Allosteric Activation Dictates PRC2 Activity Independent of Its Recruitment to Chromatin.

PRC2 is a therapeutic target for several types of cancers currently undergoing clinical trials. Its activity is regulated by a positive feedback loop whereby its terminal enzymatic product, H3K27me3, is specifically recognized and bound by an aromatic cage present in its EED subunit. The ensuing allosteric activation of the complex stimulates H3K27me3 deposition on chromatin. Here we report a stepwise feedback mechanism entailing key residues within distinctive interfacing motifs of EZH2 or EED that are found to be mutated in cancers and/or Weaver syndrome. PRC2 harboring these EZH2 or EED mutants manifested little activity in vivo but, unexpectedly, exhibited similar chromatin association as wild-type PRC2, indicating an uncoupling of PRC2 activity and recruitment. With genetic and chemical tools, we demonstrated that targeting allosteric activation overrode the gain-of-function effect of EZH2Y646X oncogenic mutations. These results revealed critical implications for the regulation and biology of PRC2 and a vulnerability in tackling PRC2-addicted cancers.

Fostering Governance and Information Partnerships for Chronic Disease Surveillance: The Multi-State EHR-Based Network for Disease Surveillance.

CONTEXT: Electronic health records (EHRs) are an emerging chronic disease surveillance data source and facilitating this data sharing is complex. PROGRAM: Using the experience of the Multi-State EHR-Based Network for Disease Surveillance (MENDS), this article describes implementation of a governance framework that aligns technical, statutory, and organizational requirements to facilitate EHR data sharing for chronic disease surveillance. IMPLEMENTATION: MENDS governance was cocreated with data contributors and health departments representing Texas, New Orleans, Louisiana, Chicago, Washington, and Indiana through engagement from 2020 to 2022. MENDS convened a governance body, executed data-sharing agreements, and developed a master governance document to codify policies and procedures. RESULTS: The MENDS governance committee meets regularly to develop policies and procedures on data use and access, timeliness and quality, validation, representativeness, analytics, security, small cell suppression, software implementation and maintenance, and privacy. Resultant policies are codified in a master governance document. DISCUSSION: The MENDS governance approach resulted in a transparent governance framework that cultivates trust across the network. MENDS's experience highlights the time and resources needed by EHR-based public health surveillance networks to establish effective governance.

Chronic pain and the use of complementary and alternative medicine in rural Victoria, Australia.

OBJECTIVE: The relationship between chronic pain and complementary and alternative medicine (CAM) use is poorly understood, and the situation in rural Australia is particularly unclear. The objective here was to determine the socio-demographic factors associated with the use of CAM for the treatment of chronic pain in a region of rural Australia. METHODS: This secondary analysis used data from a population health survey, Crossroads-II, to assess the relationships of various socio-demographic factors with the use of CAM by those suffering from chronic pain. DESIGN: Face-to-face surveys at households randomly selected from residential address lists. SETTING: A large regional centre and three nearby rural towns in northern Victoria, Australia. PARTICIPANTS: Sixteen years of age and older. MAIN OUTCOME MEASURES: Use of a CAM service to treat chronic pain. RESULTS: Being female (2.40 [1.47, 3.93], p < 0.001) and having a bachelor's degree (OR 2.24 [1.20, 4.20], p < 0.001) had a significant positive relationship with the use of CAM overall to redress chronic pain and those 50 years and older had greater odds of using manipulation therapies relative to those below 50 years (50-64: OR 0.52 [0.32, 0.86], p = 0.010; 65+: 0.37 [0.18, 0.75], p = 0.005). CONCLUSION: In the studied region, females and those with university education have the greatest odds of using CAM to treat chronic pain. This study needs to be complemented with more mechanistic investigations into the reasons people make the decisions they make about using CAM for the management of chronic pain.

Sweet Syndrome: A Review of Published Cases.

Sweet syndrome (SS), the prototypical neutrophilic dermatosis, is characterized by abrupt onset of tender plaques and nodules, classically accompanied by fever and leukocytosis. While management mainly relies on systemic corticosteroids, inadequate response can be seen in some patients that necessitates exploring other treatment options. Early diagnosis of malignancy-associated SS (MA-SS) along with detection of concomitant malignancy is crucial for improving patients' outcomes. Data regarding various clinical manifestations, extracutaneous associations, treatment, and outcomes are poorly characterized in the literature. We aimed to review all published case reports and case series to portray clinical features of SS including extracutaneous manifestations. We also describe reported treatment options and their outcomes to draw attention toward unmet therapeutic needs in the management of SS. In addition, for clinical and practical purposes, we attempted to delineate the distinction between MA-SS and nonmalignant subtypes of SS.

