Waterbird solves the string-pull test.
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ABSTRACT:
SUBMITTER: Lamarre J
PROVIDER: S-EPMC8633784 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Purpose:To define a distraction distance (pull length) cut-off that would differentiate those patients with hip microinstability and those without the disorder, called the Pull-Out Test. Methods:In total, 100 consecutive patients undergoing hip arthroscopy were included in the study. Patients were separated into a hip microinstability group (HMI) and non-hip microinstability group (NHI) based on the results of Beighton's score, the abduction-extension-external rotation test, hip extension-external rotation examination, and the prone instability test. Inclusion criteria were patients with an magnetic resonance imaging-proven labral tear who did not respond to conservative treatment and underwent hip arthroscopy. Exclusion criteria included those patients undergoing revision hip arthroscopy, had a previous surgery on the ipsilateral hip, or had severe arthritis in the hip. The Pull-Out Test was performed before surgery with the hip in 30° of abduction and the foot in 30° of external rotation. A blinded examiner places gross axial traction on the leg until a firm end point is reached. The distraction distance between the femoral head and acetabulum is the pull length. Results:In total, 32 patients made up the HMI group whereas 68 patients were in the NHI group. The average pull length for the NHI group was 0.9 ± 0.1 cm and 1.7 ± 0.4 cm for the HMI group (P < .001). Subtracting the standard deviation from the HMI group average, when defined a cut off for hip microinstability as 1.3 cm. Using this value, we found the Pull-Out Test to have a sensitivity of 0.91 and specificity of 0.96. The positive predictive value for the Pull Test was 0.91 and the negative predictive value 0.97. Conclusions:The Pull-Out Test is a useful test in identifying and confirming the presence of hip microinstability in patients undergoing hip arthroscopy. A pull-length of 1.3 cm or greater is consistent with the presence of microinstability with a specificity of 94% and a sensitivity of 96%. Level of Evidence:Level IV, diagnostic, case-control study.
| S-EPMC7120831 | biostudies-literature
Project description:String-pulling is one of the most popular tests in animal cognition because of its apparent complexity, and of its potential to be applied to very different taxa. In birds, the basic procedure involves a food reward, suspended from a perch by a string, which can be reached by a series of coordinated pulling actions with the beak and holding actions of the pulled lengths of string with the foot. The taxonomic distribution of species that pass the test includes several corvids, parrots and parids, but in other families, data are much spottier and the number of individuals per species that succeed is often low. To date, the association between string-pulling ability and other cognitive traits was never tested. It is generally assumed that string-pulling is a complex form of problem-solving, suggesting that performance on string-pulling and other problem-solving tasks should be correlated. Here, we show that individuals of two innovative species from Barbados, the bullfinch Loxigilla barbadensis and the Carib grackle Quiscalus lugubris fortirostris, pass the string-pulling test. Eighteen of the 42 bullfinches tested succeeded, allowing us to correlate performance on this test to that on several other behavioral measurements. Surprisingly, string-pulling in bullfinches was unrelated to shyness, neophobia, problem-solving, discrimination and reversal learning performance. Only two of 31 grackles tested succeeded, precluding correlational analyses with other measures but still, the two successful birds largely differed in their other behavioral traits.
| S-EPMC4988674 | biostudies-literature
Project description:A growing number of studies implicate the microbiome in the pathogenesis of intestinal inflammation. Previous work has shown that adults with esophagitis related to gastroesophageal reflux disease have altered esophageal microbiota compared to those who do not have esophagitis. In these studies, sampling of the esophageal microbiome was accomplished by isolating DNA from esophageal biopsies obtained at the time of upper endoscopy. The aim of the current study was to identify the esophageal microbiome in pediatric individuals with normal esophageal mucosa using a minimally invasive, capsule-based string technology, the Enterotest™. We used the proximal segment of the Enterotest string to sample the esophagus, and term this the "Esophageal String Test" (EST). We hypothesized that the less invasive EST would capture mucosal adherent bacteria present in the esophagus in a similar fashion as mucosal biopsy. EST samples and mucosal biopsies were collected from children with no esophageal inflammation (n = 15) and their microbiome composition determined by 16S rRNA gene sequencing. Microbiota from esophageal biopsies and ESTs produced nearly identical profiles of bacterial genera and were different from the bacterial contents of samples collected from the nasal and oral cavity. We conclude that the minimally invasive EST can serve as a useful device for study of the esophageal microbiome.
