Search results for: bottleneck

Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 32

Authors: Rouzbeh Jafari, Joe Nava

Abstract:

This study includes learnings from an engineering practice normally performed on large scale biohydrogen processes. If properly scale-up is done, biohydrogen can be a reliable pathway for biowaste valorization. Most of the studies on biohydrogen process development have used model feedstock to investigate process key performance indicators (KPIs). This study does not intend to compare different technologies with model feedstock. However, it reports economic drivers and technical challenges which help in developing a road map for expanding biohydrogen economy deployment in Canada. BBA is a consulting firm responsible for the design of hydrogen production projects. Through executing these projects, activity has been performed to identify, register and mitigate technical drawbacks of large-scale hydrogen production. Those learnings, in this study, have been applied to the biohydrogen process. Through data collected by a comprehensive literature review, a base case has been considered as a reference, and several case studies have been performed. Critical parameters of the process were identified and through common engineering practice (process design, simulation, cost estimate, and life cycle assessment) impact of these parameters on the commercialization risk matrix and class 5 cost estimations were reported. The process considered in this study is food waste and woody biomass dark fermentation. To propose a reliable road map to develop a sustainable biohydrogen production process impact of critical parameters was studied on the end-to-end process. These parameters were 1) feedstock composition, 2) feedstock pre-treatment, 3) unit operation selection, and 4) multi-product concept. A couple of emerging technologies also were assessed such as photo-fermentation, integrated dark fermentation, and using ultrasound and microwave to break-down feedstock`s complex matrix and increase overall hydrogen yield. To properly report the impact of each parameter KPIs were identified as 1) Hydrogen yield, 2) energy consumption, 3) secondary waste generated, 4) CO2 footprint, 5) Product profile, 6) $/kg-H2 and 5) environmental impact. The feedstock is the main parameter defining the economic viability of biohydrogen production. Through parametric studies, it was found that biohydrogen production favors feedstock with higher carbohydrates. The feedstock composition was varied, by increasing one critical element (such as carbohydrate) and monitoring KPIs evolution. Different cases were studied with diverse feedstock, such as energy crops, wastewater slug, and lignocellulosic waste. The base case process was applied to have reference KPIs values and modifications such as pretreatment and feedstock mix-and-match were implemented to investigate KPIs changes. The complexity of the feedstock is the main bottleneck in the successful commercial deployment of the biohydrogen process as a reliable pathway for waste valorization. Hydrogen yield, reaction kinetics, and performance of key unit operations highly impacted as feedstock composition fluctuates during the lifetime of the process or from one case to another. In this case, concept of multi-product becomes more reliable. In this concept, the process is not designed to produce only one target product such as biohydrogen but will have two or multiple products (biohydrogen and biomethane or biochemicals). This new approach is being investigated by the BBA team and the results will be shared in another scientific contribution.

Keywords: biohydrogen, process scale-up, economic evaluation, commercialization uncertainties, hydrogen economy

Procedia PDF Downloads 70

Authors: Pedro M. Rodrigues, Claudia Raposo, Denise Schrama, Marco Cerqueira

Abstract:

Farmed fish welfare is a very recent concept, widely discussed among the scientific community. Consumers’ interest regarding farmed animal welfare standards has significantly increased in the last years posing a huge challenge to producers in order to maintain an equilibrium between good welfare principles and productivity, while simultaneously achieve public acceptance. The major bottleneck of standard aquaculture is to impair considerably fish welfare throughout the production cycle and with this, the quality of fish protein. Welfare assessment in farmed fish is undertaken through the evaluation of fish stress responses. Primary and secondary stress responses include release of cortisol and glucose and lactate to the blood stream, respectively, which are currently the most commonly used indicators of stress exposure. However, the reliability of these indicators is highly dubious, due to a high variability of fish responses to an acute stress and the adaptation of the animal to a repetitive chronic stress. Our objective is to use comparative proteomics to identify and validate a fingerprint of proteins that can present an more reliable alternative to the already established welfare indicators. In this way, the culture conditions will improve and there will be a higher perception of mechanisms and metabolic pathway involved in the produced organism’s welfare. Due to its high economical importance in Portuguese aquaculture Gilthead seabream will be the elected species for this study. Protein extracts from Gilthead Seabream fish muscle, liver and plasma, reared for a 3 month period under optimized culture conditions (control) and induced stress conditions (Handling, high densities, and Hipoxia) are collected and used to identify a putative fish welfare protein markers fingerprint using a proteomics approach. Three tanks per condition and 3 biological replicates per tank are used for each analisys. Briefly, proteins from target tissue/fluid are extracted using standard established protocols. Protein extracts are then separated using 2D-DIGE (Difference gel electrophoresis). Proteins differentially expressed between control and induced stress conditions will be identified by mass spectrometry (LC-Ms/Ms) using NCBInr (taxonomic level - Actinopterygii) databank and Mascot search engine. The statistical analysis is performed using the R software environment, having used a one-tailed Mann-Whitney U-test (p < 0.05) to assess which proteins were differentially expressed in a statistically significant way. Validation of these proteins will be done by comparison of the RT-qPCR (Quantitative reverse transcription polymerase chain reaction) expressed genes pattern with the proteomic profile. Cortisol, glucose, and lactate are also measured in order to confirm or refute the reliability of these indicators. The identified liver proteins under handling and high densities induced stress conditions are responsible and involved in several metabolic pathways like primary metabolism (i.e. glycolysis, gluconeogenesis), ammonia metabolism, cytoskeleton proteins, signalizing proteins, lipid transport. Validition of these proteins as well as identical analysis in muscle and plasma are underway. Proteomics is a promising high-throughput technique that can be successfully applied to identify putative welfare protein biomarkers in farmed fish.

