Evaluation of chest X-Ray with automated interpretation algorithms for mass tuberculosis screening in prisons.

Rationale: The World Health Organization (WHO) recommends systematic tuberculosis (TB) screening in prisons. Evidence is lacking for accurate and scalable screening approaches in this setting. Objectives: To assess the diagnostic accuracy of artificial intelligence-based chest x-ray interpretation algorithms for TB screening in prisons. Methods: Prospective TB screening study in three prisons in Brazil from October 2017 to December 2019. We administered a standardized questionnaire, performed chest x-ray in a mobile unit, and collected sputum for confirmatory testing using Xpert MTB/RIF and culture. We evaluated x-ray images using three algorithms (CAD4TB version 6, LunitTB and qXR) and compared their diagnostic accuracy. We utilized multivariable logistic regression to assess the effect of demographic and clinical characteristics on algorithm accuracy. Finally, we investigated the relationship between abnormality scores and Xpert semi-quantitative results. Measurements and Main Results: Among 2,075 incarcerated individuals, 259 (12.5%) had confirmed TB. All three algorithms performed similarly overall with AUCs of 0.87-0.91. At 90% sensitivity, only LunitTB and qXR met the WHO Target Product Profile requirements for a triage test, with specificity of 84% and 74%, respectively. All algorithms had variable performance by age, prior TB, smoking, and presence of TB symptoms. LunitTB was the most robust to this heterogeneity, but nonetheless failed to meet the TPP for individuals with previous TB. Abnormality scores of all three algorithms were significantly correlated with sputum bacillary load. Conclusions: Automated x-ray interpretation algorithms can be an effective triage tool for TB screening in prisons. However, their specificity is insufficient in individuals with previous TB.

Complete biosynthesis of the bisbenzylisoquinoline alkaloids guattegaumerine and berbamunine in yeast

Benzylisoquinoline alkaloids (BIAs) are a diverse class of medicinal plant natural products. Nearly 500 dimeric bisbenzylisoquinoline alkaloids (bisBIAs), produced by the coupling of two BIA monomers, have been characterized and display a range of pharmacological properties, including anti-inflammatory, antitumor, and antiarrhythmic activities. In recent years, microbial platforms have been engineered to produce several classes of BIAs, which are rare or difficult to obtain from natural plant hosts, including protoberberines, morphinans, and phthalideisoquinolines. However, the heterologous biosyntheses of bisBIAs have thus far been largely unexplored. Here, we describe the engineering of yeast strains that produce the Type I bisBIAs guattegaumerine and berbamunine de novo. Through strain engineering, protein engineering, and optimization of growth conditions, a 10,000-fold improvement in the production of guattegaumerine, the major bisBIA pathway product, was observed. By replacing the cytochrome P450 used in the final coupling reaction with a chimeric variant, the product profile was inverted to instead produce solely berbamunine. Our highest titer engineered yeast strains produced 108 and 25 mg/L of guattegaumerine and berbamunine, respectively. Finally, the inclusion of two additional putative BIA biosynthesis enzymes, SiCNMT2 and NnOMT5, into our bisBIA biosynthetic strains enabled the production of two derivatives of bisBIA pathway intermediates de novo: magnocurarine and armepavine. The de novo heterologous biosyntheses of bisBIAs presented here provide the foundation for the production of additional medicinal bisBIAs in yeast.

Antileishmanial Drug Discovery and Development: Time to Reset the Model?

Leishmaniasis is a vector-borne parasitic disease caused by Leishmania species. The disease affects humans and animals, particularly dogs, provoking cutaneous, mucocutaneous, or visceral processes depending on the Leishmania sp. and the host immune response. No vaccine for humans is available, and the control relies mainly on chemotherapy. However, currently used drugs are old, some are toxic, and the safer presentations are largely unaffordable by the most severely affected human populations. Moreover, its efficacy has shortcomings, and it has been challenged by the growing reports of resistance and therapeutic failure. This manuscript presents an overview of the currently used drugs, the prevailing model to develop new antileishmanial drugs and its low efficiency, and the impact of deconstruction of the drug pipeline on the high failure rate of potential drugs. To improve the predictive value of preclinical research in the chemotherapy of leishmaniasis, several proposals are presented to circumvent critical hurdles—namely, lack of common goals of collaborative research, particularly in public–private partnership; fragmented efforts; use of inadequate surrogate models, especially for in vivo trials; shortcomings of target product profile (TPP) guides.

The effect of new Mycobacterium tuberculosis infection on the sensitivity of prognostic TB signatures

BACKGROUND: Tests that identify individuals at greatest risk of TB will allow more efficient targeting of preventive therapy. The WHO target product profile for such tests defines optimal sensitivity of 90% and minimum sensitivity of 75% for predicting incident TB. The CORTIS (Correlate of Risk Targeted Intervention Study) evaluated a blood transcriptomic signature (RISK11) for predicting incident TB in a high transmission setting. RISK11 is able to predict TB disease progression but optimal prognostic performance was limited to a 6-month horizon.METHODS: Using a mathematical model, we estimated how subsequent Mycobacterium tuberculosis (MTB) infection may have contributed to the decline in sensitivity of RISK11. We calculated the effect at different RISK11 thresholds (60% and 26%) and for different assumptions about the risk of MTB infection.RESULTS: Modelled sensitivity over 15 months, excluding new infection, was 28.7% (95% CI 12.3–74.1) compared to 25.0% (95% CI 12.7–45.9) observed in the trial. Modelled sensitivity exceeded the minimum criteria (>75%) over a 9-month horizon at the 60% threshold and over 12 months at the 26% threshold.CONCLUSIONS: The effect of new infection on prognostic signature performance is likely to be small. Signatures such as RISK11 may be most useful in individuals, such as household contacts, where probable time of infection is known.

