Disparate Types Research Articles

7706 Racial Disparities in Thyroid-Related Procedure Reoperation Rates: Insights from NSQIP Database

Abstract Disclosure: H.A. Erol: None. A. Liu: None. K. Wardwell: None. S. Woodruff: None. Background: Racial disparities in health outcomes are well-documented, with specific conditions affecting racial groups differently. However, the influence of race on endocrine surgery outcomes remains an evolving field of study. This research seeks to evaluate the effect of race on unplanned reoperations using the National Surgical Quality Improvement Program(NSQIP)-database and to investigate additional risk factors for reoperations in this cohort. Methods: We analyzed the NSQIP-database for thyroid-related procedures from 2012-2021 using CPT codes. Patient demographics, including age, sex, height/weight, ASA classification, and comorbid conditions, were assessed for unplanned reoperations. Univariate, multivariable logistic regression, and adjusted residual analyses were conducted assessing individual variables, adjusted odds ratios(ORs), and for post-hoc analyses. Results: Over the 10-year period, 169,251 patients were identified, with an overall reoperation incidence of 1.32%. Univariate analysis revealed that race correlated with increased reoperation rates, with the highest incidence observed among American Indian/Alaska Native (2.13%) patients, followed by Native Hawaiian/Pacific Islander (1.93%), Black/African American(1.84%), White (1.22%), and Asian(1.08%) patients. In multivariate logistic regression analysis, Black/African American (OR 1.452, 95% CI 1.293-1.630, p < 0.001) and American Indian/Alaska Native (OR 1.775, 95% CI 1.039-3.031, p = 0.036) patients had a higher risk of reoperation compared to White patients. Other factors associated with increased reoperation risk included male gender, higher ASA class, smoking, partially dependent functional status, ventilator dependency, hypertension, dialysis, disseminated cancer, bleeding disorders, and systemic inflammatory response syndrome or sepsis. Most reoperations were hematoma related(63.02%), with statistical significance noted among different ethnicities and types of reoperations. White patients had lower rates of hematoma-related procedures, fewer tracheostomies, and more additional thyroid procedures. Black/African American patients had more tracheostomies and fewer lymphatic-related or additional thyroid procedures. Conclusions: Using the NSQIP-database, Black/African American and American Indian/Alaska Native patients were at a greater risk of reoperation following thyroid surgeries, even after accounting for multiple variables. Black/African American patients also had disparate types of reoperations. These findings highlight the impact of race on thyroidectomy-related outcomes. Further research is imperative to comprehensively understand the role of race in surgical outcomes and to address healthcare disparities and inequities. Presentation: 6/2/2024

Genomics 2 Proteins portal: a resource and discovery tool for linking genetic screening outputs to protein sequences and structures

Recent advances in AI-based methods have revolutionized the field of structural biology. Concomitantly, high-throughput sequencing and functional genomics have generated genetic variants at an unprecedented scale. However, efficient tools and resources are needed to link disparate data types—to ‘map’ variants onto protein structures, to better understand how the variation causes disease, and thereby design therapeutics. Here we present the Genomics 2 Proteins portal (https://g2p.broadinstitute.org/): a human proteome-wide resource that maps 20,076,998 genetic variants onto 42,413 protein sequences and 77,923 structures, with a comprehensive set of structural and functional features. Additionally, the Genomics 2 Proteins portal allows users to interactively upload protein residue-wise annotations (for example, variants and scores) as well as the protein structure beyond databases to establish the connection between genomics to proteins. The portal serves as an easy-to-use discovery tool for researchers and scientists to hypothesize the structure–function relationship between natural or synthetic variations and their molecular phenotypes.

