UriSed 3 PRO automated microscope in screening bacteriuria at region-wide laboratory organization

BACKGROUND AND AIMS

We assessed the possibility to rule out negative urine cultures by counting with UriSed 3 PRO (77 Elektronika, Hungary) at Helsinki and Uusimaa Hospital District.

MATERIALS AND METHODS

Bacteria counting of the UriSed 3 PRO automated microscope was verified with reference phase contrast microscopy against growth in culture. After acceptance into routine, results of bacteria and leukocyte counting from 56 426 specimens with eight UriSed 3 PRO instruments were compared against results from parallel samples cultured on chromogenic agar. Laboratory data including preanalytical details were accessed through the regional database of the Helsinki and Uusimaa Hospital District.

RESULTS

A combined sensitivity of 87-92% and a negative predictive value of 90-96% with a specificity of 54-50% was reached, depending on criteria. Preanalytical data (incubation time in bladder) combined with the way of urine collection would improve these figures if reliable.

CONCLUSIONS

Complex patient populations, regional logistics and data interfases, and economics related to increased costs of additional particle counts against costs of screening cultures of all samples, did not support adaptation of a screening process of urine cultures. This conclusion was made locally, and may not be valid elsewhere.

Improved autosomal STR typing of degraded femur samples extracted using a custom demineralization buffer and DNA IQ™

Bone samples are utilized as a source of DNA in disaster victim identification and human remains investigations. However, DNA recovery from bones is time consuming and prone to contamination. A logical approach for postmortem identification is to validate efficient DNA extraction methods requiring less bone material using improved molecular kits with less hands-on time and workflows that facilitate faster turn-around time for processing. In this study, we evaluated DNA yield and amplification efficiency of DNA extracts using a new custom bone demineralization buffer (DMB; Promega) and extracted via manual and automated DNA IQ™ workflows. Including the demineralization step, the bone protocol can be completed in ∼4 h and even less with minimal sample handling when automated. Overall, a rapid and simple DNA extraction with improved allele recovery was validated using degraded bone samples exposed to tropical environments and post-disaster recovery as well as adverse conditions of embalming prior to internment.

Design and development of a new ambr250® bioreactor vessel for improved cell and gene therapy applications

The emergence of cell and gene therapies has generated significant interest in their clinical and commercial potential. However, these therapies are prohibitively expensive to manufacture and can require extensive time for development due to our limited process knowledge and understanding. The automated ambr250® stirred-tank bioreactor platform provides an effective platform for high-throughput process development. However, the original dual pitched-blade 20 mm impeller and baffles proved sub-optimal for cell therapy candidates that require suspension of microcarriers (e.g. for the culture of adherent human mesenchymal stem cells) or other particles such as activating Dynabeads® (e.g. for the culture of human T-cells). We demonstrate the development of a new ambr250® stirred-tank bioreactor vessel which has been designed specifically to improve the suspension of microcarriers/beads and thereby improve the culture of such cellular systems. The new design is unbaffled and has a single, larger elephant ear impeller. We undertook a range of engineering and physical characterizations to determine which vessel and impeller configuration would be most suitable for suspension based on the minimum agitation speed (N_JS) and associated specific power input (P/V)_JS. A vessel (diameter, T, = 60 mm) without baffles and incorporating a single elephant ear impeller (diameter 30 mm and 45° pitch-blade angle) was selected as it had the lowest (P/V)_JS and therefore potentially, based on Kolmogorov concepts, was the most flexible system. These experimentally-based conclusions were further validated firstly with computational fluid dynamic (CFD) simulations and secondly experimental studies involving the culture of both T-cells with Dynabeads® and hMSCs on microcarriers. The new ambr250® stirred-tank bioreactor successfully supported the culture of both cell types, with the T-cell culture demonstrating significant improvements compared to the original ambr250® and the hMSC-microcarrier culture gave significantly higher yields compared with spinner flask cultures. The new ambr250® bioreactor vessel design is an effective process development tool for cell and gene therapy candidates and potentially for autologous manufacture too.

