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In 1978, a Cancer Research article by Dougherty and colleagues reported the first large-scale clinical trial of photodynamic therapy (PDT) for treatment of 113 cutaneous or subcutaneous lesions associated with ten different kinds of malignancies. In classic applications, PDT depends on excitation of a tissue-localized photosensitizer with wavelengths of visible light to damage malignant or otherwise diseased tissues. Thus, in this landmark article, photosensitizer (hematoporphyrin derivative) dose, drug–light interval, and fractionation scheme were evaluated for their therapeutic efficacy and normal tissue damage. From their observations came early evidence of the mechanisms of PDT's antitumor action, and in the decades since this work, our knowledge of these mechanisms has grown to build an understanding of the multifaceted nature of PDT. These facets are comprised of multiple cell death pathways, together with antivascular and immune stimulatory actions that constitute a PDT reaction. Mechanism-informed PDT protocols support the contribution of PDT to multimodality treatment approaches. Moreover, guided by an understanding of its mechanisms, PDT can be applied to clinical needs in fields beyond oncology. Undoubtedly, there still remains more to learn; new modes of cell death continue to be elucidated with relevance to PDT, and factors that drive PDT innate and adaptive immune responses are not yet fully understood. As research continues to forge a path forward for PDT in the clinic, direction is provided by anchoring new applications in mechanistically grounded protocol design, as was first exemplified in the landmark work conducted by Dougherty and colleagues. See related article by Dougherty and colleagues, Cancer Res 1978;38:2628–35

Benchmarks for protective immunity from infection or severe disease after SARS-CoV-2 vaccination are still being defined. Here, we characterized virus neutralizing and ELISA antibody levels, cellular immune responses, and viral variants in 4 separate groups: healthy controls (HCs) weeks (early) or months (late) following vaccination in comparison with symptomatic patients with SARS-CoV-2 after partial or full mRNA vaccination. During the period of the study, most symptomatic breakthrough infections were caused by the SARS-CoV-2 Alpha variant. Neutralizing antibody levels in the HCs were sustained over time against the vaccine parent virus but decreased against the Alpha variant, whereas IgG titers and T cell responses against the parent virus and Alpha variant declined over time. Both partially and fully vaccinated patients with symptomatic infections had lower virus neutralizing antibody levels against the parent virus than the HCs, similar IgG antibody titers, and similar virus-specific T cell responses measured by IFN-γ. Compared with HCs, neutralization activity against the Alpha variant was lower in the partially vaccinated infected patients and tended to be lower in the fully vaccinated infected patients. In this cohort of breakthrough infections, parent virus neutralization was the superior predictor of breakthrough infections with the Alpha variant of SARS-CoV-2.

In this study, NMR and molecular dynamics simulations were employed to study IgG1 F

This study investigates a dispatching scheme of megawatt-scale solar PV power for a one-hour dispatching period for an entire day utilizing an isolated multiport converter configuration and battery energy storage system. A multilevel triple active bridge (TAB) dc-dc converter has been proposed where a neutral-point-clamped (NPC) H-bridge is employed in the high-voltage side, and the conventional two-level full-bridge is configured in the low-voltage side across the high-frequency transformer. The power losses between the proposed TAB-NPC converter and conventional TAB converter are compared to identify the superior multiport converter topology for this application. The converter loss analysis is conducted using the parameter values of the switching devices in the MATLAB/SIMULINK environment, and the proposed TAB-NPC converter is found to exhibit better performance than the conventional TAB for megawatt-scale grid-connected PV arrays. Furthermore, the curve fitting and Particle Swarm Optimization techniques are implemented to seek the optimum value of depth of discharge for the battery energy storage system taking into account both the cycling and calendar expenses. A fuzzy inference system as a function of the battery state of charge is also developed to accurately estimate the grid reference power for each one-hour dispatching period, which helps to develop a cost-effective energy storage system for hourly dispatching PV power scheme.

Distributed generation sources (DGs) are widely considered as important sources of power generation in distribution systems during the last few decades. Despite the substantial benefits of DGs, inc...

