Information Tools Research Articles

Identifying healthcare transmission routes of nontuberculous mycobacteria with whole genome sequencing: a systematic review.

To enumerate and describe the effect of whole genome sequencing (WGS) on epidemiological investigations of healthcare-associated transmission of nontuberculous mycobacteria (NTM). Systematic review. We performed a literature search using targeted search terms to identify articles meeting inclusion criteria. Data extraction of study characteristics and outcomes was performed by two independent researchers. The primary outcome was the author interpretation of WGS utility in the investigation of suspected healthcare-associated transmission of NTM. The secondary outcome was whether a transmission route was identified through WGS. Thirty-one studies were included in the final analysis with 28 (90%) concluding that WGS was helpful in transmission investigations and in 19 of these 28 (68%) WGS aided in identifying a transmission route. The most common identified transmission routes were water-borne point sources (10), heater-cooler units (6), patient-to-patient (4), and a healthcare worker (1). WGS is an informative tool in investigating healthcare transmission of NTM.

3D Nonequilibrium Ionization and Spectroscopic Modeling of Coronal Mass Ejections. I. Comparison with Hinode/EIS Observations

Abstract High-resolution EUV spectroscopy provides an informative diagnostic tool for the early evolution of coronal mass ejections (CMEs) since it can directly measure many physical properties of CME plasma close to the Sun that cannot be determined from white-light coronagraphs or narrowband imagers. The Hinode/EUV Imaging Spectrometer (EIS) captured a series of high-resolution EUV spectra of the 2008 April 9 event, also known as the “Cartwheel CME,” during its initial acceleration period. CMEs are inherently dynamic events, driving the plasma from ionization equilibrium, which makes the nonequilibrium ionization (NEI) effects important when analyzing spectral observations. In this work, we performed simulations of the Cartwheel CME using the Alfvén Wave Solar atmosphere Model (AWSoM) to provide insight into the plasma structure and dynamics during the early evolution of this CME. For the first time, we combined self-consistent nonequilibrium charge state calculations in the EUV spectral line synthesis for a CME simulation to account for the plasma departures from ionization equilibrium everywhere in the CME. In this first paper of the series, we compare the simulation results to the EIS observations of this event to assess the quality of the AWSoM predictions. We find that the CME is out of equilibrium, indicating that NEI effects should be considered in the EUV spectral synthesis. Overall, the model reproduces the thermodynamic evolution of the CME in the low solar corona well, as compared to the EIS observations.

Sustainability Nexus AID: soil health

The Sustainability Nexus Analytics, Informatics, and Data (AID) Programme of the United Nations University (UNU), aims to provide information, data, computational, and analytical tools to support the sustainable management and long-term security of natural resources using a nexus approach. This paper introduces the Soil Health Module of the Sustainability Nexus AID Programme. Healthy soil is crucial for life on Earth, and it is essential for ecosystem services and functioning, access to clean water, socioeconomic structure, biodiversity, and food security for the growing population of the world. Healthy soils contribute to mitigating the effects of climate change and reduce the consequences of extreme events such as flooding and drought. Healthy soils influence the hydrologic cycle by regulating transpiration, water infiltration, and soil water evaporation affecting land–atmosphere interactions. The Soil Health Module of the UNU Sustainability Nexus AID Programme aims to evolve into the ultimate focal point, supporting a diverse array of stakeholders with state-of-the-art data and tools that are essential for soil health monitoring and projection. This paper discusses the importance of adopting a nexus approach for ensuring soil health, explores the AID tools currently at our disposal for quantifying and predicting soil health, and concludes with recommendations for future effort and direction within the Sustainability Nexus AID Programme concerning soil health.

Development and evaluation of a decision aid for HPV vaccination among adults aged 27-45 years old in the United States.