A Systematic Review of Evidence-Based High School Melanoma Prevention Curricula.

Incorporation of melanoma prevention behaviors into daily lifestyles is difficult. Data suggest that high school educational programs on skin cancer prevention can be successful and should incorporate evidence-based teaching and learning strategies to achieve greatest impact. The goal of this systematic review is to describe evidence-based educational practices for a high-school melanoma curriculum through a comprehensive review of the literature. Ovid MEDLINE, Embase, CINAHL, and PyscINFO were searched in June 2020 for all original articles published between June 18, 1946 and June 17, 2020. All studies that used an educational curriculum to promote sun safety, skin exams, and early detection to high school students were included. A total of 25 studies with 22,683 adolescent participants were analyzed. Sixteen studies showed a significant increase in knowledge, twenty-one studies showed changes in behavior, and fifteen studies showed significant changes in attitudes. Limitations of this review include the heterogeneity of implementation and outcome reporting of educational curricula. These findings support incorporating active learning strategies as key aspects of creating an effective curriculum aimed at the prevention and early detection of melanoma.

Improving Structural Stability and Anticoagulant Activity of a Thrombin Binding Aptamer by Aromatic Modifications.

The thrombin binding aptamer (TBA) is a 15-mer DNA oligonucleotide (5'-GGT TGG TGT GGT TGG-3'), that can form a stable intramolecular antiparallel chair-like G-quadruplex structure. This aptamer shows anticoagulant properties by interacting with one of the two anion binding sites of thrombin, namely the fibrinogen-recognition exosite. Here, we demonstrate that terminal modification of TBA with aromatic fragments such as coumarin, pyrene and perylene diimide (PDI), improves the G-quadruplex stability. The large aromatic surface of these dyes can π-π stack to the G-quadruplex or to each other, thereby stabilizing the aptamer. With respect to the original TBA, monoPDI-functionalized TBA exhibited the most remarkable improvement in melting temperature (ΔTm ≈+18 °C) and displayed enhanced anticoagulant activity.

Cucurbit[7]uril Inhibits Islet Amyloid Polypeptide Aggregation by Targeting N Terminus Hot Segments and Attenuates Cytotoxicity.

Two "hot segments" within an islet amyloid polypeptide are responsible for its self-assembly, which in turn is linked to the decline of ß-cells in type 2 diabetes (T2D). A readily available water-soluble, macrocyclic host, cucurbit[7]uril (CB[7]), effectively inhibits islet amyloid polypeptide (IAPP) aggregation through ion-dipole and hydrophobic interactions with different residues of the monomeric peptide in its random-coil conformation. A HSQC NMR study shows that CB[7] likely modulates IAPP self-assembly by interacting with and masking major residues present in the "hot segments" at the N terminus. CB[7] also prevents the formation of toxic oligomers and inhibits seed-catalyzed fibril proliferation. Importantly, CB[7] recovers rat insulinoma cells (RIN-m) from IAPP-assembly associated cytotoxicity.

Cucurbit[7]uril Inhibits Islet Amyloid Polypeptide Aggregation by Targeting N†Terminus Hot Segments and Attenuates Cytotoxicity.

Invited for the cover of this issue is the group of Prof. Hamilton at New York University. The image depicts how cucurbit[7]uril inhibits islet amyloid polypeptide self-assembly that rescues rat insulinoma cells (a pancreatic ß-cell model) from assembly-associated cytotoxicity. Read the full text of the article at 10.1002/chem.202200456.

Travel-Associated Venous Thromboembolism.

INTRODUCTION: Long-distance travel is assumed to be a risk factor for venous thromboembolism (VTE). However, the available data have not clearly demonstrated the strength of this relationship, nor have they shown evidence for the role of thromboprophylaxis. METHODS: We performed a systematic review of the literature. We also summarized available guidelines from 5 groups. RESULTS: We found 18 studies that addressed this question. Based on the data presented in the review, we conclude that there is an association between VTE and length of travel, but this association is mild to moderate in effect size with odds ratios between 1.1 and 4. A dose-response relationship between VTE and travel time was identified, with a 26% higher risk for every 2 h of air travel (P=0.005) starting after 4 h. The quality of evidence for both travel length and thromboprophylaxis was low. However, low-risk prophylactic measures such as graduated compression stockings were shown to be effective in VTE prevention. There is heterogeneity among the different practice guidelines. The guidelines generally concur that no prophylaxis is necessary in travelers without known thrombosis risk factors and advocate for conservative treatment such as compression stockings over pharmacologic prophylaxis. CONCLUSIONS: We conclude air travel is a risk factor for VTE and that there is a dose relationship starting at 4 h. For patients with risk factors, graduated compression stockings are effective prophylaxis.

