Tool For Correction Research Articles

Bystander base editing interferes with visual function restoration in Leber congenital amaurosis.

Base editors (BEs) have emerged as a powerful tool for gene correction with high activity. However, bystander base editing, a byproduct of BEs, presents challenges for precise editing. Here, we investigated the effects of bystander edits on phenotypic restoration in the context of Leber congenital amaurosis (LCA), a hereditary retinal disorder, as a therapeutic model. We observed that in rd12 of LCA model mice, the highest editing activity version of an adenine base editors (ABEs), ABE8e, generated substantial bystander editing, resulting in missense mutations despite RPE65 expression, preventing restoration of visual function. Through AlphaFold-based mutational scanning and molecular dynamics simulations, we identified that the ABE8e-driven L43P mutation disrupts RPE65 structure and function. Our findings underscore the need for more stringent requirements in developing precise BEs for future clinical applications.

Patient and family aftercare enhance interactions between Helicopter Emergency Medicine Services and former patients and families

BackgroundHelicopter Emergency Medical Services (HEMS) in the United Kingdom (UK) deliver enhanced care to high-acuity, critically ill and injured patients. To enable patients to meet the HEMS team who treated them, many services within the UK have developed or are in the process of developing a Patient and Family Aftercare Service (PFAS). This study aims to evaluate whether the introduction of PFAS mitigates anxiety associated with patient aftercare visits.MethodsA service evaluation of anxiety in HEMS team members before and after patient aftercare visits were conducted. The study was carried out between 1 September 2023, and 31 October 2023, and patient visits were undertaken between March 2022 and July 2023. An electronic survey was distributed to the respondents who provided informed consent for participation. The survey comprised the validated generalised anxiety disorder anxiety scale (GAD-7) and five additional contextualised statements developed through the wider PFAS. Anonymised data were collected using REDCap, a secure electronic database and was analysed in R programming. Free-text comments were reported by content analysis, placed into themes, and discussed with a narrative to complement the quantitative analysis.ResultsOf the 33 recipients, 25 completed the questionnaire. Between the pre- and post-aftercare visits, a statistically significant difference was found between scores for GAD-7 (0.004, p < 0.05) and contextualised statements (0.001, p < 0.05). In addition, six broad themes were identified through content analysis. These include the emotional impact of patient interaction, coping strategies and structural changes in the aftercare system, challenges in patient and family expectations, anxieties relating to operational commitments, memory and recall of the incident, and a positive impact on personal growth.ConclusionAnxiety related to patient aftercare visits was reduced when measured before and after the patient visits. Following this service evaluation, we can hypothesise that within pre-hospital care, PFAS plays an important structural role. Future research should focus on affirming the correct tool to measure anxiety in multi-disciplinary teams and prospectively evaluating these methods collaboratively across multiple pre-hospital services.

ANÁLISE DA LUA NOVA lV

Through the astronomical calendar of UNIFEI - Federal University of Itajubá, we will research the coincident hours and minutes in different data. What do these data teach us? We will also see a new approach in counting the Lunations that can be done even by teenagers who have the correct tool available in their region. The difference between the astronomical calendar and the visual calendar, the latter used thousands of years ago, as the telescope had not been invented to help them and as the visual calendar is still used in relation to the lunations, turns of the Moon around the Earth.

First Report on Taxonomic Significance of Foliar Microanatomy of Lamiaceae Taxa from Pakistan; A Correct Tool for Taxa Authentication

