A fed-batch fermentation process for poly (3-hydroxybutyrate-co-3-hydroxyvalerate) production by Yangia sp. ND199 using molasses as substrate

A locally isolated halophilic bacterium, Yangia sp. ND199 was able to use molasses as substrate for copolymers poly(3-hydroxybutyrate-co-3-hydroxyvalerate) [P(3HB-co-3HV)] production. Cell dry weight (CDW) of 6.37 g/l, P(3HB-co-3HV) content of 43.1 wt% and P(3HB-co-3HV) concentration of 2.75 g/l were obtained by Yangia sp. after 60 h of cultivation in flask. In a batch cultivation mode in a fermentor, the CDW was increased to 9.1 g/l but P(3HB-co-3HV) content was decreased to 37 wt%. Fed-batch fermentation with two different nutrient feeding strategies was used. High CDW of 54.8 g/l was obtained after 54 h of cultivation but P(3HB-co-3HV) content was still low (39.8 wt%). Two-step fed-batch fermentation with two different nutrient feeding strategies was then designed. High CDW of 50 g/l and P(3HB-co-3HV) content of 52.9 wt% were obtained after 54 h of cultivation. The two-step fed-batch process designed here for the production of P(3HB-co-3HV) by Yangia sp. ND199 can be developed and used for further studies

Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media

Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels. This kind of data makes the existing works suffer from many difficulties to handle, especially ones using deep learning approaches. In this paper, we propose an approach to handle this problem. This work is extended from our previous work, in which we proposed to combine the typical deep learning technique of Convolutional Neural Networks with domain knowledge. The combination is used for acquiring additional training data augmentation and a more reasonable loss function. In this work, we further improve our architecture by various substantial enhancements, including negation-based data augmentation, transfer learning for word embeddings, the combination of word-level embeddings and character-level embeddings, and using multitask learning technique for attaching domain knowledge rules in the learning process. Those enhancements, specifically aiming to handle short and informal messages, help us to enjoy significant improvement in performance once experimenting on real datasets.Comment: A Preprint of an article accepted for publication by Inderscience in IJCVR on September 201

DIFFERENT FRUCTOSE FEEDING STRATEGIES FOR POLY(3-HYDROXYBUTYRATE) PRODUCTION BY Yangia sp. ND199

Yangia sp. ND199 is a halophilic bacterium isolated from mangrove soil sample. This strain was able to produce polyhydroxyalkanoate (PHA) from different carbon sources. Only homopolymer poly(3-hydroxybutyrate) (PHB) was synthesized when fructose was used as carbon source. The bacterium can accumulate high PHB content during exponential phase. Maximum cell dry weight (CDW) of 7.8 g/l and PHB content of 49 wt% were obtained after 27 h of cultivation in batch fermentation. High CDW and PHB content were achieved by using fed-batch fermentation with different fructose feeding strategies. The highest CDW of 78.5 g/l, PHB content of 67.5 wt%, and PHB productivity of 1 g/l/h were obtained by using two-stage fed-batch fermentation, is among the highest reported so far for PHB production by halophilic bacteria.       

Antibiotic use and prescription and its effects on Enterobacteriaceae in the gut in children with mild respiratory infections in Ho Chi Minh City, Vietnam. A prospective observational outpatient study.

BACKGROUND AND OBJECTIVES: Treatment guidelines do not recommend antibiotic use for acute respiratory infections (ARI), except for streptococcal pharyngitis/tonsillitis and pneumonia. However, antibiotics are prescribed frequently for children with ARI, often in absence of evidence for bacterial infection. The objectives of this study were 1) to assess the appropriateness of antibiotic prescriptions for mild ARI in paediatric outpatients in relation to available guidelines and detected pathogens, 2) to assess antibiotic use on presentation using questionnaires and detection in urine 3) to assess the carriage rates and proportions of resistant intestinal Enterobacteriaceae before, during and after consultation. MATERIALS AND METHODS: Patients were prospectively enrolled in Children's Hospital 1, Ho Chi Minh City, Vietnam and diagnoses, prescribed therapy and outcome were recorded on first visit and on follow-up after 7 days. Respiratory bacterial and viral pathogens were detected using molecular assays. Antibiotic use before presentation was assessed using questionnaires and urine HPLC. The impact of antibiotic usage on intestinal Enterobacteriaceae was assessed with semi-quantitative culture on agar with and without antibiotics on presentation and after 7 and 28 days. RESULTS: A total of 563 patients were enrolled between February 2009 and February 2010. Antibiotics were prescribed for all except 2 of 563 patients. The majority were 2nd and 3rd generation oral cephalosporins and amoxicillin with or without clavulanic acid. Respiratory viruses were detected in respiratory specimens of 72.5% of patients. Antibiotic use was considered inappropriate in 90.1% and 67.5%, based on guidelines and detected pathogens, respectively. On presentation parents reported antibiotic use for 22% of patients, 41% of parents did not know and 37% denied antibiotic use. Among these three groups, six commonly used antibiotics were detected with HPLC in patients' urine in 49%, 40% and 14%, respectively. Temporary selection of 3rd generation cephalosporin resistant intestinal Enterobacteriaceae during antibiotic use was observed, with co-selection of resistance to aminoglycosides and fluoroquinolones. CONCLUSIONS: We report overuse and overprescription of antibiotics for uncomplicated ARI with selection of resistant intestinal Enterobacteriaceae, posing a risk for community transmission and persistence in a setting of a highly granular healthcare system and unrestricted access to antibiotics through private pharmacies. REGISTRATION: This study was registered at the International Standard Randomised Controlled Trials Number registry under number ISRCTN32862422: http://www.isrctn.com/ISRCTN32862422

