A Network Model Approach to International Aid.

Decisions made by international aid donors regarding the allocation of their aid budgets to recipients can be mathematically modelled using network theory. The many countries and multilateral organisations providing developmental aid, mostly to developing countries, have numerous competing or conflicting interests, biases and motivations, often obscured by a lack of transparency and confused messaging. Using network theory, combined with other mathematical methods, these inter-connecting and inter-dependent variables are identified, revealing the complicated properties and dynamics of the international aid system. Statistical techniques are applied to the vast amount of available, open data to first understand the complexities and then identify the key variables, focusing principally on bilateral aid flows. These results are used to create a weighted network model which is subsequently adapted for use by a hypothetical aid recipient. By incorporating modern portfolio theory into this weighted network model and taking advantage of a donor's reasons for allocating their aid budgets to that recipient, a simulation is carried out treating the problem as an optimal investment portfolio of aid determinant 'assets' which illustrates how a recipient can maximise their aid receipts. Suggestions are also made for further uses and adaptations of this weighted network model.

The Impact of the Metal Interface on the Stability and Quality of a Therapeutic Fusion Protein.

Subvisible particle formation, which occurs after the sterile filtration step of the fill/finish process, is a challenge that may occur during the development of biotherapeutics with complex molecular structures. Here, we show that a stainless steel pump head from a rotary piston pump produces more protein aggregates, past the limit of the acceptable quality range for subvisible particle counts, in comparison to a ceramic pump head. The quartz crystal microbalance was used to quantify the primary layer, proteins irreversibly adsorbed at the solid-liquid interface, and the secondary diffuse gel-like layer interacting on top of the primary layer. The results showed that the mass of protein irreversibly adsorbed onto stainless steel sensors is greater than on an aluminum oxide surface (ceramic pump mimic). This suggests that the amount of adsorbed protein plays a role in surface-induced protein aggregation at the solid-liquid interface.

Self-Directed Learning among Internal Medicine Residents in the Information Age.

OBJECTIVES: The revolution in information technology and a rapidly expanding evidence base are changing residency training. Understanding the habits and preferences of trainees' self-directed learning (SDL) has never been more important. Our goal was to provide a contemporary description of residents' SDL practices. METHODS: Internal medicine residents at four university-affiliated programs were surveyed in Spring 2017. Residents estimated the number of hours in their typical week spent in SDL on service and after hours when on inpatient and noninpatient rotations, how often they used specific educational resources for SDL, and the percentage of time that they used four different modes to access resources. RESULTS: Of 384 residents, a total of 254 (66%) responded. Residents spent more total hours in SDL on noninpatient services (median 11, interquartile range 8-17) than on inpatient services (median 7, interquartile range 4-10) and the same median number of hours in SDL on clinical duty as off hours for both inpatient (median 3 hours) and noninpatient (median 5 hours) rotations. Nearly all of the respondents (99%) reported using online point-of-care resources for SDL at least once per week. Most (77%) never used printed textbooks. Desktop/laptop was the most commonly used (47% of the time) medium to access resources. CONCLUSIONS: Although the resident learning environment and resource use are changing, residents engage in as much or more time in SDL as in previous studies, with a large proportion occurring during clinical service. Understanding residents' current SDL habits will better prepare educators to support and guide our trainees.

19F Dark-State Exchange Saturation Transfer NMR Reveals Reversible Formation of Protein-Specific Large Clusters in High-Concentration Protein Mixtures.