To design, develop, and field test the HPV Decide decision tool to facilitate shared clinical decision-making recommendation for mid-adult HPV vaccination. The 'HPV Decide' online tool was developed through a 6-step process, involving community and provider advisory boards, usability testing with 10 end users (unvaccinated adults aged 27-45), field testing interviews with another 10, and interviews with 18 healthcare providers. The process incorporated both inductive and deductive qualitative data analyses. The logic model, based on the Ottawa Decision Support Framework, highlighted the importance of objective knowledge and managing decisional conflict. Iterative modifications were informed by the advisory boards, alpha testing, and usability testing. Field testing showed utility to end users, highlighting the straightforward design, and lack of medical jargon. Many expressed a desire to access the tool before doctor appointments, emphasizing its value in a healthcare context and in partnership with providers. Lastly, healthcare provider feedback highlighted information quality, structure, acceptability, and future implementation. While users recognized the tool's information quality and user-centric design, full evaluation focused on changes in informed decision making and clinic-based implementation are needed. The HPV Decide decision tool demonstrates promise in supporting informed decisions about HPV vaccination among mid-adults.

Analysis of Company Policies and Strategies Based on Identification of The Contribution Technology Needs in MSMEs Leather Processing Industry

<p class="Abstract"><strong>Technology is crucial to the success of any company, especially for Micro, Small and Medium Enterprises (MSME). MSMEs XYZ is a small and medium industry in Bandung that processes leather into bags. As a result, it is vital to boost technology by conducting a technology management analysis on these SMEs in order to maintain quality products and compete with the competition. This research aims to use the technology assessment analysis based on Technometrics models as a foundation for evaluating strengths and weaknesses linked to products and processes in MSMEs XYZ in order to get alternative strategies and policies. The measured technology components include technoware (production equipment), humanware (human resource capabilities), infoware (information tools), and orgaware are the measured technological components (organizational tools). The component contribution values for technoware (0,223), humanware (0,688), infoware (0,156), and orgaware (0,311). The Technologies Contribution value received (0,279) is a type of traditional technology with a low classification level. Recommendation for this research is acquisition within procurement of manufacturing machinery and equipment. In order to preserve company sustainability in terms of technology, MSMEs XYZ to raise investment, update products and manufacturing methods, and expand human resources.</strong><strong></strong></p><p class="Abstract"><strong><em><span lang="EN-GB">Keywords</span></em></strong><em><span lang="EN-GB">: MSME, Production, Technometrics Model.</span></em></p>

P-34. Patients’ Survey of Human Papilloma Virus Vaccination among Systemic Lupus Erythematosus Patients in Japan after Suspension of Proactive Recommendation

Abstract Background Systemic lupus erythematosus (SLE) patients are known to have a high incidence of cervical cancer. The main reason for this is considered to reflect the high rate of Human papilloma virus (HPV) infection and inadequate HPV clearance due to immunosuppressive status. Japan has been facing a problem of low HPV vaccination rates due to the suspension of proactive recommendations for routine HPV vaccination for more than eight years because of the negative media campaign. The objective of this study is to identify the factors that inhibit HPV vaccination among SLE patients to develop strategies for improving HPV vaccination rate. Figure Sources of medical information for HPV vaccinated and unvaccinated participants. We asked which informational tools participants use to gather medical information. The most trusted sources are indicated by dark bars; others are indicated by light bars. * indicates significant differences between HPV vaccinated and unvaccinated participants (p<0.05, chi-square test). (a): Answers by HPV vaccinated participants. (b): Answers by HPV unvaccinated participants. HPV, Human papilloma virus; SNS, Social networking service; TV, Television Methods We conducted a questionnaire survey of female SLE patients aged 18-45 years attending our hospital to analyze factors related to HPV vaccination. Results We obtained responses of 83 participants. Only 5 (6.0%) were received HPV vaccination, 15 (18.1%) were uncertain of their vaccine history, and 27 (32.5%) had never even heard of HPV vaccination. The reasons for unvaccinated against HPV were "don't know" with 24 participants, "missed opportunity" with 15, and "troublesome, somehow" with 8. The most trusted source of medical information for the unvaccinated was their physician (47, 60.3%) (Figure). Among the unvaccinated, those who wished to be vaccinated in the future were positively correlated with “trust of vaccine benefit” (r=0.515. p=0.014) and “accurate knowledge about HPV vaccine” (r=0.614, p=0.002), and negatively correlated with “negative attitudes toward vaccination and vaccine policy” (r=-0.562, p=0.007). Conclusion HPV vaccination rate among SLE patients in Japan was extremely low. The main reason was lack of knowledge. The most effective solution is considered to provide accurate information and adequate recommendations of HPV vaccination by attending physicians. Disclosures Yoshiaki Gu, MD, PhD, MPH, MSD K.K.: Grant/Research Support

