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| 2. |
- Amare, Azmeraw, et al.
(author)
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Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.
- 2023
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In: Research square. - : Research Square Platform LLC.
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Journal article (peer-reviewed)abstract
- Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.
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| 3. |
- Amare, Azmeraw T, et al.
(author)
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Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.
- 2023
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In: Molecular psychiatry. - 1476-5578. ; 28, s. 5251-5261
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Journal article (peer-reviewed)abstract
- Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental healthdisorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P=9.8×10-12, R2=1.9%) and continuous (P=6.4×10-9, R2=2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P=3.9×10-4, R2=0.9%), but not for the continuous outcome (P=0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
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| 5. |
- Bleiker, Simon J., et al.
(author)
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Cost-Efficient Wafer-Level Capping for MEMS and Imaging Sensors by Adhesive Wafer Bonding
- 2016
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In: Micromachines. - Basel, Switzerland : Multidisciplinary Digital Publishing Institute (MDPI). - 2072-666X. ; 7:10, s. 192-
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Journal article (peer-reviewed)abstract
- Device encapsulation and packaging often constitutes a substantial part of the fabrication cost of micro electro-mechanical systems (MEMS) transducers and imaging sensor devices. In this paper, we propose a simple and cost-effective wafer-level capping method that utilizes a limited number of highly standardized process steps as well as low-cost materials. The proposed capping process is based on low-temperature adhesive wafer bonding, which ensures full complementary metal-oxide-semiconductor (CMOS) compatibility. All necessary fabrication steps for the wafer bonding, such as cavity formation and deposition of the adhesive, are performed on the capping substrate. The polymer adhesive is deposited by spray-coating on the capping wafer containing the cavities. Thus, no lithographic patterning of the polymer adhesive is needed, and material waste is minimized. Furthermore, this process does not require any additional fabrication steps on the device wafer, which lowers the process complexity and fabrication costs. We demonstrate the proposed capping method by packaging two different MEMS devices. The two MEMS devices include a vibration sensor and an acceleration switch, which employ two different electrical interconnection schemes. The experimental results show wafer-level capping with excellent bond quality due to the re-flow behavior of the polymer adhesive. No impediment to the functionality of the MEMS devices was observed, which indicates that the encapsulation does not introduce significant tensile nor compressive stresses. Thus, we present a highly versatile, robust, and cost-efficient capping method for components such as MEMS and imaging sensors.
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| 6. |
- Blondin, Stéphane, et al.
(author)
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StaNdaRT : a repository of standardised test models and outputs for supernova radiative transfer
- 2022
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 668
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Journal article (peer-reviewed)abstract
- We present the first results of a comprehensive supernova (SN) radiative-transfer (RT) code-comparison initiative (StaNdaRT), where the emission from the same set of standardised test models is simulated by currently used RT codes. We ran a total of ten codes on a set of four benchmark ejecta models of Type Ia SNe. We consider two sub-Chandrasekhar-mass (Mtot = 1.0 M⊙) toy models with analytic density and composition profiles and two Chandrasekhar-mass delayed-detonation models that are outcomes of hydrodynamical simulations. We adopt spherical symmetry for all four models. The results of the different codes, including the light curves, spectra, and the evolution of several physical properties as a function of radius and time are provided in electronic form in a standard format via a public repository. We also include the detailed test model profiles and several Python scripts for accessing and presenting the input and output files. We also provide the code used to generate the toy models studied here. In this paper, we describe the test models, radiative-transfer codes, and output formats in detail, and provide access to the repository. We present example results of several key diagnostic features.
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| 7. |
- Maenpaa, Johanna, et al.