Turning Nature's own processes into design strategies for living bone implant biomanufacturing: a decade of Developmental Engineering

A decade after the term developmental engineering (DE) was coined to indicate the use of developmental processes as blueprints for the design and development of engineered living implants, a myriad of proof-of-concept studies demonstrate the potential of this approach in small animal models. This review provides an overview of DE work, focusing on applications in bone regeneration. Enabling technologies allow to quantify the distance between in vitro processes and their developmental counterpart, as well as to design strategies to reduce that distance. By embedding Nature's robust mechanisms of action in engineered constructs, predictive large animal data and subsequent positive clinical outcomes can be gradually achieved. To this end, the development of next generation biofabrication technologies should provide the necessary scale and precision for robust living bone implant biomanufacturing.

A fully automated microfluidic PCR-array system for rapid detection of multiple respiratory tract infection pathogens

Rapid and accurate identification of respiratory tract infection pathogens is of utmost importance for clinical diagnosis and treatment, as well as prevention of pathogen transmission. To meet this demand, a microfluidic chip-based PCR-array system, Onestart, was developed. The Onestart system uses a microfluidic chip packaged with all the reagents required, and the waste liquid is also collected and stored on the chip. This ready-to-use system can complete the detection of 21 pathogens in a fully integrated manner, with sample lysis, nucleic acid extraction/purification, and real-time PCR sequentially implemented on the same chip. The entire analysis process is completed within 1.5 h, and the system automatically generates a test report. The lower limit-of-detection (LOD) of the Onestart assay was determined to be 1.0 × 10³ copies·mL⁻¹. The inter-batch variation of cycle threshold (Ct) values ranged from 0.08% to 0.69%, and the intra-batch variation ranged from 0.9% to 2.66%. Analytical results of the reference sample mix showed a 100% specificity of the Onestart assay. The analysis of batched clinical samples showed consistency of the Onestart assay with real-time PCR. With its ability to provide rapid, sensitive, and specific detection of respiratory tract infection pathogens, application of the Onestart system will facilitate timely clinical management of respiratory tract infections and effective prevention of pathogen transmission.

Personalized automation of treatment planning in head-neck cancer: A step forward for quality in radiation therapy?

PURPOSE

To perform a comprehensive dosimetric and clinical evaluation of the new Pinnacle Personalized automated planning system for complex head-and-neck treatments.

METHODS

Fifteen consecutive head-neck patients were enrolled. Radiotherapy was prescribed using VMAT with simultaneous integrated boost strategy. Personalized planning integrates the Feasibility engine able to supply an "a priori" DVH prediction of the achievability of planning goals. Comparison between clinically accepted manually-generated (MP) and automated (AP) plans was performed using dose-volume histograms and a blinded clinical evaluation by two radiation oncologists. Planning time between MP and AP was compared. Dose accuracy was validated using the PTW Octavius-4D phantom together with the 1500 2D-array.

RESULTS

For similar targets coverage, AP plans reported less irradiation of healthy tissue, with significant dose reduction for spinal cord, brainstem and parotids. On average, the mean dose to parotids and maximal doses to spinal cord and brainstem were reduced by 13-15% (p < 0.001), 9% (p < 0.001) and 16% (p < 0.001), respectively. The integral dose was reduced by 16% (p < 0.001). The dose conformity for the three PTVs was significantly higher with AP plans (p < 0.001). The two oncologists chose AP plans in more than 80% of cases. Overall planning times were reduced to <30 min for automated optimization. All AP plans passed the 3%/2 mm γ-analysis by more than 95%.

CONCLUSION

Complex head-neck plans created using Personalized automated engine provided an overall increase of plan quality, in terms of dose conformity and sparing of normal tissues. The Feasibility module allowed OARs dose sparing well beyond the clinical objectives.

Automated synthesis of [18F]Ga-rhPSMA-7/ -7.3: results, quality control and experience from more than 200 routine productions

Introduction

The radiohybrid (rh) prostate-specific membrane antigen (PSMA)-targeted ligand [¹⁸F]Ga-rhPSMA-7 has previously been clinically assessed and demonstrated promising results for PET-imaging of prostate cancer. The ligand is present as a mixture of four stereoisomers ([¹⁸F]Ga-rhPSMA-7.1, − 7.2, − 7.3 and − 7.4) and after a preclinical isomer selection process, [¹⁸F]Ga-rhPSMA-7.3 has entered formal clinical trials. Here we report on the establishment of a fully automated production process for large-scale production of [¹⁸F]Ga-rhPSMA-7/ -7.3 under GMP conditions (EudraLex).