Populist hyperpersonalization and politicization of foreign policy institutions

Abstract This article explains how right-wing populist leaders in Hungary, Poland, Russia and Turkey have transformed their states' foreign policy institutions through personalization and politicization. We examine the transformation of foreign policy institutions in the four cases and make two contributions. First, we differentiate between disparate types of personalization by proposing the term ‘hyperpersonalization’—populist leaders' reliance on security institutions in foreign policy decision-making—which distinguishes the populist transformation of foreign policy institutions in Russia and Turkey. We argue that lower levels and speed of autocratization lead to politicization combined with milder cases of personalization of the foreign policy bureaucracy, while higher levels and speed of autocratization lead to higher levels of personalization in the foreign policy institutions. Second, we lay out the steps and patterns of populist politicization and hyperpersonalization that bring ‘deinstitutionalizing restructuring’ to foreign policy institutions. As we illustrate, this deinstitutionalizing restructuring involves concurrent bureaucratic expansion and bureaucratic retrenchment. The process is accompanied by a populist narrative that this restructuring is done to realize the ‘popular will’ or to regain ‘full sovereignty’. We conclude the article with the policy implications of this populist transformation of foreign policy institutions.

Insight into the molecular basis of the soluble storage-state to fibrous-state structural transformation of spider pyriform silk

Pyriform (or piriform) silk is a fibrous spider silk used in a composite material to attach web silks to substrates and disparate silk types together. Argiope argentata pyriform silk is formed from a protein with a central repetitive region consisting of a 234-amino acid unit (the "Py unit") repeated 21 times. We have previously shown that the Py unit behaves modularly, with a structured core of 6 α-helices that retains its structuring upon truncation of N- and C-terminal intrinsically disordered segments. Here, we apply solution-state nuclear magnetic resonance (NMR) spectroscopy to investigate the structured core of the Py unit. Based on 15N spin relaxation measurements and reduced spectral density mapping at two field strengths, the α-helical core of the Py unit exhibits minimal backbone motion beyond the tumbling of the globular domain except for one interhelical linker that exhibits a notably higher degree of dynamics. Evaluation of rotational diffusion based on 15N spin relaxation and translational diffusion by pulsed field gradient diffusion NMR demonstrates that the core of the Py unit behaves as a compact structure, with hydrodynamic behaviour consistent with a well-packed protein. Pyriform silk protein undergoes a structural transformation upon conversion from the soluble-state to the fibrous-state, with a loss of αhelical content and gain of β-sheet content. The more dynamic segment we observe midway through the structured core of the Py core, especially in the context of the intrinsically disordered segments that flank the core, would provide an initiation point for decompaction, structural transformation, and/or intermolecular interactions.

Global aerosol models considering their spatial heterogeneities based on AERONET measurements

The imprecision inherent in aerosol models poses a significant challenge in satellite- and surface- based aerosol retrieval. The correct classification of global aerosol types and understanding of their spatial heterogeneity are prerequisites for accurately deriving aerosol optical and microphysical properties and assessing their impacts on climate, air quality, and human health. In this study, a deep clustering algorithm is developed and employed to classify global aerosol types by using >160,000 records of AERONET measurements at 411 sites during 2000–2020. The proposed algorithm utilizes deep learning techniques to optimize the feature space of input variables, thereby improving the distinguishability among various aerosol types. This algorithm outperforms the commonly used K-means method with 77.4% of AERONET sites experiencing increased explained variance. Based on their unique properties (e.g., single scattering albedo, complex refractive index and dust ratio, etc.) and geographic distribution, global aerosols are classified into six types: mineral dust, smoke, two urban aerosols with different particle sizes, and two mixtures with different dominant components. The spatial heterogeneity of aerosol optical/microphysical properties is distinctly presented in our clustering results. Through the subdivision of the global domain into 11 sub-regions, a comprehensive elucidation has been undertaken to delineate the variances in volume size distribution, absorption, and scattering characteristics exhibited among disparate aerosol types, as well as within a same aerosol category. These new understandings of aerosol models and their spatial heterogeneities in this study will be highly helpful to update or optimize aerosol retrieval algorithms in the future.

