Single-Cell Measurements and Modeling and Computation of Decision-Making Errors in a Molecular Signaling System with Two Output Molecules.

A cell constantly receives signals and takes different fates accordingly. Given the uncertainty rendered by signal transduction noise, a cell may incorrectly perceive these signals. It may mistakenly behave as if there is a signal, although there is none, or may miss the presence of a signal that actually exists. In this paper, we consider a signaling system with two outputs, and introduce and develop methods to model and compute key cell decision-making parameters based on the two outputs and in response to the input signal. In the considered system, the tumor necrosis factor (TNF) regulates the two transcription factors, the nuclear factor κB (NFκB) and the activating transcription factor-2 (ATF-2). These two system outputs are involved in important physiological functions such as cell death and survival, viral replication, and pathological conditions, such as autoimmune diseases and different types of cancer. Using the introduced methods, we compute and show what the decision thresholds are, based on the single-cell measured concentration levels of NFκB and ATF-2. We also define and compute the decision error probabilities, i.e., false alarm and miss probabilities, based on the concentration levels of the two outputs. By considering the joint response of the two outputs of the signaling system, one can learn more about complex cellular decision-making processes, the corresponding decision error rates, and their possible involvement in the development of some pathological conditions.

Early Detection of Risk of Neo-Sinus Blood Stasis Post-Transcatheter Aortic Valve Replacement Using Personalized Hemodynamic Analysis.

Background: Despite the demonstrated benefits of transcatheter aortic valve replacement (TAVR), subclinical leaflet thrombosis and hypoattenuated leaflet thickening are commonly seen as initial indications of decreased valve durability and augmented risk of transient ischemic attack. Methods: We developed a multiscale patient-specific computational framework to quantify metrics of global circulatory function, metrics of global cardiac function, and local cardiac fluid dynamics of the aortic root and coronary arteries. Results: Based on our findings, TAVR might be associated with a high risk of blood stagnation in the neo-sinus region due to the lack of sufficient blood flow washout during the diastole phase (e.g., maximum blood stasis volume increased by 13, 8, and 2.7 fold in the left coronary cusp, right coronary cusp, and noncoronary cusp, respectively [N = 26]). Moreover, in some patients, TAVR might not be associated with left ventricle load relief (e.g., left ventricle load reduced only by 1.2 % [N = 26]) and diastolic coronary flow improvement (e.g., maximum coronary flow reduced by 4.94%, 15.05%, and 23.59% in the left anterior descending, left circumflex coronary artery, and right coronary artery, respectively, [N = 26]). Conclusions: The transvalvular pressure gradient amelioration after TAVR might not translate into adequate sinus blood washout, optimal coronary flow, and reduced cardiac stress. Noninvasive personalized computational modeling can facilitate the determination of the most effective revascularization strategy pre-TAVR and monitor leaflet thrombosis and coronary plaque progression post-TAVR.

On the Fabrication of High-Performance Additively Manufactured Copper Winding Using Laser Powder Bed Fusion.

Due to its exceptional electrical and thermal conductivity, pure copper is frequently employed in industry as the base metal for thermal management and electromagnetic applications. The growing need for complicated and efficient motor designs has recently accelerated the development of copper additive manufacturing (AM). The present work aims to improve the power density of the copper laser powder bed fusion (Cu-LPBF) coil by increasing the slot-filling factor (SFF) and the electrical conductivity. Firstly, the dimensional limitation of Cu-LPBF fabricated parts was identified. Sample contouring and adjusting beam offset associated with optimum scan track morphology upgraded the minimum feature spacing to 80 µm. Accordingly, the printed winding's slot-filling factor increased to 79% for square wire and 63% for round wire. A maximum electrical conductivity of 87% (IACS) was achieved by heat treatment (HT). The electrical impedance of full-size Cu-LPBF coils, newly reported in this study, was measured and compared with solid wire. It can reflect the performance of Cu-LPBF coils (power factor) in high-frequency applications. Furthermore, surface quality benefited from either sample contouring and HT, where the side surface roughness was lowered by 45% and an additional reduction of 25% after HT.

Reducing Long-Term Mortality Post Transcatheter Aortic Valve Replacement Requires Systemic Differentiation of Patient-Specific Coronary Hemodynamics.

Background Despite the proven benefits of transcatheter aortic valve replacement (TAVR) and its recent expansion toward the whole risk spectrum, coronary artery disease is present in more than half of the candidates for TAVR. Many previous studies do not focus on the longer-term impact of TAVR on coronary arteries, and hemodynamic changes to the circulatory system in response to the anatomical changes caused by TAVR are not fully understood. Methods and Results We developed a multiscale patient-specific computational framework to examine the effect of TAVR on coronary and cardiac hemodynamics noninvasively. Based on our findings, TAVR might have an adverse impact on coronary hemodynamics due to the lack of sufficient coronary blood flow during diastole phase (eg, maximum coronary flow rate reduced by 8.98%, 16.83%, and 22.73% in the left anterior descending, left circumflex coronary artery, and right coronary artery, respectively [N=31]). Moreover, TAVR may increase the left ventricle workload (eg, left ventricle workload increased by 2.52% [N=31]) and decrease the coronary wall shear stress (eg, maximum time averaged wall shear stress reduced by 9.47%, 7.75%, 6.94%, 8.07%, and 6.28% for bifurcation, left main coronary artery, left anterior descending, left circumflex coronary artery, and right coronary artery branches, respectively). Conclusions The transvalvular pressure gradient relief after TAVR might not result in coronary flow improvement and reduced cardiac load. Optimal revascularization strategy pre-TAVR and progression of coronary artery disease after TAVR could be determined by noninvasive personalized computational modeling.

