3D and 4D Printing of Multistable Structures

Three-dimensional (3D) printing is a new paradigm in customized manufacturing and allows the fabrication of complex structures that are difficult to realize with other conventional methods. Four-dimensional (4D) printing adds active, responsive functions to 3D-printed components, which can respond to various environmental stimuli. This review introduces recent ideas in 3D and 4D printing of mechanical multistable structures. Three-dimensional printing of multistable structures can enable highly reconfigurable components, which can bring many new breakthroughs to 3D printing. By adopting smart materials in multistable structures, more advanced functionalities and enhanced controllability can also be obtained in 4D printing. This could be useful for various smart and programmable actuators. In this review, we first introduce three representative approaches for 3D printing of multistable structures: strained layers, compliant mechanisms, and mechanical metamaterials. Then, we discuss 4D printing of multistable structures that can help overcome the limitation of conventional 4D printing research. Lastly, we conclude with future prospects

Structural Health Monitoring

Abstract In structural health monitoring, crack identification using scattered ultrasonic waves from a crack is one of the most active research areas. Crack size estimation is important for judging the severity of the damage. If measurements are frequently performed as the crack grows, then a better estimation of crack size may be possible by analyzing sensor signals for the same crack location with different sizes. The objective of this article is to explore the relationship between the sensor signal amplitude and crack size through experiments and simulation for estimating the size. Cracks are machined into an aluminum plate and measurements are carried out with ultrasound excitation using piezoelectric transducer arrays that alternate their role as actuators or sensors. Initially, a hole of 2.5 mm diameter is drilled in the plate, and it is gradually machined to a crack with a size up to 50 mm. Signal amplitude is measured from the sensor arrays. The migration technique is used to image the crack and to find the crack location. The maximum received signal amplitude is found to vary linearly with size from simulation and this agrees with measurements with crack size up to 30 mm. The deviation between the simulation and experiment increases as the crack grows

Depression and suicide risk prediction models using blood-derived multi-omics data

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression???17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment

Impact of prior lamivudine use on the antiviral efficacy and development of resistance to entecavir in chronic hepatitis B patients

Background/AimsTo determine the efficacies of entecavir (ETV) in nucleos(t)ide analogue (NA)-naïve chronic hepatitis B (CHB) patients and in those with prior lamivudine (LAM) use who did not develop resistance.MethodsWe retrospectively enrolled 337 patients with CHB who were treated with ETV (0.5 mg daily) for at least 30 months. The study included 270 (80.1%) NA-naïve patients and 67 (19.9%) LAM-use patients. Ten of the LAM-use patients were refractory to LAM therapy without developing resistance.ResultsGenotypic resistance to ETV developed more frequently in the LAM-use group (13.1%) than in the NA-naïve group (2.6%) at 60 months (P=0.009). In subgroup analysis, after excluding the 10 patients who were refractory to LAM therapy, the cumulative probability of ETV resistance did not differ significantly between the two groups (P=0.149). Prior LAM refractoriness and a higher hepatitis B virus DNA level at month 12 were independent predictive factors for the development of ETV resistance.ConclusionsETV resistance developed more frequently in LAM-use patients with CHB. However, prior LAM use without refractoriness did not affect the development of ETV resistance. The serum hepatitis B virus DNA level at month 12 was a major predictor for the development of ETV resistance

Anomalous Si-based composite anode design by densification and coating strategies for practical applications in Li-ion batteries