Land cover and space use influence coyote carnivory: evidence from stable-isotope analysis

For many species, the relationship between space use and diet composition is complex, with individuals adopting varying space use strategies such as territoriality to facilitate resource acquisition. Coyotes (Canis latrans) exhibit two disparate types of space use; defending mutually exclusive territories (residents) or moving nomadically across landscapes (transients). Resident coyotes have increased access to familiar food resources, thus improved foraging opportunities to compensate for the energetic costs of defending territories. Conversely, transients do not defend territories and are able to redirect energetic costs of territorial defense towards extensive movements in search of mates and breeding opportunities. These differences in space use attributed to different behavioral strategies likely influence foraging and ultimately diet composition, but these relationships have not been well studied. We investigated diet composition of resident and transient coyotes in the southeastern United States by pairing individual space use patterns with analysis of stable carbon (δ13C) and nitrogen (δ15N) isotope values to assess diet. During 2016–2017, we monitored 41 coyotes (26 residents, 15 transients) with GPS radio-collars along the Savannah River area in the southeastern United States. We observed a canopy effect on δ13C values and little anthropogenic food in coyote diets, suggesting 13C enrichment is likely more influenced by reduced canopy cover than consumption of human foods. We also observed other land cover effects, such as agricultural cover and road density, on δ15N values as well as reduced space used by coyotes, suggesting that cover types and localized, resident-like space use can influence the degree of carnivory in coyotes. Finally, diets and niche space did not differ between resident and transient coyotes despite differences observed in the proportional contribution of potential food sources to their diets. Although our stable isotope mixing models detected differences between the diets of resident and transient coyotes, both relied mostly on mammalian prey (52.8%, SD = 15.9 for residents, 42.0%, SD = 15.6 for transients). Resident coyotes consumed more game birds (21.3%, SD = 11.6 vs 13.7%, SD = 8.8) and less fruit (10.5%, SD = 6.9 vs 21.3%, SD = 10.7) and insects (7.2%, SD = 4.7 vs 14.3%, SD = 8.5) than did transients. Our findings indicate that coyote populations fall on a feeding continuum of omnivory to carnivory in which variability in feeding strategies is influenced by land cover characteristics and space use behaviors.

Abstract 7428: S2Map: An online interactive analytical platform for quantitative signal measurement of cell Secretion Signal Map

Abstract Cell communication is predominantly governed by secreted proteins, whose diverse secretion patterns often signify underlying physiological irregularities. Unraveling the intricacies of these secreted signals at the single-cell level is crucial for a comprehensive understanding of regulatory mechanisms involving various molecular agents. To elucidate the array of cell secretion signals, encompassing both anisotropic and isotropic biomolecular cues from individual immune cells or disparate cell types, we introduce the Secretion Signal Map (S2Map). S2Map is an innovative online interactive analytical platform that incorporates qualitative metrics, the signal inequality index (SII) and the signal coverage index (SCI), which are exquisitely sensitive in facilitating the measurement of dissymmetry and diffusion of cumulative signals and signal dynamics in temporal analysis. S2Map's innovation lies in its depiction of signals through real-time secretion hotspots, and cumulative secretion contour lines, complemented by the visualization of potential cell secretion signal velocities via stream plots generated by regression models. We evaluated the SII and SCI performance in distinguishing the simulated signal diffusion model. Presently, S2Map hosts a repository of 12 datasets that map single-cell and two-cell secretion dynamics. These datasets serve as a resource to explore secretion signal types. We anticipate that S2Map will be a powerful approach to delve into the complexities of physiological systems, providing insights into the regulation of protein production, such as cytokines at the remarkable resolution of single cells. The S2Map server is publicly accessible via https://au-s2map.streamlit.app/. Citation Format: Zongliang Yue, Lang Zhou, Fengyuan Huang, Pengyu Chen. S2Map: An online interactive analytical platform for quantitative signal measurement of cell Secretion Signal Map [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7428.

