Good Quality Of Model Research Articles

Predicting Long-Term Stability of an Oral Delivered Antibody Drug Product with Accelerated Stability Assessment Program Modeling.

The oral delivery of protein therapeutics offers numerous advantages for patients but also presents significant challenges in terms of development. Currently, there is limited knowledge available regarding the stability and shelf life of orally delivered protein therapeutics. In this study, a comprehensive assessment of the stability of an orally delivered solid dosage variable domain of heavy-chain antibody (VHH antibody) drug product was conducted. Four stability related quality attributes that undergo change as a result of thermal and humidity stress were identified. Subsequently, these attributes were modeled using an accelerated stability approach facilitated by ASAPprime software. To the best of our knowledge, this is the first time that this approach has been reported for an antibody drug product. We observed overall good model quality and accurate predictions regarding the protein stability during storage. Notably, we discovered that protein aggregation, formed through a degradation pathway, requires additional adjustments to the modeling method. In summary, the ASAP approach demonstrated promising results in predicting the stability of this complex solid-state protein formulation. This study sheds light on the stability and shelf life of orally delivered protein therapeutics, addressing an important knowledge gap in the field.

A method for the biological age of the heart determination

Determination of the human heart biological age (BA) is relevant for timely stratification of the risk of developing diseases, prevention, control of individual aging rate and geroprotective therapy. Aim. To study age-related changes in echocardiographic examination of the heart and to develop a formula for estimating the BA of the human heart. Materials and methods. Echocardiographic examinations of the heart were performed in 188 practically healthy people aged 30 to 79 years (73 men and 115 women), who signed an informed consent and had no clinically significant diseases in the anamnesis or at the moment. The examined were divided into age groups: I (n = 25) – 30–39 years, II (n = 40) – 40–49 years, III (n = 38) – 50–59 years, IV (n = 46) – 60–69 years, V (n = 39) – 70–79 years old. Echocardiography with Doppler in continuous-wave, pulse modes and colour mapping of flow and tissue was performed on a device Xario SSA-660A (Toshiba, Japan), sensor – PST-30BT 3.0 MHz. The state of systolic and diastolic function of the ventricles of the heart was assessed, myocardial stiffness indicators were calculated. To obtain BA formula, the calculation of the multiple linear regression equation was used based on significant features. Results. Significant increase in atrial size with age, development of diastolic dysfunction, increase in left and right ventricular myocardial infarction were found. Based on the data of the study by the method of step-by-step multiple linear regression, a formula for estimating the biological age of the human heart was obtained. The multiple correlation coefficient was a fairly high value of R = 0.847, the adjusted coefficient of determination R2 = 0.701 (F = 43.496, P ˂ 0.00001). The mean absolute error of age calculation (M ± σ) was 5.55 ± 4.24 years. The proposed formula for determining the biological age of the heart can be used for early diagnosis of accelerated aging. Conclusions. An increase in the size of the atria, the development of concentric hypertrophy of the left atrium and diastolic dysfunction, and an increase in the myocardial stiffness of the left and right ventricles of the heart, which occur with age in practically healthy people, were revealed. A formula for determining the BA of the heart with good model quality was developed using the multiple linear regression method taking into account age-related changes in the echocardiographic parameters.

Validation of the ukrainian version of Binge Eating Scale

The article presents the results of validation of the Ukrainian ver- sion of the Binge Eating Scale (BES), the psychometric properties of which have not yet been tested among the Ukrainian-speaking population. The BES is a questionnaire de- signed to identify and diagnose in- dividuals suffering from Binge-eating disorder (BED). The aim of the work was to check the psychometric properties of the Ukrainian version of BES, to es- tablish the factor structure, internal consistency and constructive validity in the sample of Ukrainian youth. A cross-sectional study of 87 par- ticipants was conducted: students from different higher education in- stitutions who could read and write in the Ukrainian language. To char- acterize the criterion of validity, the BES was compared with the data of the clinical criteria for BED on DSM- 5, which in this study is considered the gold standard for the diagnosis of BED. The Ukrainian version of BES dem- onstrated a standardized Cronbach’s alpha of 0.885, showing good internal consistency close to high (0.9). The split half size was 0.899, indi- cating a very high split half. The corre- lation between the halves of the test was 0.766720035, which indicates a fairly high reliability in terms of in- ternal consistency. Factor analysis showed a two- factor structure. This explained only 46.2 % of the variance. The ROC analysis found that the re- sulting area under the curve (AUC) was 0.811 (95 % CI: 0.713; 0.887), indicating good model quality. The results of our study confirm the psychometric reli- ability of the BES, high design and criterion validity. Thus, the Ukrainian version of BES has psychometric char- acteristics close to the original.

