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Molecular Interaction Network Approach (MINA) was used to elucidate candidate disease genes. The approach was implemented to identify novel gene association with commonly known autoimmune diseases [1]. In MINA, we evaluated the hypothesis that “network proximity” within a whole genome molecular interaction network can be used to inform the search for multigene inheritance. There are now numerous examples of gene discoveries based upon network proximity between novel and previously identified disease genes (Yin et al., 2017 [2], Wang et al., 2011 [3], and Barrenas et al., 2009 [4]). This study extends the application of interaction networks to the interrogation of Genome Wide Association studies: first, by showing that a group of nine autoimmune diseases (AuD) genes “seed genes”, are connected in a highly non-random manner within a whole genome network; and second, by showing that the minimal number of connecting genes required to connect a maximal number of AuD candidate genes are highly enriched as candidate genes for AuD predisposing mutations. The findings imply that a threshold number of candidate genes for any heritable disorder can be used to “seed” a molecular interaction network that • Serves to validate the disease status of closely associated seed genes • Identifies genes that are highly enriched as novel candidate disease genes • Provides a strategy for elucidation of epistatic gene x gene interactionsThe method could provide a critical toll for understanding the genetic architecture of common traits and disorders. Method name: MINA, Molecular Interaction Network Approach, Keywords: Autoimmune diseases, Crohn’s disease (CD), Systemic lupus erythematosus (SLE), Rheumatoid arthritis (RA), Psoriasis (PSO), Type-1 diabetes (T1D), Type-2 diabetes (T2D), Celiac disease (CeD), Multiple sclerosis (MS), Association, Molecular network

Different ligands stabilize specific conformations of the angiotensin II type 1 receptor (AT1R) that direct distinct signaling cascades mediated by heterotrimeric G proteins or β-arrestin. These different active conformations are thought to engage distinct intracellular transducers because of differential phosphorylation patterns in the receptor C-terminal tail (the "barcode" hypothesis). Here, we identified the AT1R barcodes for the endogenous agonist AngII, which stimulates both G protein activation and β-arrestin recruitment, and for a synthetic biased agonist that only stimulates β-arrestin recruitment. The endogenous and β-arrestin–biased agonists induced two different ensembles of phosphorylation sites along the C-terminal tail. The phosphorylation of eight serine and threonine residues in the proximal and middle portions of the tail was required for full β-arrestin functionality, whereas phosphorylation of the serine and threonine residues in the distal portion of the tail had little influence on β-arrestin function. Similarly, molecular dynamics simulations showed that the proximal and middle clusters of phosphorylated residues were critical for stable β-arrestin–receptor interactions. These findings demonstrate that ligands that stabilize different receptor conformations induce different phosphorylation clusters in the C-terminal tail as barcodes to evoke distinct receptor-transducer engagement, receptor trafficking, and signaling. Editor's summary: The specific patterns of phosphorylation in the intracellular tail of a G protein–coupled receptor (GPCR) are thought to act as a barcode that determines whether G proteins are stimulated or β-arrestins are recruited. Gareri et al. investigated the role of phosphorylation barcodes in signaling by the angiotensin II type 1 receptor (AT1R). AT1R elicits both G protein activation and β-arrestin recruitment in response to the endogenous agonist AngII but stimulates only β-arrestin recruitment in response to a synthetic biased agonist. The authors identified patterns of serine and threonine phosphorylation that stabilized specific conformations of β-arrestin and were necessary for β-arrestin function. These findings demonstrate the importance of phosphorylation barcodes in determining the consequences of AT1R activation. —Annalisa M. VanHook [ABSTRACT FROM AUTHOR]

