non-elevated/elevated skin temperature. We leverage the correlation between the skin temperature and the angular reflectance distribution of light, to empirically differentiate between skin at non-elevated temperature and skin at elevated temperature. We demonstrate the uniqueness of this correlation by 1) revealing the existence of a difference in the angular reflectance distribution of light from skin-like and non-skin like material and 2) exploring the consistency of the angular reflectance distribution of light in materials exhibiting optical properties similar to human skin. Finally, we demonstrate the robustness of V-TEMP by evaluating the efficacy of elevated skin temperature detection on subject videos recorded in 1) laboratory controlled environments and 2) outside-the-lab environments. V-TEMP is beneficial in two ways; 1) it is non-contact-based, reducing the possibility of infection due to contact and 2) it is scalable, given the ubiquity of video-recording devices.

Oral versus intravenous acetaminophen for perioperative pain management in adult patients undergoing non-cardiac surgery: A quantile segmented regression analysis.

STUDY OBJECTIVE: Determine whether preferential use of perioperative enteral acetaminophen is associated with changes in perioperative pain, narcotic administration, or time to meeting criteria for post anesthesia care unit (PACU) discharge, compared to preferential parenteral administration. DESIGN: Retrospective Cohort with quantile segmented regression analysis. Groups determined by date of surgery, one year pre-initiative and one year post-initiative. SETTING: Operating room and PACU of a tertiary academic medical center. PATIENTS: Adult (age > 18 years), ASA status 1-5, non-pregnant patients undergoing non-cardiac surgery of less than six hours duration admitted to the PACU postoperatively. INTERVENTIONS: A multidisciplinary initiative to preferentially utilize enteral over parenteral acetaminophen. MEASUREMENTS: The primary outcome was narcotic consumption in the PACU. Secondary outcomes were intraoperative narcotic administration, pain score on PACU admission and discharge, and time to meeting criteria for PACU discharge. RESULTS: 24,701 patients were included in the analysis; 12,379 had surgery prior to the initiative and 12,322 after. Enteral acetaminophen administration increased preoperatively from 13.49% to 26.84%, and postoperatively from 43.16% to 51.45%, while intraoperative parenteral APAP use dropped from 43.23% to 6.81%. Quantile Segmented regression analysis after adjusting for period (pre versus postintervention), day, age, gender, inpatient status, and ASA class demonstrated a decrease in adjusted median perioperative acetaminophen dose (-175 mg P < 0.001), with no significant difference in level change of intraoperative or PACU narcotic administration. There was no significant difference in median time to meet criteria for PACU discharge, though there was a significant change in the slope, (-0.36, p = 0.007.) Median pain scores measured on a standard 0-10 numeric rating scale at PACU admission did not change, while median pain scores at PACU discharge decreased slightly (-0.24 p < 0.001). There was no change in the probability of PONV. CONCLUSION: In adult patients undergoing non-cardiac surgery of <6 h duration, preferential use of enteral rather than parenteral acetaminophen is associated with non-inferior outcomes in narcotic requirements, pain scores, time to PACU discharge, and probability of PONV when compared with routine parenteral administration. Further studies are needed to validate these findings.

Diagnosis and Treatment of New-Onset Perioperative Atrial Fibrillation.

This article reviews medical and surgical risk factors for developing atrial fibrillation (AF), the most common sustained dysrhythmia in the United States. Evidence for assessment and management of patients with AF, including AF newly identified in the preoperative clinic, immediately preoperatively, intraoperatively, and unstable AF, is presented. A stepwise approach to guide anesthetic decision-making in the assessment of newly identified preoperative AF is proposed. Anesthetic considerations, including the potential impacts of anesthetic and vasopressor selection, and current evidence related to rate control and rhythm control via pharmacologic or electrical cardioversion as well as anticoagulation strategies are discussed.

Measuring Pediatric Palliative Care Quality: Challenges and Opportunities.

Pediatric palliative care (PPC) programs vary widely in structure, staffing, funding, and patient census, resulting in inconsistency in service provision. Improving the quality of palliative care for children living with serious illness and their families requires measuring care quality, ensuring that quality measurement is embedded into day-to-day clinical practice, and aligning quality measurement with healthcare policy priorities. Yet, numerous challenges exist in measuring PPC quality. This paper provides an overview of PPC quality measurement, including challenges, current initiatives, and future opportunities. While important strides toward addressing quality measurement challenges in PPC have been made, including ongoing quality measurement initiatives like the Cambia Metrics Project, the PPC What Matters Most study, and collaborative learning networks, more work remains. Providing high-quality PPC to all children and families will require a multi-pronged approach. In this paper, we suggest several strategies for advancing high-quality PPC, which includes 1) considering how and by whom success is defined, 2) evaluating, adapting, and developing PPC measures, including those that address care disparities within PPC for historically marginalized and excluded communities, 3) improving the infrastructure with which to routinely and prospectively measure, monitor, and report clinical and administrative quality measures, 4) increasing endorsement of PPC quality measures by prominent quality organizations to facilitate accountability and possible reimbursement, and 5) integrating PPC-specific quality measures into the administrative, funding, and policy landscape of pediatric healthcare.

