Through legislative changes, tariff wars, and executive actions, the Trump Administration has injected a new urgency into international technology and supply chain management, particularly between the United States and China. Analytically, the situation invites a perspective that links practical/on-the-ground responses by commercial actors in the politics of technological competition between superpowers, i.e. a discussion that bridges the gap between policy and process. This article therefore approaches management of supply chain disruption in terms of a key security issue motivating recent changes to the trade environment: the protection of intellectual property. After reviewing critical policy developments and trade statistics, we draw upon data on IP-intensive industries from global patent offices, trade classifications for products made by these IP-intensive industries, and concordance data on patent classifications to illustrate the centrality of IP to extended supply chains. With these key relationships in mind, we outline specific opportunities that intellectual property licensing provides for managing supply chain linkages between the United States and China in the current geopolitical environment. Viewing intellectual property as both a driver of and a solution to trade difficulties highlights the sorts of cross-jurisdictional nuances that can better inform policy and business decisions alike in the broader international trade regime.

Background: In the past few decades, the epidemiology of Clostridioides difficile infection (CDI) has evolved. Given recent changes in the incidence of CDI and prevention efforts, we investigated temporal changes over a period of 8 years (2009–2016) in the incidence of and risk factors for CDI. Methods: Both pediatric and adult inpatients discharged from hospitals in metropolitan New York City were included. Individual and environmental (eg, pharmacological) risk factors were identified through a matched case-control by the length of stay at a ratio of 1:4. A Cochran–Armitage test or Mann-Kendall test was used to investigate trends of incidence and risk factors. Results: During the study period, 6,038 of 694,849 (0.87%) patients had a positive test for C. difficile during their hospitalization. Of these, 2,659 of 6,038 (44.04%) were identified as hospital-acquired CDI (HA-CDI) and just over half (3,379 of 6,038, 55.96%) were identified as community-acquired CDI (CA-CDI). There were no trends in total CDI incidence rates; rather, we detected downward trends in HA-CDI and upward trends in CA-CDI (Ptrend < .05). Younger patients and patients with lower risk of illness had HA-CDI over time (Ptrend < .05). Antibiotics were administered to more patients over time and in longer cumulative days (+3% and +3.1% per year). We detected a reduction in the receipt of high-risk antibiotics in all cohorts (−0.12% per year) and a decrease in cumulative days of high-risk antibiotics in the cohort with HA-CDI (−1.1% per year). When stratified by the type of high-risk antibiotics, the use of carbapenem, cephalosporins, clindamycin, and monobactam increased (+0.53%, +1.8%, +0.5%, and +0.39% per year, respectively), whereas the use of broad-spectrum penicillins and glycylcycline significantly decreased over time in all cohorts (−1.8% and −0.22% per year). Among the cohorts with HA-CDI, only cephalosporins showed a significant upward trend (+ 5.7% per year) and only fluoroquinolones showed a significant downward trend (−2.2% per year). Lastly, a reduction of proton pump inhibitors and an increased use of histamine-2 blockers were detected in all cohorts (−3.8% and +7.3% per year) (all Ptrend < .05). Conclusions: Although the incidence of HA-CDI decreased, more effort to decrease all antibiotics use and cumulative days should be emphasized as part of antibiotic stewardship. The downward trends of high-risk antibiotics might have been associated with the decrease in the trend of HA-CDI; however, the impact of the trends of risk factors on the trend of HA-CDI should be further investigated.