(author)
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The use of granulocyte colony stimulating factor (G-CSF) and management of chemotherapy delivery during adjuvant treatment for early-stage breast cancer-Further observations from the IMPACT solid study
- 2016
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In: Breast. - : Elsevier BV. - 0960-9776 .- 1532-3080. ; 25, s. 27-33
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Journal article (peer-reviewed)abstract
- Objective: To investigate the use and impact of granulocyte colony-stimulating factors (G-CSF) on chemotherapy delivery and neutropenia management in breast cancer in a clinical practice setting. Methods: IMPACT Solid was an international, prospective observational study in patients with a physician-assessed febrile neutropenia (FN) risk of >= 20%. This analysis focused on stages I-III breast cancer patients who received a standard chemotherapy regimen for which the FN risk was published. Chemotherapy delivery and neutropenia-related outcomes were reported according to the FN risk of the regimen and intent of G-CSF use. Results: 690 patients received a standard chemotherapy regimen; 483 received the textbook dose/schedule with a majority of these regimens (84%) having a FN risk >= 10%. Patients receiving a regimen with a FN risk >= 10% were younger with better performance status than those receiving a regimen with a FN risk < 10%. Patients who received higher-risk regimens were more likely to receive G-CSF primary prophylaxis (48% vs 22%), complete their planned chemotherapy (97% vs 88%) and achieve relative dose intensity >= 85% (93% vs 86%) than those receiving lower-risk regimens. Most first FN events (56%) occurred in cycles not supported with G-CSF primary prophylaxis. Conclusion: Physicians generally recommend standard adjuvant chemotherapy regimens and were more likely to follow G-CSF guidelines for younger, good performance status patients in the curative setting, and often modify standard regimens in more compromised patients. However, G-CSF support is not optimal, indicated by G-CSF primary prophylaxis use in < 50% of high-risk patients and observation of FN without G-CSF support.
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| 8. |
- Szipka, Karoly, et al.
(author)
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Identification of machine tool squareness errors via inertial measurements
- 2019
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In: CIRP annals. - : Elsevier BV. - 0007-8506 .- 1726-0604. ; 68:1, s. 547-550
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Journal article (peer-reviewed)abstract
- The accuracy of multi-axis machine tools is affected to a large extent by the behavior of the system's axes and their error sources. In this paper, a novel methodology using circular inertial measurements quantifies changes in squareness between two axes of linear motion. Conclusions are reached through direct utilization of measured accelerations without the need for double integration of sensor signals. Results revealed that the new methodology is able to identify squareness values verified with traditional measurement methods. The work supports the integration of sensors into machine tools in order to reach higher levels of measurement automation. behalf of CIRP.
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| 9. |
- Vogl, Gregory, et al.
(author)
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Diagnostics for geometric performance of machine tool linear axes
- 2016
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In: CIRP annals. - : Elsevier. - 0007-8506 .- 1726-0604. ; 65:1, s. 377-380
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Journal article (peer-reviewed)abstract
- Machine tools degrade during operations, yet knowledge of degradation is elusive; accurately detecting degradation of linear axes is typically a manual and time-consuming process. Manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. A method was developed to use data from an inertial measurement unit (IMU) for identification of changes in the translational and angular errors due to axis degradation. A linear axis testbed, established for the purpose of verification and validation, revealed that the IMU-based method was capable of measuring geometric errors with acceptable test uncertainty ratios.
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| 10. |
- Vogl, Gregory, et al.
(author)
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Identification of machine tool geometric performance using on-machine inertial measurements
- 2017
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In: 6th International Conference on Virtual Machining Process Technology (VMPT 2017).
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Conference paper (peer-reviewed)abstract
- Machine tools degrade during operations, yet accurately detecting degradation of machine components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. Towards this goal, a method was developed to use accelerometer and rate gyroscope data from an inertial measurement unit (IMU) for identification of changes in the translational and angular errors due to axis degradation. An IMU was created for application of the method on a machine tool. As a proof of concept for detection of translational error motions, IMU data was collected on a machine tool with experimentally simulated degradation; as the worktable moved along its nominal path, a cross-axis moved along a swept sinusoidal pattern with micrometer-level amplitudes. In another experiment, data was collected at three different locations on a worktable for the same axis motion. These experiments showed that the IMU detected micrometer-level and microradian-level degradation of linear axes, revealing that the IMU-based method is plausible for use in smart machine tools.
