High precision microfluidic microencapsulation of bacteriophages for enteric delivery

A Salmonella specific bacteriophage Felix O1 (Myoviridae) was microencapsulated in a pH responsive polymer formulation. The formulation incorporated a pH responsive methacrylic acid copolymer Eudragit® S100 (10% (w/v)) with the addition of the biopolymer sodium alginate, the composition of which was varied in the range (0.5% (w/v)e2% (w/v)). The microencapsulation process employed commercially available microfluidic droplet generation devices. We have used readily available low cost microfluidic chips instead of bespoke in-house fabricated glass capillary devices which are accessible only in specialist research facilities. We show that these co-flow microfluidic devices can easily be used to prepare phage encapsulated microparticles making them suitable for use by both the phage research community and industry in order to evaluate and optimise phage compatible formulations for microencapsulation. A novelty of the work reported here is that the size of the generated monodispersed droplets could be precisely controlled in the range 50 mme200 mm by varying the flow rates of the dispersed and continuous phases. Consequently, alginate concentration and microparticle size were shown to influence the phage release profile and the degree of acid protection afforded to phages upon exposure to simulated gastric fluid (SGF). Bigger microparticles (~100 mm) showed better acid protection compared with smaller beads (~50 mm) made from the same formulation. Increasing the alginate composition resulted in improved acid protection of phages for similar particle sizes. The high viscosity formulations containing higher amounts of alginate (e.g. 2% (w/v)) negatively affected ease of droplet generation in the microfluidic device thereby posing a limitation in terms of process scale-up. Felix O1 encapsulated in the formulation containing 10% (w/v) ES100 and 1% (w/v) alginate showed excellent protection upon exposure of the gelled microparticles to SGF (pH 1 for 2 h) without the use of any antacids in the encapsulation matrix. Encapsulated phages previously exposed to SGF (pH 1 for 2 h) were released at elevated pH in simulated intestinal fluid (SIF) and were shown to arrest bacterial growth in the log growth phase. We have therefore demonstrated the microencapsulation of phages using readily available microfluidic chips to produce solid dosage microcapsule forms with a rapid pH triggered release profile suitable for targeted delivery and controlled release in the gastrointestinal tract

CO2 emission based GDP prediction using intuitionistic fuzzy transfer learning

The industrialization has been the primary cause of the economic boom in almost all countries. However, this happened at the cost of the environment, as industrialization also caused carbon emissions to increase exponentially. According to the established literature, Gross Domestic Product (GDP) is related to carbon emissions (CO2) which could be optimally employed to precisely estimate a country's GDP. However, the scarcity of data is a significant bottleneck that could be handled using transfer learning (TL) which uses previously learned information to resolve new tasks, more specifically, related tasks. Notably, TL is highly vulnerable to performance degradation due to the deficiency of suitable information and hesitancy in decision-making. Therefore, this paper proposes ‘Intuitionistic Fuzzy Transfer Learning (IFTL)’, which is trained to use CO2 emission data of developed nations and is tested for its prediction of GDP in a developing nation. IFTL exploits the concepts of intuitionistic fuzzy sets (IFSs) and a newly introduced function called the modified Hausdorff distance function. The proposed IFTL is investigated to demonstrate its actual capabilities for TL in modeling hesitancy. To further emphasize the role of hesitancy modelled with IFSs, we propose an ordinary fuzzy set (FS) based transfer learning. The prediction accuracy of the IFTL is further compared with widely used machine learning approaches, extreme learning machines, support vector regression, and generalized regression neural networks. It is observed that IFTL capably ensured significant improvements in the prediction accuracy over other existing approaches whenever training and testing data have huge data distribution differences. Moreover, the proposed IFTL is deterministic in nature and presents a novel way for mathematically computing the intuitionistic hesitation degree.© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

(E)-6-Chloro-2-(furan-2-yl­methyl­idene)-2,3,4,9-tetra­hydro-1H-carbazol-1-one

In the title compound, C17H12ClNO2, the carbazole unit is nearly planar [maximum deviation = 0.052 (1) Å]. The pyrrole ring makes dihedral angles of 1.92 (8) and 4.71 (11)° with the benzene and furan rings, respectively. Inter­molecular N—H⋯O hydrogen bonds form R 2 2(10) rings in the crystal structure

How do general practitioners experience providing care to refugees with mental health problems? A qualitative study from Denmark

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

(E)-2-(Furan-2-yl­methyl­idene)-8-methyl-2,3,4,9-tetra­hydro-1H-carbazol-1-one

In the title mol­ecule, C18H15NO2, the carbazole unit is not planar [maximum deviation from mean plane = 0.236 (2) Å]. The pyrrole ring makes dihedral angles of 1.21 (10) and 16.74 (12)° with the benzene and the furan rings, respectively. The cyclo­hexene ring adopts a half-chair conformation. In the crystal, inversion dimers linked by pairs of N—H⋯O hydrogen bonds generate R 2 2(10) loops