Perspectives of future lung toxicology studies using human pluripotent stem cells

The absence of in vitro platforms for human pulmonary toxicology studies is becoming an increasingly serious concern. The respiratory system has a dynamic mechanical structure that extends from the airways to the alveolar region. In addition, the epithelial, endothelial, stromal, and immune cells are highly organized in each region and interact with each other to function synergistically. These cells of varied lineage, particularly epithelial cells, have been difficult to use for long-term culture in vitro, thus limiting the development of useful experimental tools. This limitation has set a large distance between the bench and the bedside for analyzing the pathogenic mechanisms, the efficacy of candidate therapeutic agents, and the toxicity of compounds. Several researchers have proposed solutions to these problems by reporting on methods for generating human lung epithelial cells derived from pluripotent stem cells (PSCs). Moreover, the use of organoid culture, organ-on-a-chip, and material-based techniques have enabled the maintenance of functional PSC-derived lung epithelial cells as well as primary cells. The aforementioned technological advances have facilitated the in vitro recapitulation of genetic lung diseases and the detection of ameliorating or worsening effects of genetic and chemical interventions, thus indicating the future possibility of more sophisticated preclinical compound assessments in vitro. In this review, we will update the recent advances in lung cell culture methods, principally focusing on human PSC-derived lung epithelial organoid culture systems with the hope of their future application in toxicology studies.

Culture of spermatogonial stem cells and use of surrogate sires as a breeding technology to propagate superior genetics in livestock production: A systematic review

Background and Aim: Spermatogonial stem cells (SSCs) have previously been isolated from animals' testes, cultured in vitro, and successfully transplanted into compatible recipients. The SSC unique characteristic has potential for exploitation as a reproductive tool and this can be achieved through SSC intratesticular transplantation to surrogate sires. Here, we aimed at comprehensively analyzing published data on in vitro maintenance of SSC isolated from the testes of livestock animals and their applications. Materials and Methods: The literature search was performed in PubMed, Science Direct, and Google Scholar electronic databases. Data screening was conducted using Rayyan Intelligent Systematic Review software (https://www.rayyan.ai/). Duplicate papers were excluded from the study. Abstracts were read and relevant full papers were reviewed for data extraction. Results: From a total of 4786 full papers screened, data were extracted from 93 relevant papers. Of these, eight papers reported on long-term culture conditions (>1 month) for SSC in different livestock species, 22 papers on short-term cultures (5-15 days), 10 papers on transfection protocols, 18 papers on transplantation using different methods of preparation of livestock recipients, and five papers on donor-derived spermatogenesis. Conclusion: Optimization of SSC long-term culture systems has renewed the possibilities of utilization of these cells in gene-editing technologies to develop transgenic animals. Further, the development of genetically deficient recipients in the endogenous germline layer lends to a future possibility for the utilization of germ cell transplantation in livestock systems.

Smart Vaccine Manufacturing using Novel Biotechnology Platforms: A Study during COVID-19

Healthcare experts have come to a consensus that effective and safe vaccines are necessary to control the rapid spread of the ongoing COVID-19 pandemic across the globe. Since the traditional vaccine development and manufacturing approaches were unable to meet the rapidly growing COVID-19 vaccine demand, biopharmaceutical firms had to devise novel and smart techniques to boost the development, production, and distribution of COVID-19 vaccines in large-scale with lightning speed. This triggered their transition to smart vaccine manufacturing approaches using novel viral vector and nucleic acid biotechnology platforms. This paper tries to explore this rationality of the biopharmaceutical industry by comparing the traditional and the novel biotechnology platform-based vaccine manufacturing techniques and reviewing the COVID-19 vaccine manufacturing scenarios. To highlight the “smart” characteristics of the novel platform-based COVID-19 vaccine products and to make effective comparison with the traditional products, a well-established product classification framework is used as a reference. Finally, the study concludes by presenting the future possibility of incorporating smart manufacturing paradigms with the novel platform-based manufacturing process. It is hoped that this study would serve as an asset for the biopharmaceutical firms to appropriately streamline their strategies, resources, and goals to meet the global vaccine requirements.

Deteção de linguagem tendenciosa em decisões judiciais

The linguistic expression of subjectivity is a complex phenomenon that has been the object of reflection by several sub-areas of Linguistics and, more recently, of Computational Linguistics. Linguistic subjectivity, in terms of the linguistic expression of the speaker's opinions and attitudes, affects all levels of discourse organization and is present, to different degrees, in diverse textual genres. Subjectivity and bias are connected, in the sense that the presence of bias in discourse has been related, both in Linguistics and Computational Linguistics, to the occurrence of signs of subjectivity. Court decisions are an argumentative text genre that may convey traces of subjectivity but should not be biased. As a discourse that represents the State’s position on social matters, it should reflect the principle of Equality. Nonetheless, a preliminary analysis of cases of gender violence reveals that this is not always the case. The research proposed in this paper aims to study the linguistic formulations that convey subjectivity and bias in court decisions on gender violence against women. The goal is to develop a linguistic model to detect these instances of bias, with a future possibility of application in a tool for automatic detection of gender bias in discourse, fueled by Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques. A corpus of court decisions on gender violence has been extracted from the public access database of Instituto de Gestão Financeira e Equipamentos da Justiça (IGFEJ), and has been subject to analysis. A set of examples has been compiled in the analytical section of this study, demonstrating the possibility of connecting certain linguistic features, such as mitigation and intensification mechanisms, evidential expressions and counter-argumentative movements, to the presence of subjectivity and bias in discourse.