In this study, we evaluate the use of riboflavin-mediated collagen photocrosslinking as an experimental tool to modulate extracellular matrix (ECM) mechanical properties in 3D in vitro tumor models. Using this approach in conjunction with 3D pancreatic tumor spheroid transplants, we show that the extent of matrix photocrosslinking in reconstituted hydrogels with fixed protein concentration scales inversely with the extent of invasive progression achieved by cells infiltrating into the surrounding ECM from primary transplanted spheroids. Using cross-linking to manipulate the extent of invasion into ECM in conjunction with imaging-based treatment assessment, we further leverage this approach as a means for assaying differential therapeutic response in primary nodule and ECM-invading populations and compare response to verteporfin-based photodynamic therapy (PDT) and oxaliplatin chemotherapy. Treatment response data shows that invading cell populations (which also exhibit markers of increased EMT) are highly chemoresistant yet have significantly increased sensitivity to PDT relative to the primary nodule. In contrast, the oxaliplatin treatment achieves greater growth inhibition of the primary nodule. These findings may be significant in themselves, while the methodology developed here could have a broader range of applications in developing strategies to target invasive disease and/or mecahanobiological determinants of therapeutic response in solid tumors.

Despite increasing interest in using virtual reality (VR) for tourism marketing, limited empirical evidence exists regarding consumers’ psychological response toward VR. The current study investiga...

The present study explores the relation between social interest and well-being, as measured by perceived group membership and volunteering. Three hypotheses predicted that: (a) group membership and volunteering would be positively correlated with well-being, (b) this correlation would differ by both sex, and (c) age. We analysed Wave-6 of the World Values Survey (2010-2014), consisting of 89 564 respondents from 60 nations distributed world-wide. Group membership and volunteering were correlated with measures of well-being (as measured by both perceived happiness and perceived health); notable sex differences are outlined. Finally, age acted as a significant moderator wherein the relation between group membership and well-being was stronger among older respondents. Our findings endorse future research of social interest through active measures such as group membership and volunteering. Older populations may benefit significantly from active participation in organizations; suggesting this behavior should be promoted in maintaining a happy and healthy lifestyle later in one's life. Interventions involving social interest based practices could be advantageous for clinical populations in conjunction with other modalities. Keywords: social interest, group membership, volunteering, well-being, sex differences, age differences

Capacitive deionization (CDI) operated under inverted mode involves electronic charging and discharge steps with corresponding ion concentration and desalting coupled with simultaneous energy storage. In this work, an energy recovery system derived from a Cuk dc–dc converter is explored to transfer the energy stored from one inverted capacitive deionization (i-CDI) cell during the electronic discharge step to another during the charge step, decreasing the overall energy requirement for capacitive water desalination. The i-CDI cell, a subset of CDI architecture operated in an inverted mode, is improved by incorporating ion-selective membranes to allow inverted membrane capacitive deionization (i-MCDI), leading to enhanced charge storage achieved with reduced energy input. For example, in comparison to i-CDI that requires ∼12 J g−1 of energy input, the i-MCDI cell requires only 8 J g−1. By incorporating the recovery system, the energy penalty can be reduced to only require ∼8 and 4 J g−1 for i-CDI and i-MCDI cells, respectively. Improvement in energy recovery was shown to be achieved by reducing charge leakage, with the i-MCDI cell showing up to 3 times the leakage resistance of the i-CDI cell.

Multimodal chromatography is a powerful tool which uses multiple modes of interaction, such as charge and hydrophobicity, to purify protein-based therapeutics. In this work, we performed molecular dynamics simulations of a series of multimodal cation-exchange ligands immobilized on a hydrophilic self-assembled monolayer surface at the commercially relevant surface density (1 ligand/nm

Drawing from strategic whiteness and postracism as critical frames, and utilizing critical rhetorical analysis, this manuscript argues that the 2016 Disney animated hit film Zootopia is a postracia...

The coefficient of thermal expansion (CTE) significantly influences the performance of concrete. However, CTE measurements are both time consuming and expensive; therefore, CTE is often predicted from empirical equations based on historical data and concrete composition. In this work we demonstrate the application of linear regression and random forest machine learning methods to predict CTE and other properties from a database of Wisconsin concrete mixes. The random forest model accuracy, as assessed by cross-validation, is found to be significantly better than the American Association of State Highway and Transportation Officials (AASHTO) recommended prediction methods for CTE, denoted as level-2 and level-3.

