Search

Abstract??Magnetic powders based on metallic iron crystallites encapsulated in submicron-sized spherical silica particles have been obtained and investigated. The metallic iron clusters have been produced by the exploding wire method. The silica shells have been prepared via the modified sol-gel St?ber method and the metallic particles have been entrapped by occlusion during the silica powder formation. The entrapped iron particles are partially oxidized due to the nature of the synthetic methods employed. The obtained hybrid materials have been investigated by electron microscopy, X-ray diffraction, magnetic and ?-potential techniques. Such materials can be employed in such applications as e.g. magnetically-controlled drug vectors or electromagnetic field-shielding. [ABSTRACT FROM AUTHOR]

In this paper, a novel ultra-wideband printed monopole antenna (PMA) for microwave imaging systems is presented. The proposed antenna provides a wide usable fractional bandwidth of more than 160% (2.12-17.87 GHz). The antenna has an ordinary square radiating patch, therefore displays a good omni-directional radiation pattern even at higher frequencies and also its radiation efficiency is greater than 82% across the entire radiating band. The designed antenna has a small size of 12×18 mm2.

The Finnish mating records of Standardbred trotters (SB; n = 33 679) and Finnhorses (FH; n = 32 731) were analysed to study the effect of the level of inbreeding on foaling rates and to estimate the heritability of foaling rate. A linear mixed model was assumed, with the outcome of the foaling (foal or no foal) as the trait of the study. A restricted maximum likelihood-based method was used to calculate the estimates of the variance components. Predictions of breeding values and estimates of fixed effects were also calculated. The average level of inbreeding was 9.9% in the SB and 3.6% in the FH. The average foaling rates were better in the SB (72.6%) than in the FH (66.3%), but within each breed intense inbreeding had a statistically significant negative effect on foaling rate (P < 0.05). Also, the mating type, the age and breeding type of the mare, and the age of the stallion had statistically significant effects on foaling rate (P < 0.001). The heritability of foaling rate was between 3.4% and 3.7% in SBs and between 5.5% and 9.8% in FHs, when the outcome of the foaling was considered to be a trait of the expected foal. With the same model, the estimates of maternal genetic effect were 4.7% for SBs and 3.2% for FHs, and the estimates of the permanent environmental effects of the stallion were between 1.3% and 1.7%. Avoiding matings with very high inbreeding coefficients would improve foaling rates. It would also be possible to devise a breeding program for better equine fertility, but because the heritability is low, improvement of environmental factors deserves special attention.

En el proceso de colada continua contribuyen complicados fenómenos físicos con un marcado efecto en la calidad final del producto y en la productividad del proceso. Además, los distintos fenómenos físicos no aparecen de forma aislada, sino que interactúan unos con otros de manera acoplada, afectando a la calidad del semiproducto. El correcto diseño y ajuste es, por lo tanto, una tarea que requiere un gran conocimiento tanto de los distintos fenómenos que intervienen como de sus interacciones. En este trabajo se presenta un novedoso método de simulación que resuelve el proceso en su conjunto, siendo las variables del proceso las únicas condiciones de contorno. Mediante la utilización conjunta de herramientas comerciales (FLUENT y ABAQUS) y una serie de modelos de desarrollo propio se resuelven las interacciones entre los distintos fenómenos.

The heritability and repeatability of trotting performance traits and genetic and phenotypic correlations among these traits were estimated from repeated annual records of 6934 Finnhorse and 5298 Standardbred trotters. The number of observations in the two breeds was 19 550 and 14 184, respectively. (Co)variance components were obtained with animal model and restricted maximum likelihood (REML) method. The heritability estimates were highest for time traits (0.29 to 0.35) and lowest for number of starts (0.08 to 0.10) in the two breeds. The repeatability estimates were high for time traits but only moderate for other trotting performance traits, suggesting that repeated records improve accuracy in genetic evaluations. The genetic correlations among the performance traits, especially between time and money traits, were very high and favourable considering the breeding goals. The phenotypic associations were distinctly weaker than the genetic ones.