Abstract 4905: Multimodal transformer model improves survival prediction in lung cancer compared to unimodal approaches

Abstract Integrating multimodal lung data including clinical notes, medical images, and molecular data is critical for predictive modeling tasks like survival prediction, yet effectively aligning these disparate data types remains challenging. We present a novel method to integrate heterogeneous lung modalities by first thoroughly analyzing various domain-specific models and selecting the optimal model for embedding feature extraction per data type based on performance on representative pretrained tasks. For clinical notes, the GatorTron models showed the lowest regression loss on an initial evaluation set, with the large GatorTron-medium model achieving 12.9 loss. After selecting the top performers, we extracted robust embeddings on the full lung dataset built using the Multimodal Integration of Oncology Data System (MINDS) framework. MINDS provides an end-to-end platform for aggregating and normalizing multimodal patient data. We aligned the multimodal embeddings to a central pre-trained language model using contrastive representation learning based on a cosine similarity loss function. To adapt the language model to the new modalities, we employed a parameter-efficient tuning method called adapter tuning, which introduces small trainable adapter layers that leave the base model weights frozen. This avoids catastrophic forgetting of the pretrained weights. We evaluated our multimodal model on prognostic prediction tasks including survival regression and subtype classification using both public and internal lung cancer datasets spanning multiple histologic subtypes and stages. Our aligned multimodal model demonstrated improved performance over models utilizing only single modalities, highlighting the benefits of integrating complementary information across diverse lung data types. This work illustrates the potential of flexible multimodal modeling for critical lung cancer prediction problems using heterogeneous real-world patient data. Our model provides a strong foundation for incorporating emerging data types, modalities, and predictive tasks in the future. Citation Format: Aakash Tripathi, Asim Waqas, Yasin Yilmaz, Ghulam Rasool. Multimodal transformer model improves survival prediction in lung cancer compared to unimodal approaches [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4905.

Consumer and brand value formation, value creation and co-creation in social media brand communities

PurposeSocial media has significantly impacted the value creation processes within the consumer–brand relationship. This study aims to examine value formation processes within a cosmetics social media brand community and to establish the types of value formation associated with different categories of interactions within a social media brand community.Design/methodology/approachThe research adopted a netnographic approach and followed the operational protocols of netnography. Conversations in one large cosmetics social media brand community were observed and downloaded for analysis over a two-month period. Examples of value-creation and formation processes were identified using netnographic interpretative procedures to develop higher-order themes.FindingsThe findings supported the creation of a “Consumer and brand value creation and co-creation framework” highlighting disparate value types within the following interactions: consumer-to-consumer; brand-to-consumer; and consumer-to-brand. The identified value types were specific to the actors (i.e. consumers and brands) involved in value formation processes. The analysis also revealed consumers’ ability to independently generate value through direct interaction with a social media brand community and the brands’ role in supporting consumers in value formation through value facilitation.Originality/valueThe pivotal role of disparate actors’ interactions in value formation processes is highlighted, alongside the autonomous ability to form value with the aid of resources stored and shared within the social media brand community. The network of interactions and value-creation processes contribute to a holistic understanding of the interactions in a social media brand community. Furthermore, the research explores and highlights the emerging role of social media brand communities as “value vestiges”.

On chip all-optical distinguishing of independently placed distinct types of single Rayleigh particle

