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Background: Speech emotion recognition can be experimentally tested in native and nonnative languages, as the mechanisms involved would differ across these languages. The recognition of speech in the native language is mediated through the language, and in nonnative languages, speech emotion recognition is facilitated through affective prosody. Linguistic prosody is anchored by the left hemisphere, whereas the right hemisphere coordinates the right hemisphere. The current study was carried out with the aim of testing speech emotion recognition in native and nonnative speakers with the motive of assessing the basic role of language in mediating prosody. Methods: The study was carried out on native and nonnative speakers of Malayalam, Assamese, and Bengali. Fifteen sentences (5 declarative, 5 interrogative, and 5 exclamatory) were recorded from native speakers of the aforementioned languages; these sentences were played to native speakers and nonnative speakers of a given language. For instance, the sentences in Malayalam were played to native speakers of Malayalam and nonnative speakers (speakers of Assamese and Bengali). The response sheet had three smileys, and the participants were asked to mark the appropriate smiley after listening to the sentences. Each correct response was given a score of 1, whereas an incorrect response was given a score of 0. Results: The native speakers of Malayalam, Assamese, and Bengali secured scores of 13.14 and 15 in their native languages, respectively. In the nonnative language, the participants secured scores in the range of 2-5. The Kruskal-Wallis test showed a significant difference between the native and nonnative languages. The results depicted that the native speakers of a language were able to identify the speech emotions easily, whereas they had difficulty identifying the sentences in the other two languages. The same trend was observed for speakers of Malayalam, Assamese, and Bengali. This showed that speech emotion recognition was linguistically driven. Conclusions: The results highlight that the prosody is more linguistically driven as the performance in the native language was better than in nonnative languages. [ABSTRACT FROM AUTHOR]

Among the multiple SARS-CoV-2 variants recently reported, the Delta variant has generated the most perilous and widespread effects. Another variant, Omicron, has been identified specifically for its high transmissibility. Omicron contains numerous spike (S) protein mutations and numbers much larger than those of its predecessor variants. In this report, the author has discussed some essential structural aspects and time-based structure changes of a selected set of spike protein mutations within the Delta and Omicron variants. The expected impact of multiple point mutations within the spike protein's receptor-binding domain (RBD) and S1 of these variants are examined. Additionally, the RBDs of the more recently emerged subvariants BA.4, BA.5, and BA.2.12.1 are discussed. Within the latter group, BA.5 represents the most prevalent form of SARS-CoV-2 globally until recently. This computational work also briefly explores the temporal mutation profile for the currently circulating variants of interest (VOIs), variants under monitoring (VUMs), and variants being monitored (VBMs) including XBB.1.5, BQ.1, BA.2.75, CH.1.1, XBB, XBF, EG.5 (or Eris), and BA.2.86 (or Pirola). It is expected that these structural data can facilitate the tasks of identifying drug targets and neutralizing antibodies for the evolving variants/subvariants of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

This work presents a three-dimensional (3D) modeling exercise for undergraduate students in chemistry and health sciences disciplines, focusing on a protein-group linked to immune system regulation. Specifically, the exercise involves molecular modeling and structural analysis of tumor necrosis factor (TNF) proteins, both wild type and mutant. The structure of the tumor necrosis factor type 1 receptor (TNF-R1) is also briefly explored. TNF and TNF-R1 play major roles in maintaining human immune-system homeostasis. Upon binding with TNFR-1, the TNF can activate the nuclear factor kappa B (NF-?B), eventually resulting in apoptosis or cell death. These essential features of the clinically relevant TNF family is explored within the frame work of a readily adaptable tutorial.

Molecular modeling is pervasive in the pharmaceutical industry that employs many of our students from Biology, Chemistry and the interdisciplinary majors. To expose our students to this important aspect of their education we have incorporated a set of tutorials in our Biochemistry class. The present article describes one of our tutorials where undergraduates use modeling experiments to explore the structure of an estrogen receptor. We have employed the Molecular Operating Environment, a powerful molecular visualization software, which can be implemented on a variety of operating platforms. This tutorial reinforces the concepts of ligand binding, hydrophobicity, hydrogen bonding, and the properties of side chains and secondary structure taught in a general biochemistry class utilizing a protein that has importance in human biology.