The effects of kappa-beta-casein genotypes and b-lactoglobulin genotypes on the renneting properties and composition of milk were estimated for 174 and 155 milk samples of 59 Finnish Ayrshire and 55 Finnish Friesian cows, respectively. As well as the random additive genetic and permanent environmental effects of a cow, the model included the fixed effects for parity, lactation stage, season, kappa-beta-casein genotypes and b-lactoglobulin genotypes. Favourable renneting properties were associated with kappa-beta-casein genotypes ABA 1 A 2 , ABA 1 A 1 and AAA 1 A 2 in the Finnish Ayrshire, and with ABA 2 B, AAA 1 A 3 , AAA 2 A 3 , ABA 1 A 2 and ABA 2 A 2 in the Finnish Friesian. The favourable effect of these genotypes on curd firming time and on firmness of the curd was partly due to their association with a high kappa-casein concentration in the milk. The effect of the kappa-casein E allele on renneting properties was unfavourable compared with that of the kappa-casein B allele, and possibly with that of the A allele. The beta-lactoglobulin genotypes had no effect on renneting properties but they had a clear effect on the protein composition of milk. The beta-lactoglobulin AA genotype was associated with a high whey protein % and beta-lactoglobulin concentration and the BB genotype with a high casein % and casein number.;

A total of 8745 purebred Yorkshire and Landrace pigs extracted from Finnish progeny test station data was analysed. The pigs were weighed weekly during the test. A third degree polynomial function, age = f(weight), was fitted separately for each pig and was used to describe the growth patterns of individual pigs. Their live weight at the inflection point (LW ip ) was 72 kg, age at the inflection point (AGE ip ) 126 d, and maximum daily gain (DG max ) 1111 g/d, on average. The average daily gain from 30 to 90 kg (ADG 30-90 ) was 957 g/d and in the smaller weight ranges (30 to 50, 50 to 70 and 70 to 90 kg) the average daily gains were 829, 1042 and 1046 g/d, respectively. Genetic parameters for growth and carcass traits were estimated using REML with an animal model. The heritability estimates (h 2 ) for LW ip , AGE ip and ADG 30-90 were 0.08, 0.33 and 0.23, respectively, and for smaller weight ranges from 0.14 to 0.21. Fast growing and lean animals had higher LW ip than others and the r g between LW ip and ADG 30-90 , DG max and M% was 0.58, 0.73 and 0.57, respectively. The r g between ADG 30-90 and M% was close to zero.;

Drug substances in water bodies and groundwater have become a significant threat to the surrounding environment. This study focuses on the ability of the nanoporous carbon materials to remove ciprofloxacin from aqueous solutions under specific experimental conditions and on the development of the mathematical model that would allow describing the molecular interactions of the adsorption process and calculating the adsorption capacity of the material. Thus, based on the adsorption measurements of the 87 carbon materials, it was found that, depending on the porosity and pore size distribution, adsorption capacity values varied between 55 and 495 mg g -1 . For a more detailed analysis of the effects of different carbon textures and pores characteristics, a Quantitative nano-Structure-Property Relationship (QnSPR) was developed to describe and predict the ability of a nanoporous carbon material to remove ciprofloxacin from aqueous solutions. The adsorption capacity of potential nanoporous carbon-based adsorbents for the removal of ciprofloxacin was shown to be sufficiently accurately described by a three-parameter multi-linear QnSPR equation (R 2 = 0.70). This description was achieved only with parameters describing the texture of the carbon material such as specific surface area ( S dft ) and pore size fractions of 1.1-1.2 nm (VN21.1-1.2) and 3.3-3.4 nm (VN23.3-3.4) for pores.

Purpose: We aimed to develop a standardized method to calculate daily dose (i.e., the amount of drug a patient was exposed to per day) of any drug on a global scale using only drug information of typical observational data in the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) and a single reference table from Observational Health Data Sciences And Informatics (OHDSI)., Materials and Methods: The OMOP DRUG&#95;STRENGTH reference table contains information on the strength or concentration of drugs, whereas the OMOP DRUG&#95;EXPOSURE table contains information on patients' drug prescriptions or dispensations/claims. Based on DRUG&#95;EXPOSURE data from the primary care databases Clinical Practice Research Datalink GOLD (United Kingdom) and Integrated Primary Care Information (IPCI, The Netherlands) and healthcare claims from PharMetrics® Plus for Academics (USA), we developed four formulas to calculate daily dose given different DRUG&#95;STRENGTH reference table information. We tested the dose formulas by comparing the calculated median daily dose to the World Health Organization (WHO) Defined Daily Dose (DDD) for six different ingredients in those three databases and additional four international databases representing a variety of healthcare settings: MAITT (Estonia, healthcare claims and discharge summaries), IQVIA Disease Analyzer Germany (outpatient data), IQVIA Longitudinal Patient Database Belgium (outpatient data), and IMASIS Parc Salut (Spain, hospital data). Finally, in each database, we assessed the proportion of drug records for which daily dose calculations were possible using the suggested formulas., Results: Applying the dose formulas, we obtained median daily doses that generally matched the WHO DDD definitions. Our dose formulas were applicable to >85% of drug records in all but one of the assessed databases., Conclusion: We have established and implemented a standardized daily dose calculation in OMOP CDM providing reliable and reproducible results., (© 2024 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.)