Long-term prognostic impact of paravalvular leakage on coronary artery disease requires patient-specific quantification of hemodynamics.

Transcatheter aortic valve replacement (TAVR) is a frequently used minimally invasive intervention for patient with aortic stenosis across a broad risk spectrum. While coronary artery disease (CAD) is present in approximately half of TAVR candidates, correlation of post-TAVR complications such as paravalvular leakage (PVL) or misalignment with CAD are not fully understood. For this purpose, we developed a multiscale computational framework based on a patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-structure interaction model to quantify metrics of global circulatory function, metrics of global cardiac function and local cardiac fluid dynamics in 6 patients. Based on our findings, PVL limits the benefits of TAVR and restricts coronary perfusion due to the lack of sufficient coronary blood flow during diastole phase (e.g., maximum coronary flow rate reduced by 21.73%, 21.43% and 21.43% in the left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)). Moreover, PVL may increase the LV load (e.g., LV load increased by 17.57% (N = 6)) and decrease the coronary wall shear stress (e.g., maximum wall shear stress reduced by 20.62%, 21.92%, 22.28% and 25.66% in the left main coronary artery (LMCA), left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)), which could promote atherosclerosis development through loss of the physiological flow-oriented alignment of endothelial cells. This study demonstrated that a rigorously developed personalized image-based computational framework can provide vital insights into underlying mechanics of TAVR and CAD interactions and assist in treatment planning and patient risk stratification in patients.

A hybrid model to study how late long-term potentiation is affected by faulty molecules in an intraneuronal signaling network regulating transcription factor CREB.

Systems biology analysis of intracellular signaling networks has tremendously expanded our understanding of normal and diseased cell behaviors and has revealed paths to finding proper therapeutic molecular targets. When it comes to neurons in the human brain, analysis of intraneuronal signaling networks provides invaluable information on learning, memory and cognition-related disorders, as well as potential therapeutic targets. However, neurons in the human brain form a highly complex neural network that, among its many roles, is also responsible for learning, memory formation and cognition. Given the impairment of these processes in mental and psychiatric disorders, one can envision that analyzing interneuronal processes, together with analyzing intraneuronal signaling networks, can result in a better understanding of the pathology and, subsequently, more effective target discovery. In this paper, a hybrid model is introduced, composed of the long-term potentiation (LTP) interneuronal process and an intraneuronal signaling network regulating CREB. LTP refers to an increased synaptic strength over a long period of time among neurons, typically induced upon occurring an activity that generates high-frequency stimulations (HFS) in the brain, and CREB is a transcription factor known to be highly involved in important functions of the cognitive and executive human brain such as learning and memory. The hybrid LTP-signaling model is analyzed using a proposed molecular fault diagnosis method. It allows to study the importance of various signaling molecules according to how much they affect an intercellular phenomenon when they are faulty, i.e. dysfunctional. This paper is intended to suggest another angle for understanding the pathology and therapeutic target discovery by classifying and ranking various intraneuronal signaling molecules based on how much their faulty behaviors affect an interneuronal process. Possible relations between the introduced hybrid analysis and the previous purely intracellular analysis are investigated in the paper as well.

Process-Structure-Property Relationships of Copper Parts Manufactured by Laser Powder Bed Fusion.

The process-structure-property relationships of copper laser powder bed fusion (L-PBF)-produced parts made of high purity copper powder (99.9 wt %) are examined in this work. A nominal laser beam diameter of 100 µm with a continuous wavelength of 1080 nm was employed. A wide range of process parameters was considered in this study, including five levels of laser power in the range of 200 to 370 W, nine levels of scanning speed from 200 to 700 mm/s, six levels of hatch spacing from 50 to 150 µm, and two layer thickness values of 30 µm and 40 µm. The influence of preheating was also investigated. A maximum relative density of 96% was obtained at a laser power of 370 W, scanning speed of 500 mm/s, and hatch spacing of 100 µm. The results illustrated the significant influence of some parameters such as laser power and hatch spacing on the part quality. In addition, surface integrity was evaluated by surface roughness measurements, where the optimum Ra was measured at 8 µm ± 0.5 µm. X-ray photoelectron spectroscopy (XPS) and energy-dispersive X-ray spectroscopy (EDX) were performed on the as-built samples to assess the impact of impurities on the L-PBF part characteristics. The highest electrical conductivity recorded for the optimum density-low contaminated coils was 81% IACS.

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework.

One of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.