In this paper, the effects of process‐induced voids and surface roughness on the fatigue life of an additively manufactured material are investigated using a crack closure‐based fatigue crack growth ...model. Among different sources of damage under cyclic loadings, fatigue because of cracks originated from voids and surface discontinuities is the most life‐limiting failure mechanism in the parts fabricated via powder‐based metal additive manufacturing (AM). Hence, having the ability to predict the fatigue behaviour of AM materials based on the void features and surface texture would be the first step towards improving the reliability of AM parts. Test results from the literature on Inconel 718 fabricated via a laser powder bed fusion (L‐PBF) method are analysed herein to model the fatigue behaviour based on the crack growth from semicircular/elliptical surface flaws. The fatigue life variations in the specimens with machined and as‐built surface finishes are captured using the characteristics of voids and surface profile, respectively. The results indicate that knowing the statistical range of defect size and shape along with a proper fatigue analysis approach provides the opportunity of predicting the scatter in the fatigue life of AM materials. In addition, maximum valley depth of the surface profile can be used as an appropriate parameter for the fatigue life prediction of AM materials in their as‐built surface condition.
Lipoprotein lipase (LPL) deficiency, a rare inherited metabolic disorder, is characterized by high triglyceride (TG) levels and life-threatening acute pancreatitis. Current treatment for pediatric ...patients involves a lifelong severely fat-restricted diet, posing adherence challenges. Volanesorsen, an EMA-approved RNA therapy for adults, effectively reduces TG levels by decreasing the production of apolipoprotein C-III. This 96-week observational open-label study explores Volanesorsen's safety and efficacy in a 13-year-old female with LPL deficiency.
The patient, with a history of severe TG elevations, 53 hospital admissions, and life-threatening recurrent pancreatitis despite dietary restrictions, received weekly subcutaneous Volanesorsen injections. We designed a protocol for this investigator-initiated study, primarily focusing on changes in fasting TG levels and hospital admissions.
While the injections caused occasional pain and swelling, no other adverse events were observed. TG levels decreased during treatment, with more measurements below the pancreatitis risk threshold compared to pre-treatment. No hospital admissions occurred in the initial 14 months of treatment, contrasting with 21 admissions in the 96 weeks before. In the past 10 months, two pancreatitis episodes may have been linked to dietary noncompliance. Dietary restrictions were relaxed, increasing fat intake by 65% compared to baseline. While not fully reflected in the PedsQL, both parents and the patient narratively reported an improved quality of life.
This study demonstrates, for the first time, that Volanesorsen is tolerated in a pediatric patient with severe LPL deficiency and effectively lowers TG levels, preventing life-threatening complications. This warrants consideration for expanded access in this population.
There are several parameters that highly influence material quality and printed shape in laser Directed Energy Deposition (L-DED) operations. These parameters are usually defined for an optimal ...combination of energy input (laser power, scanning speed) and material feed rate, providing ideal bead geometry and layer height to the printing setup. However, during printing, layer height can vary. Such variation affects the upcoming layers by changing the printing distance, inducing printing to occur in a defocus zone then cumulatively increasing shape deviation. In order to address such issue, this paper proposes a novel intelligent hybrid method for in-process estimating the printing distance (
Z
s
) from melt pool images acquired during L-DED. The proposed hybrid method uses transfer learning to combine pre-trained Convolutional Neural Network (CNN) and Support Vector Regression (SVR) for an accurate yet computationally fast methodology. A dataset with 2,700 melt pool images was generated from the deposition of lines, at 60 different values of
Z
s
, and used for training. The best hybrid algorithm trained performed with a Mean Average Error (MAE) of 0.266 and a Mean Absolute Percentage Error (MAPE) of
6.7
%
. The deployment of this algorithm in an application dataset allowed the printing distance to be estimated and the final part geometry to be inferred from the data.