Peptidomimetic-Based Vesicles Inhibit Amyloid-ß Fibrillation and Attenuate Cytotoxicity.

An interruption in Aß homeostasis leads to the deposit of neurotoxic amyloid plaques and is associated with Alzheimer's disease. A supramolecular strategy based on the assembly of peptidomimetic agents into functional vesicles has been conceived for the simultaneous inhibition of Aß42 fibrillation and expedited clearance of Aß42 aggregates. Tris-pyrrolamide peptidomimetic, ADH-353, contains one hydrophobic N-butyl and two hydrophilic N-propylamine side chains and readily forms vesicles under physiological conditions. These vesicles completely rescue both mouse neuroblastoma N2a and human neuroblastoma SH-SY5Y cells from the cytotoxicity that follows from Aß42 misfolding likely in mitochondria. Biophysical studies, including confocal imaging, demonstrate the biocompatibility and selectivity of the approach toward this aberrant protein assembly in cellular milieu.

Classification of Cattle Behaviours Using Neck-Mounted Accelerometer-Equipped Collars and Convolutional Neural Networks.

Monitoring cattle behaviour is core to the early detection of health and welfare issues and to optimise the fertility of large herds. Accelerometer-based sensor systems that provide activity profiles are now used extensively on commercial farms and have evolved to identify behaviours such as the time spent ruminating and eating at an individual animal level. Acquiring this information at scale is central to informing on-farm management decisions. The paper presents the development of a Convolutional Neural Network (CNN) that classifies cattle behavioural states ('rumination', 'eating' and 'other') using data generated from neck-mounted accelerometer collars. During three farm trials in the United Kingdom (Easter Howgate Farm, Edinburgh, UK), 18 steers were monitored to provide raw acceleration measurements, with ground truth data provided by muzzle-mounted pressure sensor halters. A range of neural network architectures are explored and rigorous hyper-parameter searches are performed to optimise the network. The computational complexity and memory footprint of CNN models are not readily compatible with deployment on low-power processors which are both memory and energy constrained. Thus, progressive reductions of the CNN were executed with minimal loss of performance in order to address the practical implementation challenges, defining the trade-off between model performance versus computation complexity and memory footprint to permit deployment on micro-controller architectures. The proposed methodology achieves a compression of 14.30 compared to the unpruned architecture but is nevertheless able to accurately classify cattle behaviours with an overall F1 score of 0.82 for both FP32 and FP16 precision while achieving a reasonable battery lifetime in excess of 5.7 years.

Evolving Librarian Engagement in Undergraduate Medical Education Student Research and Scholarship.

Undergraduate Medical Education (UME) program curriculum redesign at Oregon Health & Science University (OHSU) in the early 2010s resulted in incorporation of a long-term research project-called "Scholarly Projects"-into the UME experience. Since 2014, OHSU librarians have participated in curricular support for Scholarly Projects, focusing on helping students develop skills in searching and information management at a moment when the students are starting their projects. This library participation has developed over time and continues to change in response to ongoing librarian reflection on student engagement with the material.

Quantified pre-operative neurological dysfunction predicts outcome after coronary artery bypass surgery.

AIMS: Patients undergoing coronary artery bypass grafting (CABG) surgery may experience neurological impairment. We examined whether intraoperative regional cerebral oxygen saturation (rSO2) and neurological dysfunction prior to surgery, measured by robotic technology, are important predictors of post-operative performance following CABG surgery. METHODS: Adult patients undergoing CABG surgery were recruited for this single-center prospective observational study. Intraoperative rSO2 was captured using the FORESIGHT cerebral oximeter. Neurological assessment was performed pre-operatively and 3 months following surgery using robotic technology and a standardized pen-and-paper assessment. Linear regression models were generated to determine the predictive ability of both intraoperative rSO2 and pre-operative performance on post-operative neurological outcome. RESULTS: Forty patients had complete data available for analysis. Quantified pre-operative performance accounted for a significantly larger amount of variance in post-operative outcome compared to intraoperative rSO2. In particular, pre-operative scoring on a cognitive visuospatial task accounted for 82.2% of variance in post-operative performance (b = 0.937, t(37) = 12.98, p = 1.28e-5). DISCUSSION: Our results suggest that pre-operative performance is a stronger indicator of post-operative neurological outcome than intraoperative rSO2, and should be included as an important variable when elucidating the relationship between cerebral oxygen levels and post-operative neurological impairment. Rigorous neurological assessment prior to surgery can provide valuable information about each individual patient's path to recovery. CONCLUSION: Using robotic technology, quantified neurological impairment prior to CABG surgery may better predict post-operative neurological outcomes, compared to intraoperative rSO2 values.