Methods

[¹⁸F]Fluoride in highly enriched [¹⁸O]H₂O was retained on a strong anion exchange cartridge, rinsed with anhydrous acetonitrile and subsequently eluted with a solution of [K⁺ ⊂ 2.2.2]OH⁻ in anhydrous acetonitrile into a reactor containing Ga-rhPSMA ligand and oxalic acid in DMSO. ¹⁸F-for-¹⁹F isotopic exchange at the Silicon-Fluoride Acceptor (SiFA) was performed at room temperature, followed by dilution with buffer and cartridge-based purification. Optimum process parameters were determined on the laboratory scale and thereafter implemented into an automated synthesis. Data for radiochemical yield (RCY), purity and quality control were analyzed for 243 clinical productions (160 for [¹⁸F]Ga-rhPSMA-7; 83 for [¹⁸F]Ga-rhPSMA-7.3).

Results

The automated production of [¹⁸F]Ga-rhPSMA-7 and the single isomer [¹⁸F]Ga-rhPSMA-7.3 is completed in approx. 16 min with an average RCY of 49.2 ± 8.6% and an excellent reliability of 98.8%. Based on the different starting activities (range: 31–130 GBq, 89 ± 14 GBq) an average molar activity of 291 ± 62 GBq/μmol (range: 50–450 GBq/μmol) was reached for labeling of 150 nmol (231 μg) precursor. Radiochemical purity, as measured by radio-high performance liquid chromatography and radio-thin layer chromatography, was 99.9 ± 0.2% and 97.8 ± 1.0%, respectively.

Conclusion

This investigation demonstrates that ¹⁸F-for-¹⁹F isotopic exchange is well suited for the fast, efficient and reliable automated routine production of ¹⁸F-labeled PSMA-targeted ligands. Due to its simplicity, speed and robustness the development of further SiFA-based radiopharmaceuticals is highly promising and can be of far-reaching importance for future theranostic concepts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41181-021-00120-5.

High throughput screening for autophagy

Robotized high throughput screening allows for the assessment of autophagy in a large number of samples. Here, we describe a drug discovery platform for the phenotypic identification of novel autophagy inducers by means of automated cell biology workflows employing robotized cell culture, sample preparation and data acquisition. In this setting, fluorescent biosensor cells that express microtubule-associated proteins 1A/1B light chain 3B (best known as LC3) conjugated to green fluorescent protein (GFP), are utilized together with automated high content microscopy for the image-based assessment of autophagy. In sum, we detail a drug discovery screening workflow from high throughput sample preparation and processing to data acquisition and analysis.

Verification of UriSed 3 PRO automated urine microscope in regional laboratory environment

BACKGROUND AND AIMS

Ten UriSed 3 PRO automated microscopes (77 Elektronika, Hungary) were verified for nine HUSLAB laboratories with 160 000 annual urine samples.

MATERIALS AND METHODS

Particle counting of the primary UriSed 3 PRO instrument (77 Elektronika, Hungary) was verified against reference visual microscopy with 463 urine specimens, and against urine culture on chromogenic agar plates with parallel 396 specimens. Nine secondary instruments were compared pairwise with the primary instrument.

RESULTS

Relative imprecisions compared to Poisson distribution, R(CV), were estimated to be 1.0 for white blood cell (WBC) and 1.5 for red blood cell (RBC) counts, respectively. Spearman's correlations against visual microscopy were r_S = 0.94 for WBC, r_S = 0.87 for RBC, and r_S = 0.82 for squamous epithelial cell (SEC) counts. Agreement with visual microscopy (Cohen's weighted kappa) was 0.94 for WBC, 0.89 for RBC, 0.88 for SEC, 0.59 for combined casts, and 0.49 for non-squamous epithelial cells (NEC). Bacteria were detected with a sensitivity of 90% and specificity of 39 against culture at 10⁷ CFB/L (10⁴ CFU/mL). Created flagging limits allowed automated reporting for 70-75% of patient results.

CONCLUSIONS

UriSed 3 PRO instruments were adopted into routine use after acceptance of the verification.

