Dynamic topology optimization of 3D-Printed transtibial orthopedic implant using tunable isotropic porous metamaterials.

In this paper, we introduce the design and manufacturing process of a transtibial orthopedic implant. We used medical-grade polyurethane polymer resin to fabricate a 3D porous architected implant with tunable isotropy, employing a high-speed printing method known as Continuous Liquid Interface Production (CLIP). Our objective is to enhance the weight-bearing capabilities of the bone structures in the residual limb, thereby circumventing the traditional reliance on a natural bridge. To achieve a custom-made design, we acquire the topology and morphology of the residual limb as well as the bone structure of the tibia and fibula, utilizing computed tomography (CT) and high-resolution 3D scanning. We employed a dynamic topological optimization method, informed by gait cycle data, to effectively reduce the mass of the implant. This approach, which differs from conventional static methods, enables the quantification of variations in applied forces over time. Using the Euler-Lagrange energy approach, we propose the equations of motion for a homologous multibody model with three degrees of freedom. The versatility of the Solid Isotropic Material with Penalization (SIMP) method facilitates the integration of homogenization methods for microscale porous architectures into the optimized domain. The design of these porous architectures is based on a bias-driven tuning symmetry isotropy of a Triply Periodic Minimal Surface (Schwarz Primitive surface). The internal porosity of the structure significantly reduces weight without compromising the isotropic behavior of the implant.

A Study of PLA Thin Film on SS 316L Coronary Stents Using a Dip Coating Technique.

The dip coating process is one of the recognized techniques used to generate polymeric coatings on stents in an easy and low-cost way. However, there is a lack of information about the influence of the process parameters of this technique on complex geometries such as stents. This paper studies the dip coating process parameters used to provide a uniform coating of PLA with a 4-10 µm thickness. A stainless-steel tube (AISI 316L) was laser-cut, electropolished, and dip-coated in a polylactic acid (PLA) solution whilst changing the process parameters. The samples were characterized to examine the coating's uniformity, thickness, surface roughness, weight, and chemical composition. FTIR and Raman investigations indicated the presence of PLA on the stent's surface, the chemical stability of PLA during the coating process, and the absence of residual chloroform in the coatings. Additionally, the water contact angle was measured to determine the hydrophilicity of the coating. Our results indicate that, when using entry and withdrawal speeds of 500 mm min-1 and a 15 s immersion time, a uniform coating thickness was achieved throughout the tube and in the stent with an average thickness of 7.8 µm.

Phenotypic and genetic relationships among anogenital distance, anti-Müllerian hormone, and in vitro embryo production in Gyr dairy cattle.

Anti-Müllerian hormone (AMH) concentration and number of recovered oocytes (ROOC) are phenotypic parameters associated with in vitro embryo production (IVEP). More recently, anogenital distance (AGD) has been proposed as a proxy for fertility in dairy cattle that is easy to collect at a low cost. The aim of this study was to characterize the AGD and its phenotypic and genetic associations with AMH and IVEP in Bos indicus Gyr dairy cattle. The hypothesis was that the number of ROOC, in vitro-produced embryos, and AMH concentration would increase as the AGD decreases. From July to December 2021, a single morphometrical measurement of AGD was collected in 552 donors from 6 herds in Brazil. A subset of donors had AMH assayed on the same day. Only ovum pick-up events that occurred up to 12 mo preceding and 7 mo succeeding the AGD measurement were used to assess the association between AGD, AMH, and IVEP. Thus, 472 donors (1,551 ovum pick-up events and 140 donors with AMH) were considered in the analysis. A raw average was calculated for each individual donor's ROOC, viable oocytes, total produced embryos, viability rate, and embryo rate (defined as total produced embryos/viable oocytes). Comparisons were conducted within the age categories of 3 to <6 yr or 6 to <10 yr. Phenotypic associations were performed in SAS software (SAS Institute Inc., Cary, NC). Genetic correlations were estimated using the BLUPF90 family of programs. The AGD (128.7 mm ± 14; mean ± standard deviation) had a normal distribution and was highly variable (83 to 172 mm) among the Gyr population. Our experimental hypothesis was partially supported by a phenotypic association of a greater number of total produced embryos (R2 = 0.023) as AGD decreased. Our results failed to support an increase in AMH concentration along with a decrease in AGD. In addition, positive and low genetic correlations were observed between AGD and viable oocytes (r = 0.08), and embryo rate (r = 0.20). A greater number of viable oocytes and embryos were observed in donors in the high compared with intermediate and low ROOC categories within both age categories. The age interval of 3 to <6 yr showed a greater number of recovered and viable oocytes for the high AMH compared with the low category, but no differences were observed among the AGD categories. In summary, for the Gyr breed, AGD was phenotypically inversely associated with a quantity-related parameter, such as the total number of produced embryos. In contrast, AGD showed a low genetic correlation with qualitative-related outcomes such as viable oocytes and embryo rate. Further studies should be performed to validate these retrospective analyses and to better understand the association between AGD and IVEP.

