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Malignant ameloblastoma, comprising metastasizing ameloblastoma and ameloblastic carcinoma, represents 1.6-2.2% of all odontogenic tumors. Due to its rare nature, malignant ameloblastoma has only been reported in the literature in small case series or case reports. Using the Surveillance, Epidemiology and End-Results (SEER) database, we have performed a population-based study to determine the incidence rate and the absolute survival of malignant ameloblastoma. Using the International Classification of Diseases for Oncology (ICD-O) codes 9310/3 and 9270/3, data from the SEER database were used to calculate the incidence rate and absolute survival rate of population with malignant ameloblastoma. The overall incidence rate of malignant ameloblastoma was 1.79 per 10 million person/year. The incidence rate was higher in males than females and also higher in black versus white population. The median overall survival was 17.6 years from the time of diagnosis and increasing age was associated with a statistically significant poorer survival. To our best knowledge, we report the largest population-based series of malignant ameloblastoma. The incidence rate was 1.79 per 10 million person/year and the overall survival was 17.6 years.

Ameloblastoma is the second most common odontogenic tumor, known to be slow-growing, persistent, and locally aggressive. Recent data suggests that ameloblastoma is best treated with wide resection and adequate margins. Following primary excision, bony reconstruction is often necessary for a functional and aesthetically satisfactory outcome, making early diagnosis paramount. Despite earlier diagnosis potentially limiting the extent of resection and reconstruction, an understanding of the growth rate and natural history of ameloblastoma has been notably lacking from the literature. A systematic review of the literature was conducted by reviewing relevant articles from PubMed and Web of Science databases. Each article's level of evidence was formally appraised according to the Centre of Evidence Based Medicine (CEBM), with data from each utilized in a meta-analysis of growth rates for ameloblastoma. Literature regarding the natural history of ameloblastoma is limited since the tumor is immediately acted upon at its initial detection, unless the patient voluntarily refuses a surgical intervention. From the limited data, it is derived that the highest estimated growth rate is associated with solid, multicystic type and the lowest rate with peripheral ameloblastomas. After meta-analysis, the calculated mean specific grow rate is 87.84% per year. The growth rate of ameloblastoma has been demonstrated, offering prognostic and management information, particularly in cases where a delay in management is envisaged.

The frq gene, essential for circadian clock function, is shown to differ from most other genes in Neurospora by exhibiting non-optimal codon usage; by contrast, optimization of codon usage is unexpectedly found to affect the structure and function of the coded protein, subsequently impairing circadian feedback loops. Time for non-optimal codons Many biological processes are rhythmically regulated on a daily, or circadian, cycle. Highly expressed genes, such as those regulating the circadian rhythm, normally contain optimal codons, to allow efficient expression. Two studies, from the laboratories of Carl Johnson and Yi Liu, now find that central circadian proteins in cyanobacteria and Neurospora unexpectedly use non-optimal codons, and that optimizing their codes causes a change in an adaptive response in cyanobacteria, and compromises function of the Neurospora clock. These works highlight an unanticipated selection against optimal codon usage. Codon-usage bias has been observed in almost all genomes and is thought to result from selection for efficient and accurate translation of highly expressed genes 1 , 2 , 3 . Codon usage is also implicated in the control of transcription, splicing and RNA structure 4 , 5 , 6 . Many genes exhibit little codon-usage bias, which is thought to reflect a lack of selection for messenger RNA translation. Alternatively, however, non-optimal codon usage may be of biological importance. The rhythmic expression and the proper function of the Neurospora FREQUENCY (FRQ) protein are essential for circadian clock function. Here we show that, unlike most genes in Neurospora , frq exhibits non-optimal codon usage across its entire open reading frame. Optimization of frq codon usage abolishes both overt and molecular circadian rhythms. Codon optimization not only increases FRQ levels but, unexpectedly, also results in conformational changes in FRQ protein, altered FRQ phosphorylation profile and stability, and impaired functions in the circadian feedback loops. These results indicate that non-optimal codon usage of frq is essential for its circadian clock function. Our study provides an example of how non-optimal codon usage functions to regulate protein expression and to achieve optimal protein structure and function.