Experimental and computational analysis of the coolant distribution considering the viscosity of the cutting fluid during machining with helical deep hole drills

An experimental analysis regarding the distribution of the cutting fluid is very difficult due to the inaccessibility of the contact zone within the bore hole. Therefore, suitable simulation models are necessary to evaluate new tool designs and optimize drilling processes. In this paper the coolant distribution during helical deep hole drilling is analyzed with high-speed microscopy. Micro particles are added to the cutting fluid circuit by a developed high-pressure mixing vessel. After the evaluation of suitable particle size, particle concentration and coolant pressure, a computational fluid dynamics (CFD) simulation is validated with the experimental results. The comparison shows a very good model quality with a marginal difference for the flow velocity of 1.57% between simulation and experiment. The simulation considers the kinematic viscosity of the fluid. The results show that the fluid velocity in the chip flutes is low compared to the fluid velocity at the exit of the coolant channels of the tool and drops even further between the guide chamfers. The flow velocity and the flow pressure directly at the cutting edge decrease to such an extent that the fluid cannot generate a sufficient cooling or lubrication. With the CFD simulation a deeper understanding of the behavior and interactions of the cutting fluid is achieved. Based on these results further research activities to improve the coolant supply can be carried out with great potential to evaluate new tool geometries and optimize the machining process.

Cardiac Function Index as a Possible Target Parameter Hemodynamic Correction in Abdominal Sepsis (Pilot Study)

Aim of the study: to determine the predictive value of central hemodynamic parameters in relation to mortality and evaluate their potential acceptability for goal-directed therapy during days 1-4 of treatment in patients with sepsis.Material and methods. The results of investigation and treatment of 62 patients aged 50.9±2.13 years with abdominal sepsis were analyzed. The patient severity on admission to the intensive care unit was 13 [10-15] on the APACHE II scale, 8 [6.75-9.25] on the SOFA scale. Lethal outcome 15.6±1.4 days after admission occurred in 19 (31%) patients. Central hemodynamic parameters were studied by transpulmonary thermodilution according to the standard technique. Infusions and administration of sympathomimetic drugs were performed according to Sepsis-3 guidelines. Statistical analysis was performed using logistic regression and ROC analysis.Results. The median values of the main circulatory parameters during days 1-4 of sepsis treatment were within normal ranges. Cardiac index, afterload-related cardiac performance, global cardiac ejection fraction and cardiac function index were predictors of mortality at all stages of treatment. However, the first three parameters did not provide either sufficient model quality at the study stages or a stable cutoff value with acceptable sensitivity and specificity. The cardiac function index maintained good model quality (area under the ROC curve 0.708-0.753) and a stable cutoff value (≤5.75 to ≤5.81 min-1) with acceptable and balanced sensitivity and specificity of about 70% at all study stages.Conclusion. The cardiac index, afterload cardiac performance, global cardiac ejection fraction and cardiac function index during days 1-4 of intensive care of sepsis are predictors of lethal outcome. At the same time, only the cardiac function index maintains good model quality and consistent cut-off point value with acceptable sensitivity and specificity at all stages of the study. The feasibility of using the cardiac function index as one of the parameters of goal-directed therapy aimed at cardiovascular function improvement in sepsis needs further investigation.