Objective: The fight against cervical cancer requires effective screening together with optimal and on-time treatment along the care continuum. We examined the impact of cervical cancer testing and treatment guidelines on testing practices, and follow-up adherence to guidelines., Methods: Data from Estonian electronic health records and healthcare provision claims for 50,702 women was used. The annual rates of PAP tests, HPV tests and colposcopies during two guideline periods (2nd version 2012-2014 vs 3rd version 2016-2019) were compared. To assess the adherence to guidelines, the subjects were classified as adherent, over- or undertested based on the timing of the appropriate follow-up test., Results: The number of PAP tests decreased and HPV tests increased during the 3rd guideline period (p < 0.01). During the 3rd guideline period, among 21-29-year-old women, the adherence to guidelines ranged from 38.7% (44.4…50.1) for ASC-US to 73.4% (62.6…84.3) for HSIL and among 30-59-year-old from 49.0% (45.9…52.2) for ASC-US to 65.7% (58.8…72.7) for ASCH. The highest rate of undertested women was for ASC-US (21-29y: 25.7%; 30-59y: 21.9%). The rates of over-tested women remained below 12% for all cervical pathologies observed. There were 55.2% (95% CI 49.7…60.8) of 21-24-year-olds and 57.1% (95% CI 53.6…60.6) of 25-29-year-old women who received HPV test not adherent to guidelines., Conclusions: Our findings highlighted some shortcomings in guideline adherence, especially among women under 30. The insights gained from this study help to improve the quality of care and, thus, reduce cervical cancer incidence and mortality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The author is an Editorial Board Member/Editor-in-Chief/Associate Editor/Guest Editor for [Journal name] and was not involved in the editorial review or the decision to publish this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics., Objective: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data., Design, Setting, and Participants: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146)., Outcome Measurements and Statistical Analysis: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data., Results and Limitations: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent., Conclusions: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data., Patient Summary: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: To introduce 2 R-packages that facilitate conducting health economics research on OMOP-based data networks, aiming to standardize and improve the reproducibility, transparency, and transferability of health economic models., Materials and Methods: We developed the software tools and demonstrated their utility by replicating a UK-based heart failure data analysis across 5 different international databases from Estonia, Spain, Serbia, and the United States., Results: We examined treatment trajectories of 47 163 patients. The overall incremental cost-effectiveness ratio (ICER) for telemonitoring relative to standard of care was 57 472 €/QALY. Country-specific ICERs were 60 312 €/QALY in Estonia, 58 096 €/QALY in Spain, 40 372 €/QALY in Serbia, and 90 893 €/QALY in the US, which surpassed the established willingness-to-pay thresholds., Discussion: Currently, the cost-effectiveness analysis lacks standard tools, is performed in ad-hoc manner, and relies heavily on published information that might not be specific for local circumstances. Published results often exhibit a narrow focus, central to a single site, and provide only partial decision criteria, limiting their generalizability and comprehensive utility., Conclusion: We created 2 R-packages to pioneer cost-effectiveness analysis in OMOP CDM data networks. The first manages state definitions and database interaction, while the second focuses on Markov model learning and profile synthesis. We demonstrated their utility in a multisite heart failure study, comparing telemonitoring and standard care, finding telemonitoring not cost-effective., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in "real-life" patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies., (© 2024 The Authors.)

Objective: To describe the reusable transformation process of electronic health records (EHR), claims, and prescriptions data into Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM), together with challenges faced and solutions implemented., Materials and Methods: We used Estonian national health databases that store almost all residents' claims, prescriptions, and EHR records. To develop and demonstrate the transformation process of Estonian health data to OMOP CDM, we used a 10% random sample of the Estonian population ( n  = 150 824 patients) from 2012 to 2019 (MAITT dataset). For the sample, complete information from all 3 databases was converted to OMOP CDM version 5.3. The validation was performed using open-source tools., Results: In total, we transformed over 100 million entries to standard concepts using standard OMOP vocabularies with the average mapping rate 95%. For conditions, observations, drugs, and measurements, the mapping rate was over 90%. In most cases, SNOMED Clinical Terms were used as the target vocabulary., Discussion: During the transformation process, we encountered several challenges, which are described in detail with concrete examples and solutions., Conclusion: For a representative 10% random sample, we successfully transferred complete records from 3 national health databases to OMOP CDM and created a reusable transformation process. Our work helps future researchers to transform linked databases into OMOP CDM more efficiently, ultimately leading to better real-world evidence., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

