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Viral-associated respiratory infectious diseases are one of the most prominent subsets of respiratory failures, known as viral respiratory infections (VRI). VRIs are proceeded by an infection caused by viruses infecting the respiratory system. For the past 100 years, viral associated respiratory epidemics have been the most common cause of infectious disease worldwide. Due to several drawbacks of the current anti-viral treatments, such as drug resistance generation and non-targeting of viral proteins, the development of novel nanotherapeutic or nano-vaccine strategies can be considered essential. Due to their specific physical and biological properties, nanoparticles hold promising opportunities for both anti-viral treatments and vaccines against viral infections. Besides the specific physiological properties of the respiratory system, there is a significant demand for utilizing nano-designs in the production of vaccines or antiviral agents for airway-localized administration. SARS-CoV-2, as an immediate example of respiratory viruses, is an enveloped, positive-sense, single-stranded RNA virus belonging to the coronaviridae family. COVID-19 can lead to acute respiratory distress syndrome, similarly to other members of the coronaviridae. Hence, reviewing the current and past emerging nanotechnology-based medications on similar respiratory viral diseases can identify pathways towards generating novel SARS-CoV-2 nanotherapeutics and/or nano-vaccines.

Non-physiological levels of oxygen and nutrients within the tumors result in heterogeneous cell populations that exhibit distinct necrotic, hypoxic, and proliferative zones. Among these zonal cellular properties, metabolic rates strongly affect the overall growth and invasion of tumors. Here, we report on a hybrid discrete-continuum (HDC) mathematical framework that uses metabolic data from a biomimetic two-dimensional (2D) in-vitro cancer model to predict three-dimensional (3D) behaviour of in-vitro human glioblastoma (hGB). The mathematical model integrates modules of continuum, discrete, and neurons. Results indicated that the HDC model is capable of quantitatively predicting growth, invasion length, and the asymmetric finger-type invasion pattern in in-vitro hGB tumors. Additionally, the model could predict the reduction in invasion length of hGB tumoroids in response to temozolomide (TMZ). This model has the potential to incorporate additional modules, including immune cells and signaling pathways governing cancer/immune cell interactions, and can be used to investigate targeted therapies. Meitham Amereh and colleagues report a hybrid discrete-continuum model to predict the cancerous growth, invasion, and treatment response of glioblastoma tumours. Their in-silico model uses metabolic data from a biomimetic two-dimensional in-vitro cancer model to predict three-dimensional behaviour of in-vitro human glioblastoma.

3D printing is an additive manufacturing method that involves successive deposition of layers of materials to create a construct from a digital model. 3D-printing technologies have widespread applications in medicine and are increasingly used for solving a wide variety of medical problems. In this review, we summarize existing 3D-printing technologies and explore recent advances in the development and characterization of bioinks and biomaterial inks. We will then explain characterization methods for determining the rheological and mechanical properties of printing inks and 3D-printed constructs using invasive and noninvasive methods. Lastly, four core uses in recent innovations in medicine, including tissue and organoid engineering, disease modeling, drug delivery, biosensing, patient-specific implants and challenges along with future prospects will be discussed.

Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of key genes in bone biology, particularly to intramembranous ossification, not captured at other skeletal sites. We perform a genome-wide association meta-analysis ( n  ~ 43,800) of SK-BMD, identifying 59 loci, collectively explaining 12.5% of the trait variance. Association signals cluster within gene-sets involved in skeletal development and osteoporosis. Among the four novel loci ( ZIC1 , PRKAR1A , AZIN1/ATP6V1C1 , GLRX3 ), there are factors implicated in intramembranous ossification and as we show, inherent to craniosynostosis processes. Functional follow-up in zebrafish confirms the importance of ZIC1 on cranial suture patterning. Likewise, we observe abnormal cranial bone initiation that culminates in ectopic sutures and reduced BMD in mosaic atp6v1c1 knockouts. Mosaic prkar1a knockouts present asymmetric bone growth and, conversely, elevated BMD. In light of this evidence linking SK-BMD loci to craniofacial abnormalities, our study provides new insight into the pathophysiology, diagnosis and treatment of skeletal diseases. A skull bone mineral density genome-wide association meta-analysis identifies 59 loci and studies in zebrafish evidence the role of ZIC1 , ATP6V1C1 and PRKAR1A in mineralization of the skull, and of the former two genes in cranial suture patterning.