Particle Tracking and Micromixing Performance Characterization with a Mobile Device.

Strategies to stir and mix reagents in microfluid devices have evolved concomitantly with advancements in manufacturing techniques and sensing. While there is a large array of reported designs to combine and homogenize liquids, most of the characterization has been focused on setups with two inlets and one outlet. While this configuration is helpful to directly evaluate the effects of features and parameters on the mixing degree, it does not portray the conditions for experiments that involve more than two substances required to be subsequently combined. In this work, we present a mixing characterization methodology based on particle tracking as an alternative to the most common approach to measure homogeneity using the standard deviation of pixel intensities from a grayscale image. The proposed algorithm is implemented on a free and open-source mobile application (MIQUOD) for Android devices, numerically tested on COMSOL Multiphysics, and experimentally tested on a bidimensional split and recombine micromixer and a three-dimensional micromixer with sinusoidal grooves for different Reynolds numbers and geometrical features for samples with fluids seeded with red, blue, and green microparticles. The application uses concentration field data and particle track data to evaluate up to eleven performance metrics. Furthermore, with the insights from the experimental and numerical data, a mixing index for particles (mp) is proposed to characterize mixing performance for scenarios with multiple input reagents.

Mechanical Properties of AISI 316L Lattice Structures via Laser Powder Bed Fusion as a Function of Unit Cell Features.

The growth of additive manufacturing processes has enabled the production of complex and smart structures. These fabrication techniques have led research efforts to focus on the application of cellular materials, which are known for their thermal and mechanical benefits. Herein, we studied the mechanical behavior of stainless-steel (AISI 316L) lattice structures both experimentally and computationally. The lattice architectures were body-centered cubic, hexagonal vertex centroid, and tetrahedron in two cell sizes and at two different rotation angles. A preliminary computational study assessed the deformation behavior of porous cylindrical samples under compression. After the simulation results, selected samples were manufactured via laser powder bed fusion. The results showed the effects of the pore architecture, unit cell size, and orientation on the reduction in the mechanical properties. The relative densities between 23% and 69% showed a decrease in the bulk material stiffness up to 93%. Furthermore, the different rotation angles resulted in a similar porosity level but different stiffnesses. The simulation analysis and experimental results indicate that the variation in the strut position with respect to the force affected the deformation mechanism. The tetrahedron unit cell showed the smallest variation in the elastic modulus and off-axis displacements due to the cell orientation. This study collected computational and experimental data for tuning the mechanical properties of lattice structures by changing the geometry, size, and orientation of the unit cell.

Predictive Modeling of Soft Stretchable Nanocomposites Using Recurrent Neural Networks.