Evaluation of the validity of the nSOFA score in newborns with sepsis

The objective of the study is to evaluate the discriminative ability of nSOFA in newborns with sepsis.Subjects: The study was designed as retrospective, observational, and one-center. End points included assessment of the severity as per nSOFA and pSOFA; 28-day survival. 121 patients were enrolled in the study. Microsoft Excel (Graphpad Software, San Diego, California, USA) and MedCalc (v 7.1.0.0; MedCalc Software, Belgium) were used for the analysis.Results. A study of the discriminative power of the scores showed that both assessment systems had a good model quality. However, nSOFA had a statistically more significant (p < 0.05) area under the ROC curve (0.981± 0.014).Conclusion. The high value of the discriminative ability of the nSOFA scale indicates the feasibility of its use in patients with sepsis in neonatal intensive care units

Data Life Aware Model Updating Strategy for Stream-Based Online Deep Learning

Many deep learning applications deployed in dynamic environments change over time, in which the training models are supposed to be continuously updated with streaming data to guarantee better descriptions of data trends. However, most state-of-the-art learning frameworks support well in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">offline</i> training methods while omitting <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">online model updating</i> strategies. In this work, we propose and implement <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">iDlaLayer</i> , a thin middleware layer on top of existing training frameworks that streamlines the support and implementation of online deep learning applications. In pursuit of good model quality and fast data incorporation, we design a Data Life Aware model updating strategy (DLA), which builds training data samples according to contributions of data from different life stages, and considers the training cost consumed in model updating. We evaluate iDlaLayer's performance through simulations and experiments based on TensorflowOnSpark with three representative online learning workloads. Our experimental results demonstrate that iDlaLayer reduces the overall elapsed time of ResNet, DeepFM and PageRank by 11.3, 28.2, and 15.2 percent compared to the periodic update strategy, respectively. It further achieves an average 20 percent decrease in training cost and brings about a 5 percent improvement in model quality against the traditional continuous training method.

Prognostic value of the pSOFA and PELOD 2 scales in assessing the risk of death in neonatal intensive care units

Objective. To assess the discriminatory ability of the PELOD 2 and pSOFA scales in the conditions of multidisciplinary neonatal intensive care unit. Material and methods . It is a prospective, observational, single-center study. The end points are to assess the severity of the condition on the PELOD 2 and pSOFA scales; 28-day survival. The study includes 121 patients. Results. While studying the discriminating power of the scales we have found that all scales have good model quality. At the same time, the pSOFA evaluation system has a statistically more significant (p<0.05) area under the ROC curve (0.903±0.09). Our analysis has not found significant differences in the characteristics of surrogate endpoints between the compared scales in the conditions of comparable points of separation of death risks (p<0.05). Conclusion. The high discrimination ability of the pSOFA scale allows us to recommend it for clinical use in neonatal intensive care units.

A Novel Urease Inhibitor of Ruminal Microbiota Screened through Molecular Docking.

Inhibition of the urease activity of ruminal microbiota is not only beneficial for increasing dietary and endogenic urea-N utilization efficiency in ruminants but also might be applicable for the preservation of nitrogen fertilizer in soil and treatment of gastrointestinal and urinary tract infections caused by ureolytic bacteria. To discover urease inhibitors to efficiently target ruminal microbiota, the identified ruminal microbial metagenomic urease gene was used to construct a homology model to virtually screen urease inhibitors from the ChemDiv database by molecular docking. The GMQE and QMEAN values of the homology model were 0.85 and −0.37, respectively, indicating a good model quality. The inhibition effect of the screened urease inhibitor for ruminal urea degradation was assessed by ruminal microbial fermentation in vitro. The toxic effect of the candidate inhibitor was performed using gut Caco-2 cells in vitro. The results showed that compound 3-[1-[(aminocarbonyl)amino]-5-(4-methoxyphenyl)-1H-pyrrol-2-yl] propanoic acid (ChemDiv_ID: 6238-0047, IC50 = 65.86 μM) was found to be the most effective urease inhibitor among the candidate compounds. Compound 6238-0047 significantly lowered the amount of urea degradation and ammonia production in ruminal microbial fermentation. The 24 h degradation rate of compound 6238-0047 in ruminal microbial fermentation was 3.32%–16.00%. In addition, compound 6238-0047 (10–100 μM) had no significant adverse effect on the cell viability of Caco-2 cells. Molecular docking showed that compound 6238-0047 could interact with Asp359 in the active site and Cys318 in the flap region by the hydrogen bond and Pi-Alkyl interaction, respectively. Compound 6238-0047 could be used as a novel inhibitor for decreasing the urease activity of ruminal microbiota.