Proteins frequently exist as high-concentration mixtures, both in biological environments and increasingly in biopharmaceutical co-formulations. Such crowded conditions promote protein-protein interactions, potentially leading to formation of protein clusters, aggregation, and phase separation. Characterizing these interactions and processes in situ in high-concentration mixtures is challenging due to the complexity and heterogeneity of such systems. Here we demonstrate the application of the dark-state exchange saturation transfer (DEST) NMR technique to a mixture of two differentially 19F-labeled 145 kDa monoclonal antibodies (mAbs) to assess reversible temperature-dependent formation of small and large protein-specific clusters at concentrations up to 400 mg/mL. 19F DEST allowed quantitative protein-specific characterization of the cluster populations and sizes for both mAbs in the mixture under a range of conditions. Additives such as arginine glutamate and NaCl also had protein-specific effects on the dark-state populations and cluster characteristics. Notably, both mAbs appear to largely exist as separate self-associated clusters, which mechanistically respond differently to changes in solution conditions. We show that for mixtures of differentially 19F-labeled proteins DEST NMR can characterize clustering in a protein-specific manner, offering unique tracking of clustering pathways and a means to understand and control them.

Interfacial Adsorption of a Monoclonal Antibody and Its Fab and Fc Fragments at the Oil/Water Interface.

The physical stability of a monoclonal antibody (mAb) solution for injection in a prefilled syringe may in part depend on its behavior at the silicone oil/water interface. Here, the adsorption of a mAb (termed COE-3) and its fragment antigen-binding (Fab) and crystallizable (Fc) at the oil/water interface was measured using neutron reflection. A 1.4 ± 0.1 µm hexadecane oil film was formed on a sapphire block by a spin-freeze-thaw process, retaining its integrity upon contact with the protein solutions. Measurements revealed that adsorbed COE-3 and its Fab and Fc fragments retained their globular structure, forming layers that did not penetrate substantially into the oil phase. COE-3 and Fc were found to adsorb flat-on to the interface, with denser 45 and 42 Å inner layers, respectively, in contact with the oil and a more diffuse 17-21 Å outer layer caused by fragments adsorbing in a tilted manner. In contrast, Fab fragments formed a uniform 60 Å monolayer. Monolayers were formed under all conditions studied (10-200 ppm, using three isotopic contrasts), although changes in packing density across the COE-3 and Fc layers were observed. COE-3 had a higher affinity to the interface than either of its constituent fragments, while Fab had a lower interfacial affinity consistent with its higher net surface charge. This study extends the application of high-resolution neutron reflection measurements to the study of protein adsorption at the oil/water interface using an experimental setup mimicking the protein drug product in a siliconized prefilled syringe.

Application of Magnetic Resonance to Assess Lyophilized Drug Product Reconstitution.

PURPOSE: Dynamic in-situ proton (1H) magnetic resonance imaging (MRI) and 1H T2-relaxometry experiments are described in an attempt to: (i) understand the physical processes, that occur during the reconstitution of lyophilized bovine serum albumin (BSA) and monoclonal antibody (mAb) proteins; and (ii) objectify the reconstitution time. METHODS: Rapid two-dimensional 1H MRI and diffusion weighted MRI were used to study the temporal changes in solids dissolution and characterise water mass transport characteristics. One-shot T2 relaxation time measurements were also acquired in an attempt to quantify the reconstitution time. Both MRI data and T2-relaxation data were compared to standard visual observations currently adopted by industry. The 1H images were further referenced to MRI calibration data to give quantitative values of protein concentration and, percentage of remaining undissolved solids. RESULTS: An algorithmic analysis of the 1H T2-relaxation data shows it is possible to classify the reconstitution event into three regimes (undissolved, transitional and dissolved). Moreover, a combined analysis of the 2D 1H MRI and 1H T2-relaxation data gives a unique time point that characterises the onset of a reconstituted protein solution within well-defined error bars. These values compared favourably with those from visual observations. Diffusion weighted MRI showed that low concentration BSA and mAb samples showed distinct liquid-liquid phase separation attributed to two liquid layers with significant density differences. CONCLUSIONS: T2 relaxation time distributions (whose interpretation is validated from the 2D 1H MR images) provides a quick and effective framework to build objective, quantitative descriptors of the reconstitution process that facilitate the interpretation of subjective visual observations currently adopted as the standard practice industry.