Human skin is characterized by rough, elastic, and uneven features that are difficult to recreate using conventional manufacturing technologies and rigid materials. The use of soft materials is a promising alternative to produce devices that mimic the tactile capabilities of biological tissues. Although previous studies have revealed the potential of fillers to modify the properties of composite materials, there is still a gap in modeling the conductivity and mechanical properties of these types of materials. While traditional Finite Element approximations can be used, these methodologies tend to be highly demanding of time and processing power. Instead of this approach, a data-driven learning-based approximation strategy can be used to generate prediction models via neural networks. This paper explores the fabrication of flexible nanocomposites using polydimethylsiloxane (PDMS) with different single-walled carbon nanotubes (SWCNTs) loadings (0.5, 1, and 1.5 wt.%). Simple Recurrent Neural Networks (SRNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) models were formulated, trained, and tested to obtain the predictive sequence data of out-of-plane quasistatic mechanical tests. Finally, the model learned is applied to a dynamic system using the Kelvin-Voight model and the phenomenon known as the bouncing ball. The best predictive results were achieved using a nonlinear activation function in the SRNN model implementing two units and 4000 epochs. These results suggest the feasibility of a hybrid approach of analogy-based learning and data-driven learning for the design and computational analysis of soft and stretchable nanocomposite materials.

Soft Tissue Hybrid Model for Real-Time Simulations.

In this article, a recent formulation for real-time simulation is developed combining the strain energy density of the Spring Mass Model (SMM) with the equivalent representation of the Strain Energy Density Function (SEDF). The resulting Equivalent Energy Spring Model (EESM) is expected to provide information in real-time about the mechanical response of soft tissue when subjected to uniaxial deformations. The proposed model represents a variation of the SMM and can be used to predict the mechanical behavior of biological tissues not only during loading but also during unloading deformation states. To assess the accuracy achieved by the EESM, experimental data was collected from liver porcine samples via uniaxial loading and unloading tensile tests. Validation of the model through numerical predictions achieved a refresh rate of 31 fps (31.49 ms of computation time for each frame), achieving a coefficient of determination R2 from 93.23% to 99.94% when compared to experimental data. The proposed hybrid formulation to characterize soft tissue mechanical behavior is fast enough for real-time simulation and captures the soft material nonlinear virgin and stress-softened effects with high accuracy.

Low-Cost Light-Based GelMA 3D Bioprinting via Retrofitting: Manufacturability Test and Cell Culture Assessment.

Light-based bioprinter manufacturing technology is still prohibitively expensive for organizations that rely on accessing three-dimensional biological constructs for research and tissue engineering endeavors. Currently, most of the bioprinting systems are based on commercial-grade-based systems or modified DIY (do it yourself) extrusion apparatuses. However, to date, few examples of the adoption of low-cost equipment have been found for light-based bioprinters. The requirement of large volumes of bioinks, their associated cost, and the lack of information regarding the parameter selection have undermined the adoption of this technology. This paper showcases the retrofitting and assessing of a low-cost Light-Based 3D printing system for tissue engineering. To evaluate the potential of a proposed design, a manufacturability test for different features, machine parameters, and Gelatin Methacryloyl (GelMA) concentrations for 7.5% and 10% was performed. Furthermore, a case study of a previously seeded hydrogel with C2C12 cells was successfully implemented as a proof of concept. On the manufacturability test, deviational errors were found between 0.7% to 13.3% for layer exposure times of 15 and 20 s. Live/Dead and Actin-Dapi fluorescence assays after 5 days of culture showed promising results in the cell viability, elongation, and alignment of 3D bioprinted structures. The retrofitting of low-cost equipment has the potential to enable researchers to create high-resolution structures and three-dimensional in vitro models.

Non-Ceruloplasmin Copper as a Stratification Biomarker of Alzheimer's Disease Patients: How to Measure and Use It.

Alzheimer's Disease (AD) is a type of dementia very common in the elderly. A growing body of recent evidence has linked AD pathogenesis to Copper (Cu) dysmetabolism in the body. In fact, a subset of patients affected either by AD or by its prodromal form known as Mild Cognitive Impairment (MCI) have been observed to be unable to maintain a proper balance of Cu metabolism and distribution and are characterized by the presence in their serum of increased levels of Cu not bound to ceruloplasmin (non-ceruloplasmin Cu). Since serum non-ceruloplasmin Cu is a biomarker of Wilson's Disease (WD), a well-known condition of Cu-driven toxicosis, in this review, we propose that in close analogy with WD, the assessment of non-ceruloplasmin Cu levels can be exploited as a cost-effective stratification and susceptibility/risk biomarker for the identification of some AD/MCI individuals. The approach can also be used as an eligibility criterion for clinical trials aiming at investigating Cu-related interventions against AD/MCI.