This study demonstrates how multimodal cation exchange chromatographic systems can be successfully employed to purify an IgG4 monomer from three distinct aggregate species. In addition, the steric mass action model is shown to be capable of facilitating the development of effective bind/elute processes for aggregate removal. A variety of multimodal anion and cation exchange resin materials and conditions were initially screened for both selectivity and recovery of the product. While the multimodal anion exchangers exhibited significant recovery issues, the Capto MMC and MMC ImpRes resin systems were observed to have good recoveries and some selectivity for these challenging separations under linear gradient conditions. Mechanistic modeling was then explored as a means to expedite the development of a bind/elute process for decreasing the aggregate content of this challenging monoclonal antibody mixture. The retention behavior of the monomer and the higher molecular weight species under different linear gradient conditions were used to estimate the SMA parameters of the proteins on both the Capto MMC and MMC ImpRes systems. A range of simulations were then carried out to determine an efficient bind/elute process for the removal of higher molecular weight species while also obtaining a good yield of the monomer in both resin systems. Finally, bind/elute experiments were carried out under the suggested simulation conditions for each resin system and were shown to be in good agreement with the theoretical predictions, with purities and yields of 99% and 78.6% for Capto MMC and 99.3% and 87.9% for Capto MMC ImpRes, respectively. The simple approach described in this paper presents a rapid and useful method for model-based process development of antibody monomer-aggregate separations with multimodal cation exchange chromatography.

The computational cost for the simulation of detailed models of machine-rectifier systems is expensive because of repetitive diodes switching. Average-value models (AVMs) of machine-rectifier systems have been developed that can alleviate the computational burden by neglecting the details of the switching of each individual diode while retaining the average characteristics. This paper proposes an alternative formulation of numerical AVMs of machine-rectifier systems, which makes direct use of the natural dynamic impedance of the rectifier without introducing low-frequency approximations or algebraic loops. By using this formulation, direct interface of the AVM is achieved with inductive circuitry on both the ac and dc sides allowing traditional voltage-in, current-out formulations of the circuitry on these sides to be used with the proposed formulation directly. This numerical AVM formulation is validated against an experimentally validated detailed model and compared with previous AVM formulations. It is demonstrated that the proposed AVM formulation accurately predicts the system's low-frequency behavior during both steady and transient states, including the cases where previous AVM formulations cannot predict accurate results. Both run times and numbers of time steps needed by the proposed AVM formulation are comparable to those of existing AVM formulations and significantly decreased compared with the detailed model.

Multimodal chromatography uses small ligands with multiple modes of interaction, e.g., charged, hydrophobic or hydrogen bonding, to separate proteins from complex mixtures. The mechanism by which multimodal ligands interact with proteins is expected to be affected by ligand conformations, among other factors. Here, we study conformational equilibria of two commercially used multimodal cation exchange ligands, Capto MMC and Nuvia cPrime, in a range of solvents, a Lennard-Jones (LJ) liquid, ethanol, and water, using molecular dynamics (MD) simulations. By mapping ligand conformations onto two key torsion angles, ω and φ, in these solvents and in low and high dielectric media, we quantify the relative importance of intramolecular and solvent-mediated interactions. In a high dielectric medium, Capto MMC preferentially samples three conformations, which are stabilized by a combination of an intramolecular torsion potential (on ω) and LJ interactions. In an LJ liquid, solvent molecules compete with intramolecular interactions while simultaneously providing an osmotic force, stabilizing both closer and farther distances between ligand sites. This has the overall effect of "flattening out" the conformational landscape. Interestingly, in ethanol and water, hydrogen bonding between the amide hydrogen and solvent molecules stabilizes two additional conformations of Capto MMC in which ω takes on less favorable cis-like configurations. MD simulations of ligands in free solution with three therapeutic antibody fragments show that ligand conformational equilibria remain effectively unchanged upon binding to proteins. Although, there is 20-30% dehydration of the overall ligand upon binding, the hydrogen-bonding sites are dehydrated to a much smaller extent, particularly in cis-like configurations. Conformational preferences of Nuvia cPrime are similar to that of Capto MMC, except for the effect of symmetry arising from the absence of an alkyl thiol tail. Characterizing the conformational equilibria of these two ligands in free solution and bound to a protein provides a foundation for developing a mechanistic understanding of protein-multimodal ligand interactions.