| S-EPMC3434161 | biostudies-literature
Project description:OBJECTIVES:Eosinophilic esophagitis (EoE), a chronic food allergic disease, lacks sensitive and specific peripheral biomarkers. We hypothesized that levels of EoE-related biomarkers captured using a 1-hour minimally invasive Esophageal String Test (EST) would correlate with mucosal eosinophil counts and tissue concentrations of these same biomarkers. We aimed to determine whether a 1-hour EST accurately distinguishes active from inactive EoE or a normal esophagus. METHODS:In a prospective, multisite study, children and adults (ages 7-55 years) undergoing a clinically indicated esophagogastroduodenoscopy performed an EST with an esophageal dwell time of 1 hour. Subjects were divided into 3 groups: active EoE, inactive EoE, and normal esophageal mucosa. Eosinophil-associated protein levels were compared between EST effluents and esophageal biopsy extracts. Statistical modeling was performed to select biomarkers that best correlated with and predicted eosinophilic inflammation. RESULTS:One hundred thirty-four subjects (74 children, 60 adults) with active EoE (n = 62), inactive EoE (n = 37), and patient controls with a normal esophagus (n = 35) completed the study. EST-captured eosinophil-associated biomarkers correlated significantly with peak eosinophils/high-power field, endoscopic visual scoring, and the same proteins extracted from mucosal biopsies. Statistical modeling, using combined eotaxin-3 and major basic protein-1 concentrations, led to the development of EoE scores that distinguished subjects with active EoE from inactive EoE or normal esophagi. Eighty-seven percent of children, 95% of parents, and 92% of adults preferred the EST over endoscopy if it provided similar information. DISCUSSION:The 1-hour EST accurately distinguishes active from inactive EoE in children and adults and may facilitate monitoring of disease activity in a safe and minimally invasive fashion.
| S-EPMC6784776 | biostudies-literature
Project description:ObjectiveThis study used whole-genome sequencing (WGS) to explore the genetic diversity, virulence factors, and antimicrobial resistance determinants of string test-positive Klebsiella pneumoniae (KP) over a 4-year surveillance period in Huzhou, China.MethodsIn total, 632 clinical isolates were collected via hospital surveillance from 2020 to 2023; 100 were positive in the string test and these 100 strains were subjected to antimicrobial susceptibility testing using an agar dilution method followed by WGS.ResultsThe resistance rates to cefotaxime (77.0%), trimethoprim-sulfamethoxazole (67.0%), and nalidixic acid (64.0%) were high. Multilocus sequence typing revealed high genetic diversity; there were 33 sequence types (STs) and 15 capsular serotypes. The most common ST was ST23 (16.0%) and the most common capsular serotype was K1 (22.5%). Virulome analysis revealed among-strain differences in virulence factors that affected bacterial adherence, efflux pump action, iron uptake, nutritional factors, metabolic regulation, the secretion system, and toxin production. The Kleborate strain-specific virulence scores of all 100 string test-positive KPs were derived: 28 strains scored 5, 28 scored 4, 21 scored 3, 12 scored 1, and 11 scored 0. All 77 strains with scores of 3 to 5 contained the iucA gene. The phylogeny based on whole-genome single nucleotide polymorphisms (wgSNPs) indicated high clonality; the string test-positive KP strains were grouped into six clades. Closely related isolates in each genetic cluster usually shared STs.ConclusionThe present study highlights the significance of the KP iucA gene in terms of hypervirulence and the diverse genotypes of string test-positive KP strains isolated in Huzhou hospitals.
| S-EPMC11333340 | biostudies-literature
Project description:A fundamental question in nutritional biology is how distributed systems maintain an optimal supply of multiple nutrients essential for life and reproduction. In the case of animals, the nutritional requirements of the cells within the body are coordinated by the brain in neural and chemical dialogue with sensory systems and peripheral organs. At the level of an insect society, the requirements for the entire colony are met by the foraging efforts of a minority of workers responding to cues emanating from the brood. Both examples involve components specialized to deal with nutrient supply and demand (brains and peripheral organs, foragers and brood). However, some of the most species-rich, largest, and ecologically significant heterotrophic organisms on earth, such as the vast mycelial networks of fungi, comprise distributed networks without specialized centers: How do these organisms coordinate the search for multiple nutrients? We address this question in the acellular slime mold Physarum polycephalum and show that this extraordinary organism can make complex nutritional decisions, despite lacking a coordination center and comprising only a single vast multinucleate cell. We show that a single slime mold is able to grow to contact patches of different nutrient quality in the precise proportions necessary to compose an optimal diet. That such organisms have the capacity to maintain the balance of carbon- and nitrogen-based nutrients by selective foraging has considerable implications not only for our understanding of nutrient balancing in distributed systems but for the functional ecology of soils, nutrient cycling, and carbon sequestration.