Radiation dose reduction, improved isocenter accuracy and CT scan time savings with automatic patient positioning by a 3D camera

PURPOSE

To compare CT isocenter accuracy, patient dose, and scan time in adults imaged with and without use of a 3D camera.

METHOD

571 CT examinations utilizing a 3D camera for initial patient positioning (optional radiographer isocenter adjustment) and 504 examinations scanned without the camera between 10/1/2018 and 3/19/2019 were retrospectively identified. All exams were chest or abdominopelvic CTs. The isocenters of these exams were compared with the true isocenters defined as the manually delineated centroid of the body in the CT volume. The size specific dose estimate (SSDE) (mGy) of radiation dose obtained from departmental software for the 4 most common protocols on one CT scanner was compared before and after implementation of the 3D camera. The times required for the entire scan and just the topogram "scout" were compared with and without the 3D camera for noncontrast chest and abdominopelvic CT enterography protocols. 2-tailed t-tests and Mann-Whitney U tests were used (P < 0.05 indicated statistical significance).

RESULTS

The deviation from true isocenter was 6.8 ± 6.1 mm (P = 0.043) and 16.3 ± 14.0 mm (P < 0.01) with and without the 3D camera, respectively (P < 0.01). CT radiographers accepted isocenter location without alteration in 93 % of examinations. Average SSDE savings with the 3D camera ranged 1.0-2.4 mGy (21-31 %) for the 4 most commonly performed protocols (p < 0.01). Median scout time savings was 32 s (Camera vs. No-Camera cohorts) (P < 0.01). Average noncontrast chest CT and CT enterography scan time savings were 19 s and 17 s with the 3D camera, respectively (P < 0.01).

CONCLUSIONS

The 3D camera improved accuracy of patient positioning while reducing radiation dose and examination time. Implementation of a 3D camera helps standardize workflow in a busy clinical practice.

The views of health guideline developers on the use of automation in health evidence synthesis

BACKGROUND

The increasingly rapid rate of evidence publication has made it difficult for evidence synthesis-systematic reviews and health guidelines-to be continually kept up to date. One proposed solution for this is the use of automation in health evidence synthesis. Guideline developers are key gatekeepers in the acceptance and use of evidence, and therefore, their opinions on the potential use of automation are crucial.

METHODS

The objective of this study was to analyze the attitudes of guideline developers towards the use of automation in health evidence synthesis. The Diffusion of Innovations framework was chosen as an initial analytical framework because it encapsulates some of the core issues which are thought to affect the adoption of new innovations in practice. This well-established theory posits five dimensions which affect the adoption of novel technologies: Relative Advantage, Compatibility, Complexity, Trialability, and Observability. Eighteen interviews were conducted with individuals who were currently working, or had previously worked, in guideline development. After transcription, a multiphase mixed deductive and grounded approach was used to analyze the data. First, transcripts were coded with a deductive approach using Rogers' Diffusion of Innovation as the top-level themes. Second, sub-themes within the framework were identified using a grounded approach.

RESULTS

Participants were consistently most concerned with the extent to which an innovation is in line with current values and practices (i.e., Compatibility in the Diffusion of Innovations framework). Participants were also concerned with Relative Advantage and Observability, which were discussed in approximately equal amounts. For the latter, participants expressed a desire for transparency in the methodology of automation software. Participants were noticeably less interested in Complexity and Trialability, which were discussed infrequently. These results were reasonably consistent across all participants.

CONCLUSIONS

If machine learning and other automation technologies are to be used more widely and to their full potential in systematic reviews and guideline development, it is crucial to ensure new technologies are in line with current values and practice. It will also be important to maximize the transparency of the methods of these technologies to address the concerns of guideline developers.