The development of an intellectual property strategy for a biotechnology company

<p>The 2014 Masters of Advanced Technology Enterprise (MATE) programme is a multi-disciplinary course with the goal of creating teams that explore the challenges of creating successful technology enterprises. NacreTech is the result of one of the enterprises which has been developed within this course. It has found a market application for a nacre-like material as a biodegradable osteoconductive load bearing materials for orthopaedic implants and developed a target product profile to help guide further material development to out-compete existing materials on the market. In addition a proof of concept testing plan, intellectual property strategy and regulatory analysis has been conducted. This thesis is based on the author’s experience working within NacreTech while applying current knowledge and thinking surrounding protecting intellectual property for biotechnology. In particular, the author has investigated the intellectual property aspects, such as the requirements of the complete specification, filing dates and locations, and existing strategy models, required for commercialisation of the NacreTech biomaterial and examines the factors which influenced the development of the intellectual strategy.</p>

The development of an intellectual property strategy for a biotechnology company

<p>The 2014 Masters of Advanced Technology Enterprise (MATE) programme is a multi-disciplinary course with the goal of creating teams that explore the challenges of creating successful technology enterprises. NacreTech is the result of one of the enterprises which has been developed within this course. It has found a market application for a nacre-like material as a biodegradable osteoconductive load bearing materials for orthopaedic implants and developed a target product profile to help guide further material development to out-compete existing materials on the market. In addition a proof of concept testing plan, intellectual property strategy and regulatory analysis has been conducted. This thesis is based on the author’s experience working within NacreTech while applying current knowledge and thinking surrounding protecting intellectual property for biotechnology. In particular, the author has investigated the intellectual property aspects, such as the requirements of the complete specification, filing dates and locations, and existing strategy models, required for commercialisation of the NacreTech biomaterial and examines the factors which influenced the development of the intellectual strategy.</p>

Comparative study on Mamdani-Type Fuzzy Inference Systems and Regression model for end milling process using AA 6082T6

The goal of this observes is to take a look at the effect of machining parameters on surface roughness in end milling. An incipient technique in modelling surface roughness that makes use of synthetic perspicacity implements is defined in this paper. This paper fixates on growing empirical models utilizing fuzzy logic and regression analysis. The values of surface roughness presaged with the aid of using those fashions are then in comparison. The effects confirmed that the proposed gadget can considerably boom the precision of the product profile whilst in comparison to the traditional approaches, like regression analysis. The effects designate that the regression modelling method may be effectively applied for the presage of surface roughness in dry machining.

Strand-Morphology-Based Process Optimization for Extrusion-Based Silicone Additive Manufacturing

In the silicone material extrusion (MEX) process, product profile error and performance defects are common problems due to changes in strand shape. A process optimization method considering strand morphology, denoted as SMO, which allows adjustment of the strand shape by adjusting process parameters during the printing process is presented. The relation between process parameters (extrusion speed, moving speed, nozzle height, and nozzle radius) and the geometric parameters (strand width and strand height) of the cross-section, as well as the relationship between strand spacing, layer height, and process parameters in no void constraint is discussed and verified. SMO was utilized to produce specimens with tunable strand width and strand height. Tensile tests and profile scans were performed to compare SMO with other methods to verify its feasibility. Specimens fabricated using the SMO method have up to a 7% increase in tensile strength, up to a 10% reduction in processing time, and about a 60% reduction in strand height error over unused ones. The results show that the SMO method with adjustable strand width can effectively balance efficiency and mechanical properties compared to uniform infill, and the SMO method with adjustable strand height can provide higher accuracy compared to uniform strand height. The proposed method is validated and improves the efficiency and accuracy of silicone MEX.

Development of a target product profile for a point-of-care cardiometabolic device

Introduction Multi-parameter diagnostic devices can simplify cardiometabolic disease diagnosis. However, existing devices may not be suitable for use in low-resource settings, where the burden of non-communicable diseases is high. Here we describe the development of a target product profile (TPP) for a point-of-care multi-parameter device for detection of biomarkers for cardiovascular disease and metabolic disorders, including diabetes, in primary care settings in low- and middle-income countries (LMICs). Methods A draft TPP developed by an expert group was reviewed through an online survey and semi-structured expert interviews to identify device characteristics requiring refinement. The draft TPP included 41 characteristics with minimal and optimal requirements; characteristics with an agreement level for either requirement of ≤ 85% in either the survey or among interviewees were further discussed by the expert group and amended as appropriate. Results Twenty people responded to the online survey and 18 experts participated in the interviews. Twenty-two characteristics had an agreement level of ≤ 85% in either the online survey or interviews. The final TPP defines the device as intended to be used for basic diagnosis and management of cardiometabolic disorders (lipids, glucose, HbA1c, and creatinine) as minimal requirement, and offering an expanded test menu for wider cardiometabolic disease management as optimal requirement. To be suitable, the device should be intended for level 1 healthcare settings or lower, used by minimally trained healthcare workers and allow testing using self-contained cartridges or strips without the need for additional reagents. Throughput should be one sample at a time in a single or multi-analyte cartridge, or optimally enable testing of several samples and analytes in parallel with random access. Conclusion This TPP will inform developers of cardiometabolic multi-parameter devices for LMIC settings, and will support decision makers in the evaluation of existing and future devices.