Harmonizing population health data into OMOP common data model: a demonstration using COVID-19 sero-surveillance data from Nairobi Urban Health and Demographic Surveillance System

BackgroundObservational health data are collected in different formats and structures, making it challenging to analyze with common tools. The Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM) is a standardized data model that can harmonize observational health data.ObjectiveThis paper demonstrates the use of the OMOP CDM to harmonize COVID-19 sero-surveillance data from the Nairobi Urban Health and Demographic Surveillance System (HDSS).MethodsIn this study, we extracted data from the Nairobi Urban HDSS COVID-19 sero-surveillance database and mapped it to the OMOP CDM. We used open-source Observational Health Data Sciences and Informatics (OHDSI) tools like WhiteRabbit, RabbitInAHat, and USAGI. The steps included data profiling (scanning), mapping the vocabularies using the offline USAGI and online ATHENA, and designing the extract, transform, and load (ETL) process using RabbitInAHat. The ETL process was implemented using Pentaho Data Integration community edition software and structured query language (SQL). The target OMOP CDM can now be used to analyze the prevalence of COVID-19 antibodies in the Nairobi Urban HDSS population.ResultsWe successfully mapped the Nairobi Urban HDSS COVID-19 sero-surveillance data to the OMOP CDM. The standardized dataset included information on demographics, COVID-19 symptoms, vaccination, and COVID-19 antibody test results.ConclusionsThe OMOP CDM is a valuable tool for harmonizing observational health data. Using the OMOP CDM facilitates the sharing and analysis of observational health data, leading to a better understanding of disease conditions and trends and improving evidence-based population health strategies.

Uncertainty quantification in multi-parametric MRI-based meningioma radiotherapy target segmentation

PurposeThis work investigates the use of a spherical projection-based U-Net (SPU-Net) segmentation model to improve meningioma segmentation performance and allow for uncertainty quantification.MethodsA total of 76 supratentorial meningioma patients treated with radiotherapy were studied. Gross tumor volumes (GTVs) were contoured by a single experienced radiation oncologist on high-resolution contrast-enhanced T1 MRI scans (T1ce), and both T1 and T1ce images were utilized for segmentation. SPU-Net, an adaptation of U-Net incorporating spherical image projection to map 2D images onto a spherical surface, was proposed. As an equivalence of a nonlinear image transform, projections enhance locoregional details while maintaining the global field of view. By employing multiple projection centers, SPU-Net generates various GTV segmentation predictions, the variance indicating the model’s uncertainty. This uncertainty is quantified on a pixel-wise basis using entropy calculations and aggregated through Otsu’s method for a final segmentation.Results/conclusionThe SPU-Net model poses an advantage over traditional U-Net models by providing a quantitative method of displaying segmentation uncertainty. Regarding segmentation performance, SPU-Net demonstrated comparable results to a traditional U-Net in sensitivity (0.758 vs. 0.746), Dice similarity coefficient (0.760 vs. 0.742), reduced mean Hausdorff distance (mHD) (0.612 cm vs 0.744 cm), and reduced 95% Hausdorff distance (HD95) (2.682 cm vs 2.912 cm). SPU-Net not only is comparable to U-Net in segmentation performance but also offers a significant advantage by providing uncertainty quantification. The added SPU-Net uncertainty mapping revealed low uncertainty in accurate segments (e.g., within GTV or healthy tissue) and higher uncertainty in problematic areas (e.g., GTV boundaries, dural tail), providing valuable insights for potential manual corrections. This advancement is particularly valuable given the complex extra-axial nature of meningiomas and involvement with dural tissue. The capability to quantify uncertainty makes SPU-Net a more advanced and informative tool for segmentation, without sacrificing performance.