In order to determine whether a particle is plasmonic, dielectric, or chiral, different complex processes and chemicals are applied in lab setups and pharmaceutical industries. Sorting or categorizing a particle based on distinct optical forces can be a novel technique. When a beam of light interacts with a particle, it usually pushes the particle in the direction of the light's propagation. Counterintuitively, it can also pull the particle toward the light beam or move it toward a lateral direction. As far as we know, to date, no comprehensive report exists regarding a single optical arrangement capable of inducing entirely distinct behaviors of force for three disparate types of independently placed single Rayleigh particle. This study introduces an all-optical technique aimed at effectively sorting nanoscale Rayleigh-sized objects employing a plasmonic substrate, when each distinct type of single particle is placed over the substrate independently. Unfortunately, this proposed technique does not work for the cluster or mixture of distinct particles. In our proposed configuration, a simple linearly polarized plane wave is incident onto the plasmonic substrate, thereby engendering completely different responses from three different types of nanoparticles: Gold (plasmonic), SiO2 (dielectric), and Chiral particles. We conducted individual tests for our setup using linearly polarized plane waves at angles of 30-degree, 45-degree, and 60-degree individually. Consistent results were obtained across all angles. In each of the three distinct setups involving the aforementioned particle, a dielectric Rayleigh particle experiences an optical pulling force, a plasmonic Rayleigh particle experiences an optical pushing force, and a chiral Rayleigh particle encounters an optical lateral force. These distinctive force behaviors manifest as a result of the intricate interplay between the material properties of the nanoparticles and the characteristics of the plane-polarized beam, encompassing aspects such as plasmonic response, chirality, and refractive index. Moreover, this technique presents an environmentally sustainable and economically viable alternative to the utilization of expensive and potentially hazardous chemicals in nanoparticle sorting processes within industrial domains.

Evolution of the Ikaros family transcription factors: From a deuterostome ancestor to humans

Ikaros family proteins (Ikaros, Helios, Aiolos, Eos) are zinc finger transcription factors essential for the development and function of the adaptive immune system. They also control developmental events in neurons and other cell types, suggesting that they possess crucial functions across disparate cell types. These functions are likely shared among the organisms in which these factors exist, and it is thus important to obtain a view of their distribution and conservation across organisms. How this family evolved remains poorly understood. Here we mined protein, mRNA and DNA databases to identify proteins with DNA-binding domains homologous to that of Ikaros. We show that Ikaros-related proteins exist in organisms from all four deuterostome phyla (chordates, echinoderms, hemichordates, xenacoelomorpha), but not in more distant groups. While most non-vertebrates have a single family member, this family grew to six members in the acoel worm Hofstenia miamia, three in jawless and four in jawed vertebrates. Most residues involved in DNA contact from zinc fingers 2 to 4 were identical across the Ikaros family, suggesting conserved mechanisms for target sequence recognition. Further, we identified a novel KRKxxxPxK/R motif that inhibits DNA binding in vitro which was conserved across the deuterostome phyla. We also identified a EψψxxxψM(D/E)QAIxxAIxYLGA(D/E)xL motif conserved among human Ikaros, Aiolos, Helios and subsets of chordate proteins, and motifs that are specific to subsets of vertebrate family members. Some of these motifs are targets of mutations in human patients. Finally we show that the atypical family member Pegasus emerged only in vertebrates, which is consistent with its function in bone. Our data provide a novel evolutionary perspective for Ikaros family proteins and suggest that they have conserved regulatory functions across deuterostomes.

Numerical study on the impact of geometrical parameters and employing ternary hybrid nanofluid on the hydrothermal performance of mini-channel heat sink