Contrast Echocardiography with a Quantitative Assessment of Myocardial Perfusion in Patients with Previous Q-Wave Myocardial Infarction

To assess possibilities of contrast echocardiography with quantitative evaluation of myocardial perfusion in patients with previous Q-wave myocardial infarction. We examined 15 men (42-72 years) with coronary artery disease and previous myocardial infarction, and pathological Q-wave in 2 or more ECG leads. Quantification of left ventricular (LV) myocardial perfusion was performed by calculating of the ultrasound signal tissue intensity from the LV myocardial segments during intravenous administration of the ultrasound contrast agent (SonoVue). The Tissue intensive curve (TIC) analysis was done in the end-diastolic period before and on the fourth cardiac cycle after applying the "flash". Changes in the intensity of myocardial perfusion (A4, dB) was estimated as the difference between the intensity values of the ultrasound signal in the myocardial segment during the period of filling the contrast bubbles on 4-th cardiac cycle and before applying the «flash». Measurements were performed in 16 segments of the LV. A contrast cardiac magnetic resonance imaging (contrast MRI) was performed in order to verify the LV scar. Fibrotic changes of 50% of myocardial wall or more were considered as signs of post-infarction scar. The dynamics of perfusion and scar presence in 240 myocardial segments were evaluated. The median A4 was 1 dB (range, -20 to 10 dB). MRI revealed 82 of 240 segments with the large-focal scar. The effectiveness of the diagnostic test (quantitative contrast perfusion echocardiography with A4 assessment) to detect myocardial scar was investigated. ROC curve analysis showed good model quality, AUC=0,787 (0,730-0,837); sensitivity 82.9%; specificity 75.3%; p&lt;0.01. The cut-off point for A4 was -1. A new approach to quantitative contrast assessment of perfusion allows to identify perfusion disorders with high efficiency in patients with previous Q-wave myocardial infarction.

Dengue Severity Risk Factors in New Caledonia - Design of Predictive Tool Usable By Doctors during the First Consultation

Objectives: In New Caledonia (NC), Dengue circulation was detected every year since last decade. The 2017 epidemic have affected 4,379 people with 11.5% of hospital admission and 15 deaths. The aim of this work is to study the risk factors of severe dengue during the 2017 outbreak and to develop a predictive tool, based on a model, usable by doctors during the first consultation to early assess the risk for a dengue patient to progress to a severe form. Study design: This is a non-interventional retrospective study in which a cohort of hospitalized and non-hospitalized cases, positive for dengue virus infection by qRTPCR was documented. Methods: Patients were classified in severe or non-severe dengue. We explored the association of dengue severity to patients’ characteristics, symptoms at the first consultation, dengue serotype and previous Zika and dengue infection. A predictive model of the severity usable at first consultation was built using a multivariate analysis and a cross-validation procedure. Results: A total of 771 dengue cases were studied, with 134 patients who developed severe dengue fever. The dengue serotype does not appear to influence the severity of the infection, whereas, an anterior dengue seems to be significantly related to a severe form. We created two predictive models based on patient characteristics and clinical signs, one for and one for men because of the sex and age class interaction. For both models, the variables were: age, selfdeclared ethnicity, alert signs (mucosal bleedizg, clinical liquid accumulation, abdominal pain, lethargy or anxiety) and for women model added variables were arterial hypertension, platelet aggregation inhibitor and anticoagulants treatments. The average and median AUC values for both models are > 0.80 which shows a fairly good model quality; moreover high negative predictive values (> 95%) indicate that models are quite protective. Conclusion: This study described severity and risk factors for both hospitalized and non-hospitalized patients. The developed models can be used at the first consultation and doctors will be able to early assess the risk for dengue patient to progress to a severe form and increased surveillance with possible hospitalization.