Despite the growth in school-based mental health services (SBMHS), rates of mental health help-seeking among adolescents remain low, especially for ethnic minority youth. This study examined factors associated with adolescents’ help-seeking of mental health services among a sample of 369 racially diverse high school students (age M = 15.5 years, SD = 0.72, 81.3% were ethnic minorities). We examined the relationships among mental health literacy for depression, knowledge barriers related to services and providers, perceived stigmatization by others, emotional/behavioral difficulties, and actual help-seeking behavior. Logistic regression results showed that adolescents with higher mental health literacy for depression and more emotional/behavioral difficulties are more likely to report seeking help in general and from providers outside of school specifically, but not for services inside of school alone. Asian-American students were less likely to seek help than Caucasian peers. It is important to promote mental health literacy to encourage help-seeking among high school students.

High penetration of distributed generation (DG) can cause fast voltage changes in distribution systems. Inverter-based DG can be a significant source of reactive power, which brings new opportunities to improve the performance of the distribution system. An integrated control strategy is formulated for the coordinated control of both distribution system equipment and inverter-based DG. The control strategy combines the use of inverter reactive power capability with the operation of voltage regulators in order to improve the expected value of a desired figure of merit (e.g., system losses) while maintaining appropriate system voltage magnitudes, by formulating chance constraints on the voltage magnitudes. The effectiveness of the proposed method is validated using the IEEE 123-node radial distribution system.

IntroductionPatients treated with immunotherapy are divided into two subgroups: (i) long-term survivors (LTS) and (ii) moderate survivors. Nevertheless, clinical trials (RCTs) report only average treatment effects such as hazard rate (HRs). Health economic-models often only input average treatment effects, even though it has been shown that accounting for the LTS subgroup is crucial for accurate projection of long-term survival under immunotherapy. We investigated the incorporation of a statistical mixture cure model (MCM) in a health-economic model for lung cancer as a way to account for LTS while incorporating reported average RCT-based treatment effects.MethodsWe developed a microsimulation model describing disease progression under three treatment lines in advanced lung cancer using Dutch real-world data of chemotherapies treated patients. Here we focus on first-line treatment, for which we used gompertz distribution to simulate time-to-progression. To simulate the impact of immunotherapy, we adjusted base-model assuming MCM for first-line treatment, where the LTS subgroup was not at risk to progress, but instead die from background mortality. The subgroup of moderate survivors on the other hand are at risk to progress with adjusted progression-free HR (PF-HR). We simulated the model with size of LTS (prop_LTS) ranging from 14-34 percent (keynote-001 five-year overall survival [OS], 95% confidence interval) while fixing average RCT PF-HR at 0.5. Model predictions under the different prop_LTS were compared to real-world Dutch OS as well as the long-term RCT five-year OS.ResultsWith respect to observed short-term survival outcomes, model predictions were insensitive to assumptions regarding the size of the LTS subgroup. However, to match the five-year RCT OS rate reported (32%), the prop_LTS had to be equal to 34 percent. Under this latter setting for the prop_LTS, the progression HR in the subgroup of moderate survivors was calibrated to be 1.1.ConclusionsThe use of a mixture cure model improves long-term model-based projections with the implicit assumption that moderate survivors have little or no treatment benefit.

In this article, a systematic workflow was formulated and implemented to understand selectivity differences and preferred binding patches for bispecific monoclonal antibodies (mAbs) and their parental mAbs on three multimodal cation exchange resin systems. This workflow incorporates chromatographic screening of the parent mAbs and their fragments at various pH followed by surface property mapping and protein footprinting using covalent labeling followed by liquid chromatography-mass spectrometry analysis. The chromatography screens on multimodal resins with the intact mAbs indicated enhanced selectivity as compared to single-mode interaction systems. While the bispecific antibody (bsAb) eluted between the two parental mAbs on most of the resins, the retention of the bispecific transitioned from co-eluting with one parental mAb to the other parental mAb on Capto MMC. To investigate the contribution of different domains, mAb fragments were evaluated and the results indicated that the interactions were likely dominated by the Fab domain at higher pH. Protein surface property maps were then employed to hypothesize the potential preferred binding patches in the solvent-exposed regions of the parental Fabs. Finally, protein footprinting was carried out with the parental mAbs and the bsAb in the bound and unbound states at pH 7.5 to identify the preferred binding patches. Results with the intact mAb analysis supported the hypothesis that interactions with the resins were primarily driven by the residues in the Fab fragments and not the Fc. Furthermore, peptide mapping data indicated that the light chain may be playing a more important role in the higher binding of Parent A as compared with Parent B in these resin systems. Finally, results with the bsAb indicated that both halves of the molecule contributed to binding with the resins, albeit with subtle differences as compared to the parental mAbs. The workflow presented in this paper lays the foundation to systematically study the chromatographic selectivity of large multidomain molecules which can provide insights into improved biomanufacturability and expedited downstream bioprocess development.