How Can States Regulate De-Spatialized Phenomena? The Case of Occupational Licensing

The Covid-19 pandemic compelled U.S. states to forge their own paths to guide their citizens through new dangers and challenges, yet made clear that state borders cannot hold against pathogens, people, or technology. How can states regulate increasingly de-spatialized phenomena? State legislators and regulators face this dilemma in the case of occupational licensing. This paper identifies a spatial mismatch between the individual state jurisdiction of occupational licensing regulations and the interstate reach of services provision by practitioners of licensed occupations. It investigates the origins of this mismatch, as well as a functional mismatch between state occupational licensing regimes established before 1900 and the current context. By building on insights from historical analysis of legacy state occupational licensing regimes; learning from examples of regulation of de-spatialized and digitalized economic activity; enlisting historical institutionalist-defined modes of gradual institutional change; and updating a classic typology of policy tools for regulation, a risk-based classification template for state regulation of services provided by professionals and skilled workers in currently licensed occupations is proposed. More broadly, analysis of the case of occupational licensing illustrates the potential of diversifying regulation of de-spatialized phenomena from authoritative mandates to regulatory programs comprised of a policy mix of mandate, information, incentive, and multi-mechanism tools better suited to porous political borders.

P0361 Clinical outcomes of acute severe colitis in Latin American: a case series

Abstract Background Acute severe ulcerative colitis (ASUC) is a potentially life-threatening complication of ulcerative colitis (UC), affecting up to 25% of patients throughout the course of the disease. Although it typically presents as an acute exacerbation of a chronic condition, ASUC can also be the initial manifestation of UC in up to one-third of patients. It is regarded as a clinical emergency, and in some cases, a surgical emergency due to the high risk of progression to colectomy. Optimal management of ASUC requires hospitalization and the involvement of a multidisciplinary team. Methods Medical records were queried using informatics tool to identify patients with ICD-9/10 code for CD and clinical terms associated with ASUC and UC between January 2014 and January 2024. Data on demographics, IBD phenotype, clinical and endoscopic activity, medical treatment and surgical procedures were obtained. The diagnosis of ASUC was established according to the Truelove and Witts criteria. Results A total of 41 patients with UC developed ASUC. According to the Montreal classification, 19 (61%) patients had pancolitis and 20 (60%) of them were diagnosed between 17 and 40 years old. In the studied case series, 26 (63.4%) were female and 26 (66.7%) were non-smokers. Additionally, more than half of the patients (58.3%) presented with extraintestinal manifestations. During the course of ASUC, nearly all patients received corticosteroid therapy (91,7%), 14(41%) required rescue therapy and 17 (41.5%) patients underwent colectomy. In this cohort, over 70% of patients experienced surgical complications and 11 (29.7%) were admitted to the intensive care unit. Lower hemoglobin levels at admission were identified as an independent risk factor for ICU admission, with each 1 g/dL increase reducing the risk by 53% (p < 0.05). Eleven patients (26.8%) required hospital readmission due to a recurrence of ASUC, none of whom had undergone colectomy during the prior hospitalization (p < 0.05). Conclusion Our findings indicate a high burden of ASUC in Latin America. Despite medical management, a significant proportion of patients required rescue therapy or surgical intervention, with a notable incidence of postoperative complications and ICU admissions. The high readmission rate highlights the need for improved long-term management strategies to reduce recurrence and enhance patient outcomes.

Exploring the performance of large language models on hepatitis B infection-related questions: A comparative study.

