The design of biomimetic porous scaffolds has been gaining attention in the biomedical sector lately. Shells, marine sponges, shark teeth, cancellous bone, sea urchin spine, and the armadillo armor structure are examples of biological systems that have already been studied to drive the design of innovative, porous, and multifunctional structures. Among these, triply periodic minimal surfaces (TPMSs) have attracted the attention of scientists for the fabrication of biomimetic porous scaffolds. The interest stems from their outstanding properties, which include mathematical controllable geometry features, highly interconnected porous architectures, high surface area to volume ratio, less stress concentration, tunable mechanical properties, and increased permeability. All these distinguishing features enable better cell adhesion, optimal integration to the surrounding tissue avoiding stress shieldings, a good permeability of fluid media and oxygen, and the possibility of vascularization. However, the sophisticated geometry of these TPMS-based structures has proven challenging to fabricate by conventional methods. The emergence of additive manufacturing (AM) and the enhanced manufacturing freedoms and flexibility it guarantees could solve some of the bottlenecks, thus leading to a surge of interest in designing and fabricating such structures in this field. Also, the feasibility of using AM technologies allows for obtaining size programmable TPMS printable in various materials, from polymers to metal alloys. Here, a comprehensive overview of 3D-printed TPMS porous structures is provided from a design for additive manufacturing (DfAM) and application perspective. First, design strategies, geometry design algorithms, and related topological optimization are introduced according to diverse requirements. Based on that, the performance control of TPMS and the pros and cons of the different AM processes for fabricating TPMS scaffolds are summarized. Lastly, practical applications of 3D-printed biomimetic TPMS porous structures for the biomedical field are presented to clarify the advantages and potential of such structures.

The evaluation of inoculation processes of microorganisms by robotic systems as well as by lab-technicians is compensable and can be missing consistency as human judgment will depend on the individual and may therefore be biased and less effective than models and algorithms evaluating spatial patterns. To address this problem, nearest neighbor analysis was used to investigate if it could be utilized as a method to evaluate isolation processes. The nearest neighbor analysis results in a comparable numeric value on the isolation process, which can be used to assess results of different inoculation processes. In this article, images of Petri dishes and simulated plates are used to investigate the effectiveness of nearest neighbor analysis, which is a method within spatial statistics. This analysis is applied to spatial data created by applying computer vision to localize the colonies on the plates. When evaluating plates made with the streaking technique method, it was found to be ineffective as the dense parts of the distribution resulted in the computer vision being unable to locate all of the colonies. Therefore, the nearest neighbor analysis is not suitable to evaluate streaking plates and other methods to evaluate such plates should be developed. However, when evaluating Petri dishes where the spread plating technique had been applied, it was found that nearest neighbor analysis can be a useful way to systematically evaluate isolation processes.

High-Performance Liquid Chromatography-Tandem Mass Spectrometry has emerged triumphant over the years as a reliable and high throughput clinical instrument to assess different metabolic irregularities. One of the latest applications of LC-MS/MS has been in the field of quantification of glucocorticoids, such as cortisol and cortisone from saliva, that can be an indicator of abnormalities such as Congenital Adrenal Hyperplasia (CAH), Cushing's Syndrome, and Addison's disease. We have developed and validated an LC-MS/MS-based assay for simultaneous detection of cortisol and cortisone in human saliva, which requires only 20 µL of sample, to measure cortisol across a 0.5 - 70 ng/mL range, and cortisone across a 1.2- 100 ng/mL range, respectively. The developed method exhibits linearity of R2>0.99, for both analytes, inclusive of both MRMs, and a percent coefficient of variation that is less than or equal to 20%. Using dilute-and-shoot for sample preparation, we have exhibited sample accuracy of 100±20 for the assay calibrators, and integrated Needle Wash Solvent Chemistry for minimal sample carryover, making it adaptable for crucial for potential diagnostic use. We have exhibited a method that is simplistic, specific, and highly automatable on liquid handling platforms, such as the JANUS® G3 Workstation. With our innovation, we have introduced a potential to test 81-unknown samples in singlicate within an on-deck plating time of fewer than four minutes. We performed additional verification studies, including an accelerated stability study and a freeze-thaw study showcasing the potential long-term usability of our proposed prototype kit. Overall, this work presents an optimized LC-MS/MS method with automated sample preparation that is ready to be utilized for cortisol-cortisone detection for clinical diagnostic contexts related to Cushing's Disease, among other adrenal and endocrine disorders.