Rapid prototyping, Proteins, Genetic research, Mail-order industry, Fluorescence, Protein biosynthesis, Genes, Escherichia coli, and DNA synthesis

Byline: Jared Lynn Dopp, Samuel Michael Rothstein, Thomas Joseph Mansell,Nigel Forest Reuel Keywords: cell-free protein synthesis; linear template; rolling circle amplification Abstract In this study, we present a minimal template design and accompanying methods to produce assayable quantities of custom sequence proteins within 24hr from receipt of inexpensive gene fragments from a DNA synthesis vendor. This is done without the conventional steps of plasmid cloning or cell-based amplification and expression. Instead the linear template is PCR amplified, circularized, and isothermally amplified using a rolling circle polymerase. The resulting template can be used directly with cost-optimized, scalably-manufactured Escherichia coli extract and minimal supplement reagents to perform cell-free protein synthesis (CFPS) of the template protein. We demonstrate the utility of this template design and 24hr process with seven fluorescent proteins (sfGFP, mVenus, mCherry, and four GFP variants), three enzymes (chloramphenicol acetyltransferase, a chitinase catalytic domain, and native subtilisin), a capture protein (anti-GFP nanobody), and 2 antimicrobial peptides (BP100 and CA(1-7)M(2-9)). We detected each of these directly from the CFPS reaction using colorimetric, fluorogenic, and growth assays. Of especial note, the GFP variant sequences were found from genomic screening data and had not been expressed or characterized before, thus demonstrating the utility of this approach for phenotype characterization of sequenced libraries. We also demonstrate that the rolling circle amplified version of the linear template exhibits expression similar to that of a complete plasmid when expressing sfGFP in the CFPS reaction. We evaluate the cost of this approach to be $61/mg sfGFP for a 4hr reaction. We also detail limitations of this approach and strategies to overcome these, namely proteins with posttranslational modifications. CAPTION(S): Supplementary information

Theater -- Theater reviews, Rapid prototyping, Medical research, Medicine, Experimental, and CT imaging

Purpose Rapid prototyping and intraoperative computed tomography (CT) are increasingly used in orbital reconstruction when placement of implants is indicated and accurate anatomic restoration is mandatory. The purpose of this study was to review the outcomes of orbital reconstructions at a single institution and the influence of intraoperative CT and rapid prototyping on the rate of return to the operating theater. Materials and Methods A retrospective cohort analysis was performed from 2013 through 2016 to assess whether rapid prototyping and intraoperative imaging were used and the need for further revision surgery. Clinical notes were reviewed and data were collected for patient gender, age, fracture pattern, preoperative diplopia, and enophthalmos. Also noted were whether rapid prototyping and intraoperative imaging were used, the number of 'spins' required, plating systems, postoperative diplopia and enophthalmos, restoration of orbital form, and the need for further surgical intervention. Patients were excluded if no orbital implants were inserted or if they were lost to follow-up. Results Three hundred thirty-one cases of orbital trauma were reviewed (248 male and 83 female patients; age range, 7 to 96 yr; mean age, 37.5 yr). In total, 154 orbital reconstructions were performed from 2013 through 2016. Five cases required a return to the operating theater for implant revision. All 5 cases did not use intraoperative imaging (P = .0016), and 4 did not have a rapid prototype bio-model (P = .006). Twenty-five of 110 cases (22.7%) using intraoperative CT required intraoperative revision. Conclusion The present study shows improved outcomes for patients treated for orbital fractures when intraoperative imaging and rapid prototyping bio-modeling are used. As a result, postoperative imaging and the morbidity of revision surgery can be avoided. These technologies should be available and considered standard of care to any surgeon performing reconstruction of orbital fractures. Author Affiliation: (*) Consultant, Oral and Maxillofacial Surgery, Christchurch Public Hospital, Canterbury District Health Board, Christchurch, New Zealand ([Dagger]) Registrar, Oral and Maxillofacial Surgery, Christchurch Public Hospital, Canterbury District Health Board, Christchurch, New Zealand ([double dagger]) Head of Unit, Oral and Maxillofacial Surgery, Christchurch Public Hospital, Canterbury District Health Board, Christchurch, New Zealand (s.) Consultant, Oral and Maxillofacial Surgery, Christchurch Public Hospital, Canterbury District Health Board, Christchurch, New Zealand * Address correspondence and reprint requests to Dr Nguyen: Oral and Maxillofacial Surgery, Floor 5, Riverside Building, Christchurch Public Hospital, Canterbury District Health Board, Christchurch, New Zealand Article History: Received 5 January 2019; Accepted 4 February 2019 (footnote) Conflict of Interest Disclosures: None of the authors have any relevant financial relationship(s) with a commercial interest. Byline: Edward Nguyen, BDSc (Hons), MBBS (Hons), FRACDS (OMS) [edwardnguyen168@gmail.com] (*), Jamie Lockyer, BDS, Jason Erasmus, BChD, MBChB, MChD (OMS), Christopher Lim, BDSc, MBBS, FRACDS (OMS)