Nowadays, electric warships are involved in complex missions involving multiple simultaneous operations. In order to ensure mission success, future ships must be designed in a way that optimizes their performance in presence of complex mission loads. The metric operability has played a major role in assessing mission performance. This paper discusses the evolution of this metric from fixed load-based early-stage shipboard electrical system design to the current approaches of using dynamic mission profiles. Results for a notional two-function problem involving multiple missions are shown to demonstrate the current state of operability-based approaches for the evaluation of power system performance.

Background Lentiviral vectors (LVVs) hold great promise as delivery tools for gene therapy and chimeric antigen receptor T cell (CAR-T) therapy. Their ability to target difficult to transfect cells and deliver genetic payloads that integrate into the host genome makes them ideal delivery candidates. However, several challenges remain to be addressed before LVVs are more widely used as therapeutics including low viral vector concentrations and the absence of suitable scale-up methods for large-scale production. To address these challenges, we have developed a high throughput microscale HEK293 suspension culture platform that enables rapid screening of conditions for improving LVV productivity. Key results High density culture (40 million cells mL-1 ) of HEK293 suspension cells in commercially available media was achieved in microscale 96-deep well plate platform at liquid volumes of 200 μL. Comparable transfection and LVV production efficiencies were observed at the microscale, in conventional shake flasks and a 1-L bioreactor, indicating that significant scale-down does not affect LVV concentrations and predictivity of scale-up. Optimization of production step allowed for final yields of LVVs to reach 1.5 × 107 TU mL-1 . Conclusions The ability to test a large number of conditions simultaneously with minimal reagent use allows for the rapid optimization of LVV production in HEK293 suspension cells. Therefore, such a system may serve as a valuable tool in early stage process development and can be used as a screening tool to improve LVV concentrations for both batch and perfusion based systems.

Several observational studies suggested that gut microbiome-affecting-medication impairs the effectiveness of immunotherapy in patients with metastatic non-small-cell lung cancer (NSCLC). We postulated that if the effectiveness of immunotherapy is affected by drug-related changes of the microbiome, a stronger association between the use of co-medication and overall survival (OS) will be observed in patients treated with immunotherapy as compared to patients treated with chemotherapy. In a retrospective matched cohort study, immunotherapy patients were matched (1:1) to patients treated with chemotherapy in the pre immunotherapy era. The association between the use of antibiotics, opioids, proton pump inhibitors, metformin and other antidiabetics on OS was assessed with multivariable cox-regression analyses. Interaction tests were applied to investigate whether the association differs between patients treated with immuno- or chemotherapy. A total of 442 patients were studied. The use of antibiotics was associated with worse OS (adjusted Hazard Ratio (aHR) 1.39, p = 0.02) independent of the type of therapy (chemotherapy or immunotherapy). The use of opioids was also associated with worse OS (aHR 1.33, p = 0.01). The other drugs studied showed no association with OS. Interaction term testing showed no effect modification by immuno- or chemotherapy for the association of antibiotics and opioids with OS. The use of antibiotics and opioids is similarly associated with worse outcomes in both chemotherapy and immunotherapy treated NSCLC patients. This suggests that the association is likely to be a consequence of confounding rather than disturbing the composition of the microbiome.

Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Sonderforschungsbereich 1116, University Düsseldorf Background Left ventricular (LV) function is considered of major importance to estimate prognosis of patients with ST-segment elevation myocardial infarction (STEMI) [1]. Although transthoracic echocardiography (TTE) after STEMI is recommended to assess for LV function and identify patients at high risk for rehospitalisation due to heart failure, Cardiovascular Magnetic Resonance (CMR) is still considered the gold standard for an adequate quantification of volumes, function and infarct size (IS) [2]. In addition, unenhanced TTE has been shown to underestimate LV function [3]. It is complicating that parameters such as IS and area-at risk (AAR) are thought to further deteriorate prognosis [4,5]. Purpose To test the hypothesis that cross-modality 2D/3D analyses using TTE, CMR and cineventriculography are comparable for the determination of LV-function in STEMI and that infarct patterns influence the determination of LV-function and volumes across modalities. Methods In a group of 70 patients after STEMI, estimation of LV function and volumes was performed by biplane cineventriculography during acute catheterization, biplane (2D) CMR 28 ± 16 hours (1 day) as well as 2D/3D-CMR and TTE 114 ± 31 hours (5 days) post STEMI. 3D-TTE after STEMI was only performed in a subset of 36 patients respectively. IS and AAR were assessed by T2-weighted and contrast enhanced CMR (1.5T) as percentage of the LV mass. Results Both, 2D- and 3D-, LV ejection fraction (LVEF) were comparable between the single modalities. Stroke volume (SV) and LV end-diastolic volume (LVEDV) were underestimated when comparing 2D- to 3D-CMR and when comparing TTE/cineventriculography to CMR. Correlating IS to the difference of 2D- and 3D-CMR, higher IS/AAR did not alter previous results, except from a fairly increased difference in SV (R = 0.3). For 2D-TTE versus 2D-CMR, higher IS/AAR increased differences in LVEDV (IS & AAR: p Conclusions There is good agreement between LVEF analysis across dimensions (2D and 3D) and different modalities (TTE, cineventriculography and CMR) whereas the comparison of SV and LVEDV is hampered. However, with increasing IS or AAR, LVEF differences between modalities increase and 3D-CMR, if available, or alternatively 3D-TTE should be used for the most accurate estimation of LVEF.

In studies of electron and proton radiotherapy, ultrahigh dose rates of FLASH radiotherapy appear to produce fewer toxicities than standard dose rates while maintaining local tumor control. FLASH-proton radiotherapy (F-PRT) brings the spatial advantages of PRT to FLASH dose rates (>40 Gy/second), making it important to understand if and how F-PRT spares normal tissues while providing antitumor efficacy that is equivalent to standard-proton radiotherapy (S-PRT). Here we studied PRT damage to skin and mesenchymal tissues of muscle and bone and found that F-PRT of the C57BL/6 murine hind leg produced fewer severe toxicities leading to death or requiring euthanasia than S-PRT of the same dose. RNA-seq analyses of murine skin and bone revealed pathways upregulated by S-PRT yet unaltered by F-PRT, such as apoptosis signaling and keratinocyte differentiation in skin, as well as osteoclast differentiation and chondrocyte development in bone. Corroborating these findings, F-PRT reduced skin injury, stem cell depletion, and inflammation, mitigated late effects including lymphedema, and decreased histopathologically detected myofiber atrophy, bone resorption, hair follicle atrophy, and epidermal hyperplasia. F-PRT was equipotent to S-PRT in control of two murine sarcoma models, including at an orthotopic intramuscular site, thereby establishing its relevance to mesenchymal cancers. Finally, S-PRT produced greater increases in TGFβ1 in murine skin and the skin of canines enrolled in a phase I study of F-PRT versus S-PRT. Collectively, these data provide novel insights into F-PRT-mediated tissue sparing and support its ongoing investigation in applications that would benefit from this sparing of skin and mesenchymal tissues. Significance: These findings will spur investigation of FLASH radiotherapy in sarcoma and additional cancers where mesenchymal tissues are at risk, including head and neck cancer, breast cancer, and pelvic malignancies.

In this paper, we evaluate how employing fraction collection and multistep gradients with RoboColumns® (Repligen, formally Atoll) affects both comparison to benchtop experimental data and column simulation parameter estimation. These operational differences arise from the RoboColumn® system (operated on an automated liquid handling device) requiring offline analysis for determination of elution profiles rather than the continuous in-line UV curves obtained with larger scale systems. In addition, multistep gradients are used to model the smooth linear gradients of larger scale systems because sequential injections are used to provide liquid flow. Comparisons of two sets of column simulations was first carried out to demonstrate that fraction collection reduced the first moments of the elution peaks by 1/2 of the fraction volumes. Additional column simulations determined that the effect of a multistep gradient approximation on retention volume was dependent upon the gradient step length. An empirical transformation was then developed to correct the first moments obtained from gradient experimental data using the RoboColumn® system. These corrected values provided a more direct comparison of the experimental data at different scales and resulted in a significant improvement in agreement with results obtained using a 20 mL benchtop column. Linear steric mass-action (SMA) parameters were then estimated using the corrected values and employed to successfully predict the performance of the benchtop system data. Finally, these parameters were demonstrated to be well suited for modeling the RoboColumn® gradient data when properly accounting for multistep gradients and fraction collection. This work continues previous investigations into understanding system differences associated with robotic liquid handling devices and proposes a methodology for properly accounting for operational differences to predict operation at larger scales using conventional chromatography systems.