Multi-Scale Peak and Trough Detection Optimised for Periodic and Quasi-Periodic Neuroscience Data.

OBJECTIVES: The reliable detection of peaks and troughs in physiological signals is essential to many investigative techniques in medicine and computational biology. Analysis of the intracranial pressure (ICP) waveform is a particular challenge due to multi-scale features, a changing morphology over time and signal-to-noise limitations. Here we present an efficient peak and trough detection algorithm that extends the scalogram approach of Scholkmann et al., and results in greatly improved algorithm runtime performance. MATERIALS AND METHODS: Our improved algorithm (modified Scholkmann) was developed and analysed in MATLAB R2015b. Synthesised waveforms (periodic, quasi-periodic and chirp sinusoids) were degraded with white Gaussian noise to achieve signal-to-noise ratios down to 5 dB and were used to compare the performance of the original Scholkmann and modified Scholkmann algorithms. RESULTS: The modified Scholkmann algorithm has false-positive (0%) and false-negative (0%) detection rates identical to the original Scholkmann when applied to our test suite. Actual compute time for a 200-run Monte Carlo simulation over a multicomponent noisy test signal was 40.96 ± 0.020 s (mean ± 95%CI) for the original Scholkmann and 1.81 ± 0.003 s (mean ± 95%CI) for the modified Scholkmann, demonstrating the expected improvement in runtime complexity from [Formula: see text] to [Formula: see text]. CONCLUSIONS: The accurate interpretation of waveform data to identify peaks and troughs is crucial in signal parameterisation, feature extraction and waveform identification tasks. Modification of a standard scalogram technique has produced a robust algorithm with linear computational complexity that is particularly suited to the challenges presented by large, noisy physiological datasets. The algorithm is optimised through a single parameter and can identify sub-waveform features with minimal additional overhead, and is easily adapted to run in real time on commodity hardware.

Statistical Signal Properties of the Pressure-Reactivity Index (PRx).

OBJECTIVES: The pressure-reactivity index (PRx) is defined in terms of the moving correlation coefficient between intracranial pressure (ICP) and mean arterial pressure (MAP) and is a measure of cerebral autoregulation ability. Plots of PRx against cerebral perfusion pressure (CPP) show a U-shaped behaviour: the minimum reflecting optimal cerebral autoregulation (CPPopt). However U-shaped behaviour may also occur by chance. To date there has been no evaluation of the statistical properties of these signals. MATERIALS AND METHODS: We simulated PRx/CPP distributions using synthetic ICP and MAP signals from Gaussian noise with known cross-correlation and calculated the statistical distribution of extrema in the PRx/CPP relationship. RESULTS: The calculation of PRx on random data is statistically biased to show a U-shaped behaviour when the signals are positively cross-correlated (equivalent to PRx > 0). For PRx < 0, the bias is towards an inverse U-shaped behaviour. We demonstrate that this bias is eliminated by Fisher transforming the PRx data before CPPopt analysis. CONCLUSIONS: Cross-correlated signals are biased to show a U-shaped distribution. A CPPopt-like behaviour will be observed more often than not even from random ICP and MAP signals that do not exhibit autoregulation, unless PRx is Fisher transformed. Care must be taken in interpreting CPPopt in terms of physiology calculated from untransformed data.

Empirical Correction for Differences in Chemical Exchange Rates in Hydrogen Exchange-Mass Spectrometry Measurements.