Simple Protocol for Capturing Both Linear-Response and State-Specific Effects in Excited-State Calculations with Continuum Solvation Models.

We present an effective computational protocol (cLR2) to describe both solvatochromism and fluorosolvatochromism. This protocol, which couples the polarizable continuum model to time-dependent density functional theory, simultaneously accounts for both linear-response and state-specific solvation effects. A series of test cases, including solvatochromic and fluorosolvatochromic compounds and excited-state intramolecular proton transfers, are used to highlight that cLR2 is especially beneficial for modeling bright excitations possessing a significant charge-transfer character, as well as cases in which an accurate balance between states of various polarities should be restored.

Behavioral and neurochemical effects in mice after one-generation exposure to low doses of manganese: Focus on offspring development.

The risk of exposure to toxic metals is a known concern to human populations. The overexposure to Mn can lead to a pathological condition, with symptoms similar to Parkinson's disease. Although toxicity of Mn has been reported, studies in neonates are scarce but necessary, as Mn can cross biological barriers. The present study evaluated if chronic perinatal exposure to Mn at low doses lead to neurotoxic effects in mice, after direct and indirect exposure. Couples of mice were exposed to Mn (0.013, 0.13, and 1.3 mg kg-1.day-1) for 60 days prior to mating, as well as during gestation and lactation. The offspring was distributed into two groups: animals that were not exposed after weaning - parental exposure only (PE); and animals subject to additional 60-day exposure through gavages after weaning - parental and direct exposure (PDE). Neurological effects were evaluated by Mn quantification, behavior tests and biochemical markers in the brain. PDE animals had alterations in short/long-term memory and increased anxiety-like behavior. Exposure to Mn triggered a decrease of glutathione-s-transferase and increase of cholinesterase activity in different regions of the brain. These findings highlight the risk of exposure to low doses of Mn over a generation and at early stages of development.

Exploring the Spatial Features of Electronic Transitions in Molecular and Biomolecular Systems by Swift Electrons.

We devise a new kind of experiment that extends the technology of electron energy loss spectroscopy to probe (supra-)molecular systems: by using an electron beam in a configuration that avoids molecular damage and a very recently introduced electron optics setup for the analysis of the outcoming electrons, one can obtain information on the spatial features of the investigated excitations. Physical insight into the proposed experiment is provided by means of a simple but rigorous model to obtain the transition rate and selection rule. Numerical simulations of DNA G-quadruplexes and other biomolecular systems, based on time dependent density functional theory calculations, point out that the conceived new technique can probe the multipolar components and even the chirality of molecular transitions, superseding the usual optical spectroscopies for those cases that are problematic, such as dipole-forbidden transitions, at a very high spatial resolution.

Neuropsychiatric Symptoms Among Hispanics: Results of the Maracaibo Aging Study.

BACKGROUND: Neuropsychiatric symptoms play an important role in diagnosing and clinical follow-up of cognitive impairment and dementia. OBJECTIVE: We investigated the relationship between neuropsychiatric symptoms, cognitive impairment, and dementia in Hispanics. METHODS: We included 529 participants (age ≥40 years) from the Maracaibo Aging Study with standardized neuropsychiatric assessments, including the Neuropsychiatric Inventory (NPI). Based on the Clinical Dementia Rating and the Mini-Mental State Examination scores, participants' cognitive status was categorized into normal cognition, mild/moderate, and severe cognitive impairment. Diagnosis of dementia was established in a consensus conference. Statistical analyses included multivariable logistic regression models and area under the curve (AUC). RESULTS: The mean age of participants was 59.3 years, and 71.8%were women. The proportion of dementia was 6.8%. Disturbed sleep, anxiety, and depression were the most common neuropsychiatric symptoms in the study sample. In crude analyses, the proportions of hallucinations, aberrant motor behavior, agitation/aggression, apathy, delusions, irritability, eating disturbance, depression, and euphoria were differently distributed among cognitive status groups (p < 0.05). After accounting for confounders, aberrant motor behavior and agitation/aggression remained significantly associated with cognitive impairment and dementia (p < 0.05). The inclusion of the NPI domains significantly improved the AUC to discriminate severe cognitive impairment and dementia compared to a basic model that included sex, age, education, alcohol, obesity, serum glucose, total cholesterol, hypertension, and stroke. CONCLUSION: Neuropsychiatric symptoms are associated with severe cognitive impairment and dementia. The addition of NPI items to the global cognitive assessment might help early detection of dementia in primary care settings.