DIABETES RISK AND ASSOCIATIONS WITH DEMOGRAPHIC AND BEHAVIORAL FACTORS IN RUSSIAN POPULATION: DATA FROM THE ESSE-RF STUDY

Aim. To evaluate 10-year risk of potential development of type 2 diabetes (DM) in Russian population with the FINDRISC score, and to assess its associations with social, demographic and behavioral factors by the data from epidemiological study ESSE-RF. Material and methods. In the work, the data used, from multi-center study (Epidemiology of cardiovascular diseases in various regions of Russian Federation: ESSE-RF). Totally, 21923 persons investigated, age 25-64 y.o., of those 1045 (3,76% males, 5,39% females) had DM. To the final analysis 20878 persons included (8058 males, 12820 females) with no DM, for whom the 10-year risk was assessed with the FINDRISC (The FINnish Diabetes RIsk SCore). Level of risk and probability of DM onset were evaluated by the points summation. Also, associations were analyzed with education, marital status, place of inhabitance, income, smoking and alcohol status. Results. The threshold for high DM risk in Russian population was set at ≥12 level, with AUC 0,76, that represents good quality of model. The prevalence of the high risk by Russian criteria was 20,4%. Multifactorial analysis demonstrated that after correction for region and age, DM high risk was associated with smoking cessation (odds ratio (OR) 1,34; 95% confidence interval (CI) 1,14-1,58; р=0,0004) and alcohol consumption (OR 2,01; 95% CI 1,48-2,71; р=0,0001), and in women — with low income, low educational level and being married. Conclusion. Mean score by FINDRISC was 6,5±0,03, and absolute risk 5,3%. There were associations found of higher DM risk (≥12 points) with behavioral factors in males and social-demographic factors in women.

Shikimate Kinase of Yersinia pestis: A Sequence, Structural and Functional Analysis

Yersinia pestis, the causative organism of Plague, is widely recognized as a potential bioterrorism threat. Due to the absence of homologs in human, Shikimate Kinase (SK) is considered as an excellent drug target in several bacterial and protozoan parasites. Ample literature evidences confirm the suitability of this protein as a good target. Therefore, Shikimate Kinase of Shikimate pathway in Yersinia pestis represents an attractive drug target. In the present study, a clustering approach was undertaken to select the proper representative for Shikimate Kinase sequences belonging to Yersinia pestis for structure determination. Three-dimensional models of the enzyme for KFB61218.1 (SK1), EFA47400.1 (SK2) and WP_016255950.1 (SK3) were generated using a comparative molecular modeling approach where structures were developed using the single specific template as well as multiple closely associated templates. The structures of Shikimate Kinase developed using comparative modeling were evaluated for stereochemical quality using various structural validation tools. Results from structural assessment tools indicated the reasonably good quality of models.

Can’t See the Trees for the Forest? Why IS-ServQual Items Matter

Despite longstanding concern with the dimensionality of the service quality construct as measured by ServQual and IS-ServQual instruments, variations on the IS-ServQual instrument have been enduringly prominent in both academic research and practice in the field of IS. We explain the continuing popularity of the instrument based on the salience of the item set for predicting overall customer satisfaction, suggesting that the preoccupation with the dimensions has been a distraction. The implicit mutual exclusivity of the items suggests a more appropriate conceptualization of IS-ServQual as a formative index. This conceptualization resolves the paradox in IS-ServQual research, that of how an instrument with such well-known and well-documented weaknesses continue to be very influential and widely used by academics and practitioners. A formative conceptualization acknowledges and addresses the criticisms of IS-ServQual, while simultaneously explaining its enduring salience by focusing on the items rather than the “dimensions.” By employing an opportunistic sample and adopting the most recent IS-ServQual instrument published in a leading IS journal (virtually, any valid IS- ServQual sample in combination with a previously tested instrument variant would suffice for study purposes), we demonstrate that when re-specified as both first-order and second-order formatives, IS-ServQual has good model quality metrics and high predictive power on customer satisfaction. We conclude that this formative specification has higher practical use and is more defensible theoretically.