Funding: None

Disclosures: None

Background: Pseudomonas aeruginosa is an important nosocomial pathogen associated with intrinsic and acquired resistance mechanisms to major classes of antibiotics. To better understand clinical risk factors for drug-resistant P. aeruginosa infection, decision-tree models for the prediction of fluoroquinolone and carbapenem-resistant P. aeruginosa were constructed and compared to multivariable logistic regression models using performance characteristics. Methods: In total, 5,636 patients admitted to 4 hospitals within a New York City healthcare system from 2010 to 2016 with blood, respiratory, wound, or urine cultures growing PA were included in the analysis. Presence or absence of drug-resistance was defined using the first culture of any source positive for P. aeruginosa during each hospitalization. To train and validate the prediction models, cases were randomly split (60 of 40) into training and validation datasets. Clinical decision-tree models for both fluoroquinolone and carbapenem resistance were built from the training dataset using 21 clinical variables of interest, and multivariable logistic regression models were built using the 16 clinical variables associated with resistance in bivariate analyses. Decision-tree models were optimized using K-fold cross validation, and performance characteristics between the 4 models were compared. Results: From 2010 through 2016, prevalence of fluoroquinolone and carbapenem resistance was 32% and 18%, respectively. For fluoroquinolone resistance, the logistic regression algorithm attained a positive predictive value (PPV) of 0.57 and a negative predictive value (NPV) of 0.73 (sensitivity, 0.27; specificity, 0.90) and the decision-tree algorithm attained a PPV of 0.65 and an NPV of 0.72 (sensitivity 0.21, specificity 0.95). For carbapenem resistance, the logistic regression algorithm attained a PPV of 0.53 and a NPV of 0.85 (sensitivity 0.20, specificity 0.96) and the decision-tree algorithm attained a PPV of 0.59 and an NPV of 0.84 (sensitivity 0.22, specificity 0.96). The decision-tree partitioning algorithm identified prior fluoroquinolone resistance, SNF stay, sex, and length-of-stay as variables of greatest importance for fluoroquinolone resistance compared to prior carbapenem resistance, age, and length-of-stay for carbapenem resistance. The highest-performing decision tree for fluoroquinolone resistance is illustrated in Fig. 1. Conclusions: Supervised machine-learning techniques may facilitate prediction of P. aeruginosa resistance and risk factors driving resistance patterns in hospitalized patients. Such techniques may be applied to readily available clinical information from hospital electronic health records to aid with clinical decision making.

Funding: None

Disclosures: None

This white paper identifies knowledge gaps and new challenges in healthcare epidemiology research, assesses the progress made toward addressing research priorities, provides the Society for Healthcare Epidemiology of America (SHEA) Research Committee's recommendations for high-priority research topics, and proposes a road map for making progress toward these goals. It updates the 2010 SHEA Research Committee document, “Charting the Course for the Future of Science in Healthcare Epidemiology: Results of a Survey of the Membership of SHEA,” which called for a national approach to healthcare-associated infections (HAIs) and a prioritized research agenda. This paper highlights recent studies that have advanced our understanding of HAIs, the establishment of the SHEA Research Network as a collaborative infrastructure to address research questions, prevention initiatives at state and national levels, changes in reporting and payment requirements, and new patterns in antimicrobial resistance.

Epidemiological data link adolescent cannabis use to psychosis and schizophrenia, but its contribution to schizophrenia neuropathology remains controversial. First-episode schizophrenia (FES) patients show regional cerebral grey- and white-matter changes as well as a distinct pattern of regional grey-matter loss in the vermis of the cerebellum. The cerebellum possesses a high density of cannabinoid type 1 receptors involved in the neuronal diversification of the developing brain. Cannabis abuse may interfere with this process during adolescent brain maturation leading to ‘schizophrenia-like’ cerebellar pathology. Magnetic resonance imaging and cortical pattern matching techniques were used to investigate cerebellar grey and white matter in FES patients with and without a history of cannabis use and non-psychiatric cannabis users. In the latter group we found lifetime dose-dependent regional reduction of grey matter in the right cerebellar lobules and a tendency for more profound grey-matter reduction in lobule III with younger age at onset of cannabis use. The overall regional grey-matter differences in cannabis users were within the normal variability of grey-matter distribution. By contrast, FES subjects had lower total cerebellar grey-matter:total cerebellar volume ratio and marked grey-matter loss in the vermis, pedunculi, flocculi and lobules compared to pair-wise matched healthy control subjects. This pattern and degree of grey-matter loss did not differ from age-matched FES subjects with comorbid cannabis use. Our findings indicate small dose-dependent effects of juvenile cannabis use on cerebellar neuropathology but no evidence of an additional effect of cannabis use on FES cerebellar grey-matter pathology.