Automated flow control of a multi-lane swimming chamber for small fishes indicates species-specific sensitivity to experimental protocols

In fishes, swimming performance is considered an important metric to measure fitness, dispersal and migratory abilities. The swimming performance of individual larval fishes is often integrated into models to make inferences on how environmental parameters affect population-level dynamics (e.g. connectivity). However, little information exists regarding how experimental protocols affect the swimming performance of marine fish larvae. In addition, the technical setups used to measure larval fish swimming performance often lack automation and accurate control of water quality parameters and flow velocity. In this study, we automated the control of multi-lane swimming chambers for small fishes by developing an open-source algorithm. This automation allowed us to execute repeatable flow scenarios and reduce operator interference and inaccuracies in flow velocity typically associated with manual control. Furthermore, we made structural modifications to a prior design to reduce the areas of lower flow velocity. We then validated the flow dynamics of the new chambers using computational fluid dynamics and particle-tracking software. The algorithm provided an accurate alignment between the set and measured flow velocities and we used it to test whether faster critical swimming speed (U crit) protocols (i.e. shorter time intervals and higher velocity increments) would increase U crit of early life stages of two tropical fish species [4-10-mm standard length (SL)]. The U crit of barramundi (Lates calcarifer) and cinnamon anemonefish (Amphiprion melanopus) increased linearly with fish length, but in cinnamon anemonefish, U crit started to decrease upon metamorphosis. Swimming protocols using longer time intervals (more than 2.5 times increase) negatively affected U crit in cinnamon anemonefish but not in barramundi. These species-specific differences in swimming performance highlight the importance of testing suitable U crit protocols prior to experimentation. The automated control of flow velocity will create more accurate and repeatable data on swimming performance of larval fishes. Integrating refined measurements into individual-based models will support future research on the effects of environmental change.

An unattended HS-SPME-GC-MS/MS combined with a novel sample preparation strategy for the reliable quantitation of C8 volatiles in mushrooms: A sample preparation strategy to fully control the volatile emission

Eight carbon (C8) compounds are the key characteristic flavors of mushrooms. The quantitative analysis of the volatiles in mushrooms is challenging especially with the unattended HS-SPME-GC-MS. An unattended HS-SPME-GC-MS/MS in combination with novel sample preparation of the complete control of volatile emissions was developed for the quantitation of the C8 volatiles in mushrooms. The sample preparation strategy was composed of freeze-drying, rehydration, and the addition of a 15% citric acid solution. With this strategy, the volatile emission from mushroom was fully controlled at a certain time point. This method was found to be highly reliable, sensitive, precise, and accurate. This method was successfully applied to measure the contents of the C8 volatiles in the beech, button, and shiitake mushrooms. 1-Octene-3-ol was the most predominant compound in the mushrooms, representing 62.4, 69.0, and 89.2% of the total C8 volatiles in the beech, button, and shiitake mushrooms, respectively.

Fully automatic peak frequency estimation of the posterior dominant rhythm in a large retrospective hospital EEG cohort

•

Fully automatic estimation of the peak frequency of the posterior dominant rhythm.

•

Automatic estimates are very similar to human ratings.

•

Algorithm made available with a simple graphical interface.

Objective

To develop and test a fully automated method for estimation of the peak frequency of the posterior dominant rhythm (PDR) in a large retrospective EEG cohort.

Methods

Thresholding was used to select suitable EEG data segments for spectral estimation for electrode O1 and O2. A random sample of 100 peak frequency estimates were blindly rated by two independent raters to validate the results of the automatic PDR peak frequency estimates. We investigated the relationship with age, sex and binary EEG classification.

Results

There were 9197 eligible EEGs which resulted in a total of 6104 PDR peak frequency estimates. The relationship between automatic estimates and age was found to be consistent with the literature. The correlation between human ratings and automatic scoring was very high, rho = 0.94–0.95. There was a sex difference of d = 0.33 emerging at puberty with females having a faster PDR peak frequency than males.

Conclusions

Fully automatic PDR peak frequency estimation not dependent on annotated EEG produced results that are very close to human ratings.

Significance

PDR peak frequency can be automatically estimated. A compiled version of the algorithm is included as an app for independent use.

Effect of automation transparency in the management of multiple unmanned vehicles

Automated decision aids can undoubtedly benefit system performance, but have the potential to provide incorrect advice, creating the possibility for automation disuse or misuse. This paper examined the extent to which increased automation transparency could improve the accuracy of automation use in a simulation of unmanned vehicle control. Participants were required to assign the best unmanned vehicle to complete missions. An automated recommender system provided advice but was not always reliable. Three levels of automation transparency were manipulated between-participants. Providing transparency regarding the reasoning underlying automated recommendations improved the accuracy of automation use, with no cost to decision time or subjective workload. Higher transparency in the form of projected decision outcome visualizations led to faster decisions, but less accurate automation use and an automation bias. Implications for the design of transparent interfaces to improve human-autonomy teaming outcomes in time-pressured environments are discussed.

