Modelling and prediction of bacterial attachment to polymers

Infection by pathogenic bacteria on implanted and indwelling medical devices during surgery causes large morbidity and mortality worldwide. Attempts to ameliorate this important medical issue have included development of antimicrobial surfaces on materials, ‘no touch’ surgical procedures, and development of materials with inherent low pathogen attachment. The search for new materials is increasingly being carried out by high throughput methods. Efficient methods for extracting knowledge from these large data sets are essential. We used data from a large polymer microarray exposed to three clinical pathogens to derive robust and predictive machine-learning models of pathogen attachment. The models could predict pathogen attachment for the polymer library quantitatively. The models also successfully predicted pathogen attachment for a second-generation library, and identified polymer surface chemistries that enhance or diminish pathogen attachment

Heat, molecular vibrations, and adiabatic driving in non-equilibrium transport through interacting quantum dots

In this article we review aspects of charge and heat transport in interacting quantum dots and molecular junctions under stationary and time-dependent non-equilibrium conditions due to finite electrical and thermal bias. In particular, we discuss how a discrete level spectrum can be beneficial for thermoelectric applications, and investigate the detrimental effects of molecular vibrations on the efficiency of a molecular quantum dot as an energy converter. In addition, we consider the effects of a slow time-dependent modulation of applied voltages on the transport properties of a quantum dot and show how this can be used as a spectroscopic tool complementary to standard dc-measurements. Finally, we combine time-dependent driving with thermoelectrics in a double-quantum dot system - a nanoscale analogue of a cyclic heat engine - and discuss its operation and the main limitations to its performance.Comment: Review article submitted to PSS (b) for the special issue "Quantum transport at the molecular scale

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Früherkennung des Typ-1-Diabetes in der Fr1da-Studie: Diagnosestellung im asymptomatischen Stadium.

Background: Islet autoantibody detection allows the diagnosis of type 1 diabetes at an early stage, where the patient is still free of symptoms. This allows the prevention of severe complications through education and monitoring and allows initiation of preventative therapies to avoid progression. Fr1da study: The Fr1da study is offered in the context of compulsory preventive medical check-ups for children between the ages of 2 and 5 years. If at least two positive islet autoantibodies are detected in capillary blood, the diagnosis of early stage type 1 diabetes is made. Children and their parents are invited to participate in education sessions to learn about the disease and receive a preventive check-up plan for regular testing of blood and urine glucose, HbA1c, and growth. An anxiety and stress assessment is also performed. Results: Since 2015, over 75,000 children between the ages of 2 and 5 years have been screened for the presence of islet autoantibodies. To date, about 200 children diagnosed with early stage of type 1 diabetes have participated in the education and counselling programme. The psychological assessment revealed no serious distress in any of the families. In addition, no case of ketoacidosis has occurred so far. Conclusion: The Fr1da study has shown that staging for early type 1 diabetes within a public health setting appears to be feasible. The Fr1da study can be easily tranferred to the rest of Germany and is been done since 2016 in Lower Saxony within the framework of the Fr1dolin study

Potential antioxidant response to coffee - A matter of genotype?

In a human intervention trial, a coffee, combining nature green coffee bean constituents and dark roast products was studied towards its potential to activate the Nrf2/ARE-pathway in PBLs. The study coffee was identified as a strong inducer of Nrf2 and downstream GST1A1 and UGT1A1 gene transcription. However, the response of the participants was found to depend on the respective genotype. The -651 SNP in the Nrf2 gene as well as the heterozygote 6/7 sequence in the UGT1A1 gene significantly down-regulated the susceptibility to respond to coffee, proposing the existing genotype to be critical for the response to the coffee

A Simple Preoperative Score Predicting Failure Following Decompression Surgery for Degenerative Lumbar Spinal Stenosis.

BACKGROUND CONTEXT Proper patient selection is crucial for the outcome of surgically treated degenerative lumbar spinal stenosis (DLSS). Nevertheless, there is still not a clear consensus regarding the optimal treatment option for patients with DLSS. PURPOSE To investigate the treatment failure rate and introduce a simple, preoperative score to aid surgical decision-making. STUDY DESIGN/SETTING Retrospective observational study. PATIENT SAMPLE Four hundred forty-five patients who underwent surgical decompression for DLSS. OUTCOME MEASURES Treatment failure (defined as conversion to a fusion of a previously decompressed level) of lumbar decompression. MATERIALS AND METHODS Several risk factors associated with worse outcomes and treatment failures, such as age, body mass index, smoking status, previous surgery, low back pain (LBP), facet joint effusion, disk degeneration, fatty infiltration of the paraspinal muscles, the presence of degenerative spondylolisthesis and the facet angulation, were investigated. RESULTS At a mean follow-up of 44±31 months, 6.5% (29/445) of the patients underwent revision surgery with spinal fusion at an average of 3±9 months following the lumbar decompression due to low back or leg pain. The baseline LBP (≥7) [odds ratio (OR)=5.4, P 2 mm) in magnetic resonance imaging (OR=4.2, P 4) (OR=3.2, P =0.03) were associated with an increased risk for treatment failure following decompression for DLSS. The receiver operating characteristic curve analysis demonstrated that a score≥6 points yielded a sensitivity of 90% and specificity of 64% for predicting a treatment failure following lumbar decompression for DLSS in the present cohort. CONCLUSIONS The newly introduced score quantifying amounts of LBP, facet effusions, and disk degeneration, could predict treatment failure and the need for revision surgery for DLSS patients undergoing lumbar decompression without fusion. Patients with scores >6 have a high chance of needing fusion following decompression surgery. LEVEL OF EVIDENCE Retrospective observational study, Level III