Integrating enzymatic treatment and acid hydrolysis potentially improves the economics of cellulose nanocrystal (CNC) production and demonstrates a sustainable cellulosic ethanol co-generation strategy. In this study, the effect of enzymatic treatment on filter paper and wood pulp fibers, and CNCs generated via subsequent acid hydrolysis were assessed. Characterization was performed using a pulp quality monitoring system, scanning and transmission electron microscopies, dynamic light scattering, X-ray diffraction, and thermogravimetric analysis. Enzymatic treatment partially reduced fiber length, but caused swelling, indicating simultaneous fragmentation and layer erosion. Preferential hydrolysis of less ordered cellulose by cellulases slightly improved the crystallinity index of filter paper fiber from 86% to 88%, though no change was observed for wood pulp fibre. All CNC colloids were stable with zeta potential values below −39 mV and hydrodynamic diameters ranging from 205 to 294 nm. Furthermore, the temperature for the peak rate of CNC thermal degradation was generally not affected by enzymatic treatment. These findings demonstrate that CNCs of comparable quality can be produced from an enzymatically-mediated acid hydrolysis biorefining strategy that co-generates fermentable sugars for biofuel production.

Breast reconstruction plays an integral role in the holistic management of breast cancer, with assessment of breast volume, shape, and projection vital in planning breast reconstruction surgery. Current practice includes two-dimensional (2D) photography and visual estimation in selecting ideal volume and shape of breast implants or soft-tissue flaps. Other objective quantitative means of calculating breast volume have been reported, such as direct anthropomorphic measurements or three-dimensional (3D) photography, but none have proven reliably accurate. We describe a novel approach to volumetric analysis of the breast, through the creation of a haptic, tactile model, or 3D print of scan data. This approach comprises use of a single computed tomography (CT) or magnetic resonance imaging (MRI) scan for volumetric analysis, which we use to compare to simpler estimation techniques, create software-generated 3D reconstructions, calculate, and visualize volume differences, and produce biomodels of the breasts using a 3D printer for tactile appreciation of volume differential. Using the technique described, parenchymal volume was assessed and calculated using CT data. A case report was utilized in a pictorial account of the technique, in which a volume difference of 116 cm 3 was calculated, aiding reconstructive planning. Preoperative planning, including volumetric analysis can be used as a tool to aid esthetic outcomes and attempt to reduce operative times in post-mastectomy breast reconstruction surgery. The combination of accurate volume calculations and the production of 3D-printed haptic models for tactile feedback and operative guidance are evolving techniques in volumetric analysis and preoperative planning in breast reconstruction.

Background The growth of the cellulosic ethanol industry is currently impeded by high production costs. One possible solution is to improve the performance of fermentation itself, which has great potential to improve the economics of the entire production process. Here, we demonstrated significantly improved productivity through application of an advanced fermentation approach, named self-cycling fermentation (SCF), for cellulosic ethanol production. Results The flow rate of outlet gas from the fermenter was used as a real-time monitoring parameter to drive the cycling of the ethanol fermentation process. Then, long-term operation of SCF under anaerobic conditions was improved by the addition of ergosterol and fatty acids, which stabilized operation and reduced fermentation time. Finally, an automated SCF system was successfully operated for 21 cycles, with robust behavior and stable ethanol production. SCF maintained similar ethanol titers to batch operation while significantly reducing fermentation and down times. This led to significant improvements in ethanol volumetric productivity (the amount of ethanol produced by a cycle per working volume per cycle time)—ranging from 37.5 to 75.3%, depending on the cycle number, and in annual ethanol productivity (the amount of ethanol that can be produced each year at large scale)—reaching 75.8 ± 2.9%. Improved flocculation, with potential advantages for biomass removal and reduction in downstream costs, was also observed. Conclusion Our successful demonstration of SCF could help reduce production costs for the cellulosic ethanol industry through improved productivity and automated operation.

Background The cellulosic ethanol industry has developed efficient strategies for converting sugars obtained from various cellulosic feedstocks to bioethanol. However, any further major improvements in ethanol productivity will require development of novel and innovative fermentation strategies that enhance incumbent technologies in a cost-effective manner. The present study investigates the feasibility of applying self-cycling fermentation (SCF) to cellulosic ethanol production to elevate productivity. SCF is a semi-continuous cycling process that employs the following strategy: once the onset of stationary phase is detected, half of the broth volume is automatically harvested and replaced with fresh medium to initiate the next cycle. SCF has been shown to increase product yield and/or productivity in many types of microbial cultivation. To test whether this cycling process could increase productivity during ethanol fermentations, we mimicked the process by manually cycling the fermentation for five cycles in shake flasks, and then compared the results to batch operation. Results Mimicking SCF for five cycles resulted in regular patterns with regards to glucose consumption, ethanol titer, pH, and biomass production. Compared to batch fermentation, our cycling strategy displayed improved ethanol volumetric productivity (the titer of ethanol produced in a given cycle per corresponding cycle time) and specific productivity (the amount of ethanol produced per cellular biomass) by 43.1 ± 11.6 and 42.7 ± 9.8%, respectively. Five successive cycles contributed to an improvement of overall productivity (the aggregate amount of ethanol produced at the end of a given cycle per total processing time) and the estimated annual ethanol productivity (the amount of ethanol produced per year) by 64.4 ± 3.3 and 33.1 ± 7.2%, respectively. Conclusions This study provides proof of concept that applying SCF to ethanol production could significantly increase productivities, which will help strengthen the cellulosic ethanol industry.