Experimental investigation of the generation and decay of coherent structures, namely, streaks (accompanied by a counter-rotating vortex pair) and hairpin vortices in pipe flow, is carried out by artificial injection of continuous disturbances. Flow visualization and velocity measurements show that for small amplitudes of disturbances (v0) streaks are produced, and increasing v0 produces instability waves on the streaks, which further break down into an array of hairpin vortices. However, the streaks and hairpins decay along the downstream direction (X). In fact, the critical value of v0 required for the initiation of hairpins at a given Re (Reynolds number) varies with the streamwise distance (in contrast to the previously found scaling of v0 ~ Re−1, valid only close to the location of injection, i.e. smaller X). This is a consequence of the decay of the coherent structures in the pipe. Moreover, the hairpins have been found to decay more slowly with increasing Re. Measurements of energy in the cross-sectional plane of the pipe, and maps of disturbance velocity at various X-locations show the transient growth and decay of energy for relatively low v0. For higher v0 and Re the energy has been seen to increase continuously along the length of the pipe under observation. Owing to the increase in the cross-sectional area occupied by the disturbance along the X-direction, it is observed that energy can transiently increase even when the total disturbance magnitude is decreasing. Observing the similarity of the present work and other investigations wherein decay of turbulence in pipe flow is found, a schematic illustration of the transition surface for pipe flow on a v0−Re−X, three-dimensional coordinate system is presented.

Background. Pharmaceutical industry funding of psychiatric research has increased significantly in recent decades, raising the question of a relationship between pharmaceutical company funding of clinical psychiatric studies and the outcomes of those studies. This study examines this relationship.

Method. Abstracts of articles from 1992 and 2002 in four peer-reviewed psychiatric journals were examined. Drug outcomes (n=542) for clinical studies were evaluated and then compared across sponsorship source. Outcome raters were blind to source of sponsorship. The percentage of these studies sponsored by drug companies in 2002 v. 1992 was also compared. In a secondary analysis, the contribution of a series of potentially mediating variables to the relationship between sponsorship source and study outcome was assessed via logistic regression.

Results. The percentage of studies sponsored by drug companies increased from 25% in 1992 to 57% in 2002. Favorable outcomes were significantly more common in studies sponsored by the drug manufacturer (78%) than in studies without industry sponsorship (48%) or sponsored by a competitor (28%). These relationships remained after controlling for the effects of journal, year, drug studied, time since FDA drug approval, diagnosis, sample size, and selected study design variables.

Conclusions. These data indicate an association between pharmaceutical industry funding of clinical studies and positive outcomes of those studies. Further research is needed to elucidate the mechanisms underlying this relationship.

The evolution of a finite-amplitude three-dimensional localized disturbance, having an initial dipole Gaussian vorticity distribution, embedded in an external unbounded irrotational plane stagnation flow (${{\bm U}}\,{=}\,(Ay,Ax,0)$) is investigated. Using the fluid impulse integral as a characteristic of such a disturbance, the viscous vorticity equation is integrated analytically. Accordingly, the fluid impulse associated with such disturbances decays and grows exponentially along the principal axes $x\,{=}\,y$ and $x\,{=}\,{-}y$, respectively. Numerical simulations, carried out for both linear and nonlinear disturbances at a Reynolds number of 40, confirm the above predictions. The simu- lations have also been compared with the solution of the linear viscous vorticity disturbance equation. While the solution predicts the vorticity distribution for the linear case, it fails to predict the essential characteristics of a nonlinear disturbance associated with its self-induced movement. Finally, it is shown that the fluid impulse and the disturbance kinetic energy follow the same trend, i.e. when the fluid impulse increases with time so does the kinetic energy and vice versa. The correspondence between them suggests the use of the fluid impulse to predict the stability of a localized disturbance.

Conducting polymers (CP) are a promising area in the field of micro actuators, and have potential applications in micro robotics. Their properties are modelled as having an electro-chemical active component and a passive viscoelastic component. Methods exist to model the passive component as a configuration of springs and dashpots and the electro-active effects as a strain generator. Typically, the strain is assumed to be proportional to the charge transferred, and the two components are assumed to be independent. We show that there is a significant interaction between the two components for polypyrrole actuators, by observing the dynamic elastic modulus whilst varying the electric potential. The elastic modulus was measured in-situ by applying a high frequency rectangular isotonic stress input and recording the corresponding strain output. Two separate potential control inputs, vs. a reference electrode, were used. In the first experiment, a triangular voltage signal with variable frequency was applied to the PPy helix tube actuator and in the second experiment; a step voltage signal was applied to the actuator. The value of total real modulus was calculated during both experiments to evaluate the effect of actuation on the mechanical properties of PPy actuator. The performance of the mentioned method was confirmed by comparing its results to that of a sinusoidal stress input during a temperature ramp through the glass transition of polyethylene terephthalate (PET). We show that polypyrrole actuators show a complex change in stiffness with contractile state, which mimic skeletal muscle [1].