In light of the Deepwater Horizon accident, the oil and gas industry has undertaken various national and global initiatives to advance our knowledge, understanding and approach to oil spill preparedness and response. Notable amongst these, are the IPIECAIOGP (International Association of Oil and Gas Producers) Oil Spill Response Joint Industry Project (OSR-JIP) and the American Petroleum Institute's Joint Industry Task Force (APIJITF). These alone represent million dollars of investment and the collective contribution of hundreds of subject matter experts from around the world. The above two initiatives have produced numerous technical reports, good practice guides and recommended practices that have offered significant advances in industry's oil spill preparedness and response capabilities. Additionally, the various research projects conducted primarily by API have greatly enhanced the understanding of the efficacy and fate and effects of selected response options with a focus on subsea dispersant injection. This paper provides an overview and assessment of the key outcomes of these programs as well as highlighting some of the key breakthrough projects including spill impact mitigation assessment (SIMA), incident management, tiered provision of response capability, wildlife response and dispersants. The authors also describe briefly how the industry has continued this legacy through ongoing API and IPIECA/IOGP programs, together with a brief exploration of the full extent of value which may be derived from these kinds of initiatives.

Chronic pain conditions present in various forms, yet all feature symptomatic impairments in physical, mental, and social domains. Rather than assessing symptoms as manifestations of illness, we used them to develop a chronic pain classification system. A cohort of real-world treatment-seeking patients completed a multidimensional patient-reported registry as part of a routine initial evaluation in a multidisciplinary academic pain clinic. We applied hierarchical clustering on a training subset of 11448 patients using nine pain-agnostic symptoms. We then validated a three-cluster solution reflecting a graded scale of severity across all symptoms and eight independent pain-specific measures in additional subsets of 3817 and 1273 patients. Negative affect-related factors were key determinants of cluster assignment. The smallest subset included follow-up assessments that were predicted based on baseline cluster assignment. Findings provide a cost-effective classification system that promises to improve clinical care and alleviate suffering by providing putative markers for personalized diagnosis and prognosis.

In this paper, we examined the chromatographic behavior of a new class of guanidine-based multimodal anion exchange resins. The selectivities and protein recoveries on these resins were first evaluated using linear gradient chromatography with a model acidic protein library at pH 5, 6 and 7. While a single-guanidine based resin exhibited significant recovery issues at high ligand density, a bis-guanidine based resin showed high recoveries of all but two of the proteins evaluated in the study. In addition, the bis-guanidine resin showed a more pH dependent selectivity pattern as compared to the low density single-guanidine resin. The salt elution range for the low density single-guanidine and bis-guanidine resins was also observed to vary from 0.250 to 0.621 M and 0.162 to 0.828 M NaCl, respectively. A QSAR model was then developed to predict the elution behavior of these proteins on the guanidine prototypes at multiple pH with overall training and test scores of 0.88 and 0.85, respectively. In addition, molecular dynamics simulations were performed with these ligands immobilized on a self-assembled monolayer (SAM) to characterize their conformational preferences and to gain insight into the molecular basis of their chromatographic behavior. Finally, a recently developed framework was employed to evaluate the separability of the bis-guanidine resin as well as its orthogonality to the multimodal cation exchanger, Nuvia cPrime. This evaluation was carried out using a second model protein library which included both acidic and basic proteins. The results of this analysis indicated that the bis-guanidine prototype exhibited both higher pair separability (0.73) and pair enhancement (0.42) as compared to the less hydrophobic commercial Nuvia aPrime 4A with pair separability and enhancement factors of 0.57 and 0.22, respectively. The enhanced selectivity and orthogonality of this new multimodal anion exchange ligand may offer potential opportunities for bioprocessing applications.

Effects of synthetic and neutralized vinsol resin (NVR) air-entraining admixtures (AEAs) were compared through air-content measurements of freshly mixed concrete, hardened cylinders, and co...