The Internet of Things enhancing animal welfare and farm operational efficiency.

The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role.

Contrasting effects of high-starch and high-sugar diets on ruminal function in cattle.

The experiment reported in this research paper aimed to determine whether clinical and subclinical effects on cattle were similar if provided with isoenergetic and isonitrogenous challenge diets in which carbohydrate sources were predominantly starch or sugar. The study was a 3 × 3 Latin square using six adult Jersey cows with rumen cannulae, over 9 weeks. In the first 2 weeks of each 3 week experimental period cows were fed with a maintenance diet and, in the last week, each animal was assigned to one of three diets: a control diet (CON), being a continuation of the maintenance diet; a high starch (HSt) or a high sugar (HSu) diet. Reticuloruminal pH and motility were recorded throughout the study period. Blood and ruminal samples were taken on day-1 (TP-1), day-2 (TP-2) and day-7 (TP-7) of each challenge week. Four clinical variables were recorded daily: diarrhoea, inappetence, depression and ruminal tympany. The effects of treatment, hour of day and day after treatment on clinical parameters were analysed using linear mixed effects (LME) models. Although both challenge diets resulted in a decline in pH, an increase in the absolute pH residuals and an increase in the number of minutes per day under pH 5.8, systemic inflammation was only detected with the HSt diet. The challenge diets differentially modified amplitude and period of reticuloruminal contractions compared with CON diet and both were associated with an increased probability of diarrhoea. The HSu diet reduced the probability of an animal consuming its complete allocation. Because the challenge diets were derived from complex natural materials (barley and molasses respectively), it is not possible to assign all the differential effects to the difference in starch and sugar concentration: non-starch components of barley or non-sugar components of molasses might have contributed to some of the observations. In conclusion, substituting much of the starch with sugar caused no substantial reduction in the acidosis load, but inflammatory response was reduced while feed rejection was increased.

Non-Destructive Identification of Fibre Orientation in Multi-Ply Biaxial Laminates Using Contact Temperature Sensors.

Fibre orientation within composite structures dictates the material properties of the laminate once cured. The ability to accurately and automatically assess fibre orientation of composite parts is a significant enabler in the goal to optimise the established processes within aftermarket aerospace industries. Incorrect ply lay-up results in a structure with undesirable material properties and as such, has the potential to fail under safe working loads. Since it is necessary to assure structural integrity during re-manufacture and repair assessment, the paper demonstrates a novel method of readily and non-destructively determining fibre orientation throughout multi-ply Biaxial woven composite laminates using point temperature contact sensors and data analysis techniques. Once cured, only the outermost laminates are visible to assess orientation. The inspection method is conducted visually, with reference guides to allow for rapid adoption with minimum training, as well as harnessing established temperature sensors within the Maintenance Repair and Overhaul (MRO) environment. The system is amenable to integration within existing repair/re-manufacture processes without significant impact to process flow. The method is able to identify noisy samples with an accuracy, precision and recall of 0.9, and for synthetically created samples of double the cure ply thickness, a precision of 0.75, a recall of 0.7 and an accuracy of 0.87.

Composite Laminate Delamination Detection Using Transient Thermal Conduction Profiles and Machine Learning Based Data Analysis.

Delaminations within aerospace composites are of particular concern, presenting within composite laminate structures without visible surface indications. Transmission based thermography techniques using contact temperature sensors and surface mounted heat sources are able to detect reductions in thermal conductivity and in turn impact damage and large disbonds can be detected. However delaminations between Carbon Fibre Reinforced Polymer (CFRP) plies are not immediately discoverable using the technique. The use of transient thermal conduction profiles induced from zonal heating of a CFRP laminate to ascertain inter-laminate differences has been demonstrated and the paper builds on this method further by investigating the impact of inter laminate inclusions, in the form of delaminations, to the transient thermal conduction profile of multi-ply bi-axial CFRP laminates. Results demonstrate that as the distance between centre of the heat source and delamination increase, whilst maintaining the delamination within the heated area, the resultant transient thermal conduction profile is measurably different to that of a homogeneous region at the same distance. The method utilises a supervised Support Vector Classification (SVC) algorithm to detect delaminations using temperature data from either the edge of the defect or the centre during a 140 s ramped heating period to 80 °C. An F1 score in the classification of delaminations or no delamination at an overall accuracy of over 99% in both training and with test data separate from the training process has been achieved using data points effected by transient thermal conduction due to structural dissipation at 56.25 mm.