The foliar epidermal, stomatal and trichome properties are frequently used as plant microscopic attributes from a taxonomic or ecological perspective. Among the angiosperm families, the Lamiaceae is one of the most taxonomically difficult, economically significant, and medicinally important families. To better understand the foliar microanatomy of Lamiaceae taxa obtained from Northern Pakistan, this study attempts to determine the variational and diagnostic features of 27 species that were analyzed using light microscopy (LM) and scanning electron microscopy (SEM). UPGMA cluster analysis, principal component analysis (PCA) and semantic differential chart (SDC) were used to characterize, visualize, and compare the leaf micromorphology across all species. Three different types of epidermal cell types were examined on both foliar surfaces i.e., irregular, hexagonal, and polygonal. Anticlinal wall pattern also shows variation. Anomocytic stomata is dominant in 8 studied species followed by paractic in 5 species, anisocytic in 4 species and diacytic in 2 species. The trichomes could be broadly classified into two groups, glandular trichomes (GTs) and non-glandular trichomes (NGTs). Lamiaceae has two types of glandular trichomes, small capitate and large peltate, which differ in size, structure, and distribution. In present research five distinct forms of non-glandular trichomes are unicellular, multicellular, stellate, branched, and unbranched trichomes. The results that characterized, illustrated, and contrasted the leaf anatomical characteristics of the Lamiaceae taxa can be better understood with the aid of statistical analysis. Future research will depend on these findings to improve the systematics of Lamiaceae taxa. These characteristics have a large taxonomic potential when considered as a whole.

A review of cognitive aids and their application to emergency management in Australia

Decision-making in disasters and major crises faced by emergency services globally is a difficult combination of science and art to master. To assist decision-makers in these environments, a number of cognitive aids have been developed and subsequently adopted by individuals and organisations alike. However, these aids vary according to their intent and the context in which they are intended to be applied. This review explores the use of cognitive aids in the context of emergency management and explores how existing knowledge regarding the use of cognitive aids from other industries may be translated to emergency management. An iterative literature review of academic and industry material related to cognitive aids during incident and crisis response across a broad range of international emergency service and other industries within the last 20 years was completed. Ultimately, cognitive aids are not a silver bullet when it comes to decision-making in the emergency management context. The correct tool (that is correctly designed) must be correctly applied by trained and competent end users. The Australian emergency management sector may benefit from future research exploring how these existing tools adhere to the good practice principles identified in this study.

Total Ankle Arthroplasty as a Correction Tool for Foot Deformities: Analyzing the Impact on Medial Column Alignment Adaptation Through Weightbearing Computed Tomography.

While weightbearing computed tomography (WBCT) has been instrumental in analyzing total ankle arthroplasty (TAA) positioning, there is a notable gap in the literature regarding adaptive changes in the foot's medial column after TAA. This study aims to bridge this gap by comparing preoperative and postoperative alignments of the foot's medial column and analyzing if a correlation exists between TAA coronal alignment correction and medial column alignment adaptation. Sixty patients who underwent a lateral approach TAA for end-stage osteoarthritis (OA) between January 2021 and April 2023 were included in this retrospective study. Patients were divided into varus (n = 30) and valgus (n = 30) groups. Preoperative and postoperative WBCT scans were analyzed to measure medial column alignment. Statistical analysis evaluated alignment corrections and correlations. Both groups showed significant plantarflexion of the second tarsometatarsal (TMT) angle, with a median adaptation of -1 degree (IQR -3, 0; P < .01) in the valgus group and -1 degree (IQR -3, 0; P = .03) in the varus group. The varus group exhibited increased plantarflexion of the first TMT angle (median -1 degree, IQR -1, -2; P = .03). Both groups demonstrated increased adduction of the medial column. The talonavicular coverage angle adaptation averaged 7.2 ± 14 degrees (P < .01) in the valgus and 9 ± 12 degrees (P < .01) in the varus group. The talo-first metatarsal axial angle adaptation was 5 ± 13 degrees (P = .03) in the valgus group and 9.5 ± 15 degrees (P = .08) in the varus group. WBCT analysis revealed significant medial column adaptation post-TAA in varus and valgus alignments. However, no correlation was found between hindfoot correction and forefoot adaptation, making it challenging to predict the need for additional realignment surgeries. Future studies should explore the relationship between tibiotalar correction and medial column alignment to improve outcomes and the influence of total ankle design on medial column adaptation. Level III, retrospective case control study.

Characterization of an At-Risk Population for Nonalcoholic Fatty Liver Disease (NAFLD) in a Primary Care Setting Along the U.S.-Mexico Border.