Background: Patient sex is known to affect patient outcomes in sports medicine. Historically, many studies on athletes have focused on male athletes and been generalized to female athletes. Hypothesis: Studies with female first or senior authors will isolate female athletes as study participants more frequently than studies with male first or senior authors. Study Design: Systematic review; Level of evidence, 4. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocols, original research studies published between 2017 and 2021 that analyzed athletes were systematically screened from the 6 top sports medicine journals (British Journal of Sports Medicine ; Arthroscopy: The Journal of Arthroscopic and Related Surgery ; Knee Surgery, Sports Traumatology, Arthroscopy ; American Journal of Sports Medicine ; Orthopaedic Journal of Sports Medicine ; Sports Health: A Multidisciplinary Approach). Articles were included for analysis if they met the following criteria: (1) original sports medicine research study, (2) analysis involving athletes, and (3) inclusion of ≥10 participants. Exclusion criteria included (1) review articles of any type and (2) cadaveric studies. The determination of author sex was completed using the name-to-gender assignment algorithm Genderize.io (https://genderize.io/). Results: A total of 1146 studies were included in quantitative analysis. There were 246 studies with a female first author (21.5%) and 191 studies with a female senior author (16.7%). When looking at all authors (first, senior, and intermediate), 19.9% were female. Female first authors were over 4 times more likely to isolate female athletes in clinical research than male first authors (17.5% vs 3.8%, respectively; P <.001). Female senior authors were approximately twice as likely to isolate female athletes compared with male senior authors (11.5% vs 5.8%, respectively; P <.001). Conclusion: Female first authors were significantly more likely to perform research isolating female athletes. While improving the frequency of female athlete research is multifactorial, increasing the number of female researchers may have a direct effect on improving gender equality in sports medicine research. [ABSTRACT FROM AUTHOR]

This study frames continued long-term participation in community engagement activities as indicative of a sense of "purpose" as defined by Damon, Menon, and Cotton Bronk (2003). Using data from US-based National Longitudinal Study of Adolescent Health, we examined factors that predict whether students participating in civic engagement activities between the ages of 12 and 18 would report similar participation six years later. Multilevel logistic regression analyses revealed no demographic differences beyond age and highest level of education attained. However, continued participation was most likely among individuals who participated in a combination of voluntary and required community-based civic activities as an adolescent, and who participated in any of a number of various types of extracurricular activities. Other factors, including religiosity, sense of belonging in school, achievement, and having parents engaged in civic activities, were also positively related to continued community engagement. (Contains 2 tables.)

The purpose of this study is to examine the social and self-perceptions of twice-exceptional "students", those students who meet criteria for being identified as both gifted and learning disabled. In particular, we focus on how twice-exceptional students are similar to, or different from, students with only a learning disability or who are only identified as gifted. Using data collected from the National Longitudinal Study of Adolescent Health, we identified a group of 90 twice-exceptional adolescents as well as three matched comparison groups. Overall, twice-exceptional adolescents had less positive perceptions of maternal relationships and self-concept than did gifted or nonidentified adolescents. Further, perceptions of maternal relationships mediated and moderated group differences in self-concept. Implications for adults working with twice-exceptional adolescents are discussed. (Contains 3 tables and 1 figure.)

Abstract Addressing the uncertainty and variability in the quality of 3D printed metals can further the wide spread use of this technology. Process mapping for new alloys is crucial for determining optimal process parameters that consistently produce acceptable printing quality. Process mapping is typically performed by conventional methods and is used for the design of experiments and ex situ characterization of printed parts. On the other hand, in situ approaches are limited because their observable features are limited and they require complex high-cost setups to obtain temperature measurements to boost accuracy. Our method relaxes these limitations by incorporating the temporal features of molten metal dynamics during laser-metal interactions using video vision transformers and high-speed imaging. Our approach can be used in existing commercial machines and can provide in situ process maps for efficient defect and variability quantification. The generalizability of the approach is demonstrated by performing cross-dataset evaluations on alloys with different compositions and intrinsic thermofluid properties.

Metal additive manufacturing is associated with thermal cycles of high rates of heating, melting, cooling, and solidification. Some areas within the build experience thermal cycles that depend on the paths of the energy source. Additionally, geometrical features, such as thin walls and overhangs, can lead to heat accumulation, potentially affecting the microstructure, fatigue life, and induced residual stresses that may lead to dimensional distortion and cracking. The identification of significant heat accumulation can be used for part quality monitoring to inform the design process, enhance the quality of printed parts, and optimize the process parameters. This study aims to efficiently identify heat accumulation with affordable in-situ infrared imaging for further characterization and mitigation to enhance the quality of printed parts. A computational framework employing machine learning is developed to identify zones of local heat accumulation in real time. The effectiveness of this approach is demonstrated by experiments conducted on a build with a wide variety of geometrical features. In addition, characterization and detailed analyses of detected local heat accumulation zones are provided.