A barrier to the use of hydrogen exchange-mass spectrometry (HX-MS) in many contexts, especially analytical characterization of various protein therapeutic candidates, is that differences in temperature, pH, ionic strength, buffering agent, or other additives can alter chemical exchange rates, making HX data gathered under differing solution conditions difficult to compare. Here, we present data demonstrating that HX chemical exchange rates can be substantially altered not only by the well-established variables of temperature and pH but also by additives including arginine, guanidine, methionine, and thiocyanate. To compensate for these additive effects, we have developed an empirical method to correct the hydrogen-exchange data for these differences. First, differences in chemical exchange rates are measured by use of an unstructured reporter peptide, YPI. An empirical chemical exchange correction factor, determined by use of the HX data from the reporter peptide, is then applied to the HX measurements obtained from a protein of interest under different solution conditions. We demonstrate that the correction is experimentally sound through simulation and in a proof-of-concept experiment using unstructured peptides under slow-exchange conditions (pD 4.5 at ambient temperature). To illustrate its utility, we applied the correction to HX-MS excipient screening data collected for a pharmaceutically relevant IgG4 mAb being characterized to determine the effects of different formulations on backbone dynamics.

Hepatitis C Cascade of Care Among Pregnant Women on Opioid Agonist Pharmacotherapy Attending a Comprehensive Prenatal Program.

Background Given the large increases in opioid use among pregnant women and associations with hepatitis C virus (HCV) infection, screening pregnant women who are on (opioid agonist) pharmacotherapy for HCV infection has potential to inform medical care for these mothers as well as their newborns. We investigated the HCV testing cascade among pregnant women on pharmacotherapy in order to describe exposure and infection rates and to identify opportunities that would improve care. Methods Secondary analyses of laboratory results were performed for HCV testing, including anti-HCV, viremia (RNA) and genotype. Information was abstracted from the medical records of women who were followed at a comprehensive prenatal care clinic for women with substance use disorders at the University of New Mexico. Results The sample included 190 pregnant women, of whom 188 were on pharmacotherapy (43.7% on buprenorphine and 55.3% on methadone); the remaining two had tested positive for heroin or prescription opioids. A total of 178 (93.7%) were tested for anti-HCV, 94 (98.9%) of whom were tested for RNA, and 41 (57.7%) were genotyped. Prevalence of exposure to HCV by anti-HCV results was 53.3%, and 37.3% were positive for HCV RNA indicating chronic infection. Conclusions The high prevalence of exposure and infection with HCV in pregnant women involved in pharmacotherapy for a substance use disorder indicate a need for ongoing surveillance and testing for HCV. Identifying HCV during pregnancy is crucial because this identification would serve to enhance medical care and potentially prevent vertical transmission. Identifying HCV would also facilitate referrals to newly available curative HCV treatments following delivery.

Explaining the non-newtonian character of aggregating monoclonal antibody solutions using small-angle neutron scattering.

A monoclonal antibody solution displays an increase in low shear rate viscosity upon aggregation after prolonged incubation at 40°C. The morphology and interactions leading to the formation of the aggregates responsible for this non-Newtonian character are resolved using small-angle neutron scattering. Our data show a weak repulsive barrier before proteins aggregate reversibly, unless a favorable contact with high binding energy occurs. Two types of aggregates were identified after incubation at 40°C: oligomers with radius of gyration ∼10 nm and fractal submicrometer particles formed by a slow reaction-limited aggregation process, consistent with monomers colliding many times before finding a favorable strong interaction site. Before incubation, these antibody solutions are Newtonian liquids with no increase in low shear rate viscosity and no upturn in scattering at low wavevector, whereas aggregated solutions under the same conditions have both of these features. These results demonstrate that fractal submicrometer particles are responsible for the increase in low shear rate viscosity and low wavevector upturn in scattered intensity of aggregated antibody solutions; both are removed from aggregated samples by filtering.

Effects of salts from the Hofmeister series on the conformational stability, aggregation propensity, and local flexibility of an IgG1 monoclonal antibody.