This study aimed to determine the burden of suspected nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) in a predominantly Hispanic patient population and explore the utility of the American Gastroenterological Association's NAFLD Clinical Care Pathway (CCP). Electronic medical records (n = 223) were used to divide patients into risk groups based on the amount of metabolic risk factors they presented, diabetic status, or if they presented other liver diseases. Fribosis-4 (FIB-4) scores were used to determine the risk for advanced fibrosis. Most patients (83.8%) were considered at risk for NAFLD based on CCP criteria, and about a third of patients (33.2%) were found to be at indeterminate (n = 60; 26.9%) or high risk (n = 14; 6.3%) for advanced fibrosis. Most indeterminate-risk patients (78.3%) were not referred for liver imaging. This study demonstrates the potential of the CCP as a corrective tool that could help to better identify and screen patients at risk for NAFLD.

Pengaruh Tingkat Pengetahuan terhadap Perilaku Pengguna Lensa Kontak Lunak di BONBON SOFTLENS

Eyes are an important sense that require assistance such as contact lenses for people with vision impairments. Contact lenses have evolved from vision correction tools to cosmetic accessories, especially among teenagers. However, improper behavior in using contact lenses can increase the risk of eye infections. This research uses a quantitative method with an associative approach. Data were collected through questionnaires from 125 respondents. The results of the study showed that all questionnaire items were valid and reliable. The coefficient of determination analysis indicated that knowledge influences behavior by 33.2%. The partial test (T-test) showed that knowledge significantly affects the behavior of soft contact lens users, with a T-value of 7.826. The conclusion is that higher knowledge levels significantly improve the behavior of contact lens users in following proper procedures, reducing the risk of complications such as eye infections. This study emphasizes the importance of education for contact lens users to promote safe and effective usage practices.

Ornaments for efficient allele-specific expression estimation with bias correction

Allele-specific expression plays a crucial role in unraveling various biological mechanisms, including genomic imprinting and gene expression controlled by cis-regulatory variants. However, existing methods for quantification from RNA-sequencing (RNA-seq) reads do not adequately and efficiently remove various allele-specific read mapping biases, such as reference bias arising from reads containing the alternative allele that do not map to the reference transcriptome or ambiguous mapping bias caused by reads containing the reference allele that map differently from reads containing the alternative allele. We present Ornaments, a computational tool for rapid and accurate estimation of allele-specific transcript expression at unphased heterozygous loci from RNA-seq reads while correcting for allele-specific read mapping biases. Ornaments removes reference bias by mapping reads to a personalized transcriptome and ambiguous mapping bias by probabilistically assigning reads to multiple transcripts and variant loci they map to. Ornaments is a lightweight extension of kallisto, a popular tool for fast RNA-seq quantification, that improves the efficiency and accuracy of WASP, a popular tool for bias correction in allele-specific read mapping. In experiments with simulated and human lymphoblastoid cell-line RNA-seq reads with the genomes of the 1000 Genomes Project, we demonstrate that Ornaments improves the accuracy of WASP and kallisto, is nearly as efficient as kallisto, and is an order of magnitude faster than WASP per sample, with the additional cost of constructing a personalized index for multiple samples. Additionally, we show that Ornaments finds imprinted transcripts with higher sensitivity than WASP, which detects imprinted signals only at gene level.

Acute promyelocytic leukemia: the first reported case diagnosed by immunophenotyping in Mozambique

Patients with acute promyelocytic leukemia (APL), a subtype of acute myeloid leukemia (AML), often present with severe leucocytosis and thrombocytopenia, which may lead to symptoms that require prompt diagnosis and treatment. Immunophenotyping combined with cytomorphology is a valuable tool for identifying APL patients. We describe the case of a 9-year-old male patient who was diagnosed with APL in July 2022 using immunophenotyping combined with cytomorphology. The patient was treated with chemotherapy and is now in full remission in the maintenance phase. This case demonstrated the importance of timely differential diagnosis using the correct tools, allowing inclusion in the appropriate treatment protocol.

