Advanced error modeling and Bayesian uncertainty quantification in mechanistic liquid chromatography modeling.

Current mechanistic chromatography process modeling methods lack the ability to account for the impact of experimental errors beyond detector noise (e.g. pump delays and variable feed composition) on the uncertainty in calibrated model parameters and the resulting model-predicted chromatograms. This paper presents an uncertainty quantification method that addresses this limitation by determining the probability distribution of parameters in calibrated models, taking into consideration multiple realistic sources of experimental error. The method, which is based on Bayes' theorem and utilizes Markov chain Monte Carlo with an ensemble sampler, is demonstrated to be robust and extensible using synthetic and industrial data. The corresponding software is freely available as open-source code at https://github.com/modsim/CADET-Match.

Advanced score system and automated search strategies for parameter estimation in mechanistic chromatography modeling.

Least squares estimation of unknown parameters from measurement data is a well-established standard method in chromatography modeling but can suffer from critical disadvantages. The description of real-world systems is generally prone to unaccounted mechanisms, such as dispersion in external holdup volumes, and systematic measurement errors, such as caused by pump delays. In this scenario, matching the shape between simulated and measured chromatograms has been found to be more important than the exact peak positions. We have therefore developed a new score system that separately accounts for the shape, position and height of individual peaks. A genetic algorithm is used for optimizing these multiple objectives. Even for non-conflicting objectives, this approach shows superior convergence in comparison to single-objective gradient search, while conflicting objectives indicate incomplete models or inconsistent data. In the latter case, Pareto optima provide important information for understanding the system and improving experiments. The proposed method is demonstrated with synthetic and experimental case studies of increasing complexity. All software is freely available as open source code (https://github.com/modsim/CADET-Match).

Robust mechanistic modeling of protein ion-exchange chromatography.

Mechanistic models for ion-exchange chromatography of proteins are well-established and a broad consensus exists on most aspects of the detailed mathematical and physical description. A variety of specializations of these models can typically capture the general locations of elution peaks, but discrepancies are often observed in peak position and shape, especially if the column load level is in the non-linear range. These discrepancies may prevent the use of models for high-fidelity predictive applications such as process characterization and development of high-purity and -productivity process steps. Our objective is to develop a sufficiently robust mechanistic framework to make both conventional and anomalous phenomena more readily predictable using model parameters that can be evaluated based on independent measurements or well-accepted correlations. This work demonstrates the implementation of this approach for industry-relevant case studies using both a model protein, lysozyme, and biopharmaceutical product monoclonal antibodies, using cation-exchange resins with a variety of architectures (SP Sepharose FF, Fractogel EMD SO3-, Capto S and Toyopearl SP650M). The modeling employs the general rate model with the extension of the surface diffusivity to be variable, as a function of ionic strength or binding affinity. A colloidal isotherm that accounts for protein-surface and protein-protein interactions independently was used, with each characterized by a parameter determined as a function of ionic strength and pH. Both of these isotherm parameters, along with the variable surface diffusivity, were successfully estimated using breakthrough data at different ionic strengths and pH. The model developed was used to predict overloads and elution curves with high accuracy for a wide variety of gradients and different flow rates and protein loads. The in-silico methodology used in this work for parameter estimation, along with a minimal amount of experimental data, can help the industry adopt model-based optimization and control of preparative ion-exchange chromatography with high accuracy.

The Italian National Surveillance System for Occupational Injuries: Conceptual Framework and Fatal Outcomes, 2002-2016.

Background: A national database of work-related injuries has been established in Italy since 2002, collecting information on the injured person, his/her work tasks, the workplace and the risk factors contributing to incident dynamics, according to a model called Infor.Mo. Methods: A descriptive study of occupational fatal injuries, excluding work-related fatal traffic injuries, that occurred in Italy from 2002 to 2016 (15 years) was performed. Results: Among 4874 victims involved, all were males, mainly >51 years of age (43.2%), predominantly self-employed (27.8%) or workers with non-standard contracts (25%). About 18.4% and 17.3% of fatal events occurred in micro-enterprises belonging to, respectively, construction and agriculture. A wide range of nationalities (59 countries in addition to Italy) was identified. Overall, 18.9% of work-related fatal injuries were due to some form of hazardous energy-mechanical, thermal, electrical or chemical-that was normally present in the workplace. Workers' falls from height (33.5%), heavy loads falling on workers from height (16.7%) and vehicles exiting their route and overturning (15.9%) were the events causing the greatest proportion of occupational fatal injuries in the present study (from 2002 to 2016) and in the initial pilot phase, focused on years 2002-2004, with a similar distribution of fatal events between the two time periods. The activity of the injured person made up 43.3% of 9386 risk factors identified in 4874 fatalities. Less common risk factors were related to work equipment (20.2%), work environment (14.9%), third-party activity (9.8%), personal protective equipment/clothing (8.0%) and materials (3.7%). The activity of the injured person remained the most relevant contributing factor even when the incident was caused by two or more risk factors. Discussion: Occupational fatal injuries occurred mainly in small size firms (up to nine employees) in hazardous workplaces. Small companies, which account for 68% (2888/4249) of all firms in the present study, generally have fewer resources to remain current with the continuously evolving health and safety at work regulations; moreover, these firms tend to be less compliant with health and safety at work regulations since they are less likely to be inspected by occupational vigilance services. Perspectives: An approach being introduced in Italy relies on the use of economic incentives to promote safe and healthy workplaces. The comparison of pre-intervention and post-intervention rates of work-related injuries by means of interrupted time series analyses could detect whether the intervention will have an effect significantly greater than the underlying secular trend.