Patients with hepatitis B virus (HBV) infection require chronic and personalized care to improve outcomes. Large language models (LLMs) can potentially provide medical information for patients. To examine the performance of three LLMs, ChatGPT-3.5, ChatGPT-4.0, and Google Gemini, in answering HBV-related questions. LLMs' responses to HBV-related questions were independently graded by two medical professionals using a four-point accuracy scale, and disagreements were resolved by a third reviewer. Each question was run three times using three LLMs. Readability was assessed via the Gunning Fog index and Flesch-Kincaid grade level. Overall, all three LLM chatbots achieved high average accuracy scores for subjective questions (ChatGPT-3.5: 3.50; ChatGPT-4.0: 3.69; Google Gemini: 3.53, out of a maximum score of 4). With respect to objective questions, ChatGPT-4.0 achieved an 80.8% accuracy rate, compared with 62.9% for ChatGPT-3.5 and 73.1% for Google Gemini. Across the six domains, ChatGPT-4.0 performed better in terms of diagnosis, whereas Google Gemini demonstrated excellent clinical manifestations. Notably, in the readability analysis, the mean Gunning Fog index and Flesch-Kincaid grade level scores of the three LLM chatbots were significantly higher than the standard level eight, far exceeding the reading level of the normal population. Our results highlight the potential of LLMs, especially ChatGPT-4.0, for delivering responses to HBV-related questions. LLMs may be an adjunctive informational tool for patients and physicians to improve outcomes. Nevertheless, current LLMs should not replace personalized treatment recommendations from physicians in the management of HBV infection.

The impact of parameter variation in the quantification of forensic genetic evidence

Technological advancements have allowed the detection of increasingly complex forensic genetics samples, as minimum amounts of DNA can now be detected in crime scenes or other settings of interest. The weight of the evidence depends on several parameters regarding the population and sample-related analytical factors, the latter in a greater number when the DNA amount is considered. This led to the development of probabilistic genotyping software (PGS), able to deal with the associated complexities. This study aims to evaluate the impact on the evidence’s weighing, when different analytical threshold values are used, and when different models and/or estimates for analytical artifacts, such as stutters or drop-in parameters, are considered. To reach this goal, three PGS, based on different statistical models, were used to analyze real casework pairs of samples composed of a mixture with either two or three estimated contributors, and a single-source sample associated. The obtained results show that the estimation of these parameters must not be overlooked, as they may considerably impact the outcome. This underlines the importance of proper parametrization in the analysis of forensic genetics identification problems when using complex samples, and the understanding by practitioners of how probabilistic genotyping informatics tools work to use them accurately.

A novel framework unveiling the importance of heterogeneous selection and drift on the community structure of symbiotic microbial indicator taxa across altitudinal gradients in amphibians.

Distinguishing the drivers regulating microbial community assembly is essential in microbial ecology. We propose a novel modeling framework to partition the relative contributions of each individual or group of microbial DSUs and DTUs into different underpinning mechanisms. An empirical study on amphibian symbiotic microbes notably enlarges insight into community assembly patterns in the herpetological symbiotic ecosystem and demonstrates that the proposed statistical framework is an informative and sturdy tool to quantify microbial assembly processes at both levels of DSUs and DTUs. More importantly, our proposed modeling framework can provide in-depth insights into microbiota community assembly within the intricate tripartite host-environment-microbe relationship.

Utilizing innovative two curves in nomogram.

Nomograms are valuable tools in clinical research for predicting patient outcomes. Understanding threshold values within these models is crucial for assessing the model's effectiveness and practical application in clinical environments. We developed two novel interpretive curves to enhance the utility of nomograms. These curves were designed to provide clear visualization of how clinical prediction models perform across various thresholds. The curves are applied to two case studies to demonstrate their practical application and efficacy. In both examples, the novel curves successfully highlighted critical threshold values and revealed changes in prediction accuracy across these thresholds. This enhanced the understanding of the nomogram's performance, providing clinicians with more informative decision-making tools. The introduction of these interpretive curves allows for a more nuanced understanding of nomogram-based predictions, offering insights into threshold effects that can inform clinical decisions.