PP.06.39

Objective: Single nucleotide polymorphisms (SNPs) can contribute to differences in the prevalence of common complex diseases such as cardiovascular disease (CVD). The arterial stiffness (AS) is well recognized as an intermediate phenotype of CVD. AS is complex in origin, with contributions from lifestyle and genetic factors. However, the association between SNPs and generally increased AS remains unclear. In the current study we assessed whether or not the multi-locus genetic risk score (GRS) based on selected SNPs are associated with AS in Polish hypertensive cohort. Design and method: The study population included subjects (N = 669, mean age 54,45 ± 13,53) from the Care North cohort. AS was assessed as carotid-femoral pulse wave velocity (PWV). All subjects were genotyped for 171 SNPs previously shown to be associated with CVD and its risk. Linear regression assuming an additive model was applied to identify and compare the effect size of tested SNPs. For GRS construction, SNPs significant at p-value <0.1 were selected. The association between GRS and PWV was analyzed using linear regression and Kruskall-Wallis test in unadjusted and adjusted models. Results: Factors such as age, gender, 24-hour pulse pressure, kidney function and obesity explained 41.41% PWV variance and were included into adjusted model. In unadjusted and adjusted model 15 and 17 SNPs were selected, respectively. SNPs were associated with blood pressure, lipid concentration and risk of myocardial infarction and coronary artery disease. Each genetic risk score explained a greater proportion of PWV variance than any individual SNP (from 0.24 to 0.89% variance explained). Adjusted and unadjusted GRS explained 8.42% and 6.83% PWV variance, respectively. Similar results were obtained by internal validation what confirmed the good quality of models. The linear association between GRS and PWV was observed. The differences between the PWV mean values in quartiles of GRS were highly statistically significant: p-value 2,48 × 10–11 and 8,06 × 10–9 for unadjusted and adjusted models, respectively (Fig.).Conclusions: Our findings indicate that GRS was associated with AS independently of age, gender, blood pressure, kidney function and obesity in Polish hypertensive population. This implies that GRS may help to identify patients at greater risk for increased AS.

Testing selected optimal descriptors with artificial neural networks

Eleven properties have been modeled with the objective of checking the importance for model purposes of mixed descriptors made of empirical parameters, molecular connectivity indices and random numbers. The mixed descriptors with random indices have a descriptive character which is satisfactorily confirmed by the leave-one-out method of statistical analysis. The introduction of a partition of the set of compounds into training and evaluation sets decreases drastically the probability to find a mixed descriptor with random indices with good model quality. Two properties, the magnetic susceptibility and the elutropic values, insist on having optimal descriptors with random indices. The overall model study underlines the importance of semiempirical descriptors made of experimental parameters and molecular connectivity indices, as well as the importance of a perturbation parameter that has been introduced into the valence delta number to encode the contribution of the depleted hydrogen atoms. The use of complete graphs to encode the core electrons of higher-row atoms is also underlined. The model quality of the mixed descriptors obtained with combinatorial regressive methods has also been tested with three-layered feed-forward artificial neural network (ANN) methods. This methodology not only confirms the validity of the descriptors but also improves their model quality widening, thus, their predictive ability.

In Silico Structural Analysis and Characterization of Human Kiss-1 Receptor: A Metastasis Suppressor Protein in Melanomas and Breast Cancer

Metastasis, a major cause of death in cancer patients, involves the spread of a tumor or cancer to distant parts of the body as primary cancer, invasion of surrounding tissue, spread through circulation, re-invasion and proliferation in distant organs. KiSS1 is a metastasis-suppressor protein that suppresses metastases in malignant melanomas and in some breast carcinomas, without affecting tumorigenicity and also may be mediated in part by cell cycle arrest and induction of apoptosis in malignant cells. To understand the operational mechanism, structural model is always important. Therefore, in present study a complete structural analysis and three- dimensional (3D) modeling of KiSS-1 receptor, with a molecular weight of 42,586 kDa, of Homo sapiens was carried out. The 398 amino acid sequence of the KiSS-1 receptor protein was retrieved from Uniprot KB database (Acc. no: Q969F8). Based on the PDB Blast result and analysis the three-dimensional structure of KiSS-1R was predicted by using the SWISS MODEL, ESyPred 3D protein comparative modeling server. The predicted model was further assessed by Rampage, VERIFY-3D and PROCHECK graph with acceptable scores. The overall result provides evidence of good quality of model and furnishes an adequate foundation for functional analysis of experimentally derived crystal structures and also helps in understanding metastasis.