This work examines the effect of three anions from the Hofmeister series (sulfate, chloride, and thiocyanate) on the conformational stability and aggregation rate of an IgG1 monoclonal antibody (mAb) and corresponding changes in the mAb's backbone flexibility (at pH 6 and 25 °C). Compared to a 0.1 M NaCl control, thiocyanate (0.5 M) decreased the melting temperatures (Tm) for three observed conformational transitions within the mAb by 6-9 °C, as measured by differential scanning calorimetry. Thiocyanate also accelerated the rate of monomer loss at 40 °C over 12 months, as monitored by size exclusion chromatography. Backbone flexibility, as measured via H/D exchange mass spectrometry, increased in two segments in the CH2 domain with more subtle changes across several additional regions. Chloride (0.5 M) caused slight increases in the Tm values, small changes in aggregation rate, and minimal yet consistent decreases in flexibility across various domains with larger effects noted within the VL, CH1, and CH3 domains. In contrast, 0.5 M sulfate increased Tm values, had small stabilizing influences on aggregate formation over time, yet substantially increased the flexibility of two specific regions in the CH1 and VL domains. While thiocyanate-induced conformational destabilization of the mAb correlated with increased local flexibility of specific regions in the CH2 domain (especially residues 241-251 in the heavy chain), the stabilizing anion sulfate did not affect these CH2 regions.

Multifractal analysis of hemodynamic behavior: intraoperative instability and its pharmacological manipulation.

BACKGROUND: Physiologic instability is a common clinical problem in the critically ill. Many natural feedback systems are nonlinear, and seemingly random fluctuations may result from the amplification of external perturbations or even arise de novo as a consequence of their underlying dynamics. Characterization of the underlying nonlinear state may be of clinical importance, providing a technique to monitor complex physiology in real-time, guiding patient care and improving outcomes. METHODS: We employ the wavelet modulus maxima technique to characterize the multifractal properties of heart rate and mean arterial pressure physiology retrospectively for four patients during open abdominal aortic aneurysm repair. We calculated point-estimates for the dominant Hölder exponent (hm, hm) and multifractal spectrum width-at-half-height for both heart rate and mean arterial pressure signals. We investigated how these parameters changed with the administration of an intravenous vasoconstrictor and examined how this varied with atropine pretreatment. RESULTS: Hypotensive patients showed lower values of hm, consistent with a more highly fluctuating and complex behavior. Treatment with a vasoconstrictor led to a transient increase in hm, revealing the appearance of longer-range correlations, but did not impact hm. On the other hand, prior treatment with atropine had no effect on hm behavior but did tend to increase hm. CONCLUSIONS: Hypotension leads to a reduction in dominant Hölder exponents for mean arterial pressure, demonstrating an increasing signal complexity consistent with the activation of important homeokinetic processes. Conversely, pharmacological interventions may also alter the underlying dynamics. Pharmacological restoration of homeostasis leads to system decomplexification, suggesting that homeokinetic mechanisms are derecruited as homeostasis is restored.

A Delphi consensus statement for digital surgery.

The use of digital technology is increasing rapidly across surgical specialities, yet there is no consensus for the term 'digital surgery'. This is critical as digital health technologies present technical, governance, and legal challenges which are unique to the surgeon and surgical patient. We aim to define the term digital surgery and the ethical issues surrounding its clinical application, and to identify barriers and research goals for future practice. 38 international experts, across the fields of surgery, AI, industry, law, ethics and policy, participated in a four-round Delphi exercise. Issues were generated by an expert panel and public panel through a scoping questionnaire around key themes identified from the literature and voted upon in two subsequent questionnaire rounds. Consensus was defined if >70% of the panel deemed the statement important and <30% unimportant. A final online meeting was held to discuss consensus statements. The definition of digital surgery as the use of technology for the enhancement of preoperative planning, surgical performance, therapeutic support, or training, to improve outcomes and reduce harm achieved 100% consensus agreement. We highlight key ethical issues concerning data, privacy, confidentiality and public trust, consent, law, litigation and liability, and commercial partnerships within digital surgery and identify barriers and research goals for future practice. Developers and users of digital surgery must not only have an awareness of the ethical issues surrounding digital applications in healthcare, but also the ethical considerations unique to digital surgery. Future research into these issues must involve all digital surgery stakeholders including patients.

