Advanced Analytical Techniques for the Analysis of Toxic Inhaled Agent Exposure and Pharmacokinetic Investigation

Toxic inhalation agents (TIAs) (i.e., chlorine (Cl2), cyanide (HCN), etc.) are highly poisonous. However, they have a variety of industrial uses, such as health, agro-food, building, textiles, transport, leisure activities, cosmetics, etc. In addition, TIAs can be used as chemical agents in terrorist events or conventional warfare. The ability to detect TIAs in biological and environmental samples is important for preparing use, determining individual exposure, limiting hazardous exposure, etc. Therefore, developing simple and sensitive analytical methods for TIAs, TIA metabolites, and antidotes for those toxic agents is very important. The focus of this study was chlorine and cyanide. Chlorine is a poisonous and corrosive industrial chemical that causes irritation and damages the respiratory tract, eyes, and skin. Chlorine is known to form a stable adduct with tyrosine-protein adducts (e.g., 3-chlorotyrosine (Cl-Tyr) and 3,5-dichloro tyrosine (Cl2-Tyr)). These adducts are used as biomarkers to confirm chlorine exposure. However, those methods required time-consuming and tedious sample preparation. Therefore, we developed a novel base hydrolysis technique for chloro-tyrosine protein adducts to produce 2,6-dichlorophenol (2,6-DCP). The 2,6-DCP was extracted from the hydrolysate and analyzed via UHPLC-MS/MS analysis of this marker. The method produced excellent sensitivity for 2,6-DCP with the detection limit of 7.8 g/kg (corresponding to 7.2 nM in the final solution) and calibration curve linearity extending from 0.054 - 54 mg/kg (R2 0.9997 and overall %RA 94). The accuracy and precision (100 14%, and 15% relative standard deviation, respectively) of the method were good. The validated method successfully detected elevated levels of 2,6-DCP from plasma protein isolated from chlorine-exposed rats. Another method for the analysis of chlorine was developed for aqueous samples. As chlorine is a water-soluble compound, this toxic irritant gas forms hypochlorous acid and hydrochloric acid in an aqueous environment upon exposure. Here, we study hypochlorite anion (ClO-) in an aqueous solution with the fluorescent probe, as this technique has been known for its high sensitivity, better selectivity, fast response, and ease of use. In this study, we synthesized a probe called fluorescein thioacid (FSH) for rapid and sensitive ClO- detection in an aqueous solution. The probe FSH has shown the selectivity toward ClO- for the strong oxidative property, producing fluorescein. Probe FSH could detect in the range of 5-200 M with a detection limit of 1.72 M. The probe FSH is very easy to synthesize with excellent properties, including high selectivity, excellent sensitivity, good water solubility, and fast response. This probe would be beneficial to the analytical researchers for monitoring the ClO- levels in aqueous solutions. Cyanide is a TIA, as with chlorine, but inhibits mitochondrial cytochrome oxidase upon exposure by blocking electron transport and decreasing oxidative metabolism. Because each of the current antidotes, approved by the U.S. Food and Drug Administration (FDA) (i.e., hydroxocobalamin), has significant disadvantages, especially for mass casualty situations, dimethyl trisulfide (DMTS) has recently been developed as a next-generation cyanide antidote. DMTS converts cyanide to a less toxic substance called thiocyanate, which is more effective than thiosulfate and can be administered intramuscularly (IM). Hence, the pharmacokinetic behavior of intranasal (IN) and intramuscular (IM)-administration of DMTS was evaluated. A total of 47 rats and 35 swine were studied for IN and IM administration of DMTS. Generally, the PK characteristics of DMTS were well-suited for the rapid treatment of cyanide poisoning. These results should be helpful in elaborating guidelines for administering DMTS as a cyanide antidote

Economic Contribution of Tourism Industry in Bangladesh

Bangladesh is a country of natural beauty, hilly mountains, longest beach, favorable climate, seven seasons which are the key factors to develop eco-tourism, sustainable tourism and rural tourism. Bangladesh has many archeological and historical sites too. And the hospitality of people and local culture, life style is a unique selling point. Tourism is a growing industry in Bangladesh. It generated 1, 25,000 international tourists in 2014 and international tourism generated US$ 1.5 trillion in export earnings and international tourist arrivals grew by 4.3% in 2014 to 1.133 billion. According to WTTC direct employment support by travel and tourism is forecast to raise by 2.9 percent per annum to 1,785,000 jobs or 1.9 percent of total employment in 2023.In this paper, we tried to show the current scenario of tourism industry and the contribution on GDP. Keywords: Tourism, Economy, Banglades