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| 11. |
- Vogl, G. W., et al.
(author)
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Identification of machine tools linear axes performance using on-machine embedded inertia measurement units
- 2017
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In: Laser Metrology and Machine Performance XII - 12th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2017. - : euspen. - 9780956679093 ; , s. 65-74
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Conference paper (peer-reviewed)abstract
- The current trend in manufacturing industry is from mass production towards flexible and adaptive manufacturing systems and cloud manufacturing. Self-learning machines and robot systems can play an essential role in the development of intelligent manufacturing systems and can be deployed to deal with a variety of tasks that can require flexibility and accuracy. However, in order for the machine tool (physical and control system) to deal with the desired task in a cognitive and efficient manner, the system must be "aware" of its capability and,most importantly,its limitations in order to avoid them and adjust itself to the desired task. Thus, characterization of machine tool accuracy and capability is necessary to realize that. In this study,data from a machine-embedded inertial measurement unit (IMU), consisting of accelerometers and rate gyroscopes,was used for identification of changes in linearand angular errormotions due to changes in operational conditionsor component degradation.The IMU-based results were validated against laser-based measurement results,demonstratingthat the IMU-based method is capable of detecting micrometer-level and microradian-level degradation of machine tool linearaxes.Thus, manufacturers could use themethod to efficientlyand robustly diagnose the condition of their machine tool linear axeswith minimal disruptions to production.
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| 12. |
- Vogl, Gregory W., et al.
(author)
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Inertial Measurement Unit for On-Machine Diagnostics of Machine Tool Linear Axes
- 2016
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Conference paper (peer-reviewed)abstract
- Machine tools degrade during operations, yet knowledge of degradation is elusive; accurately detecting degradation of machines' components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated, efficient, and robust methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. Towards this end, a method was developed to use data from an inertial measurement unit (IMU) for identification of changes in the translational and angular errors due to axis degradation. The IMU-based method uses data from accelerometers and rate gyroscopes to identify changes in linear and angular errors due to axis degradation. A linear axis testbed, established for the purpose of verification and validation, revealed that the IMU-based method was capable of measuring geometric errors with acceptable test uncertainty ratios. Specifically, comparison of the IMU-based and laser-based results demonstrate that the IMU-based method is capable of detecting micrometer-level and microradian-level degradation of linear axes. Consequently, an IMU was created for application of the IMU-based method on a machine tool as a proof of concept for detection of linear axis error motions. If the data collection and analysis are integrated within a machine controller, the process may be streamlined for the optimization of maintenance activities and scheduling, supporting more intelligent decision-making by manufacturing personnel and the development of self-diagnosing smart machine tools.
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| 13. |
- Vogl, Gregory W., et al.
(author)
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Root-cause analysis of wear-induced error motion changes of machine tool linear axes
- 2019
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In: International journal of machine tools & manufacture. - : Elsevier BV. - 0890-6955 .- 1879-2170. ; 143, s. 38-48
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Journal article (peer-reviewed)abstract
- Manufacturers need online methods that give up-to-date information of system capabilities to know and predict the performance of their machine tools. Use of an inertial measurement unit (IMU) is attractive for on-machine condition monitoring, so methods based on spatial filters were developed to determine rail wear conditions of linear guideways of a carriage from its IMU-based error motion. Rail wear-induced changes in translational and angular error motions as small as 1.5 mu m and 3.0 microradians, respectively, could be resolved. A corresponding two-part root-cause analysis procedure was developed to determine the rail locations of error motion degradation as well as the most probable physical location of damage that causes the detected error motion changes. Another analysis method determined the root cause of non-localized damage along each rail. These approaches support the development of smart machine tools that provide actionable intelligence to manufacturers for early warnings of system degradation.
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