Characterization of Porous Scaffolds Fabricated by Joining Stacking Based Laser Micro-Spot Welding (JS-LMSW) for Tissue Engineering Applications.

A novel manufacturing approach was used to fabricate metallic scaffolds. A calibration of the laser cutting process was performed using the kerf width compensation in the calculations of the tool trajectory. Welding defects were studied through X-ray microtomography. Penetration depth and width resulted in relative errors of 9.4%, 1.0%, respectively. Microhardness was also measured, and the microstructure was studied in the base material. The microhardness values obtained were 400 HV, 237 HV, and 215 HV for the base material, HAZ, and fusion zone, respectively. No significant difference was found between the microhardness measurement along with different height positions of the scaffold. The scaffolds' dimensions and porosity were measured, their internal architecture was observed with micro-computed tomography. The results indicated that geometries with dimensions under 500 µm with different shapes resulted in relative errors of ~2.7%. The fabricated scaffolds presented an average compressive modulus ~13.15 GPa, which is close to cortical bone properties. The proposed methodology showed a promising future in bone tissue engineering applications.

E-Skin Development and Prototyping via Soft Tooling and Composites with Silicone Rubber and Carbon Nanotubes.

The strategy of embedding conductive materials on polymeric matrices has produced functional and wearable artificial electronic skin prototypes capable of transduction signals, such as pressure, force, humidity, or temperature. However, these prototypes are expensive and cover small areas. This study proposes a more affordable manufacturing strategy for manufacturing conductive layers with 6 × 6 matrix micropatterns of RTV-2 silicone rubber and Single-Walled Carbon Nanotubes (SWCNT). A novel mold with two cavities and two different micropatterns was designed and tested as a proof-of-concept using Low-Force Stereolithography-based additive manufacturing (AM). The effect SWCNT concentrations (3 wt.%, 4 wt.%, and 5 wt.%) on the mechanical properties were characterized by quasi-static axial deformation tests, which allowed them to stretch up to ~160%. The elastomeric soft material's hysteresis energy (Mullin's effect) was fitted using the Ogden-Roxburgh model and the Nelder-Mead algorithm. The assessment showed that the resulting multilayer material exhibits high flexibility and high conductivity (surface resistivity ~7.97 × 104 Ω/sq) and that robust soft tooling can be used for other devices.

LAPKaans: Tool-Motion Tracking and Gripping Force-Sensing Modular Smart Laparoscopic Training System.

Laparoscopic surgery demands highly skilled surgeons. Traditionally, a surgeon's knowledge is acquired by operating under a mentor-trainee method. In recent years, laparoscopic simulators have gained ground as tools in skill acquisition. Despite the wide range of laparoscopic simulators available, few provide objective feedback to the trainee. Those systems with quantitative feedback tend to be high-end solutions with limited availability due to cost. A modular smart trainer was developed, combining tool-tracking and force-using employing commercially available sensors. Additionally, a force training system based on polydimethylsiloxane (PDMS) phantoms for sample stiffness differentiation is presented. This prototype was tested with 39 subjects, between novices (13), intermediates (13), and experts (13), evaluating execution differences among groups in training exercises. The estimated cost is USD $200 (components only), not including laparoscopic instruments. The motion system was tested for noise reduction and position validation with a mean error of 0.94 mm. Grasping force approximation showed a correlation of 0.9975. Furthermore, differences in phantoms stiffness effectively reflected user manipulation. Subject groups showed significant differences in execution time, accumulated distance, and mean and maximum applied grasping force. Accurate information was obtained regarding motion and force. The developed force-sensing tool can easily be transferred to a clinical setting. Further work will consist on a validation of the simulator on a wider range of tasks and a larger sample of volunteers.