Use of Molecular Markers for Doubled Haploid Technology: From Academia to Plant Breeding Companies

Molecular markers are employed for doubled haploid (DH) technology by researchers and applied plant breeders in many crops. In the 1990s, isozymes and RFLPs were commonly used marker technologies to characterize DHs and were later replaced by PCR- based markers (e.g., RAPDs, AFLPs, ISSRs, SSRs) and today by SNPs. Markers are used for multiple purposes in DH production, that is, for the study of genes underlying haploid induction and confirming homozygous plants of gametophytic origin. Furthermore, they are tools for investigating segregation in DH populations and for mapping simple and complex traits using DHs. The deployment of DHs and markers for developing trait-linked markers are demonstrated with examples from rapeseed, wheat, and barley. Marker development for resistance to viruses derived from genetic resources and their use in, for example, pyramiding of resistance genes, are given as an example for the combination of DH-technology and marker development in research. Today, marker systems amenable to automation are frequently used in applied plant breeding. Practical examples are given from Lantmännen (LM) ( https://Lantmannen.com ) using large-scale genotyping for variety development based on SSRs and SNPs.

Deriving alpha angle from anterior-posterior dual-energy x-ray absorptiometry scans: an automated and validated approach

Introduction: Alpha angle (AA) is a widely used measure of hip shape that is commonly used to define cam morphology, a bulging of the lateral aspect of the femoral head. Cam morphology has shown strong associations with hip osteoarthritis (OA) making the AA a clinically relevant measure. In both clinical practice and research studies, AA tends to be measured manually which can be inconsistent and time-consuming. Objective: We aimed to (i) develop an automated method of deriving AA from anterior-posterior dual-energy x-ray absorptiometry (DXA) scans; and (ii) validate this method against manual measures of AA. Methods: 6,807 individuals with left hip DXAs were selected from UK Biobank. Outline points were manually placed around the femoral head on 1,930 images before training a Random Forest-based algorithm to place the points on a further 4,877 images. An automatic method for calculating AA was written in Python 3 utilising these outline points. An iterative approach was taken to developing and validating the method, testing the automated measures against independent batches of manually measured images in sequential experiments. Results: Over the course of six experimental stages the concordance correlation coefficient, when comparing the automatic AA to manual measures of AA, improved from 0.28 [95% confidence interval 0.13-0.43] for the initial version to 0.88 [0.84-0.92] for the final version. The inter-rater kappa statistic comparing automatic versus manual measures of cam morphology, defined as AA ³≥60°, improved from 0.43 [80% agreement] for the initial version to 0.86 [94% agreement] for the final version. Conclusions: We have developed and validated an automated measure of AA from DXA scans, showing high agreement with manually measuring AA. The proposed method is available to the wider research community from Zenodo.

Symptoms of convergence and accommodative insufficiency predict engagement and cognitive fatigue during complex task performance with and without automation

Deficits in the accommodative and/or vergence responses have been linked with inattentive behavioral symptoms. While using automated systems (e.g., self-driving cars, autopilot), operators (e.g., drivers, pilots, soldiers) visually monitor displays for critical changes, making deficits in the accommodative and/or vergence responses potentially hazardous for individuals remaining actively engaged in the task at hand. The purpose of this study was to determine if symptoms of accommodative-vergence deficits predict an individual's level of task engagement and cognitive fatigue while performing a flight simulation task with or without automation. Eighty-four participants performed a flight simulation task with or without automation. Prior to task completion, self-report accommodative-convergence deficit symptoms were assessed with the Convergence Insufficiency Symptom Survey (CISS). Before and after the flight simulation task participants rated their task engagement and cognitive fatigue. Electroencephalographic activity (EEG) was recorded concurrently during task performance. Results showed that higher scores on the CISS were related to increased feelings of fatigue and decreased ratings of task engagement. The CISS was also positively related to parietal-occipital fast alpha power during the last 10 min of the task for participants using automation, suggesting increased cortical idling. CISS scores did not predict performance. Results have implications for optimizing operator cognitive states over extended task performance.