Defect Detection in Aerospace Sandwich Composite Panels Using Conductive Thermography and Contact Sensors.

Sandwich panels consisting of two Carbon Fibre Reinforced Polymer (CFRP) outer skins and an aluminium honeycomb core are a common structure of surfaces on commercial aircraft due to the beneficial strength-weight ratio. Mechanical defects such as a crushed honeycomb core, dis-bonds and delaminations in the outer skins and in the core occur routinely under normal use and are repaired during aerospace Maintenance, Repair and Overhaul (MRO) processes. Current practices rely heavily on manual inspection where it is possible minor defects are not identified prior to primary repair and are only addressed after initial repairs intensify the defects due to thermal expansion during high temperature curing. This paper reports on the development and characterisation of a technique based on conductive thermography implemented using an array of single point temperature sensors mounted on one surface of the panel and the concomitant induced thermal profile generated by a thermal stimulus on the opposing surface to identify such defects. Defects are classified by analysing the differential conduction of thermal energy profiles across the surface of the panel. Results indicate that crushed core and impact damage are detectable using a stepped temperature profile of 80 ∘C The method is amenable to integration within the existing drying cycle stage and reduces the costs of executing the overall process in terms of time-to-repair and manual effort.

Identifying Defects in Aerospace Composite Sandwich Panels Using High-Definition Distributed Optical Fibre Sensors.

Automated methods for detecting defects within composite materials are highly desirable in the drive to increase throughput, optimise repair program effectiveness and reduce component replacement. Tap-testing has traditionally been used for detecting defects but does not provide quantitative measurements, requiring secondary techniques such as ultrasound to certify components. This paper reports on an evaluation of the use of a distributed temperature measurement system-high-definition fibre optic sensing (HD-FOS)-to identify and characterise crushed core and disbond defects in carbon fibre reinforced polymer (CFRP)-skin, aluminium-core, sandwich panels. The objective is to identify these defects in a sandwich panel by measuring the heat transfer through the panel thickness. A heater mat is used to rapidly increase the temperature of the panel with the HD-FOS sensor positioned on the top surface, measuring temperature. HD-FOS measurements are made using the Luna optical distributed sensor interrogator (ODISI) 9100 system comprising a sensor fabricated using standard single mode fibre (SMF)-20 of external diameter 250 µm, including the cladding. Results show that areas in which defects are present modulate thermal conductivity, resulting in a lower surface temperature. The resultant data are analysed to identify the length, width and type of defect. The non-invasive technique is amenable to application in challenging operational settings, offering high-resolution visualisation and defect classification.

Automatic Annotation of Subsea Pipelines using Deep Learning.

Regulatory requirements for sub-sea oil and gas operators mandates the frequent inspection of pipeline assets to ensure that their degradation and damage are maintained at acceptable levels. The inspection process is usually sub-contracted to surveyors who utilize sub-sea Remotely Operated Vehicles (ROVs), launched from a surface vessel and piloted over the pipeline. ROVs capture data from various sensors/instruments which are subsequently reviewed and interpreted by human operators, creating a log of event annotations; a slow, labor-intensive and costly process. The paper presents an automatic image annotation framework that identifies/classifies key events of interest in the video footage viz. exposure, burial, field joints, anodes, and free spans. The reported methodology utilizes transfer learning with a Deep Convolutional Neural Network (ResNet-50), fine-tuned on real-life, representative data from challenging sub-sea environments with low lighting conditions, sand agitation, sea-life and vegetation. The network outputs are configured to perform multi-label image classifications for critical events. The annotation performance varies between 95.1% and 99.7% in terms of accuracy and 90.4% and 99.4% in terms of F1-Score depending on event type. The performance results are on a per-frame basis and corroborate the potential of the algorithm to be the foundation for an intelligent decision support framework that automates the annotation process. The solution can execute annotations in real-time and is significantly more cost-effective than human-only approaches.