The Soundscapes of Our Elsewheres

In this article, ethnomusicologist Sylvia Angelique Alajaji interviews electronic music composer, filmmaker, sound artist, and producer Lara Sarkissian on her career, artistic process, making music as an Armenian in diaspora, and the ways she uses music to bring into conversation the various (often quieted) presents of the diaspora with its many (often quieted) pasts, thus creating soundscapes of future possibility.

Capability of Indonesian Hot cell Towards Pebble Bed Post Irradiation Examination

Post irradiation examination is one of the requirements to obtain licensing of nuclear fuel, and the purpose of this activity is to represent the performance of nuclear fuel itself. Currently, Indonesia is developing the 10 MWth high-temperature reactor type with its fuel in the form of pebble bed. Indonesia has a hot cell installation that has a function to do post-irradiated examinations. This hot cell mainly used for plate and rod type fuel. This paper wants to show this installation capability to perform the post-irradiation examinations based on its documents and current status. We also show the future possibility of performing pebble bed post-irradiation examinations. The hot cell installation in Indonesia, mainly divided into two areas. First areas are to perform the examinations in the intact form of fuel and second areas are to perform in the small specimen of fuel. For the future pebble bed examinations, Indonesian hot cell structure is possible to perform these examinations. These examinations are possible with limiting amount and stay time of fuel inside the hot cell. The current status gap with requirements for pebble bed tests such as handling tool, deconsolidation apparatus, simulation accident test apparatus also is described.

Use of Molecular Genetic Analyses in Danish Routine Newborn Screening

Historically, the analyses used for newborn screening (NBS) were biochemical, but increasingly, molecular genetic analyses are being introduced in the workflow. We describe the application of molecular genetic analyses in the Danish NBS programme and show that second-tier molecular genetic testing is useful to reduce the false positive rate while simultaneously providing information about the precise molecular genetic variant and thus informing therapeutic strategy and easing providing information to parents. When molecular genetic analyses are applied as second-tier testing, valuable functional data from biochemical methods are available and in our view, such targeted NGS technology should be implemented when possible in the NBS workflow. First-tier NGS technology may be a promising future possibility for disorders without a reliable biomarker and as a general approach to increase the adaptability of NBS for a broader range of genetic diseases, which is important in the current landscape of quickly evolving new therapeutic possibilities. However, studies on feasibility, sensitivity, and specificity are needed as well as more insight into what views the general population has towards using genetic analyses in NBS. This may be sensitive to some and could have potentially negative consequences for the NBS programme.

The Whole-Genome Sequence of the Novel Yeast Species Metschnikowia persimmonesis Isolated from Medicinal Plant Diospyros kaki Thunb

The new yeast Metschnikowia persimmonesis KCTC 12991BP (KIOM G15050 strain) exhibits strong antimicrobial activity against some pathogens. This activity may be related to the medicinal profile of secondary metabolites that could be found in the genome of this species. Therefore, to explore its future possibility of producing some beneficial activities, including medicinal ability, we report high quality whole-genome assembly of M. persimmonesis produced by PacBio RSII sequencer. The final draft assembly consisted of 16 scaffolds with GC content of 45.90% and comprised a fairly complete set (82.8%) of BUSCO result using Saccharomycetales lineage data set. The total length of the genome was 16.473 Mb, with a scaffold N50 of 1.982 Mb. Annotation of the M. persimmonesis genome revealed presence of 7,029 genes and 6,939 functionally annotated proteins. Based on the analysis of phylogenetic relationship and the average nucleotide identities (ANI), M. persimmonesis was proved to a novel species within the Metschnikowia genus. This finding is expected to significantly contribute to the discovery of high-value natural products from M. persimmonesis as well as for genome biology and evolution comparative analysis within Metschnikowia species.

Application of Artificial Neural Network to Predict TDS Concentrations of the River Thamirabarani, India

River water quality modeling is of prime importance in predicting the health of the rivers and in turn warns the human society about the future possibility of water problem in that area. Total dissolved solids is a prominent parameter used to access the quality of the river water. In our current study, artificial neural networking models have been developed to predict the concentrations of total dissolved solids of the river Thamirabarani in India. Neural Network toolbox of the MATLAB 2017 application was used to create and train the models. Monthly data from year 2016 to 2019 at four different sites near Thamirabarani river were procured from Tamilnadu pollution control board. Many artificial neural network architectures were built and the best performing architecture was selected for this study. With several parameters such as pH, chloride, turbidity, hardness, dissolved oxygen as input and the total dissolved solids as output parameter, the model was trained for many iterations and a final architecture was arrived which predicts the futuristic TDS concentrations of Thamirabarani in a more accurate manner. The predicted and the expected values were very close to each other. The root mean square error (RMSE) values for the selected stations such as Papanasam, Cheranmahadevi, Tirunelveli and Punnaikayal were 0.565, 0.591, 0.648 and 0.67 respectively.