Filtering by
![137047-Thumbnail Image.png](/s3/files/styles/width_400/public/2021-05/137047-Thumbnail%20Image.png?itok=LkGh2-UB)
![147692-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/147692-Thumbnail%20Image.png?versionId=hIRiiWAIglc1P2lFflS5HoHA.KFvAlLw&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240618/us-west-2/s3/aws4_request&X-Amz-Date=20240618T202348Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=160683a92a1b613b576b0dffff4369892bae6e4521d64997d12e22e977de3ea5&itok=axv431DU)
Much is still unknown about dominance hierarchies. Many different species form dominance hierarchies and each species have very different ways of forming these hierarchies. Some engage in various different dominance interactions to establish a dominant position. This experiment aims to use the ant species, Harpegnathos saltator, as a model to explore what sets dominant individuals, or gamergates in this case, apart from non-dominant individuals, or non-gamergates. H. saltator ants perform various different behaviors such as dueling, which is a mutually beneficial behavior, dominance biting, which is an aggressive behavior, and policing which is used to bring down those who are dominant. These behaviors can be used to study the importance of initiation and aggression in hierarchy formation. This experiment will explore how aggression through dominance biting, duel initiation, group size, and time period affect the formation of gamergates. To do so, socially unstable colonies of 15, 30, and 60 ants were video recorded for days until gamergates were established. Then, from the recordings, a period of high activity was selected and observed for dueling, duel initiation, dominance biting, dominance bite downs, and policing. The results showed that gamergates tended to perform dominance biting and dominance bite downs far more than non-gamergates during the period of high activity, but not as clearly with duelling and duel initiations. It was inconclusive whether or not the combination of both dueling and dominance biting was what set gamergates apart from non gamergates as different groups showed different results. Gamergates performed visibly more dominance bite downs than non-gamergates, so aggression may be important in setting gamergates apart from non-gamergates. In terms of group size, the smallest group had the least number of gamergates and the least activity, and the medium and large group had a similar number of gamergates and activity.
![141473-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-06/141473-Thumbnail%20Image.png?versionId=lEiBSbazXh6rO9.4_YXpySOYQRNcOnP6&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240530/us-west-2/s3/aws4_request&X-Amz-Date=20240530T154456Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=c31c845f94b4acdd128ace7e6ebdf6f4dec47238ccb7a5cf802b2677cb60d536&itok=-DqC2NMZ)
Critical flicker fusion thresholds (CFFTs) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases and are thought to underlie a number of visual processing skills, including reading. Here, we compare the impact of two vision-training approaches, one involving contrast sensitivity training and the other directional dot-motion training, compared to an active control group trained on Sudoku. The three training paradigms were compared on their effectiveness for altering CFFT. Directional dot-motion and contrast sensitivity training resulted in significant improvement in CFFT, while the Sudoku group did not yield significant improvement. This finding indicates that dot-motion and contrast sensitivity training similarly transfer to effect changes in CFFT. The results, combined with prior research linking CFFT to high-order cognitive processes such as reading ability, and studies showing positive impact of both dot-motion and contrast sensitivity training in reading, provide a possible mechanistic link of how these different training approaches impact reading abilities.
![141474-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-06/141474-Thumbnail%20Image.png?versionId=ghW0Y9UCht88oLKWsCjFU9tM_TY9Dc3c&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240606/us-west-2/s3/aws4_request&X-Amz-Date=20240606T023947Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=51ee880627f4b51add0e31b7924c141822a3cc17d977083113da35e68c399d44&itok=uWO4W9vS)
Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.