Thermal management and temperature control of the electrical, electronic, and electrochemical devices during their operation have always been a challenge for proper performance and further development of them. In this regard, the utilization of liquid-cooled mini-channel heat sinks (MCHSs) and improving their capability for heat dissipation have been considered an effective method in past decades. The current study aims to improve the hydrothermal performance and temperature uniformity of MCHS. To this end, several channel configurations with novel geometrical cross sections, namely basic case and cases 1–4, are designed to investigate the influence of geometrical parameters on the mini-channel performance and temperature distribution inside the heat sink. Moreover, the hydrothermal improvement of each model in comparison to the basic case is computed through a parameter, namely performance evaluation criteria (PEC). Additionally, the impact of employing water-based ternary hybrid nanofluid (THNF) containing TiO2-MgO-GO ternary hybrid nanoparticles (THNPs) with various volume fractions and shape factors (SFs) instead of distilled water in the mini-channel with optimized hydrothermal behavior is thoroughly scrutinized. the outcomes endorse that in case 3 with trapezoidal geometry and PEC parameter equal to 1.2, the Nusselt number improves by 3.2 and 1.3 times, in comparison to case 2 (lowest values of Nusselt number) and base case, at Reynolds number of 831. Also, this is observed that hydraulic diameter directly impacts the pressure drop, and by decrement of that, the pressure drop heightens. However, case 2 with a rhombus geometry results in better temperature uniformity due to its larger effective heat transfer area. Furthermore, it is observed that the volume fraction and SF of THNP significantly affect the hydrothermal behavior of THNF inside the MCHS. For instance, by employing THNF with volume fractions of 0.03 % and 0.05 %, the average heat transfer coefficient (HTC) improves by 9 % and 17 %, pressure drop increases by 220 Pa and 370 Pa, and thermal resistance reduces by 9 % and 25 %, respectively, at Reynolds number of 1496, compared to distilled water. Further, THNF with a volume fraction of 0.05 %, reduces the maximum temperature of the heat sink by 3 K in comparison to distilled water, at a Reynolds number of 831. In addition, the utilization of disparate types of THNP with various SF, including spherical (sf = 3), platelets (sf = 5.7), blades (sf = 8.6), and lamina (sf = 16.1576) is examined and disclosed with volume fraction of 0.05 % and SF of 16.1576 instead of 3, HTC roughly elevates by 67 % and thermal resistance decreases by 47 %, at a Reynolds number of 831.

MicroRNA Profiling of Red Blood Cells for Lung Cancer Diagnosis.

Despite extensive endeavors to establish cell-free circulating biomarkers for lung cancer diagnosis, clinical adoption remains elusive. Noteworthy, emergent evidence suggests the pivotal roles of red blood cells (RBCs) and their derivatives in tumorigenesis, illuminating potential avenues for diagnostic advancements using blood cell-derived microRNAs (miRNAs). We executed microarray analyses on three principal blood cell types-RBCs, peripheral blood mononuclear cells (PBMCs), and neutrophils-encompassing 26 lung cancer patients and 26 healthy controls. Validation was performed using droplet digital PCR within an additional cohort comprising 42 lung cancer and 39 control cases. Our investigation unearthed distinct miRNA profiles associated with lung cancer across all examined blood cell types. Intriguingly, RBC-miRNAs emerged as potential novel biomarkers for lung cancer, an observation yet to be documented. Importantly, integrating miRNAs from disparate blood cell types yielded a superior diagnostic accuracy for lung cancer over individual cell-type miRNAs. Subsequently, we formulated three diagnostic panels, adeptly discerning non-small cell lung cancer, adenocarcinoma, and squamous cell carcinoma, maintaining consistency across various disease stages. RBC-derived molecules introduce novel cancer biomarkers, and exploiting miRNA profiles across varied blood cell types unveils a promising frontier for lung cancer's early detection and histological classification.

Effect of primary carbides on rolling contact fatigue behaviors of M50 bearing steel

It is perceived that the fatigue performance of high-strength steel is preponderantly affected by internal defects. Inclusions may be efficaciously controlled and primary carbides have been proved to be the principal type of defects in M50 bearing steels. Primary carbides in service-status M50 were systematically characterized and the rolling contact fatigue (RCF) properties were evaluated under different friction conditions in this work. An innovative method of shakedown analysis was proposed for the first time, extending the shakedown analysis of materials as an integral based on traditional shakedown theory to that of weaker internal defects. By the response of primary carbides, the RCF process was separated into a plastic instability period and an elastic shakedown period. The accumulation of plastic deformation around carbides before shakedown was proposed as the RCF damage parameter, and the influence of primary carbides was studied based on the damage criterion. The competition between surface and internal fatigue initiation was revealed via different friction coefficients. A predictive model for RCF initiation was established, which could predict the critical sizes for disparate types of primary carbides not deleterious to RCF performance, and the critical sizes under typical industrial service condition were reckoned.

