Three-Dimensional Bioprinting Materials with Potential Application in Preprosthetic Surgery

Current methods in handling maxillofacial defects are not robust and are highly dependent on the surgeon’s skills and the inherent potential in the patients’ bodies for regenerating lost tissues. Employing custom-designed 3D printed scaffolds that securely and effectively reconstruct the defects by using tissue engineering and regenerative medicine techniques can revolutionize preprosthetic surgeries. Various polymers, ceramics, natural and synthetic bioplastics, proteins, biomolecules, living cells, and growth factors as well as their hybrid structures can be used in 3D printing of scaffolds, which are still under development by scientists. These scaffolds not only are beneficial due to their patient-specific design, but also may be able to prevent micromobility, make tension free soft tissue closure, and improve vascularity. In this manuscript, a review of materials employed in 3D bioprinting including bioceramics, biopolymers, composites, and metals is conducted. A discussion of the relevance of 3D bioprinting using these materials for craniofacial interventions is included as well as their potential to create analogs to craniofacial tissues, their benefits, limitations, and their application

Late Bayesian inference in mental transformations

Many skills rely on performing noisy mental computations on noisy sensory measurements. Bayesian models suggest that humans compensate for measurement noise and reduce behavioral variability by biasing perception toward prior expectations. Whether a similar strategy is employed to compensate for noise in downstream mental and sensorimotor computations is not known. We tested humans in a battery of tasks and found that tasks which involved more complex mental transformations resulted in increased bias, suggesting that humans are able to mitigate the effect of noise in both sensorimotor and mental transformations. These results indicate that humans delay inference in order to account for both measurement noise and noise in downstream computations.Alfred P. Sloan Foundation (BR-2014-102)Esther A. and Joseph Klingenstein FundSimons Foundation (542993SPI)McKnight Endowment Fund for NeuroscienceMcGovern Institute for Brain Research at MI

A Handbook of Early Arabic Kufic Script: Reading, Writing, Calligraphy, Typography, Monograms

A comprehensive textbook of the early Arabic Kufic script, written as a complete reference book for calligraphers, designers, and students of art history and the history of Arabic language and scripts. This beautiful and powerful script was derived from the earlier Hijazi Mashq style of Mecca and Medina, which was invented by early Muslim scribes to record the Quran. Today, the many historical manuscripts displayed in numerous museums around the world can attest to development and evolution of this remarkable and versatile script. Authored by master calligrapher, Mousavi Jazayeri, this book is the first book written in English that is solely dedicated to the study, learning and revival of the fascinating script behind the first mature Arabic calligraphic style, which was the official script of the Islamic Near East for centuries, before being replaced by the modern Naskh style. In this handbook, Mousavi Jazayeri who had discovered the lost art of cutting the qalam (pen) for early Kufic more than twenty years ago, explains with detailed, clear illustrations how to write early Kufic using a calligraphic pen and even a regular pen. He guides students patiently through the process involved in creating amazing, modern monograms. With clear, ample examples taken from the old Quranic manuscripts, art history students, font designers, and scholars of the history of the Arabic language and scripts can use this reference book to learn the key aspects of the early Kufic script as a writing system

Incidence of Snake Bites in Kashan, Iran During an Eight Year Period (2004-2011)

Background: Snake bites are one of the significant health problems in the tropical and subtropical regions. Snake bite is a common medical emergency in Iran, and the epidemiological features and management of such cases vary from region to region. Objectives: This present research study was conducted to obtain new information about the epidemiology of snake bites in the region of Kashan, located in the central part of Iran. Patients and Methods: This research was a descriptive retrospective study. Data from 2004 to 2011 of snakebite cases were collected from case reports. Information included; age and sex of the victim, district, month of incident, mortality, and time of bite. Results: The results of this study showed that the majority of snake bite patients were male (96%). The age distribution of patients indicated that the greatest rate of snake bites occurred among the 15-24 year old group. Data collected in this study revealed that the highest incidence of snake bite cases took place in summer (60%) and the lowest number occurred in winter, with no snake bite cases being recorded. The peak number of snakebite cases was seen during June-September. Conclusions: It was concluded that snake bite cases in Kashan are similar to other areas in Iran from an epidemiological point of view, including; age distribution rates, gender and site of the bites. The existence of Macrov ipera lebetina, a dangerous venomous snake, can cause a range of clinical effects among residents in central parts of Iran, such as Kashan area

A cerebellar mechanism for learning prior distributions of time intervals

Knowledge about the statistical regularities of the world is essential for cognitive and sensorimotor function. In the domain of timing, prior statistics are crucial for optimal prediction, adaptation and planning. Where and how the nervous system encodes temporal statistics is, however, not known. Based on physiological and anatomical evidence for cerebellar learning, we develop a computational model that demonstrates how the cerebellum could learn prior distributions of time intervals and support Bayesian temporal estimation. The model shows that salient features observed in human Bayesian time interval estimates can be readily captured by learning in the cerebellar cortex and circuit level computations in the cerebellar deep nuclei. We test human behavior in two cerebellar timing tasks and find prior-dependent biases in timing that are consistent with the predictions of the cerebellar model

Boundary condition nomenclature confusion in groundwater flow modelling

© 2019 John Wiley & Sons, Inc. This author accepted manuscript is made available following 12 month embargo from date of publication (April 2019) in accordance with the publisher’s archiving policyTo solve the partial differential equations of groundwater flow, the information about head (h) and/or head gradient (∇h) must be specified along the boundaries of a model domain. The descriptors of different boundary condition (BC) types are drawn from founding mathematicians mainly of the 19th century (Cheng and Cheng 2005). Mathematically, there are five different BC types, including: Dirichlet (Type 1), Neumann (Type 2), Robin (Type 3), Cauchy and Mixed (Liu 2018). These names are sometimes used in communicating the BCs of groundwater flow models, and therefore, correct association between nomenclature and the mathematical form of BCs is important for properly communicating model characteristics

Development of universal influenza vaccines targeting conserved viral proteins

Vaccination is still the most efficient way to prevent an infection with influenza viruses. Nevertheless, existing commercial vaccines face serious limitations such as availability during epidemic outbreaks and their efficacy. Existing seasonal influenza vaccines mostly induce antibody responses to the surface proteins of influenza viruses, which frequently change due to antigenic shift and or drift, thus allowing influenza viruses to avoid neutralizing antibodies. Hence, influenza vaccines need a yearly formulation to protect against new seasonal viruses. A broadly protective or universal influenza vaccine must induce effective humoral as well as cellular immunity against conserved influenza antigens, offer good protection against influenza pandemics, be safe, and have a fast production platform. Nanotechnology has great potential to improve vaccine delivery, immunogenicity, and host immune responses. As new strains of human epidemic influenza virus strains could originate from poultry and swine viruses, development of a new universal influenza vaccine will require the immune responses to be directed against viruses from different hosts. This review discusses how the new vaccine platforms and nanoparticles can be beneficial in the development of a broadly protective, universal influenza vaccine