![148329-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/148329-Thumbnail%20Image.png?versionId=eN84GMnnqcbijY6OccI_MOLA3KouIroz&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240618/us-west-2/s3/aws4_request&X-Amz-Date=20240618T183018Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=a76ab1bdd76917c88a1d35ae3aaa099496c4921bd3c95404629b79b1853e3fb9&itok=GLMdz5aA)
Olfactory discrimination tasks can provide useful information about how olfaction may have evolved by demonstrating which types of compounds animals will detect and respond to. Ants discriminate between nestmates and non-nestmates by using olfaction to detect the cuticular hydrocarbons on other ants, and Camponotus floridanus have particularly clear and aggressive responses to non-nestmates. A new method of adding hydrocarbons to ants, the “Snow Globe” method was further optimized and tested on C. floridanus. It involves adding hydrocarbons and a solvent to a vial of water, vortexing it, suspending hydrocarbon droplets throughout the solution, and then dipping a narcotized ant in. It is hoped this method can evenly coat ants in hydrocarbon. Ants were treated with heptacosane (C27), nonacosane (C29), hentriacontane (C31), a mixture of C27/C29/C31, 2-methyltriacontane (2MeC30), S-3-methylhentriacontane (SMeC31), and R-3-methylhentriacontane (RMeC31). These were chosen to see how ants reacted in a nestmate recognition context to methyl-branched hydrocarbons, R and S enantiomers, and to multiple added alkanes. Behavior assays were performed on treated ants, as well as two untreated controls, a foreign ant and a nestmate ant. There were 15 replicates of each condition, using 15 different queenright colonies. The Snow Globe method successfully transfers hydrocarbons, as confirmed by solid phase microextraction (SPME) done on treated ants, and the behavior assay data shows the foreign control, SMeC31, and the mixture of C27/29/31 were all statistically significant in their differences from the native control. The multiple alkane mixture received a significant response while single alkanes did not, which supports the idea that larger variations in hydrocarbon profile are needed for an ant to be perceived as foreign. The response to SMeC31 shows C. floridanus can respond during nestmate recognition to hydrocarbons that are not naturally occurring, and it indicates the nestmate recognition process may simply be responding to any compounds not found in the colony profile and rather than detecting particular foreign compounds.
![148500-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/148500-Thumbnail%20Image.png?versionId=125A9Rnxu_gA2DecgxX1e2XCzJ1IsdWR&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240618/us-west-2/s3/aws4_request&X-Amz-Date=20240618T082455Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=053694633ff0aad2f4ec4a5c392bce544978693676867118334e9eca79c0aebc&itok=DVCXRfhn)
As life expectancy increases worldwide, age related diseases are becoming greater health concerns. One of the most prevalent age-related diseases in the United States is dementia, with Alzheimer’s disease (AD) being the most common form, accounting for 60-80% of cases. Genetics plays a large role in a person’s risk of developing AD. Familial AD, which makes up less than 1% of all AD cases, is caused by autosomal dominant gene mutations and has almost 100% penetrance. Genetic risk factors are believed to make up about 49%-79% of the risk in sporadic cases. Many different genetic risk factors for both familial and sporadic AD have been identified, but there is still much work to be done in the field of AD, especially in non-Caucasian populations. This review summarizes the three major genes responsible for familial AD, namely APP, PSEN1 and PSEN2. Also discussed are seven identified genetic risk factors for sporadic AD, single nucleotide polymorphisms in the APOE, ABCA7, NEDD9, CASS4, PTK2B, CLU, and PICALM genes. An overview of the main function of the proteins associated with the genes is given, along with the supposed connection to AD pathology.
![130932-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/130932-Thumbnail%20Image.png?versionId=qGAU8_Gij9VWDav4IniVKS.XPZynRmEd&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240618/us-west-2/s3/aws4_request&X-Amz-Date=20240618T202348Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=fdb136f265642d282084fbecf3122cf361990b95011b14462a57a89feed93772&itok=jJqTN1Bp)
![131300-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/131300-Thumbnail%20Image.png?versionId=G2XOt4txZZ70Z6jaPzYtzgqO9jrLaAqf&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240618/us-west-2/s3/aws4_request&X-Amz-Date=20240618T195934Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=15f9bda48c3fe97847be83bc53829c78fc6e6296c1334340ce78fa6f4e6b2756&itok=86AMIiqL)
![131323-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/131323-Thumbnail%20Image.png?versionId=2ZybMwnxPBbPP07vg9_7ktovcsOstnRL&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240618/us-west-2/s3/aws4_request&X-Amz-Date=20240618T225929Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=c22736169932eed4f2c1d3694a11607255c57e15958181dc4051390aab469e5b&itok=gRNI1aPB)
Adaptation of Camponotus floridanus’ Cuticular Hydrocarbon Profile under High Temperature Conditions
![132382-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/132382-Thumbnail%20Image.png?versionId=9CcJ9zOTwnaqnoRKy5De9mwtENF1b1tJ&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240618/us-west-2/s3/aws4_request&X-Amz-Date=20240618T223312Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=42928efbe0d5064cff53ba00ebb097a2e7b8639d872e705fd503d08b9e9eb1fb&itok=GjkmBCOr)