Toward Standardised Vocabularies for Norwegian Archaeology

The Museum of Cultural History (MCH) at the University of Oslo, Norway, has undertaken a series of infrastructure projects with the aim of improving the standardisation of archaeological data and increasing data integration at both a national and international level. This builds on decades of earlier work and includes a revision of shared National database systems (unimus), integration of previously disparate data types and spatial data (ADED), and more recently the development of a 3D publishing platform (BItFROST). These projects feed into broader aims of large-scale data integration as part of the European-wide ARIADNE Research Infrastructure. This article provides an overview of the history and development of these systems in Norway and takes a look at some of the roads still ahead.

Remote homolog detection places insect chemoreceptors in a cryptic protein superfamily spanning the tree of life

Many proteins exist in the so-called "twilight zone" of sequence alignment, where low pairwise sequence identity makes it difficult to determine homology and phylogeny.1,2 As protein tertiary structure is often more conserved,3 recent advances in ab initio protein folding have made structure-based identification of putative homologs feasible.4,5,6 We present a pipeline for the identification and characterization of distant homologs and apply it to 7-transmembrane-domain ion channels (7TMICs), a protein group founded by insect odorant and gustatory receptors. Previous sequence and limited structure-based searches identified putatively related proteins, mainly in other animals and plants.7,8,9,10 However, very few 7TMICs have been identified in non-animal, non-plant taxa. Moreover, these proteins' remarkable sequence dissimilarity made it uncertain whether disparate 7TMIC types (Gr/Or, Grl, GRL, DUF3537, PHTF, and GrlHz) are homologous or convergent, leaving their evolutionary history unresolved. Our pipeline identified thousands of new 7TMICs in archaea, bacteria, and unicellular eukaryotes. Using graph-based analyses and protein language models to extract family-wide signatures, we demonstrate that 7TMICs have structure and sequence similarity, supporting homology. Through sequence- and structure-based phylogenetics, we classify eukaryotic 7TMICs into two families (Class-A and Class-B), which are the result of a gene duplication predating the split(s) leading to Amorphea (animals, fungi, and allies) and Diaphoretickes (plants and allies). Our work reveals 7TMICs as a cryptic superfamily, with origins close to the evolution of cellular life. More generally, this study serves as a methodological proof of principle for the identification of extremely distant protein homologs.

Mycoviruses: trends in plant-fungus-mycovirus interactions and ‘biocontrol’ prospects in agriculture and the environment

Mycoviruses are cosmopolitan in plants, animals, fungi, bacteria, in soils, and water. There is a scarcity of information about them, which necessitated this review to provide some leads on where research should focus. Mycoviruses are able to persist in disparate types of hosts by utilizing diverse measures. They may engage either parasitic, pathogenic, or mutualistic tendencies. Mycoviruses employ many existential strategies that can be utilized by man. Hypovirulence may be induced in fungal hosts by mycoviruses via RNA silencing, alteration of genetic expression, and disruption of the transcriptome. Mycoviruses interact with killer phenotypes of yeasts and Ustilago spp. and proffer advantages to these fungi. Mycovirus interaction with some plants result in provision of thermal tolerance to plants. Based on their mode of microbe destruction mycoviruses may be used for waste disposal and termination of some life processes. For instance, grazer viruses completely oxidize the organic content of their host into carbon dioxide and inorganic nutrients, while lytic viruses release the organic material from their hosts without modification. Viruses may be utilized to facilitate the exchange of genetic material from one host to another. However, pathogenic mycoviruses exist especially in mushrooms.