Keywords: aquaculture, fish welfare, proteomics, welfare biomarkers

Procedia PDF Downloads 107

Authors: Mohiuddin Ahsanul Kabir Chowdhury, Nafisa Lira Huq, Afroza Khanom, Rafiqul Islam, Abdullah Nurus Salam Khan, Farhana Karim, Nabila Zaka, Shams El Arifeen, Sk. Masum Billah

Abstract:

After having astounding achievements in reducing maternal mortality and achieving the target for Millennium Development Goal (MDG) 5, the Government of Bangladesh has set new target to reduce Maternal Mortality Ratio (MMR) to 70 per 100,000 live births aligning with targets of Sustainable Development Goals (SDGs). Aversion of deaths from maternal complication by ensuring quality health care could be an important path to accelerate the rate of reduction of MMR. This formative research was aimed at exploring the provision of quality maternal health services at different level of health facilities. The study was conducted in 1 district hospital (DH) and 4 Upazila health complexes (UHC) of Kurigram district of Bangladesh, utilizing both quantitative and qualitative research methods. We conducted 14 key informant interviews with facility managers and 20 in-depth interviews with health care providers and support staff. Besides, we observed 387 normal deliveries from which we found 17 cases of post partum haemorrhage (PPH) and 2 cases of eclampsia during the data collection period extended from July-September 2016. The quantitative data were analyzed by using descriptive statistics, and the qualitative component underwent thematic analysis with the broad themes of facility readiness for maternal complication management, and management of complications. Inadequacy in human resources has been identified as the most important bottleneck to provide quality care to manage maternal complications. The DH had a particular paucity of human resources in medical officer cadre where about 61% posts were unfilled. On the other hand, in the UHCs the positions mostly empty were obstetricians (75%, paediatricians (75%), staff nurses (65%), and anaesthetists (100%). The workload on the existing staff is increased because of the persistence of vacant posts. Unavailability of anesthetists and consultants does not permit the health care providers (HCP) of lower cadres to perform emergency operative procedures and forces them to refer the patients although referral system is not well organized in rural Bangladesh. Insufficient bed capacity, inadequate training, shortage of emergency medicines etc. are other hindrance factors for facility readiness. Among the 387 observed delivery case, 17 (4.4%) were identified as PPH cases, and only 2 cases were found as eclampsia/pre-eclampsia. The majority of the patients were treated with uterine message (16 out of 17, 94.1%) and injectable Oxytocin (14 out of 17, 82.4%). The providers of DH mentioned that they can manage the PPH because of having provision for diagnostic and blood transfusion services, although not as 24/7 services. Regarding management of eclampsia/pre-eclampsia, HCPs provided Diazepam, MgSO4, and other anti-hypertensives. The UHCs did not have MgSO4 at stock even, and one facility manager admitted that they treat eclampsia with Diazepam only. The nurses of the UHCs were found to be afraid to handle eclampsia cases. The upcoming interventions must ensure refresher training of service providers, continuous availability of essential medicine and equipment needed for complication management, availability of skilled health workforce, availability of functioning blood transfusion unit and pairing of consultants and anaesthetists to reach the newly set targets altogether.

Keywords: Bangladesh, health facilities, maternal complications, quality of care

Procedia PDF Downloads 197