COVID-19 and other acute respiratory viruses can have a long-term impact on health. We aimed to assess the common features and differences in the post-acute phase of COVID-19 compared with other non-chronic respiratory infections (RESP) using population-based electronic health data. We applied the self-controlled case series method where prescription drugs and health care utilisation were used as indicators of health outcomes during the six-month-long post-acute period. The incidence rate ratios of COVID-19 and RESP groups were compared. The analysis included 146 314 individuals. Out of 5452 drugs analysed, 14 had increased administration after COVID-19 with drugs for cardiovascular diseases (trimetazidine, metoprolol, rosuvastatin) and psychotropic drugs (alprazolam, zolpidem, melatonin) being most prevalent. The health impact of COVID-19 was more apparent among females and individuals with non-severe COVID-19. The increased risk of exacerbating pre-existing conditions was observed for the COVID-19 group. COVID-19 vaccination did not have effect on drug prescriptions but lowered the health care utilisation during post-acute period. Compared with RESP, COVID-19 increased the use of outpatient services during the post-infection period. The long-term negative impact of COVID-19 on life quality must be acknowledged, and supportive health care and public health services provided., (© 2023. The Author(s).)

Electronically stored medical records offer a rich source of data for investigating treatment trajectories and identifying best practices in healthcare. These trajectories, which consist of medical interventions, give us a foundation to evaluate the economics of treatment patterns and model the treatment paths. The aim of this work is to introduce a technical solution for the aforementioned tasks. The developed tools use the open source Observational Health Data Sciences and Informatics Observational Medical Outcomes Partnership Common Data Model to construct treatment trajectories and implement these to compose Markov models for composing financial analysis between standard of care and alternatives.

Importance: Large-scale data on type-specific human papillomavirus (HPV) prevalence and disease burden worldwide are needed to guide cervical cancer prevention efforts. Promoting the research and application of health care big data has become a key factor in modern medical research., Objective: To examine the prevaccination prevalence of high-risk HPV (hrHPV) and type distribution by cervical cytology grade in Estonia., Design, Setting, and Participants: This cross-sectional study used text mining and the linking of data from electronic health records and health care claims to examine type-specific hrHPV positivity in Estonia from 2012 to 2019. Participants were women aged at least 18 years. Statistical analysis was performed from September 2021 to August 2022., Main Outcomes and Measures: Type-specific hrHPV positivity rate by cervical cytological grade., Results: A total of 11 017 cases of cervical cytology complemented with data on hrHPV testing results between 2012 and 2019 from 66 451 women aged at least 18 years (mean [SD] age, 48.1 [21.0] years) were included. The most common hrHPV types were HPV16, 18, 31, 33, 51 and 52, which accounted for 73.8% of all hrHPV types detected. There was a marked decline in the positivity rate of hrHPV infection with increasing age, but the proportion did not vary significantly based on HPV type. Implementation of nonavalent prophylactic vaccination was estimated to reduce the number of women with high-grade cytology by 50.5% (95% CI, 47.4%-53.6%) and the number with low-grade cytology by 27.8% (95% CI, 26.3%-29.3%), giving an overall estimated reduction of 33.1% (95% CI, 31.7%-34.5%) in the number of women with precancerous cervical cytology findings., Conclusions and Relevance: In this cross-sectional study, text mining and natural language processing techniques allowed the detection of precursors to cervical cancer based on data stored by the nationwide health system. These findings contribute to the literature on type-specific HPV distribution by cervical cytology grade and document that α-9 phylogenetic group HPV types 16, 31, 33, 52 and α-7 phylogenetic group HPV 18 are the most frequently detected in normal-to-high-grade precancerous lesions in Estonia.