Artificial intelligence model for automated surgical instrument detection and counting: an experimental proof-of-concept study

BackgroundRetained surgical items (RSI) are preventable events that pose a significant risk to patient safety. Current strategies for preventing RSIs rely heavily on manual instrument counting methods, which are prone to human error. This study evaluates the feasibility and performance of a deep learning-based computer vision model for automated surgical tool detection and counting.MethodsA novel dataset of 1,004 images containing 13,213 surgical tools across 11 categories was developed. The dataset was split into training, validation, and test sets at a 60:20:20 ratio. An artificial intelligence (AI) model was trained on the dataset, and the model’s performance was evaluated using standard object detection metrics, including precision and recall. To simulate a real-world surgical setting, model performance was also evaluated in a dynamic surgical video of instruments being moved in real-time.ResultsThe model demonstrated high precision (98.5%) and recall (99.9%) in distinguishing surgical tools from the background. It also exhibited excellent performance in differentiating between various surgical tools, with precision ranging from 94.0 to 100% and recall ranging from 97.1 to 100% across 11 tool categories. The model maintained strong performance on a subset of test images containing overlapping tools (precision range: 89.6–100%, and recall range 97.2–98.2%). In a real-time surgical video analysis, the model maintained a correct surgical tool count in all non-transition frames, with a median inference speed of 40.4 frames per second (interquartile range: 4.9).ConclusionThis study demonstrates that using a deep learning-based computer vision model for automated surgical tool detection and counting is feasible. The model’s high precision and real-time inference capabilities highlight its potential to serve as an AI safeguard to potentially improve patient safety and reduce manual burden on surgical staff. Further validation in clinical settings is warranted.

Enhancing Engagement and Autonomy in Advanced Japanese Learning as the Second Language through AI-Assisted Video Production

This study delves into the integration of generative AI in second language acquisition, particularly focusing on advanced Japanese learners' autonomy and motivation enhancement through video production. Drawing from Japan's educational guidelines and prior research, the investigation examines the roles of generative AI in language education, emphasizing ethical considerations and strategies for effective integration (Mollick Mollick, 2023). The course implemented a hybrid approach, combining language instruction with media production, where students created YouTube videos in Japanese. Their productions were supported by AI tools for language correction, narration, and content generation. Results indicate that while AI facilitated practical language learning, instructor guidance remained crucial for ensuring accuracy and contextual appropriateness. The study highlights challenges such as overreliance on AI-generated content and the need for nuanced communication in prompt engineering. Despite these challenges, students demonstrated cultural understanding and improved nonverbal communication skills through video production. Future research aims to analyze students' reflections on their experiences, shedding light on their insights and future applications of AI in language learning.

StepBrain: A 3-Dimensionally Printed Multicompartmental Anthropomorphic Brain Phantom to Simulate PET Activity Distributions.

An innovative multicompartmental anatomic brain phantom (StepBrain) is described to simulate the invivo tracer uptake of gray matter, white matter, and striatum, overcoming the limitations of currently available phantoms. Methods: StepBrain was created by exploiting the potential of fused deposition modeling 3-dimensional printing to replicate the real anatomy of the brain compartments, as modeled through ad hoc processing of healthy-volunteer MR images. Results: A realistic simulation of 18F-FDG PET brain studies, using target activity to obtain the real concentration ratios, was obtained, and the results of postprocessing with partial-volume effect correction tools developed for human PET studies confirmed the accuracy of these methods in recovering the target activity concentrations. Conclusion: StepBrain compartments (gray matter, white matter, and striatum) can be simultaneously filled, achieving different concentration ratios and allowing the simulation of different (e.g., amyloid, tau, or 6-fluoro-l-dopa) tracer distributions, with a potentially valuable role for multicenter PET harmonization studies.

Revisiting the dead time effects of Insight-HXMT/ME on timing analysis

ABSTRACT Dead time is a common instrumental effect of X-ray detectors, which would alter the behaviour of timing properties of astronomical signals, such as distorting the shape of power density spectra (PDS), affecting the root-mean-square of potential quasi-periodic oscillation signals, etc. We revisit the effects of the dead time of Medium Energy X-ray telescope (ME) onboard Insight-HXMT based on the simulation of electronic read-out mechanism that causes the dead time and the real data. We investigate dead time effects on the pulse profile as well as the quasi–periodic oscillation (QPO) signals. The dead time coefficient suggests a linear correlation with the observed count rate in each phase bin of the pulse profile according to the simulation of periodic signal as well as the real data observed on Swift J0243.6+6124. The Fourier-amplitude-difference (FAD) method could well recover the intrinsic shape of the observed PDS in the case that the PDS is from two identical detectors. We apply this technique on ME, by splitting the nine FPGA modules into two groups. The results indicate that the FAD technique suits the case when two groups of detectors are not largely different; and the recovered PDS of Sco X-1 observed by ME slightly enhances the significance of the previously known QPO signal, meanwhile the root-mean-square of QPO is significantly improved. We provide the FAD correction tool implemented in HXMTDAS for users in the future to better analyse QPO signals.

