Reversible self-assembly of patchy particles into monodisperse icosahedral clusters

We systematically study the design of simple patchy sphere models that reversibly self-assemble into monodisperse icosahedral clusters. We find that the optimal patch width is a compromise between structural specificity (the patches must be narrow enough to energetically select the desired clusters) and kinetic accessibility (they must be sufficiently wide to avoid kinetic traps). Similarly, for good yields the temperature must be low enough for the clusters to be thermodynamically stable, but the clusters must also have enough thermal energy to allow incorrectly formed bonds to be broken. Ordered clusters can form through a number of different dynamic pathways, including direct nucleation and indirect pathways involving large disordered intermediates. The latter pathway is related to a reentrant liquid-to-gas transition that occurs for intermediate patch widths upon lowering the temperature. We also find that the assembly process is robust to inaccurate patch placement up to a certain threshold, and that it is possible to replace the five discrete patches with a single ring patch with no significant loss in yield.Comment: 12 pages, 12 figure

Epistasis and the evolution of antimicrobial resistance

The fitness effects of a mutation can depend, sometimes dramatically, on genetic background; this phenomenon is often referred to as "epistasis." Epistasis can have important practical consequences in the context of antimicrobial resistance (A

Unknown Risk on the Farm: Does Agricultural Use of Ionophores Contribute to the Burden of Antimicrobial Resistance?

Ionophores are the second most widely used class of antibiotic in agriculture, with over 4 million kilograms sold in the United States in 2016. Because ionophores are not used in humans, it is widely assumed that their agricultural use will not impact human health. Consequently, these drugs have not been subject to the same regulations as medically important antibiotics. Here, I argue that the current evidence base is insufficient to conclude that ionophores do not contribute to human relevant antimicrobial resistance. It is unclear whether ionophore resistance can result in cross-resistance to medically important antibiotics. Moreover, recent evidence suggests that ionophore use may coselect for resistance to vancomycin in some cases. Systematic investigation of the consequences of agricultural ionophore use for human health is therefore imperative

A spatially shifted beam approach to subwavelength focusing

Although negative-refractive-index metamaterials have successfully achieved subwavelength focusing, image resolution is limited by the presence of losses. In this Letter, a metal transmission screen with subwavelength spaced slots is proposed that focuses the near-field beyond the diffraction limit and furthermore, is easily scaled from microwave frequencies to the optical regime. An analytical model based on the superposition of shifted beam patterns is developed that agrees very well with full-wave simulations and is corroborated by experimental results at microwave frequencies.Comment: 5 pages, 7 figures. Content updated following reviewer comments to match final published pape

An sRNA Screen for Reversal of Quinolone Resistance in Escherichia coli

In light of the rising prevalence of antimicrobial resistance (AMR) and the slow pace of new antimicrobial development, there has been increasing interest in the development of adjuvants that improve or restore the effectiveness of existing drugs. Here, we use a novel small RNA (sRNA) screening approach to identify genes whose knockdown increases ciprofloxacin (CIP) sensitivity in a resistant strain of Escherichia coli 5000 sRNA constructs were initially screened on a gyrA S83L background, ultimately leading to 30 validated genes whose disruption reduces CIP resistance. This set includes genes involved in DNA replication, repair, recombination, efflux, and other regulatory systems. Our findings increase understanding of the functional interactions of DNA Gyrase, and may aid in the development of new therapeutic approaches for combating AMR

Spectral properties of Schr\"{o}dinger-type operators and large-time behavior of the solutions to the corresponding wave equation

Let $L$ be a linear, closed, densely defined in a Hilbert space operator, not necessarily selfadjoint. Consider the corresponding wave equations &(1) \quad \ddot{w}+ Lw=0, \quad w(0)=0,\quad \dot{w}(0)=f, \quad \dot{w}=\frac{dw}{dt}, \quad f \in H. &(2) \quad \ddot{u}+Lu=f e^{-ikt}, \quad u(0)=0, \quad \dot{u}(0)=0, where $k>0$ is a constant. Necessary and sufficient conditions are given for the operator $L$ not to have eigenvalues in the half-plane Re$z<0$ and not to have a positive eigenvalue at a given point $k_d^2 >0$. These conditions are given in terms of the large-time behavior of the solutions to problem (1) for generic $f$. Sufficient conditions are given for the validity of a version of the limiting amplitude principle for the operator $L$. A relation between the limiting amplitude principle and the limiting absorption principle is established

Measuring activities of daily living in stroke patients with motion machine learning algorithms: A pilot study

Measuring activities of daily living (ADLs) using wearable technologies may offer higher precision and granularity than the current clinical assessments for patients after stroke. This study aimed to develop and determine the accuracy of detecting different ADLs using machine-learning (ML) algorithms and wearable sensors. Eleven post-stroke patients participated in this pilot study at an ADL Simulation Lab across two study visits. We collected blocks of repeated activity ( atomic activity) performance data to train our ML algorithms during one visit. We evaluated our ML algorithms using independent semi-naturalistic activity data collected at a separate session. We tested Decision Tree, Random Forest, Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost) for model development. XGBoost was the best classification model. We achieved 82% accuracy based on ten ADL tasks. With a model including seven tasks, accuracy improved to 90%. ADL tasks included chopping food, vacuuming, sweeping, spreading jam or butter, folding laundry, eating, brushing teeth, taking off/putting on a shirt, wiping a cupboard, and buttoning a shirt. Results provide preliminary evidence that ADL functioning can be predicted with adequate accuracy using wearable sensors and ML. The use of external validation (independent training and testing data sets) and semi-naturalistic testing data is a major strength of the study and a step closer to the long-term goal of ADL monitoring in real-world settings. Further investigation is needed to improve the ADL prediction accuracy, increase the number of tasks monitored, and test the model outside of a laboratory setting