Intrinsic aqueous solubility is a foundational property for understanding the chemical, technological, pharmaceutical, and environmental behavior of drug substances. Despite years of solubility research, molecular structure-based prediction of the intrinsic aqueous solubility of drug substances is still under active investigation. This paper describes the authors' systematic data-driven modelling in which two fit-for-purpose training data sets for intrinsic aqueous solubility were collected and curated, and three quantitative structure-property relationships were derived to make predictions for the most recent solubility challenge. All three models perform well individually, while being mechanistically transparent and easy to understand. Molecular descriptors involved in the models are related to the following key steps in the solubility process: dissociation of the molecule from the crystal, formation of a cavity in the solvent, and insertion of the molecule into the solvent. A consensus modeling approach with these models remarkably improved prediction capability and reduced the number of strong outliers by more than two times. The performance and outliers of the second solubility challenge predictions were analyzed retrospectively. All developed models have been published in the QsarDB.org repository according to FAIR principles and can be used without restrictions for exploring, downloading, and making predictions.

The processes preceding the detachment of cytochrome c (cyt c) from the inner mitochondrial membrane in intrinsic apoptosis involve peroxidation of cardiolipin (CL) catalyzed by cyt c-CL complex. In the present work, we studied the effect of 17 dietary flavonoids on the peroxidase activity of cyt c bound to liposomes. Specifically, we explored the relationship between peroxidase activity and flavonoids' (1) potential to modulate cyt c unfolding, (2) effect on the oxidation state of heme iron, (3) membrane permeability, (4) membrane binding energy, and (5) structure. The measurements revealed that flavones, flavonols, and flavanols were the strongest, while isoflavones were the weakest inhibitors of the oxidation. Flavonoids' peroxidase inhibition activity correlated positively with their potential to suppress Trp-59 fluorescence in cyt c as well as the number of OH groups. Hydrophilic flavonoids, such as catechin, having the lowest membrane permeability and the strongest binding with phosphocholine (PC) based on the quantum chemical calculations exhibited the strongest inhibition of Amplex Red (AR) peroxidation, suggesting a membrane-protective function of flavonoids at the surface. The results of the present research specify basic principles for the design of molecules that will control the catalytic oxidation of lipids in mitochondrial membranes. These principles take into account the number of hydroxyl groups and hydrophilicity of flavonoids., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The ESA-JAXA BepiColombo mission to Mercury will provide simultaneous measurements from two spacecraft, offering an unprecedented opportunity to investigate magnetospheric and exospheric particle dynamics at Mercury as well as their interactions with solar wind, solar radiation, and interplanetary dust. The particle instrument suite SERENA (Search for Exospheric Refilling and Emitted Natural Abundances) is flying in space on-board the BepiColombo Mercury Planetary Orbiter (MPO) and is the only instrument for ion and neutral particle detection aboard the MPO. It comprises four independent sensors: ELENA for neutral particle flow detection, Strofio for neutral gas detection, PICAM for planetary ions observations, and MIPA, mostly for solar wind ion measurements. SERENA is managed by a System Control Unit located inside the ELENA box. In the present paper the scientific goals of this suite are described, and then the four units are detailed, as well as their major features and calibration results. Finally, the SERENA operational activities are shown during the orbital path around Mercury, with also some reference to the activities planned during the long cruise phase., (© The Author(s) 2021.)

Permeability is used to describe and evaluate the absorption of drug substances in the human gastrointestinal tract (GIT). Permeability is largely dependent on fluctuating pH that causes the ionization of drug substances and also influences regional absorption in the GIT. Therefore, classification models that characterize permeability at wide ranges of pH were derived in the current study. For this, drug substances were described with six data series that were measured with a parallel artificial membrane permeability assay (PAMPA), including a permeability profile at four pH values (3, 5, 7.4, and 9), and the highest and intrinsic membrane permeability. Logistic regression classification models were developed and compared by using two distinct sets of descriptors: (1) a hydrophobicity descriptor, the logarithm of the octanol-water partition (logP ow ) or distribution (logD) coefficient and (2) theoretical molecular descriptors. In both cases, models have good classification and descriptive capabilities for the training set (accuracy: 0.76-0.91). Triple validation with three sets of drug substances shows good prediction capability for all models: validation set (accuracy: 0.73-0.91), external validation set (accuracy: 0.72-0.9), and the permeability classes of FDA reference drugs for the biopharmaceutical classification system (BCS) (accuracy: 0.72-0.88). The identification of BCS permeability classes was further improved with decision trees that consolidated predictions from models with each descriptor type. These decision trees have higher confidence and accuracy (0.91 for theoretical molecular descriptors and 0.81 for hydrophobicity descriptors) than the individual models in assigning drug substances into BCS permeability classes. A detailed analysis of classification models and related decision trees suggests that they are suitable for predicting classes of permeability for passively transported drug substances, including specifically within the BCS framework. All developed models are available at the QsarDB repository ( http://dx.doi.org/10.15152/QDB.206 ).