Si-based Li-ion battery (LIB) anode materials often possess porous structures to accommodate the intrinsic volumetric expansion of Si upon cycling. However, the porous structure may cause poor initial coulombic efficiency (ICE), inadequate cycle life due to the continuous generation of a solid-electrolyte interface, and incompatibility with calendaring processes. To overcome these issues, we designed an optimized Si/C (P?Si/C) composite anode consisting of Si nanoparticles, graphite, and pitch, with a highly densified structure, suppressing Si expansion and enabling compatibility with the calendaring process. To further enhance the cycle life, the surface of the P?Si/C composite was modified by chemical vapor deposition using CH4 gas (C?Si/C). The P?Si/C anode exhibited a high ICE of 88.0% with a rapid surge up to 99.0% after only the 4th cycle. The C?Si/C anode presented an improved capacity retention of 49.5% after the 39th cycle, compared with 46.0% for the P?Si/C anode after the 31st cycle, while maintaining the same ICE. Moreover, anodes prepared with 8 wt% P?Si/ C or C?Si/C and 92 wt% graphite (m-P-Si/C and m-C-Si/C, respectively) showed higher capacity retentions compared with pure Si/C anodes. The m-C-Si/C anode exhibited a higher capacity retention of 80.1% after the 40th cycle, compared with 71.2% for the m-P-Si/C anode. The m-C-Si/C anode also displayed an extremely low expansion rate and the majority of the expansion was elastically recovered. This C?Si/C composite provided a controllable means to modify the performance of LIBs by simple mixing with graphite

Decreased Exosomal Acetylcholinesterase Activity in the Plasma of Patients With Parkinson’s Disease

Exosomes, which are small extracellular vesicles produced from various cell types, contain a variety of molecular constituents, such as proteins, lipids, and RNA. Recently, exosomal biomarkers have been investigated to probe the understanding and diagnosis of neurodegenerative disorders. Previous reports have demonstrated increased exosomal α-synuclein (α-syn) in patients with Parkinson’s disease (PD) in comparison to healthy controls (HC). Interestingly, the cholinergic loss was revealed in the central and peripheral nervous systems in histopathology and molecular neuroimaging. Thereby, we simultaneously examined acetylcholinesterase (AChE) with α-syn as exosomal markers. Exosomes were isolated from the plasma of 34 FP-CIT PET proven patients with PD and 29 HC. Exosomal α-syn and AChE activity were quantified andthe relationship with clinical parameters was analyzed. Remarkably, exosomal AChE activity was significantly decreased in PD compared to HC (P = 0.002). Moreover, exosomal AChE activity in PD revealed a strong negative correlation with disease severity, including H&Y (P = 0.007) and UPDRS part III (P = 0.047) scores. By contrast, no significant difference in exosomal α-syn concentration was observed between groups. These results support the occurrence of cholinergic dysfunction in PD, and they could be implicated with disease progression, especially motor deficits. Exosomal AChE activity with advanced exosome isolation techniques may be a reliable biomarker for the early diagnosis and prognosis of PD

Blood amyloid-β oligomerization associated with neurodegeneration of Alzheimers disease

Introduction Oligomeric amyloid-ß is a major toxic species associated with Alzheimers disease pathogenesis. Methods used to measure oligomeric amyloid-β in the blood have increased in number in recent years. The Multimer Detection System-Oligomeric Amyloid-β (MDS-OAβ) is a specific method to measure oligomerization tendencies in the blood. The objective of this study was to determine the association between amyloid-ß oligomerization in the plasma and structural changes of the brain. Methods We studied 162 subjects composed of 92 community-based normal healthy subjects, 17 with subjective cognitive decline, 14 with mild cognitive impairment and 39 with Alzheimers disease dementia. All subjects underwent MDS-OAβ and three-dimensional T1 magnetic resonance imaging. To determine the structural changes of the brain that are statistically correlated with MDS-OAβ level, we used voxel-based morphometry with corrections for age and total intracranial volume covariates. Results We found brain volume reduction in the bilateral temporal, amygdala, parahippocampal and lower parietal lobe and left cingulate and precuneus regions (family-wise error, p < 0.05). Reduction was also found in white matter in proximity to the left temporal and bilateral lower parietal lobes and posterior corpus callosum (family-wise error, p < 0.05). Brain volume increment was not observed in any regions within grey or white matter. Discussion Findings suggest that substantial correlation exists between amyloid ß oligomerization in the blood and brain volume reduction in the form of Alzheimers disease despite of uncertainty in the casual relationship.This work was supported by a grant of the Korea Healthcare Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (HI14C1251)