Evaluating simulation tools for securing sensor data with blockchain: A comprehensive analysis

Securing data generated from diverse sensors poses a critical challenge in contemporary applications, particularly due to the escalating volume of data and its vulnerability to security breaches. Blockchain technology has emerged as a promising solution, yet the implementation of blockchain applications entails significant costs. Assessing the feasibility of such implementations through simulation is imperative but has been hindered by a lack of details survey about the simulation tools leading to wrong choice of tools by the researchers, as every application is unique and requires specific blockchain platform as per use.This paper covers an extensive survey of 32 simulation tools used in blockchain, focusing on their advantages, limitations, platform used, and capability to evaluate performance metrics of blockchain applications. This enables the researchers to choose the correct simulation tool for their work. The work allows the programmer to test their application using the correct simulation tool, saving implementation costs and time. Furthermore, we discussed CBlockSim, a simulation tool designed specifically for blockchain applications, elucidating its functionality through a comparative study of Bitcoin and Ethereum.Our work contributes to advancing the understanding and application of simulation tools in blockchain-based sensor data security, offering insights that can significantly enhance the security posture of sensor networks.

Minimum viable product “Ailey Robot Improves Verbal Skills” for the development of preschool children

This paper specifically examines MVP “Ailey Robot Improves Verbal Skills” as a tool for preschool aged children’s verbal skills development. Initial project aims to develop competent verbal skills as an aid tool for simple verbal correction in native (Russian) language and the associative object thinking improvement for children aged 3 years old, as well as is objected to increase the vocabulary of older children (up to seven aged ones). One of most significant activities for preschoolers is a role-playing game with a plot helping children to orient in social relations and estimate human activity’ values and motives through the acceptance of a certain role. With technological development, online platforms and applications are becoming the most accessible and increasingly popular method of teaching children from 3 to 7 years old. The content of thematic levels in the application covers various areas of daily life, which helps the child develop important situational and social skills, while the game format increases internal motivation to learn. The “Ailey Robot Improves Verbal Skills” service uses artificial intelligence models to create an exciting and effective learning environment for children and serves as an informative auxiliary tool for parents and speech specialists. In this paper we aimed to review this online application’s main features, analyze its performance, and identify its pros &amp; cons.

Is It Still Time for Safety Walkaround? Pilot Project Proposing a New Model and a Review of the Methodology.

Background and Objectives: Healthcare facilities are complex systems due to the interaction between different factors (human, environmental, management, and technological). As complexity increases, it is known that the possibility of error increases; therefore, it becomes essential to be able to analyze the processes that occur within these contexts to prevent their occurrence, which is the task of risk management. For this purpose, in this feasibility study, we chose to evaluate the application of a new safety walkaround (SWA) model. Materials and Methods: A multidisciplinary working group made up of experts was established and then the subsequent phases of the activity were divided into three stages, namely the initial meeting, the operational phase, and the final meeting, to investigate knowledge regarding patient safety before and subsequently through visits to the department: the correct compilation of the medical record, adherence to evidence-based medicine (EBM) practices, the overall health and the degree of burnout of the various healthcare professionals, as well as the perception of empathy of staff by patients. Results: This working group chose to start this pilot project in the vascular surgery ward, demonstrating the ability of the tool used to capture the different aspects it set out to collect. In detail, the new version of SWA proposed in this work has made it possible to identify risk situations and system vulnerabilities that have allowed the introduction of corrective tools; detect adherence to existing company procedures, reschedule training on these specific topics after reviewing, and possibly update the same procedures; record the patient experience about the doctor-patient relationship and communication to hypothesize thematic courses on the subject; evaluate workers' perception of their health conditions about work, and above all reassure operators that their well-being is in the interest of the management of the healthcare company, which is maintained. Conclusions: Therefore, the outcome of the present study demonstrates the versatility and ever-present usefulness of the SWA tool.