Magnetization and Rapid prototyping

Byline: Jon-Fredrik Nielsen, Douglas C. Noll Keywords: pulse sequence programming; pulse sequence prototyping; platform-independent; open source; open MRI Purpose To introduce a framework for rapid prototyping of MR pulse sequences. Methods We propose a simple file format, called 'TOPPE', for specifying all details of an MR imaging experiment, such as gradient and radiofrequency waveforms and the complete scan loop. In addition, we provide a TOPPE file 'interpreter' for GE scanners, which is a binary executable that loads TOPPE files and executes the sequence on the scanner. We also provide MATLAB scripts for reading and writing TOPPE files and previewing the sequence prior to hardware execution. With this setup, the task of the pulse sequence programmer is reduced to creating TOPPE files, eliminating the need for hardware-specific programming. No sequence-specific compilation is necessary; the interpreter only needs to be compiled once (for every scanner software upgrade). We demonstrate TOPPE in three different applications: k-space mapping, non-Cartesian PRESTO whole-brain dynamic imaging, and myelin mapping in the brain using inhomogeneous magnetization transfer. Results We successfully implemented and executed the three example sequences. By simply changing the various TOPPE sequence files, a single binary executable (interpreter) was used to execute several different sequences. Conclusion The TOPPE file format is a complete specification of an MR imaging experiment, based on arbitrary sequences of a (typically small) number of unique modules. Along with the GE interpreter, TOPPE comprises a modular and flexible platform for rapid prototyping of new pulse sequences. Magn Reson Med 79:3128-3134, 2018. [c] 2017 International Society for Magnetic Resonance in Medicine. Supporting information: Additional Supporting Information may be found in the online version of this article Additional Supporting Information may be found in the online version of this article. CAPTION(S): Fig. S1. Pulse sequence diagram for the k-space trajectory measurements shown in Figure 3. Fig. S2. Example of a TOPPE sequence with multiple (64) different gy and gz waveforms associated with one .mod file. Only two of the waveforms are shown. All 64 waveforms are loaded into scanner memory during sequence prescription. During sequence execution, the particular waveform to be played out is selected on-the-fly according to the corresponding entry in scanloop.txt. In this example, each waveform is of duration 40 ms. We successfully ran this sequence and switched the waveforms during sequence execution (not shown), according to the instructions in scanloop.txt. With the possibility of up to 20 different .mod files, each containing multiple waveforms, we believe TOPPE will be sufficiently flexible for most applications. However, we have observed that there appears to be a limit on total waveform memory allowed by our GE scanner: for example, the multi-waveform .mod file shown here appears to nearly reach the total memory limit. Fig. S3. Example of a relatively complex pulse sequence that is not easily implemented using traditional programming techniques: Arterial Spin Labeling with stack-of-spirals readout. Following a (velocity-selective) spin tagging pulse and a transit delay of a1/41.3 sec, a train of alternating RF excitation and data readout modules are played out (total duration a1/40.7 sec). kz (partition) encode ordering is center-out (not shown). The flip angle is increased to maintain constant signal following each excitation. For a given readout repetition interval and assuming tissue T1 of gray matter at 3T, we obtained the optimal flip angle schedule using the Matlab function fmincon. Implementing such a sequence using traditional programming techniques would be relatively laborious, and would in any case likely require the ASL tagging pulse, flip angle schedule, and perhaps the spiral readouts to be loaded from external files. Fig. S4. Another example of a relatively complex pulse sequence that is not easily implemented using traditional programming techniques: A set of 12 triangular readout gradients used to measure gradient impulse response function, as implemented in (15). Although the waveforms differ only by their time to peak (ranging from 50 to 160 I1/4s in 10 I1/4s increments), there is no direct way to encode these waveforms programmatically during run-time. In TOPPE, one can either associate each waveform with its own .mod file, or load all 12 waveforms into a single module (after zero-padding to ensure equal waveform duration).