Urban population size and road traffic collisions in Europe.

Millions of road traffic collisions take place every year, leading to significant knock-on effects. Many of these traffic collisions take place in urban areas, where traffic levels can be elevated. Yet, little is known about the extent to which urban population size impacts road traffic collision rates. Here, we use urban scaling models to analyse geographic and road traffic collision data from over 300 European urban areas in order to study this issue. Our results show that there is no significant change in the number of road traffic collisions per person for urban areas of different sizes. However, we find individual urban locations with traffic collision rates which are remarkably high. These findings have the potential to inform policies for the allocation of resources to prevent road traffic collisions across the different cities.

The effect of dragon-kings on the estimation of scaling law parameters.

Scaling laws are used to model how different quantifiable properties of cities, such as the number of road traffic accidents or average house prices, vary as a function of city population size, with parameters estimated from data. Arcaute et al. raised the issue of whether specific cities with extremely large population sizes, known as dragon-kings, should be considered separately from other smaller cities when estimating the scaling law parameters since the two types of cities tend to display different behaviour. Through the analysis of randomly generated samples, we find that the inclusion of dragon-kings in the scaling analysis does not affect the estimated values for the parameters but only provided that all the data points satisfy the same scaling law. We also analyse randomly generated samples where data corresponding to a particular city deviates from the scaling law followed by the rest of the cities. We then show that deviations corresponding to dragon-king cities have the most significant effect on the estimated values of the scaling parameters. The extent of this effect also depends on which estimation procedure is used. Our results have important implications on the suitability of scaling laws as a model for urban systems.

The One Note System: Implementation and Initial Perceptions of Student Documentation in the Electronic Health Records Under the New Centers for Medicare and Medicaid Services Guidelines.

Introduction Medical students have been documenting notes in the electronic health records (EHR) for many years but often wrote separate notes from housestaff and faculty because licensed providers (LPs) could not bill the Centers for Medicare and Medicaid Services (CMS) for Evaluation and Management (E/M) services. However, in 2018, CMS updated its policy to allow LPs to simply verify any component of an E/M service under appropriate supervision, allowing LPs to bill a full medical student note. Methods At Virginia Commonwealth University Health Systems (VCUHS), a task force was formed to develop and pilot the One Note System (ONS), a system that incorporates the new CMS guidelines for certain note types. In June 2019, or 10 months after implementation of the ONS, the authors developed and distributed a survey that explored perceptions regarding the ONS among medical students, housestaff (residents and fellows), and faculty. Results The results showed that most participants were aware of the ONS and preferred email as the form of training. Overall, the ONS had a positive impact on faculty and housestaff workflow, improved self-reported faculty wellbeing, and increased meaning in student work. Only a minority reported barriers to implementing the ONS. Conclusions The One Note System was successfully implemented at VCUHS and positively received. Other outcomes to measure include impact of the ONS on student and trainee education, compliance and billing, quality and quantity of documentation, and faculty and housestaff burnout rates.

A continuous binning for discrete, sparse and concentrated observations.

Discrete observations from data which are obtained from sparse, and yet concentrated events are often observed (e.g. road accidents or murders). Traditional methods to compute summary statistics often include placing the data in discrete bins but for this type of data this approach often results in large numbers of empty bins for which no function or summary statistic can be computed. Here, a method for dealing with sparse and concentrated observations is constructed, based on a sequence of non-overlapping bins of varying size, which gives a continuous interpolation of data for computing summary statistics of the values for the data, such as the mean. The method presented here overcomes the problem which sparsity and concentration present when computing functions to represent the data. Implementation of the method presented here is facilitated via open access to the code. •A new method for computing functions over sparse and concentrated data is constructed.•The method allows straightforward functions to be computed over partitions of the data, such as the mean, but also more complicated functions, such as coefficients, ratios, correlations, regressions and others.