Remittance and Dutch Disease Phenomenon: Case of Bangladesh and Pakistan

The paper has been designed to explore whether the impact of remittance on the real exchange rate causes any Dutch disease problem for Bangladesh and Pakistan. These two South Asian countries have been targeted to figure out if the outcomes are similar for the countries with almost the same economic structure. Johansen co-integration approach, Vector Error Correction Method (VECM), and Granger Causality test have been employed taking real exchange rate as regressand and remittance and other attributing variables as explanatory variables with an aim to address the study objective. The study has used data from the World Development Indicators database ranging from 1986 to 2019. The results for both countries reveal that remittance is significantly negatively related to the real exchange rate which implying the appreciation of the domestic currency. However, this appreciation causes the Dutch disease phenomenon for neither Bangladesh nor Pakistan

Development of an Atlas-Based Segmentation of Cranial Nerves Using Shape-Aware Discrete Deformable Models for Neurosurgical Planning and Simulation

Twelve pairs of cranial nerves arise from the brain or brainstem and control our sensory functions such as vision, hearing, smell and taste as well as several motor functions to the head and neck including facial expressions and eye movement. Often, these cranial nerves are difficult to detect in MRI data, and thus represent problems in neurosurgery planning and simulation, due to their thin anatomical structure, in the face of low imaging resolution as well as image artifacts. As a result, they may be at risk in neurosurgical procedures around the skull base, which might have dire consequences such as the loss of eyesight or hearing and facial paralysis. Consequently, it is of great importance to clearly delineate cranial nerves in medical images for avoidance in the planning of neurosurgical procedures and for targeting in the treatment of cranial nerve disorders. In this research, we propose to develop a digital atlas methodology that will be used to segment the cranial nerves from patient image data. The atlas will be created from high-resolution MRI data based on a discrete deformable contour model called 1-Simplex mesh. Each of the cranial nerves will be modeled using its centerline and radius information where the centerline is estimated in a semi-automatic approach by finding a shortest path between two user-defined end points. The cranial nerve atlas is then made more robust by integrating a Statistical Shape Model so that the atlas can identify and segment nerves from images characterized by artifacts or low resolution. To the best of our knowledge, no such digital atlas methodology exists for segmenting nerves cranial nerves from MRI data. Therefore, our proposed system has important benefits to the neurosurgical community

Student dropout risk detection at University of Évora

Currently, student dropout is a global problem in higher education affecting the results of education systems. In addition to providing state-of-the-art education, any institution needs to maintain its student flow rate, which means that predicting dropout is critical to measuring the success of an education system. This work focuses on identifying the risk of dropout at the University of Évora based on students’ academic performance. We propose a set of aca- demic information as predictive attributes and present machine learning models that have a precision of 96.8% and f1-measure of 94.8% as perfor- mance in identifying students at risk of dropping out. In this regard, 13 years of academic data were collected from four different academic programs (the academic years 2006/2007 to 2018/2019 and Man- agement, Biology, Informatics Engineering and Nursing programs). After collecting the students’ academic records, anonymizing the information and pre-processing the data, an engineering and attribute selection process was conducted, building the data sets. Various machine learning algorithms were applied and their performance was compared; models were built with Deci- sion Trees (DT), Naïve Bayes (NB), Support Vector Machines (SVM) and Random Forest (RF), with the latter algorithm having obtained the best performance in terms of recall; Sumário: Detecção de Risco de Abandono de Alunos na Universidade de Évora Atualmente, o abandono escolar é um problema global no ensino superior que afeta os resultados dos sistemas educativos. Além de fornecer educação de ponta, qualquer instituição precisa manter a taxa de fluxo de alunos, o que significa que a previsão do abandono escolar é essencial para medir o sucesso de um sistema de ensino. Este trabalho centra-se na identificação do risco de abandono escolar na Uni- versidade de Évora com base no desempenho escolar dos alunos. Propomos um conjunto de informação académica como atributos preditivos e apresen- tamos modelos de aprendizagem automática que apresentam uma precisão de 96.8% e f1-medir de 94.8% como desempenho na identificação de alunos em risco de desistência. Nesse sentido, foram recolhidos 13 anos de dados académicos de quatro cursos diferentes (anos letivos de 2006/2007 a 2018/2019 e cursos de Gestão, Bi- ologia, Engenharia Informática e Enfermagem). Após a recolha do percurso académico dos alunos, a anonimização da informação e o pré-processamento dos dados, foi conduzido um processo de engenharia e seleção de atributos, construindo assim os conjuntos de dados. Foram aplicados vários algoritmos de aprendizagem automática e o seu desempenho foi comparado; foram con struídos modelo com Árvores de Decisão (DT), Naïve Bayes (NB), Máquinas de Vetores de Suporte (SVM) e Random Forest (RF), tendo este último al- goritmo obtido o melhor desempenho no que respeita à cobertura