Unlocking Writing Potential: Assessing the Impact of Grammarly on Jordanian EFL Students' Writing Proficiency

This quantitative research examines Grammarly's impact on 60 Jordanian EFL students' writing. 60 students are enough to derive statistically significant conclusions about Grammarly's effects on writing. An experimental group of 30 students uses Grammarly while writing, whereas a control group of 30 students does not. Both groups write the identical assignments and are assessed using specified criteria. A pre-test compares both groups' grammatical correctness, vocabulary, and writing quality. After the pre-test, the experimental group uses Grammarly, while the control group does not. Students' writing skills are retested following the intervention. Grammarly's impact on EFL Jordanian students' writing is quantified by analyzing pre- and post-test results. T-tests or ANOVA are used to compare experimental and control group mean scores. Grammar, vocabulary, and writing quality are compared between the two groups. This study adds to the quantitative research on EFL online grammar correction tools. Grammarly's effects on EFL Jordanian students' writing abilities would assist educators and practitioners to decide whether to use such technologies in language training.

PyHySCO: GPU-enabled susceptibility artifact distortion correction in seconds.

Over the past decade, reversed gradient polarity (RGP) methods have become a popular approach for correcting susceptibility artifacts in echo-planar imaging (EPI). Although several post-processing tools for RGP are available, their implementations do not fully leverage recent hardware, algorithmic, and computational advances, leading to correction times of several minutes per image volume. To enable 3D RGP correction in seconds, we introduce PyTorch Hyperelastic Susceptibility Correction (PyHySCO), a user-friendly EPI distortion correction tool implemented in PyTorch that enables multi-threading and efficient use of graphics processing units (GPUs). PyHySCO uses a time-tested physical distortion model and mathematical formulation and is, therefore, reliable without training. An algorithmic improvement in PyHySCO is its use of the one-dimensional distortion correction method by Chang and Fitzpatrick to initialize the non-linear optimization. PyHySCO is published under the GNU public license and can be used from the command line or its Python interface. Our extensive numerical validation using 3T and 7T data from the Human Connectome Project suggests that PyHySCO can achieve accuracy comparable to that of leading RGP tools at a fraction of the cost. We also validate the new initialization scheme, compare different optimization algorithms, and test the algorithm on different hardware and arithmetic precisions.

Forensic DNA phenotyping using Oxford Nanopore Sequencing system.

In forensic science, the demand for precision, consistency, and cost-effectiveness has driven the exploration of next-generation sequencing technologies. This study investigates the potential of Oxford Nanopore Sequencing (ONT) Technology for analyzing the HIrisPlex-S panel, a set of 41 single nucleotide polymorphism (SNP) markers used to predict eye, hair, and skin color. Using ONT sequencing, we assessed the accuracy and reliability of ONT-generated data by comparing it with conventional capillary electrophoresis (CE) in 18 samples. The Guppy v6.1 was used as a basecaller, and sample profiles were obtained using Burrows-Wheeler Aligner, Samtools, BCFtools, and Python. Comparing accuracy with CE, we found that 62% of SNPs in ONT-unligated samples were correctly genotyped, with 36% showing allele dropout, and 2% being incorrectly genotyped. In the ONT-ligated samples, 85% of SNPs were correctly genotyped, with 10% showing allele dropout, and 5% being incorrectly genotyped. Our findings indicate that ONT, particularly when combined with ligation, enhances genotyping accuracy and coverage, thereby reducing allele dropouts. However, challenges associated with the technology's error rates and the impact on genotyping accuracy are recognized. Phenotype predictions based on ONT data demonstrate varying degrees of success, with the technology showing high accuracy in several cases. Although ONT technology holds promise in forensic genetics, further optimization and quality control measures are essential to harness its full potential. This study contributes to the ongoing efforts to refine sequence read tuning and improve correction tools in the context of ONT technology's application in forensic genetics.