Demographics, comorbidities and outcomes in hospitalized Covid-19 patients in rural southwest Georgia.

BACKGROUND: There is limited data on outcomes in patients with coronavirus disease 2019 (Covid-19) in rural United States (US). This study aimed to describe the demographics, and outcomes of hospitalized Covid-19 patients in rural Southwest Georgia. METHODS: Using electronic medical records, we analyzed data from all hospitalized Covid-19 patients who either died or survived to discharge between 2 March 2020 and 6 May 2020. RESULTS: Of the 522 patients, 92 died in hospital (17.6%). Median age was 63 years, 58% were females, and 87% African-Americans. Hypertension (79.7%), obesity (66.5%) and diabetes mellitus (42.3%) were the most common comorbidities. Males had higher overall mortality compared to females (23 v 13.8%). Immunosuppression [odds ratio (OR) 3.6; (confidence interval (CI): 1.52-8.47, p=.003)], hypertension (OR 3.36; CI:1.3-8.6, p=.01), age ≥65 years (OR 3.1; CI:1.7-5.6, p<.001) and morbid obesity (OR 2.29; CI:1.11-4.69, p=.02), were independent predictors of in-hospital mortality. Female gender was an independent predictor of decreased in-hospital mortality. Mortality in intubated patients was 67%. Mortality was 8.9% in <50 years, compared to 20% in ≥50 years. CONCLUSIONS: Immunosuppression, hypertension, age ≥ 65 years and morbid obesity were independent predictors of mortality, whereas female gender was protective for mortality in hospitalized Covid-19 patients in rural Southwest Georgia. KEY MESSAGES Patients hospitalized with Covid-19 in rural US have higher comorbidity burden. Immunosuppression, hypertension, age ≥ 65 years and morbid obesity are independent predictors of increased mortality. Female gender is an independent predictor of reduced mortality.

Multi-state steric mass action model and case study on complex high loading behavior of mAb on ion exchange tentacle resin.

Tentacle resins for IEX are increasingly applied in preparative chromatography for their higher selectivity and higher capacities in comparison to IEX resins without tentacles. However, tentacle resins are often observed to cause unusual elution behavior of monoclonal antibodies under high loading conditions. Understanding this elution behavior is important for a quality by design approach, as it is now mandated by regulatory agencies. A model-based analysis of load, wash and gradient elution is performed for a monoclonal antibody (mAb) on Fractogel SO3-. Four experiments with increasing loaded mass show complex peak shapes and formation of a shoulder under overloaded conditions. We hypothesize that the observed peak shapes are caused by mAbs binding in multiple states on the tentacle ion-exchange resin. A new multi-state SMA binding model is used for testing this hypothesis. A two-state binding model is found to quantitatively reproduce all four experiments. An in-depth analysis reveals that the shoulder formation under overloaded conditions can be explained by multi-state binding that particularly manifests in rapid but weak re-adsorption of eluting molecules near the column end. The introduced multi-state SMA model combines features of the so-called spreading model (multiple bound states) and of the standard SMA model (salt dependency). It is by no means limited to ion-exchange chromatography on tentacle resins, but the same concept can be applied for studying systems that are based on other physical mechanisms. The new model can potentially improve mechanistic understanding and facilitate quantitative simulation of various phenomena, such as caused by reorientation, reconformation or unfolding of bound species. Similar concepts can be applied for studying surface-induced aggregation and denaturation.

Engineered calcium-precipitable restriction enzyme.

We have developed a simple system for tagging and purifying proteins. Recent experiments have demonstrated that RTX (Repeat in Toxin) motifs from the adenylate cyclase toxin gene (CyaA) of B. pertussis undergo a conformational change upon binding calcium, resulting in precipitation of fused proteins and making this method a viable alternative for bioseparation. We have designed an iGEM Biobrick comprised of an RTX tag that can be easily fused to any protein of interest. In this paper, we detail the process of creating an RTX tagged version of the restriction enzyme EcoRI and describe a method for expression and purification of the functional enzyme.

Jellyfish stings and their management: a review.

Jellyfish (cnidarians) have a worldwide distribution. Despite most being harmless, some species may cause local and also systemic reactions. Treatment of jellyfish envenomation is directed at: alleviating the local effects of venom, preventing further nematocyst discharges and controlling systemic reactions, including shock. In severe cases, the most important step is stabilizing and maintaining vital functions. With some differences between species, there seems to be evidence and consensus on oral/topical analgesics, hot water and ice packs as effective painkillers and on 30 s application of domestic vinegar (4%-6% acetic acid) to prevent further discharge of unfired nematocysts remaining on the skin. Conversely, alcohol, methylated spirits and fresh water should be carefully avoided, since they could massively discharge nematocysts; pressure immobilization bandaging should also be avoided, as laboratory studies show that it stimulates additional venom discharge from nematocysts. Most treatment approaches are presently founded on relatively weak evidence; therefore, further research (especially randomized clinical trials) is strongly recommended. Dissemination of appropriate treatment modalities should be deployed to better inform and educate those at risk. Adequate signage should be placed at beaches to notify tourists of the jellyfish risk. Swimmers in risky areas should wear protective equipment.