Laser Surface Texturing and Electropolishing of CoCr and Ti6Al4V-ELI Alloys for Biomedical Applications.

The interplay between a prosthetic and tissue represents an important factor for the fixation of orthopedic implants. Laser texturing tests and electropolishing were performed on two materials used in the fabrication of medical devices, i.e., CoCr and Ti6Al4V-ELI alloys. The material surface was textured with a diode-pumped solid state (DPSS) laser and its effect on the surface quality and material modification, under different combinations of laser power and marking speed, were investigated. Our results indicate that an increment of energy per unit length causes an incremental trend in surface roughness parameters. Additionally, phase transformation on the surface of both alloys was achieved. Chemical analysis by energy dispersive X-ray spectrometer (EDX) shows the formation of (Co(Cr,Mo)) phase and the M23C6 precipitate on the CoCr surface; while quantitative analysis of the X-ray diffractometer (XRD) results demonstrates the oxidation of the Ti alloy with the formation of Ti2O and Ti6O from the reduction of the α-Ti phase. The behaviors were both related with an increase of the energy per unit length. Control of the final surface roughness was achieved by an electropolishing post-treatment, minimizing the as-treated values. After polishing, a reduction of surface roughness parameters was obtained in a range between 3% and 44%, while no changes in chemical composition or present phases were observed.

Characterization of Soft Tooling Photopolymers and Processes for Micromixing Devices with Variable Cross-Section.

In this paper, we characterized an assortment of photopolymers and stereolithography processes to produce 3D-printed molds and polydimethylsiloxane (PDMS) castings of micromixing devices. Once materials and processes were screened, the validation of the soft tooling approach in microfluidic devices was carried out through a case study. An asymmetric split-and-recombine device with different cross-sections was manufactured and tested under different regime conditions (10 < Re < 70). Mixing performances between 3% and 96% were obtained depending on the flow regime and the pitch-to-depth ratio. The study shows that 3D-printed soft tooling can provide other benefits such as multiple cross-sections and other potential layouts on a single mold.

Soil microbial community, enzyme activity, C and N stocks and soil aggregation as affected by land use and soil depth in a tropical climate region of Brazil.

The impact of agricultural land-use on soil microbial community composition and enzyme activity has not been extensively investigated in Ultisols. We investigated soil health parameters by analyzing phospholipid fatty acids (PLFAs), extracellular enzyme activity, C and N stocks, and soil structure. Four land uses were established in a tropical climate region of Brazil: native Cerrado (savanna), monoculture pasture [Urochloa brizantha (Hochst. Ex A. Rich.) R. Webster 'Marandu'], an integrated crop-livestock system (ICLS), and maize (Zea mays)-fallow in a no-tillage system. Soil microbial biomass was 40% higher in the native Cerrado than in the monoculture pasture, ICLS, and no-tillage maize. Soil organic carbon was positively correlated with microbial community composition (MB; gram-; AC; AMF; Fungi; F: B ratio) and enzyme activity (bG, AP, NAG). Large macroaggregates were positively correlated with bG, AP, and AMF. In summary, the native Cerrado had a higher level of carbon at the soil surface and greater soil structure with increased microbial biomass, gram+ bacteria, AMF, fungi, and F:B ratio in a tropical region of Brazil. However, bG and AP enzyme activities were lower in the ICLS and no-till maize at the soil surface (0-5 cm) compared to the native Cerrado. The conversion of native Cerrado to agricultural systems shifted the soil microbial community composition, enzyme activity, C and N, and soil structure of this sandy soil of the Brazilian Cerrado.