EFFECT OF FRAMEWORK AND COMPLEMENTARITY DETERMINING REGION CHARGE ON VH DOMAIN SOLUBILITY

The use of VH domains in diagnostic and therapeutic applications circumvents many of the issues associated with antibodies. Nevertheless, VH domains still have limitations such as a tendency to aggregate. They usually contain hydrophobic residues within their complementarity determining regions (CDRs) that facilitate binding to target antigens but also mediate VH domain aggregation, which is a great concern for therapeutic applications. This thesis focuses on the engineering of the VH framework and CDR1 to prevent VH aggregation. We used two strategies to increase the stability and solubility of the VH domain. First, we used a previously discovered autonomous human VH-B1a as a starting point and increased its net charge by introducing charge mutations in the framework region. We observed that our designed +VH domain showed increased thermostability, but the reversible folding ability and solubility were lower compared to near-neutrally charged VH-B1a. Second, we mutated CDR1 of VH-B1a and +VH domains by introducing a series of positively and negatively charged residues, and assessed the effect of net framework charge and CDR1 charge on improving VH domain thermostability and solubility. From the analysis of CDR1-mutated VH-B1a and +VH domains, we noticed a position specific effect of a single lysine or two lysines in CDR1. Moreover, +VH can overcome the position specific effect of single lysine mutation, and the positional effect of double lysine mutation was better tolerated in +VH domain compared to VH-B1a. Significant aggregation resistance of VH domain was noticed in the presence of three negative (DDD) or positive (KKK) charge in the CDR1 of VH-B1a and +VH, respectively. Furthermore, VH-B1a was better at tolerating negative charge in CDR1, whereas +VH was better at tolerating either positive or negative charge. Our findings demonstrate that in addition to the net framework charge and CDR1 charge, a positional effect of CDR1 mutation affects thermostability and aggregation resistance. Our results demonstrate that the +VH domain will be a good starting template for the construction of phage displayed libraries that will be enriched in highly thermostable and aggregation resistant VH variants

Extending Asphalt Pavement Life Using Thin Whitetopping

Due to budget constraints, many highway agencies are becoming interested in pavement preservation or rehabilitation rather than reconstruction to ensure pavement is in serviceable condition. Thin whitetopping (TWT) is the process of rehabilitating distressed asphalt concrete (AC) pavements by using a concrete overlay. This study was done to develop a design catalog for existing AC pavements to be overlaid with TWT. The finite element (FE) analysis was performed with SolidWorks, which is the 3-D FE software program used to develop this design catalog. The design considered different TWT thicknesses, existing AC layer thickness and modulus, the bonding condition between TWT and the existing AC layer, shoulder conditions and temperature differentials. Each model was built as a three-layer pavement system—composed of concrete (TWT), asphalt layer, and subgrade soil. The traffic load was modeled as a constant pressure with a rectangular area applied at the surface and with intensity equal to the tire inflation pressure of 100 psi. The expected lives of TWT overlays were estimated using fatigue equations developed by the Portland Cement Association (PCA). Results obtained from this study show that interface bonding condition is the most important factor affecting the behavior of TWT. With the increase of TWT thickness or existing AC thickness or AC modulus and the addition of a paved shoulder, concrete tensile stress decreases. Curling stress increases with the increase of TWT thickness and is not a function of AC properties. A design catalog was developed in terms of service life of the pavement. Unlike the unbonded TWT with an unpaved shoulder that results in catastrophic loss of rehabilitated pavement life, bonded TWT is expected to last 10 years, assumed in design. Thus, proper bonding must be ensured in order to have extended pavement life. PowerPoint presentation attached below as Related File. Link to webinar video: http://vimeo.com/3739799