Transforming universities in interactive digital platform: case of city university of science and information technology

The purpose of this research was to understand the automation of Higher Education Institutes (HEIs), and to evaluate the automated process from the perspective of developing country. A single case study of City University of Science and Information Technology (CUSIT), Pakistan was selected as a unit of analysis. Mix methodology was used in this research. Semi-structured in-depth interviews were conducted from the top management as a primary source while secondary data regarding usage and functions of LMS was collected for the period of 2 years (four semesters Fall-2017-Spring 2019). Data from both sources was utilized, and triangulated for case building and analysis. It was found that CUSIT has a state-of-the-art automated infrastructure, management information system (MIS) and learning management system (LMS) which facilitates faculty, staff and administration. LMS provides an integrated and digital platform to key stakeholders particularly to the teachers for sharing course outlines, lesson plan, assignment generation and submission, announcements and generating assessment reports. Similarly, the student gets access to all course material, assignments, assessment report, notices, and other relevant information at any point of time. However, the system lacks some of the major E-learning features with limited support to the large file size, real time learning, online classes, real time feedback and query system etc. Furthermore, this study identified few seldomly used functions of automated system as well as few duplications and operational activities which requires consideration by the management. The case of CUSIT proves to be a practical case for all those universities who are facing challenges due to corona virus pandemic and are looking for a solution to continue education through distance learning and e-learning platforms. This study supports the automation of HEIs and provides lesson learned for the academia and management of HEIs by identification of success features as well as limitations of the system.

Automation of Immunoglobulin Glycosylation Analysis

The development of reliable, affordable, high-resolution glycomics technologies that can be used for many samples in a high-throughput manner are essential for both the optimization of glycosylation in the biopharmaceutical industry as well as for the advancement of clinical diagnostics based on glycosylation biomarkers. We will use this chapter to review the sample preparation processes that have been used on liquid-handling robots to obtain high-quality glycomics data for both biopharmaceutical and clinical antibody samples. This will focus on glycoprotein purification, followed by glycan or glycopeptide generation, derivatization and enrichment. The use of liquid-handling robots for glycomics studies on other sample types beyond antibodies will not be discussed here. We will summarize our thoughts on the current status of the field and explore the benefits and challenges associated with developing and using automated platforms for sample preparation. Finally, the future outlook for the automation of glycomics will be discussed along with a projected impact on the field in general.

Routine Analysis of N-Glycans Using Liquid Chromatography Coupled to Routine Mass Detection

Analysis of N-glycans are commonly conducted via enzymatic release, labeling, and liquid chromatography (LC) separation and fluorescent detection. Mass spectrometry (MS) has been increasingly used as an orthogonal detection method to provide additional structural information and increase the confidence of N-glycan analysis. In this chapter, we describe a method to perform routine analysis of N-glycans including the sample preparation with a signal-enhancement label, LC-MS data generation, and data analysis. Using this method, up to 24 N-glycan samples can be prepared at one time and analyzed by LC-MS. With the addition of automation platform, up to 96 N-glycan samples can be prepared and analyzed in a high-throughput manner.

Deriving alpha angle from anterior-posterior dual-energy x-ray absorptiometry scans: an automated and validated approach

Introduction: Alpha angle (AA) is a widely used imaging measure of hip shape that is commonly used to define cam morphology, a bulging of the lateral aspect of the femoral head. Cam morphology has shown strong associations with hip osteoarthritis (OA) making the AA a clinically relevant measure. In both clinical practice and research studies, AA tends to be measured manually which can be inconsistent and time-consuming. Objective: We aimed to (i) develop an automated method of deriving AA from anterior-posterior dual-energy x-ray absorptiometry (DXA) scans; and (ii) validate this method against manual measures of AA. Methods: 6,807 individuals with left hip DXAs were selected from UK Biobank. Outline points were manually placed around the femoral head on 1,930 images before training a Random Forest-based algorithm to place the points on a further 4,877 images. An automatic method for calculating AA was written in Python 3 utilising these outline points. An iterative approach was taken to developing and validating the method, testing the automated measures against independent batches of manually measured images in sequential experiments. Results: Over the course of six experimental stages the concordance correlation coefficient, when comparing the automatic AA to manual measures of AA, improved from 0.28 [95% confidence interval 0.13-0.43] for the initial version to 0.88 [0.84-0.92] for the final version. The inter-rater kappa statistic comparing automatic versus manual measures of cam morphology, defined as AA ³≥60°, improved from 0.43 [80% agreement] for the initial version to 0.86 [94% agreement] for the final version. Conclusions: We have developed and validated an automated measure of AA from DXA scans, showing high agreement with manually measuring AA. The proposed method is available to the wider research community from Zenodo.