Robust Gaussian Process Modelling For Engine Calibration

AbstractThe performance of model-based engine calibration is highly dependent on the type of modelling which is used. A problem for state of the art algorithms for engine calibration arises, if outliers occur in the measurement data. Since outliers are not considered in recent types of modelling for engine calibration, they have to be removed before model training, in order to get a good model quality and a good prediction. This has serious drawbacks because either manual interaction is needed to identify the outliers, or automatic detection of outliers is not very robust if there are many outliers in the measurement data. In contrast to state of the art algorithms, a gaussian process modelling is presented, which is robust to outliers. After an introduction, the state of the art of modelling in engine calibration is presented and the drawbacks regarding outliers are shown. This is followed by a robust gaussian process formulation. At the end a simple theoretical example and an application on a diesel engine are given.

Aspartate carbamoyltransferase of Plasmodium falciparum as a potential drug target for designing anti-malarial chemotherapeutic agents

Malaria remains one of the leading causes of deaths attributable to a communicable disease globally. The reemergence of drug-resistant Plasmodium falciparum, the most fatal human malarial parasite, has necessitated the exploration of different pathways to provide the urgently required novel drug targets. Aspartate carbamoyltransferase, an enzyme of de novo pyrimidine biosynthetic pathway in Plasmodium represents an attractive drug target. The enzyme was characterized using in silico tools. Tertiary (3D) structure of the enzyme was generated using the structure of Aspartate carbamoyltransferase of Pyrococcus abyssi (PDB ID: 1ML4) as template by comparative modeling and validated by various structural quality validation tools. The model was stable during the simulation with the equilibrium root-mean-square standard deviation value of ~1 A. Results from structure assessment tools indicated the reasonably good quality of model. Several inhibitor molecules were docked in the active site of the modeled protein for determining the binding affinity of these molecules toward the protein. Out of various inhibitors used in the study, 3-(4-Hydroxy-phenyl)-2-(2-phosphono-acetylamino)-propionic acid showed highest binding affinity towards ACT. This study provides new insights towards understanding the 3-D Pf ACT structure and binding affinity of selected inhibitor compounds and also paves a way for designing novel anti-malarials.

Modelling potential distribution of the threatened tree species Juniperus oxycedrus: how to evaluate the predictions of different modelling approaches?

AbstractQuestions: How can predictions of potential species distribution derived from presence‐only data and different modelling algorithms be compared and evaluated? Where does suitable habitat for Juniperus oxycedrus exist within the study area and which bioclimatic variables prove to be most important in the prediction of J. oxycedrus potential distribution?Location: Central High Atlas, Morocco.Methods: Ecological niche factor analysis (ENFA), maximum entropy approach (MAXENT) and generalized linear models (GLM) were applied to either presence‐only data of J. oxycedrus (ENFA and MAXENT) or presence–absence data (GLM), using bioclimatic variables as predictors. Model accuracy of ENFA, MAXENT and GLM was assessed using their specific evaluation measures and prediction success by means of the minimal predicted area (MPA). Finally, the three maps of potential species distribution were intersected to investigate their consistency in the geographic distribution of predicted suitable habitat.Results: Species distribution models calculated by ENFA, MAXENT and GLM show good model quality according to their evaluation measures. However, calculation of MPA revealed considerable discrepancies in geographic distribution and spatial extent of areas predicted as suitable habitat for J. oxycedrus.Conclusion: Suitable habitat for J. oxycedrus is predicted using all applied modelling approaches in 8% of the study area (mostly the north‐western part). MAXENT gave the best results considering model accuracy and prediction success according to the MPA scores. Predictors representing maximum temperature and potential radiation were selected in all methods to explain species occurrences. This points to a possible shift of the species' potential distribution in cases of a rise in summer temperature due to climate change.