[Preference of patients with inflammatory bowel disease regarding information and shared decision-making: results from a cross-sectional survey in Germany]. / Zu welchen Themen wünschen Patientinnen und Patienten mit Morbus Crohn oder Colitis ulcerosa mehr Informationen und welche eigene Rolle bevorzugen sie bei medizinischen Behandlungsentscheidungen? Ergebnisse einer Betroffenenbefragung in Deutschland.

BACKGROUND: Evidence-based and consented pathways for patients with inflammatory bowel diseases (IBD, Crohn's disease, ulcerative colitis) call for tailored education programmes to foster shared decision-making and patient self-management. Their preferences should be taken into account. METHODS: In 2005 a cross-sectional postal questionnaire survey was conducted in different regions of Germany. Adult patients with ulcerative colitis (UC) or Crohn's disease (CD) were recruited from specialised gastroenterological practices, university outpatient clinics and the member registry of the relevant patient organisation DCCV. They returned a questionnaire including (inter)nationally established scales (e. g., HADS) as well as questions on their information needs, preferred information sources and their role in decision-making. RESULTS: Data of 1056 responders could be analysed (65 % female; CD: 58 %; DCCV member: 71 %). The mean age of the patients was 42 (SD 12,8) years. Almost all patients wanted more information on "treatment alternatives" (83 %), "causes of disease" (80 %) and "what can I (still) do by myself" (79 %). 27 % of the patients asked for more information on 15 or more of overall 19 topics. The high information need was significantly associated with HADS potential depressive disorder (score > 8) and HADS probable anxiety disorder (score > 10). Most IBD patients (70 %) obviously regard their physicians as the most desirable source of information, 67 % prefer an active involvement in clinical decision-making. CONCLUSIONS: The data demonstrate high information needs of IBD patients and may serve in the planning of future educational programmes.

Apparatus for in situ monitoring of copper in coastal waters.

Apparatus is designed and tested to determine metals in situ in seawater. Voltammetry with a vibrating gold microwire electrode (VGME) is combined with a battery powered potentiostat and a processor board and is tested for in situ monitoring of copper (Cu) in coastal waters. The VGME was combined with solid state reference and counter electrodes to make a single vibrating probe which was rated up to a depth of 40 m. The measuring mode for Cu was square-wave anodic stripping voltammetry whilst dissolved oxygen (DO) was monitored by a linear sweep scan in a negative potential direction. The working electrode was reactivated between measurements using a suitable potential sequence. The novelties of this work are the field-testing of apparatus incorporating a VGME for copper monitoring, which eliminates the need for pumping and reagents, but has sufficient sensitivity for low ambient levels of copper, and the use of a novel potential sequence to stabilise the response over a long time period. The apparatus has a measuring time of about 6 weeks and a measuring frequency of 12 h(-1). Measurement is reagent-free and power use is low as no pump is required. Experiments are carried out to test the stability of response of the system at various temperatures and its robustness with respect to long-term copper monitoring. Preliminary data were obtained during autonomous deployment over several weeks on a buoy in the Irish Sea. Vertical movement of the buoy caused individual measurements to have a variability of about 15%. It was found that longer term variability of the electrode could be minimised by normalisation of the Cu response over that of DO as the response was related to diffusion through the electrode surface which was similarly affected. The detected fraction of Cu (labile Cu) amounted to 1.5-4 nM during different deployments at a total Cu concentration of ∼10 nM. The same ratio was found by voltammetry in samples taken to the laboratory. The new apparatus has demonstrated that metals in coastal waters can be monitored at trace level, much facilitating the monitoring of outfalls and local water contamination. Because of its sensitivity the apparatus would be of use in estuarine as well as coastal waters, with the aim of monitoring intermittent variability in the copper concentration.

Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years.

Radiocarbon dating is the gold standard in archeology to estimate the age of skeletons, a key to studying their origins. Many published ancient genomes lack reliable and direct dates, which results in obscure and contradictory reports. We developed the temporal population structure (TPS), a DNA-based dating method for genomes ranging from the Late Mesolithic to today, and applied it to 3,591 ancient and 1,307 modern Eurasians. TPS predictions aligned with the known dates and correctly accounted for kin relationships. TPS dating of poorly dated Eurasian samples resolved conflicting reports in the literature, as illustrated by one test case. We also demonstrated how TPS improved the ability to study phenotypic traits over time. TPS can be used when radiocarbon dating is unfeasible or uncertain or to develop alternative hypotheses for samples younger than 10,000 years ago, a limitation that may be resolved over time as ancient data accumulate.