Medical bioremediation of age-related diseases

Catabolic insufficiency in humans leads to the gradual accumulation of a number of pathogenic compounds associated with age-related diseases, including atherosclerosis, Alzheimer's disease, and macular degeneration. Removal of these compounds is a widely researched therapeutic option, but the use of antibodies and endogenous human enzymes has failed to produce effective treatments, and may pose risks to cellular homeostasis. Another alternative is "medical bioremediation," the use of microbial enzymes to augment missing catabolic functions. The microbial genetic diversity in most natural environments provides a resource that can be mined for enzymes capable of degrading just about any energy-rich organic compound. This review discusses targets for biodegradation, the identification of candidate microbial enzymes, and enzyme-delivery methods

The Lippmann–Schwinger Formula and One Dimensional Models with Dirac Delta Interactions

We show how a proper use of the Lippmann–Schwinger equation simplifies the calculations to obtain scattering states for one dimensional systems perturbed by N Dirac delta equations. Here, we consider two situations. In the former, attractive Dirac deltas perturbed the free one dimensional Schrödinger Hamiltonian. We obtain explicit expressions for scattering and Gamow states. For completeness, we show that the method to obtain bound states use comparable formulas, although not based on the Lippmann–Schwinger equation. Then, the attractive N deltas perturbed the one dimensional Salpeter equation. We also obtain explicit expressions for the scattering wave functions. Here, we need regularisation techniques that we implement via heat kernel regularisation

Cars, CONSORT 2010, and Clinical Practice

Just like you would not buy a car without key information such as service history, you would not "buy" a clinical trial report without key information such as concealment of allocation. Implementation of the updated CONSORT 2010 statement enables the reader to see exactly what was done in a trial, to whom and when. A fully "CONSORTed" trial report does not necessarily mean the trial is a good one, but at least the reader can make a judgement. Clear reporting is a pre-requisite for judgement of study quality. The CONSORT statement evolves as empirical research moves on. CONSORT 2010 is even clearer than before and includes some new items with a particular emphasis on selective reporting of outcomes. The challenge is for everyone to use it

The "Solar Model Problem" Solved by the Abundance of Neon in Stars of the Local Cosmos

The interior structure of the Sun can be studied with great accuracy using observations of its oscillations, similar to seismology of the Earth. Precise agreement between helioseismological measurements and predictions of theoretical solar models has been a triumph of modern astrophysics (Bahcall et al. 2005). However, a recent downward revision by 25-35% of the solar abundances of light elements such as C, N, O and Ne (Asplund et al. 2004) has broken this accordance: models adopting the new abundances incorrectly predict the depth of the convection zone, the depth profiles of sound speed and density, and the helium abundance (Basu Antia 2004, Bahcall et al. 2005). The discrepancies are far beyond the uncertainties in either the data or the model predictions (Bahcall et al. 2005b). Here we report on neon abundances relative to oxygen measured in a sample of nearby solar-like stars from their X-ray spectra. They are all very similar and substantially larger than the recently revised solar value. The neon abundance in the Sun is quite poorly determined. If the Ne/O abundance in these stars is adopted for the Sun the models are brought back into agreement with helioseismology measurements (Antia Basu 2005, Bahcall et al. 2005c).Comment: 13 pages, 3 Figure

Glycated haemoglobin (HbA1c ) and fasting plasma glucose relationships in sea-level and high-altitude settings.

AIM: Higher haemoglobin levels and differences in glucose metabolism have been reported among high-altitude residents, which may influence the diagnostic performance of HbA1c . This study explores the relationship between HbA1c and fasting plasma glucose (FPG) in populations living at sea level and at an altitude of > 3000 m. METHODS: Data from 3613 Peruvian adults without a known diagnosis of diabetes from sea-level and high-altitude settings were evaluated. Linear, quadratic and cubic regression models were performed adjusting for potential confounders. Receiver operating characteristic (ROC) curves were constructed and concordance between HbA1c and FPG was assessed using a Kappa index. RESULTS: At sea level and high altitude, means were 13.5 and 16.7 g/dl (P > 0.05) for haemoglobin level; 41 and 40 mmol/mol (5.9% and 5.8%; P < 0.01) for HbA1c ; and 5.8 and 5.1 mmol/l (105 and 91.3 mg/dl; P < 0.001) for FPG, respectively. The adjusted relationship between HbA1c and FPG was quadratic at sea level and linear at high altitude. Adjusted models showed that, to predict an HbA1c value of 48 mmol/mol (6.5%), the corresponding mean FPG values at sea level and high altitude were 6.6 and 14.8 mmol/l (120 and 266 mg/dl), respectively. An HbA1c cut-off of 48 mmol/mol (6.5%) had a sensitivity for high FPG of 87.3% (95% confidence interval (95% CI) 76.5 to 94.4) at sea level and 40.9% (95% CI 20.7 to 63.6) at high altitude. CONCLUSION: The relationship between HbA1c and FPG is less clear at high altitude than at sea level. Caution is warranted when using HbA1c to diagnose diabetes mellitus in this setting