A mobile phone text messaging intervention to manage fatigue for people with multiple sclerosis, spinal cord injury, and stroke: Development and usability testing

BACKGROUND: Fatigue significantly affects daily functioning in persons with disabilities. Fatigue management can be challenging, and the information provided during routine physician visits to manage fatigue can be overwhelming. One way to address fatigue is to increase knowledge, skills, and confidence for self-management (ie, patient activation). Self-management programs have shown promising effects in targeting fatigue in persons with disabilities. However, satisfaction with self-management programs is low for persons with disabilities, and tailoring interventions to personalized needs has been recommended. SMS text messaging is increasingly being used to implement health behavior change interventions in a person\u27s natural environment. Little has been done to link mobile health approaches with patient activation and self-management to address fatigue in persons with disabilities. OBJECTIVE: This study aimed to develop and test a mobile phone-based fatigue self-management SMS text messaging intervention targeting patient activation in 3 groups of persons with disabilities: persons with multiple sclerosis, persons who had a stroke, and persons with a spinal cord injury. METHODS: We used evidence-based resources and input from a consumer advisory board (CAB; composed of 2 participants from each of the 3 disability groups) and a neurologist to develop the intervention. The study was conducted using a 4-step process: development of the initial SMS text messaging library and categorization of the content into 9 content areas, review and modification of the SMS text messages by the neurologist and CAB, integration of the content library into a digital platform, and utility testing by CAB members. RESULTS: A total of 6 CAB participants rated SMS text messages covering 9 domain areas of fatigue self-management with good clarity (mean ratings=3.5-5.0 out of 5) and relevance (mean ratings=3.2-5.0 out of 5). Overall, SMS text messaging content was reported by CAB participants as helpful, clear, and well suited for a mobile health intervention. The CAB reached consensus on the time of day that SMS text messages should be sent (morning) and their frequency (once per day). This feedback led the research team to narrow down the program to deliver 48 SMS text messages, 1 per day, Monday through Thursday only, a total of 4 SMS text messages per week, over a 12-week period. The final set of SMS text messages was programmed into a digital platform with a predefined delivery schedule. The usability of the intervention was high, with 55 (83%) out of 66 responses endorsing the highest rating. CONCLUSIONS: This study demonstrates a step-by-step process for developing a fatigue self-management SMS text messaging intervention for persons with disabilities. For this population, whose access to health services is often limited, this intervention provides an alternative delivery model to increase access to fatigue information and deliver content that aligns with the person\u27s needs

Use of ultra-low dose computed tomography versus abdominal plain film for assessment of stone-free rates after shock-wave lithotripsy: implications on emergency room visits, surgical procedures, and cost-effectiveness

The aims of this investigation were: (1) to compare residual stone-fragment (RSF) detection rates of ultra-low dose computed tomography (ULD-CT) and abdominal plain film (KUB) in urolithiasis patients undergoing shock-wave lithotripsy (SWL), and (2) to evaluate the downstream sequelae of utilizing these two disparate imaging pathways of differing diagnostic fidelity. A retrospective chart-review of patients undergoing SWL at two high-volume surgical centers was undertaken (2013-2016). RSF diagnostic rates of ULD-CT and KUB were assessed, and the impact of imaging modality used on subsequent emergency room (ER) visits, unplanned procedures, and cost-effectiveness was investigated. Adjusted analyses examined association between imaging modality used and outcomes, and Markov decision-tree analysis was performed to identify a cost advantageous scenario for ULD-CT over KUB. Of 417 patients studied, 57 (13.7%) underwent ULD-CT while the remaining 360 underwent KUB. The RSF rates were 36.8% and 22.8% in the ULD-CT and KUB groups, respectively (p = 0.019). A 5.6% and 18% of the patients deemed stone-free on ULD-CT and KUB, respectively, returned to the ER (p = 0.040). Similarly, 2.8% and 15.1% needed an unplanned surgery (p = 0.027). These findings were confirmed on multivariable analyses, Odds ratios CT-ULD versus KUB: 0.19 and 0.10, respectively, p \u3c 0.05. With regards to cost-effectiveness, at low ULD-CT charges, the ULD-CT follow-up pathway was economically more favorable, but with increasing ULD-CT charges, the KUB follow-up pathway superseded. ULD-CT seems to provide a more \u27true\u27 estimate of stone-free status, and in consequence mitigates unwanted emergency and operating room visits by reducing untimely stent removals and false patient reassurances. Further, at low ULD-CT costs, it may also be economically more favorable

The fitness costs of antibiotic resistance mutations

Antibiotic resistance is increasing in pathogenic microbial populations and is thus a major threat to public health. The fate of a resistance mutation in pathogen populations is determined in part by its fitness. Mutations that suffer little or no fitness cost are more likely to persist in the absence of antibiotic treatment. In this review, we performed a meta-analysis to investigate the fitness costs associated with single mutational events that confer resistance. Generally, these mutations were costly, although several drug classes and species of bacteria on average did not show a cost. Further investigations into the rate and fitness values of compensatory mutations that alleviate the costs of resistance will help us to better understand both the emergence and management of antibiotic resistance in clinical settings