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Project description:Monitoring and detection of cyanide are of crucial interest as the latter plays versatile roles in many biological events, is ubiquitous in environment, and responsible for several acute poisoning and adverse health effects if ingested. We describe herein the synthesis and characterization of novel phenothiazine-based push–pull chromogenic chemosensors suitable for naked eye cyanide sensing. Indeed, specific detections were achieved for cyanide with a LOD of ca 9.12 to 4.59 µM and, interestingly, one of the new chemosensors has also revealed an unprecedented affinity for acetate with a LOD of ca 2.68 µM. Moreover, as proof of concept for practical applications, a paper test strip was prepared allowing its use for efficient qualitative naked eye cyanide sensing.
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Project description:Standardizing clinical laboratory test results is critical for conducting clinical data science research and analysis. However, standardized data processing tools and guidelines are inadequate. In this paper, a novel approach for standardizing categorical test results based on supervised machine learning and the Jaro-Winkler similarity algorithm is proposed. A supervised machine learning model is used in this approach for scalable categorization of the test results into predefined groups or clusters, while Jaro-Winkler similarity is used to map text terms into standard clinical terms within these corresponding groups. The proposed method is applied to 75062 test results from two private hospitals in Bangladesh. The Support Vector Classification algorithm with a linear kernel has a classification accuracy of 98%, which is better than the Random Forest algorithm when categorizing test results. The experiment results show that Jaro-Winkler similarity achieves a remarkable 99.93% success rate in the test result standardization for the majority of groups with manual validation. The proposed method outperforms previous studies that concentrated on standardizing test results using rule-based classifiers on a smaller number of groups and distance similarities such as Cosine similarity or Levenshtein distance. Furthermore, when applied to the publicly available MIMIC-III dataset, our approach also performs excellently. All these findings show that the proposed standardization technique can be very beneficial for clinical big data research, particularly for national clinical research data hubs in low- and middle-income countries.
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Project description:Feed-forward deep convolutional neural networks (DCNNs) are, under specific conditions, matching and even surpassing human performance in object recognition in natural scenes. This performance suggests that the analysis of a loose collection of image features could support the recognition of natural object categories, without dedicated systems to solve specific visual subtasks. Research in humans however suggests that while feedforward activity may suffice for sparse scenes with isolated objects, additional visual operations ('routines') that aid the recognition process (e.g. segmentation or grouping) are needed for more complex scenes. Linking human visual processing to performance of DCNNs with increasing depth, we here explored if, how, and when object information is differentiated from the backgrounds they appear on. To this end, we controlled the information in both objects and backgrounds, as well as the relationship between them by adding noise, manipulating background congruence and systematically occluding parts of the image. Results indicate that with an increase in network depth, there is an increase in the distinction between object- and background information. For more shallow networks, results indicated a benefit of training on segmented objects. Overall, these results indicate that, de facto, scene segmentation can be performed by a network of sufficient depth. We conclude that the human brain could perform scene segmentation in the context of object identification without an explicit mechanism, by selecting or "binding" features that belong to the object and ignoring other features, in a manner similar to a very deep convolutional neural network.
| S-EPMC7406083 | biostudies-literature
Project description:Electric guitar playing is ubiquitous in practically all modern music genres. In the hands of an experienced player, electric guitars can sound as expressive and distinct as a human voice. Unlike other more quantised instruments where pitch is a discrete function, guitarists can incorporate micro-tonality and, as a result, vibrato and sting-bending are idiosyncratic hallmarks of a player. Similarly, a wide variety of techniques unique to the electric guitar have emerged. While the mechano-acoustics of stringed instruments and vibrating strings are well studied, there has been comparatively little work dedicated to the underlying physics of unique electric guitar techniques and strings, nor the mechanical factors influencing vibrato, string-bending, fretting force and whammy-bar dynamics. In this work, models for these processes are derived and the implications for guitar and string design discussed. The string-bending model is experimentally validated using a variety of strings and vibrato dynamics are simulated. The implications of these findings on the configuration and design of guitars is also discussed.
| S-EPMC4108333 | biostudies-literature