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Research identify the group for lead – zinc ore type to prepare exploration in Ban Lim area, Caobang province, Vietnam

Ban Lim area, Caobang province has proposed high potential of lead-zinc resources, which have occurred in different geological formations. In this paper, based on the collecting, synthetics and processing geological data, especially applied mathematical methods to recognize studied objects of exploration process and quantitative description. The results show that the lead-zinc orebodies in Ban Lim area are mainly occurred in lens-shaped and distributed in layered surfaces of dolomitized limestone of Coc Xo formation. The average lead-zinc content of the orebodies is in a range from 3.27% to 8.33%, its coefficient of variation (Vc) is in a range from 13.71% (evenly) to 137.92% (very unevenly). On the whole, the lead-zinc contents of the orebodies in Ban Lim area mainly comply with the standard normal distribution. The average thicknesses of the orebodies are in a range from 0.92 m to 6.48 m, its coefficient of variation (Vm) is in the range from 8.7% (stable) to 132.95% (very unstable). Quantitative calculation results have shown that Ban Lim lead-zinc deposit belongs to group III of deposits. For the exploration of this type of minerals, it is recommended to use linear grid pattern. Appropriate exploration grid pattern for category 122 reserve is (60-80)×(30-40) m

Poly(3-Hydroxybutyrate-co-3-Hydroxyvalerate) Production by a Moderate Halophile Yangia sp ND199 Using Glycerol as a Carbon Source

Yangia sp. ND199, a moderate halophile isolated from mangrove soil sample in Vietnam, was found to accumulate poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) from unrelated carbon sources in a medium with 4.5 % (w/v) NaCl. Cultivation with glycerol as carbon source and yeast extract as nitrogen source resulted in maximum cell dry weight of 5.7 g/l and PHBV content of 52.8 wt% (containing 2.9 mol% of 3HV) after 40 h. The 3HV content of the PHBV was the highest during initial stages of copolymer production and decreased with increase in the copolymer amount with time, but was not affected by changing the pH of the culture medium. Only homopolymer poly(3-hydroxybutyrate) was synthesized when monosodium glutamate was used as the nitrogen source. Fed-batch cultivation of Yangia sp. ND199 with glycerol and yeast extract gave PHBV content and productivity of 53.2 wt% and 0.44 g/l/h, respectively, which were reduced to 40.6 wt% and 0.25 g/l/h, respectively, with crude glycerol as carbon source. Both the copolymer content and productivity were improved to 56 wt% and 0.61 g/l/h, respectively, by using 1:1 mixture of crude glycerol and high fructose corn syrup. This is the first report of PHBV production by a wild-type halophilic bacterium using glycerol as carbon source

Handling negative mentions on social media channels using deep learning

Social media channels such as social networks, forum or online blogs have been emerging as major sources from which brands can gather user opinions about their products, especially the negative mentions. This kind of task, popular known as sentiment analysis, has been addressed recently by many deep learning approaches. However, negative mentions on social media have their own language characteristics which require certain adaptation and improvement from existing works for better performance. In this paper, we propose a new architecture for handling negative mentions on social media channels. As compared to the architecture published in our previous work, we expose substantial change in the combination manner of deep neural network layers for better training and classification performance on social-oriented messages. We also propose the way to re-train the pre-trained embedded words for better reflect sentiment terms, introducing the resultant sentimentally-embedded word vectors. Finally, we introduce the concept of a penalty matrix which incurs more reasonable loss function when handling negative mentions. Our experiments on real datasets demonstrated significant improvement