Efficient measurement of spoken English skills: Design and validation of a 6-minute assessment

Efficient measurement of spoken language skills can improve educational and commercial services. Traditional spoken language assessments often require 30–90 minutes. We report the development and validation of a prototype mobile-browser test of spoken English, “APro”, that participants complete in 6–8 minutes. The APro test presents a stratified random draw of 20 interactive tasks (from pool of 377) to participants whose spoken responses are automatically scored, scaled, and reported. APro aggregates skill-specific measures from disparate task types such as open descriptions and story retellings. Each skill-specific score was independently validated, then combined into an overall spoken English score. APro scoring was trained on 30,000 responses from 354 non-native pilot-test participants who connected remotely from their nine home countries on five continents. The final APro instrument was validated on an independent sample of 79 participants resident in seven countries. In the validation set, human and machine scoring of same-test APro administrations correlated r = 0.98, suggesting accurate speech processing. APro scores predicted much of the score variance in traditional concurrent assessments from Oxford, r = 0.86, and Pearson, r = 0.92. Finally, we present detailed results on two new interactive tasks and share changes to the content, procedure, and scoring that yield improved accuracy at shorter duration. [Work supported in part by Google LLC.]

Performing Qualitative Content Analysis of Video Data in Social Sciences and Medicine: The Visual-Verbal Video Analysis Method

Videos are ubiquitous and have significantly impacted our communication and information consumption. The video, as data, has helped researchers understand how human interactions and relationships develop and change, and how patterns emerge in various circumstances and interpretations. Given the expanding relevance of video data in social science and medical research and the constant introduction of new formats and sources, it is critical to be able to conduct a thorough analysis of this multimodal data. However, the few methodologies (e.g., Actor Network Theory, Picture Theory) appropriate to video data analysis lack detailed guidelines on how to select, organize, and examine the multimodality of video data. This article aims to overcome this practice or methodological gap by proposing and demonstrating the Visual-Verbal Video Analysis (VVVA) method, a six-step framework adapted from Multimodal Theory and Visual Grounded Theory for organizing and evaluating video material according to the following dimensions: general characteristics of the video; multimodal characteristics; visual characteristics; characteristics of primary and secondary characters; and content and compositional characteristics including the transmission of messages, emotions, and discourses. This article also looks at the theories underlying video data analysis, focusing on Grounded Theory and Multimodality Theory, and provides multiple examples of coding and interpretive processes to deepen understanding and comprehension. The VVVA data extraction matrices provide a systematic coding approach for verbal, visual, and textual content, allowing for structured, coherent extraction that supports the discovery of patterns and links among disparate types of information. The VVVA method may be applied to a wide range of video data in social and medical sciences that vary in length and originate from different sources (e.g., open access web sources, pre-recorded organizational videos and recordings created for research purposes). The VVVA method effectively tracks the ongoing research process, and can manage data sets of various sizes.

Disparate behavioral types in wild and reared juveniles of gilthead seabream

Fish differ consistently in behavior within the same species and population, reflecting distinct behavioral types (BTs). Comparing the behavior of wild and reared individuals provides an excellent opportunity to delve into the ecological and evolutionary consequences of BTs. In this work, we evaluated the behavioral variation of wild and reared juvenile gilthead seabreams, Sparus aurata, a highly relevant species for aquaculture and fisheries. We quantified behavioral variation along the five major axes of fish behavioral traits (exploration-avoidance, aggressiveness, sociability, shyness-boldness, and activity) using standardized behavioral tests and a deep learning tracking algorithm for behavioral annotation. Results revealed significant repeatability in all five behavior traits, suggesting high consistency of individual behavioral variation across the different axes in this species. We found reared fish to be more aggressive, social and active compared to their wild conspecifics. Reared individuals also presented less variance in their aggressiveness, lacking very aggressive and very tame individuals. Phenotypic correlation decomposition between behavioral types revealed two different behavioral syndromes: exploration-sociability and exploration-activity. Our work establishes the first baseline of repeatability scores in wild and reared gilthead seabreams, providing novel insight into the behavior of this important commercial species with implications for fisheries and aquaculture.