This multi-tier STEM Career Builder grant, funded by the National Science Foundation, focused on professional development to prepare high school teachers for teaching information systems and analytics. The project teams partnered with Apple, IBM, and the FBI to research and develop innovations including forensic databases, immersive environments, and forensic analytical tools with interdisciplinary curricula, real-world contexts, and emerging technologies. Thirty teachers were provided with four knowledge-acquisition and skill-development venues with innovations: an annual conference, teacher institute, and a summer academy. Mixed data were collected via surveys and focus groups. Project findings revealed that strategic PD and innovations impacted teachers positively.

Background Since the advent of free tissue transfer approximately 40 years ago, constant improvement particularly in the preoperative planning phase has led to flap success rate reaching 99% and improved patient outcomes. The use of imaging, such as computed tomographic angiography (CTA) or magnetic resonance angiography (MRA), for preoperative planning is now routine. However, current image modalities are restricted by being represented in two dimensions (2D) and have led to clinicians seeking novel methods of utilising the scan data, such as augmented (AR) or virtual reality (VR) and holograms. These mixed-reality devices facilitate a natural mode of visual perception and have the capacity to introduce tactile feedback. However, most AR devices are currently expensive, bulky and complicated and require tedious image registration processes. We illustrate our projector-based direct AR technique using CTA, or ARC, for preoperative planning. Methods Our bespoke ARC method consists of compact, affordable hardware (MacBook, Philips pocket projector and a 15-cm ruler) and free, open-source software (OsiriX). We have utilised this technique in six cases of perforator flaps of the thigh and abdomen (anterolateral thigh (ALT), transverse upper gracilis (TUG) and deep inferior epigastric artery perforator (DIEP) flaps. Results In all cases, 3D-reconstructed images of perforators from CTA were accurately projected onto the donor site. System calibration was rapid and convenient to use. Conclusions We illustrate a novel technique of projector-based AR CTA (or ARC) for preoperative planning in perforator flaps. The technique is affordable and readily reproducible. Level of Evidence: Level IV, diagnostic study.

Glioblastoma (GBM) is among the most invasive and lethal of cancers, frequently infiltrating surrounding healthy tissue and giving rise to rapid recurrence. It is therefore critical to establish experimental model systems and develop therapeutic approaches that enhance anti-tumor immunity. In the current study, we have employed a newly developed murine glioma model to assess the efficacy of a novel picornavirus vaccination approach for the treatment of established tumors. The GL261-Quad system is a variation of the GL261 syngeneic glioma that has been engineered to expresses model T cell epitopes including OVA257-264. MRI revealed that both GL261 and GL261-Quad tumors display characteristic features of human gliomas such as heterogeneous gadolinium leakage and larger T2 weighted volumes. Analysis of brain-infiltrating immune cells demonstrated that GL261-Quad gliomas generate detectable CD8+ T cell responses toward the tumor-specific Kb:OVA257-264 antigen. Enhancing this response via a single intracranial or peripheral vaccination with picornavirus expressing the OVA257-264 antigen increased anti-tumor CD8+ T cells infiltrating the brain, attenuated progression of established tumors, and extended survival of treated mice. Importantly, the efficacy of the picornavirus vaccination is dependent on functional cytotoxic activity of CD8+ T cells, as the beneficial response was completely abrogated in mice lacking perforin expression. Therefore, we have developed a novel system for evaluating mechanisms of anti-tumor immunity in vivo, incorporating the GL261-Quad model, 3D volumetric MRI, and picornavirus vaccination to enhance tumor-specific cytotoxic CD8+ T cell responses and track their effectiveness at eradicating established gliomas in vivo.