Additive manufacturing (AM) requires a significant capital investment to acquire a machine, procure raw material, and train operators to begin production. This substantial overhead means ...interruptions to the AM build process can become a costly event if the interruption results in significantly reduced build quality. Interruptions in the form of power outages, lack of powder feedstock, and/or loss of shielding gas can cause the machine to operate in an unintended manner, interrupting the build and potentially even stopping the entire process. An interrupted laser powder bed fusion process could result in reduced mechanical properties, localized failures, and physical characteristics that distinguish an interrupted component from a continuous one. This investigation aims to explore the effect of various build interruption conditions (i.e., duration of the interruption and air exposure) on microstructural and mechanical properties of Al-Si-10Mg fabricated via a laser powder bed fusion (LPBF) system. Seven builds were completed for this study, a control along with six interruption experiments with three distinct time lengths for the interruption periods: 15 min, 12 and 24 h. Each interruption period was repeated to explore the effects of air exposure during the stoppage. The effects of interruptions were characterized by x-ray computed tomography, optical microscopy, scanning electron microscopy, Vickers microhardness, and destructive oxide testing. Strain rate-controlled tension tests were conducted to determine mechanical properties. Results indicated no reduction in mechanical properties (i.e., tensile and micro-hardness) for any of the interrupted specimens when compared to the control and literature on LPBF-processed Al-Si-10Mg. However, the 24-h group specimens experienced the most failures near the interruption location, indicating that failure location can be influenced by prolonged stoppage and air exposure.
Clozapine is an effective atypical antipsychotic drug applied in the treatment of resistant schizophrenia. The drug is mainly metabolized by cytochrome P-450 (CYP) enzymes especially the isozyme ...CYP1A2. Remarkably, the effective dosage varies widely among patients, making it necessary to individualize drug therapy with clozapine. The explanation for dosage variation may be differences in drug metabolism, and more specifically of CYP1A2 activity. This study is aimed at determining to what extent variability in clozapine dose can be explained by pharmacokinetic (PK) factors and more specifically by CYP1A2 activity in effectively treated psychiatric patients.
In 22 evaluable patients with a schizophrenic disorder chronically using clozapine, the CYP1A2 activity and the clozapine clearance were estimated. For calculation of the pharmacokinetic parameters of clozapine, population PK software based upon Bayesian analysis was used. Caffeine clearance was estimated with the paraxanthine/caffeine ratio and served as estimate of CYP1A2 activity.
A significant linear relationship was found between the clozapine dose and clozapine clearance (
R: 0.71;
P<0.05), whereas no relationship was found between clozapine dosage and clozapine serum trough concentration. Moreover, individual caffeine and clozapine clearances were found to be significantly related (
R: 0.62;
P<0.05) as were clozapine dose per kg body weight and P/C mol ratio (
R: 0.44;
P<0.05).
We conclude that CYP1A2 activity is an important determinant of the variability of effective clozapine doses in psychiatric patients.
Cytochrome P450 1A2 (CYP1A2) plays an important role in drug metabolism. Provocation with caffeine is used to estimate CYP1A2 activity, but in most tests a long period of caffeine abstinence has to ...be taken into account. We compared two novel methods with the currently applied test.
The pharmacokinetic (PK) parameters of caffeine and paraxanthine were estimated in eight caffeine‐taking healthy volunteers by fitting serum concentration–time data to a two‐compartment PK model. Then a three‐step approach was followed. Step 1: The caffeine administration regimens of three provocation methods, which differ by their periods of abstinence, together with the PK parameters of each volunteer, were entered in a PK simulation program and the molecular ratio of the paraxanthine/caffeine concentration (P/C molratio) of each method was estimated for the individual volunteers. Step 2: For each method a relationship for the population between the caffeine clearance (Clc) and the corresponding P/C molratio was empirically established. Step 3: The true caffeine clearance (Clc tr) of each volunteer, as found by fitting the individual PK curve, was compared for all three methods with the clearance estimated from the individual P/C molratio using the relationship of step 2. The predictive values for Clc of the three methods did not differ significantly from Clc tr. For the three methods the values for bias were 6.7, 4.3 and 3.1%, respectively and for precision they were 12.3, 20.6 and 17.8%.
We conclude that the two novel methods of caffeine provocation show good predictive performance for Clc when compared with the conventional method. Abstaining from caffeine for a long period is not necessary to estimate CYP1A2 activity (using the P/C molratio) accurately.