Development of an Automated Image Analyzer for Microvessel Density Measurement in Bone Marrow Biopsies

Angiogenesis is important for the proliferation and survival of multiple myeloma (MM) cells. Bone marrow (BM) microvessel density (MVD) is a useful marker of angiogenesis and an increase in MVD can be used as a marker of poor prognosis in MM patients. We developed an automated image analyzer to assess MVD from images of BM biopsies stained with anti-CD34 antibodies using two color models. MVD was calculated by merging images from the red and hue channels after eliminating non-microvessels. The analyzer results were compared with those obtained by two experienced hematopathologists in a blinded manner using the 84 BM samples of MM patients. Manual assessment of the MVD by two hematopathologists yielded mean±SD values of 19.4±11.8 and 20.0±11.8. The analyzer generated a mean±SD of 19.5±11.2. The intraclass correlation coefficient (ICC) and Bland-Altman plot of the MVD results demonstrated very good agreement between the automated image analyzer and both hematopathologists (ICC=0.893 [0.840–0.929] and ICC=0.906 [0.859–0.938]). This automated analyzer can provide time- and labor-saving benefits with more objective results in hematology laboratories.

Promises and Perils of Artificial Intelligence in Neurosurgery

Artificial intelligence (AI)-facilitated clinical automation is expected to become increasingly prevalent in the near future. AI techniques may permit rapid and detailed analysis of the large quantities of clinical data generated in modern healthcare settings, at a level that is otherwise impossible by humans. Subsequently, AI may enhance clinical practice by pushing the limits of diagnostics, clinical decision making, and prognostication. Moreover, if combined with surgical robotics and other surgical adjuncts such as image guidance, AI may find its way into the operating room and permit more accurate interventions, with fewer errors. Despite the considerable hype surrounding the impending medical AI revolution, little has been written about potential downsides to increasing clinical automation. These may include both direct and indirect consequences. Directly, faulty, inadequately trained, or poorly understood algorithms may produce erroneous results, which may have wide-scale impact. Indirectly, increasing use of automation may exacerbate de-skilling of human physicians due to over-reliance, poor understanding, overconfidence, and lack of necessary vigilance of an automated clinical workflow. Many of these negative phenomena have already been witnessed in other industries that have already undergone, or are undergoing "automation revolutions," namely commercial aviation and the automotive industry. This narrative review explores the potential benefits and consequences of the anticipated medical AI revolution from a neurosurgical perspective.

Automated engineering of synthetic metabolic pathways for efficient biomanufacturing

Metabolic engineering involves the engineering and optimization of processes from single-cell to fermentation in order to increase production of valuable chemicals for health, food, energy, materials and others. A systems approach to metabolic engineering has gained traction in recent years thanks to advances in strain engineering, leading to an accelerated scaling from rapid prototyping to industrial production. Metabolic engineering is nowadays on track towards a truly manufacturing technology, with reduced times from conception to production enabled by automated protocols for DNA assembly of metabolic pathways in engineered producer strains. In this review, we discuss how the success of the metabolic engineering pipeline often relies on retrobiosynthetic protocols able to identify promising production routes and dynamic regulation strategies through automated biodesign algorithms, which are subsequently assembled as embedded integrated genetic circuits in the host strain. Those approaches are orchestrated by an experimental design strategy that provides optimal scheduling planning of the DNA assembly, rapid prototyping and, ultimately, brings forward an accelerated Design-Build-Test-Learn cycle and the overall optimization of the biomanufacturing process. Achieving such a vision will address the increasingly compelling demand in our society for delivering valuable biomolecules in an affordable, inclusive and sustainable bioeconomy.