The influence of pH on human intestinal absorption is frequently not considered in early drug discovery studies in the modelling and subsequent prediction of intestinal absorption for drug candidates. To bridge this gap, in this study, experimental membrane permeability data were measured for current and former drug substances with a parallel artificial membrane permeability assay (PAMPA) at different pH values (3, 5, 7.4 and 9). The presented data are in good agreement with human intestinal absorption, showing a clear influence of pH on the efficiency of intestinal absorption. For the measured data, simple and general quantitative structure-activity relationships (QSARs) were developed for each pH that makes it possible to predict the pH profiles for passive membrane permeability (i.e., a pH-permeability profile), and these predictions coincide well with the experimental data. QSARs are also proposed for the data series of highest and intrinsic membrane permeability. The molecular descriptors in the models were analysed and mechanistically related to the interaction pattern of permeability in membranes. In addition to the regression models, classification models are also proposed. All models were successfully validated and blind tested with external data. The models are available in the QsarDB repository (http://dx.doi.org/10.15152/QDB.203)., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: Modern activity trackers, including the Fitbit Zip, enable the measurement of both the step count as well as physical activity (PA) intensities. However, there is a need for field-based validation studies in a variety of populations before using trackers for research. Therefore, the purpose of the current study was to investigate the validity of Fitbit Zip step count, moderate to vigorous physical activity (MVPA) and sedentary minutes, in different school segments in 3rd grade students., Methods: Third grade students (N = 147, aged 9-10 years) wore a Fitbit Zip and an ActiGraph GT3x-BT accelerometer simultaneously on a belt for five days during school hours. The number of steps, minutes of MVPA and sedentary time during class time, physical education lessons and recess were extracted from both devices using time filters, based on the information from school time tables obtained from class teachers. The validity of the Fitbit Zip in different school segments was assessed using Bland-Altman analysis and Spearman's correlation., Results: There was a strong correlation in the number of steps in all in-school segments between the two devices (r = 0.85-0.96, P < 0.001). The Fitbit Zip overestimated the number of steps in all segments, with the greatest overestimation being present in physical education lessons (345 steps). As for PA intensities, the agreement between the two devices in physical education and recess was moderate for MVPA minutes (r = 0.56 and r = 0.72, P < 0.001, respectively) and strong for sedentary time (r = 0.85 and r = 0.87, P < 0.001, respectively). During class time, the correlation was weak for MVPA minutes (r = 0.24, P < 0.001) and moderate for sedentary time (r = 0.57, P < 0.001). For total in-school time, the correlation between the two devices was strong for steps (r = 0.98, P < 0.001), MVPA (r = 0.80, P < 0.001) and sedentary time (r = 0.94, P < 0.001)., Conclusion: In general, the Fitbit Zip can be considered a relatively accurate device for measuring the number of steps, MVPA and sedentary time in students in a school-setting. However, in segments where sedentary time dominates (e.g. academic classes), a research-grade accelerometer should be preferred.

Background: Trichoderma reesei is one of the main sources of biomass-hydrolyzing enzymes for the biotechnology industry. There is a need for improving its enzyme production efficiency. The use of metabolic modeling for the simulation and prediction of this organism's metabolism is potentially a valuable tool for improving its capabilities. An accurate metabolic model is needed to perform metabolic modeling analysis., Results: A whole-genome metabolic model of T. reesei has been reconstructed together with metabolic models of 55 related species using the metabolic model reconstruction algorithm CoReCo. The previously published CoReCo method has been improved to obtain better quality models. The main improvements are the creation of a unified database of reactions and compounds and the use of reaction directions as constraints in the gap-filling step of the algorithm. In addition, the biomass composition of T. reesei has been measured experimentally to build and include a specific biomass equation in the model., Conclusions: The improvements presented in this work on the CoReCo pipeline for metabolic model reconstruction resulted in higher-quality metabolic models compared with previous versions. A metabolic model of T. reesei has been created and is publicly available in the BIOMODELS database. The model contains a biomass equation, reaction boundaries and uptake/export reactions which make it ready for simulation. To validate the model, we dem1onstrate that the model is able to predict biomass production accurately and no stoichiometrically infeasible yields are detected. The new T. reesei model is ready to be used for simulations of protein production processes.