Integrating pressure sensor control into semi-solid extrusion 3D printing to optimize medicine manufacturing

Semi-solid extrusion (SSE) is a three-dimensional printing (3DP) process that involves the extrusion of a gel or paste-like material via a syringe-based printhead to create the desired object. In pharmaceuticals, SSE 3DP has already been used to manufacture formulations for human clinical studies. To further support its clinical adoption, the use of a pressure sensor may provide information on the printability of the feedstock material in situ and under the exact printing conditions for quality control purposes. This study aimed to integrate a pressure sensor in an SSE pharmaceutical 3D printer for both material characterization and as a process analytical technology (PAT) to monitor the printing process. In this study, three materials of different consistency were tested (soft vaseline, gel-like mass and paste-like mass) under 12 different conditions, by changing flow rate, temperature, or nozzle diameter. The use of a pressure sensor allowed, for the first time, the characterization of rheological properties of the inks, which exhibited temperature-dependent, plastic and viscoelastic behaviours. Controlling critical material attributes and 3D printing process parameters may allow a quality by design (QbD) approach to facilitate a high-fidelity 3D printing process critical for the future of personalized medicine

Expectancy-based strategic processes are influenced by spatial working memory load and individual differences in working memory capacity

The present research examined whether imposing a high (or low) working memory (WM) load in different types of nonverbal WM task could affect the implementation of expectancy-based strategic processes in a sequential verbal Stroop task. Participants had to identify a colored target (a red vs. green patch) that was preceded by a prime word (RED or GREEN), which was incongruent with the target color on 80% of the trials, and congruent on 20% of trials. Previous findings have shown that participants can strategically use this information to predict the upcoming target color, and avoid the standard Stroop interference effect. The Stroop task was combined with different types of nonverbal WM task. In Experiment 1, participants had to retain sets of four arrows that pointed either in the same direction (low load) or in different directions (high load). In Experiment 2, they had to remember the spatial locations of four dots which either formed a straight line (low load) or were randomly scattered in a square grid (high load).In addition, participants in the two experiments performed a change localization task to obtain a measure of their WM capacity (WMC). The results in both experiments showed a reliable interaction between prime-target congruency and WM load. When participants performed the Stroop task under high WM load, they were unable to efficiently ignore the incongruence of the prime, as they consistently showed a standard Stroop effect, regardless of their WMC. Under a low WM load, however, a strategy-dependent (reversed Stroop) effect was observed. This ability to ignore the incongruence of the prime was modulated by WMC, such that the reversed Stroop effect was mainly found in higher WMC participants. The findings that expectancy-based strategies on a verbal Stroop task are modulated by load on different types of spatial WM tasks point at a domain-general effect of WM on strategic processing. The present results also suggest that the impact of loading WM on expectancy-based strategies can be modulated by individual differences in WMC

Scoping review of measures of treatment burden in patients with multimorbidity: advancements and current gaps

Objectives: To identify, assess, and summarize the measures to assess burden of treatment in patients with multimorbidity (BoT-MMs) and their measurement properties. Study Design and Setting: MEDLINE via PubMed was searched from inception until May 2021. Independent reviewers extracted data from studies in which BoT-MMs were developed, validated, or reported as used, including an assessment of their measurement properties (e.g., validity and reliability) using the COnsensus-based Standards for the selection of health Measurement INstruments. Results: Eight BoT-MMs were identified across 72 studies. Most studies were performed in English (68%), in high-income countries (90%), without noting urban-rural settings (90%). No BoT-MMs had both sufficient content validity and internal consistency; some measurement properties were either insufficient or uncertain (e.g., responsiveness). Other frequent limitations of BoT-MMs included absent recall time, presence of floor effects, and unclear rationale for categorizing and interpreting raw scores. Conclusion: The evidence needed for use of extant BoT-MMs in patients with multimorbidity remains insufficiently developed, including that of suitability for their development, measurement properties, interpretability of scores, and use in low-resource settings. This review summarizes this evidence and identifies issues needing attention for using BoT-MMs in research and clinical practice

Predicting pharmaceutical inkjet printing outcomes using machine learning

Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex polydrug implants. However, the multi-factorial nature of the inkjet printing process makes formulation (e.g., composition, surface tension, and viscosity) and printing parameter optimization (e.g., nozzle diameter, peak voltage, and drop spacing) an empirical and time-consuming endeavour. Instead, given the wealth of publicly available data on pharmaceutical inkjet printing, there is potential for a predictive model for inkjet printing outcomes to be developed. In this study, machine learning (ML) models (random forest, multilayer perceptron, and support vector machine) to predict printability and drug dose were developed using a dataset of 687 formulations, consolidated from in-house and literature-mined data on inkjet-printed formulations. The optimized ML models predicted the printability of formulations with an accuracy of 97.22%, and predicted the quality of the prints with an accuracy of 97.14%. This study demonstrates that ML models can feasibly provide predictive insights to inkjet printing outcomes prior to formulation preparation, affording resource- and time-savings