Insights from social media into public perspectives on investigative genetic genealogy.

Social media sites like X (formerly Twitter) increasingly serve as spaces for the public to discuss controversial topics. Social media can spark extreme viewpoints and spread biased or inaccurate information while simultaneously allowing for debate around policy-relevant topics. The arrest of Joseph J. DeAngelo in April 2018 ignited a barrage of social media conversations on how DNA and genetic genealogy led to the suspect. These conversations continued over the following years as policies changed and as the use of the approach expanded. We examined social media coverage of investigative genetic genealogy (IGG) to characterize the volume and temporal patterns in the topics and sentiments of these public conversations. First, using a data analytics tool Brandwatch Consumer Research, we built flexible search strings to collect tweets from the social media platform Twitter/X for IGG-relevant content published from 2018 to 2022, resulting in 24,209 tweets. Second, we applied informatics tools to the dataset to generate topic clusters and analyze trends in cluster volume and distribution over time to define the top 25 peaks in tweet volume, representing the 25 events that generated the highest volume of conversation over the 5-year period. Third, drawing on the contextual framework of key IGG events, we selected three of the top ten events to code for sentiment along with a randomly sampled subset of tweets across the timeframe. Qualitative coding for position on IGG revealed a majority of tweets were supportive of the use of IGG, but key concerns were also voiced about the ethics of IGG. Over a third of conversations on Twitter/X were on either cases solved or suggestions for use of IGG. We archived the social media data for future research. These data highlight key areas of public support and concern within IGG processes and across application contexts.

Assessing ChatGPT's Capability in Addressing Thyroid Cancer Patient Queries: A Comprehensive Mixed-Methods Evaluation.

Literature suggests patients with thyroid cancer have unmet informational needs in many aspects of care. Patients often turn to online resources for their health-related information, and generative artificial intelligence programs such as ChatGPT are an emerging and attractive resource for patients. To assess the quality of ChatGPT's responses to thyroid cancer-related questions. Four endocrinologists and 4 endocrine surgeons, all with expertise in thyroid cancer, evaluated the responses to 20 thyroid cancer-related questions. Responses were scored on a 7-point Likert scale in areas of accuracy, completeness, and overall satisfaction. Comments from the evaluators were aggregated and a qualitative analysis was performed. Overall, only 57%, 56%, and 52% of the responses "agreed" or "strongly agreed" that ChatGPT's answers were accurate, complete, and satisfactory, respectively. One hundred ninety-eight free-text comments were included in the qualitative analysis. The majority of comments were critical in nature. Several themes emerged, which included overemphasis of diet and iodine intake and its role in thyroid cancer, and incomplete or inaccurate information on risks of both thyroid surgery and radioactive iodine therapy. Our study suggests that ChatGPT is not accurate or reliable enough at this time for unsupervised use as a patient information tool for thyroid cancer.

Association Between Digital Front Doors and Social Care Use for Community-Dwelling Adults in England: Cross-Sectional Study.

Requests for public social care support can be made through an online portal. These digital "front doors" can help people navigate complex social care systems and access services. These systems can be set up in different ways, but there is little evidence about the impact of alternative arrangements. Digital front-door systems should help people better access services, particularly low-intensity services (high-intensity care is likely to require a full in-person assessment). This study aimed to investigate the association between 2 primary digital front door arrangements, easy-read information, and self-assessment tools provided on official websites, and the type of social care support that is offered: ongoing low-level support (OLLS), short-term care (STC) and long-term care (LTC). Information on front door arrangements was collected from the official websites of 152 English local authorities in 2021. We conducted a cross-sectional analysis using aggregated service use data from official government returns at the local authority level. The independent variables were derived from the policy information collected, specifically focusing on the availability of online digital easy-read information and self-assessment tools for adults and caregivers through official websites. The dependent variables were the rates of using social care support, including OLLS, STC, and LTC, across different age groups: the adult population (aged 18 and older), younger population (aged between 18 and 64 years), and older population (aged 65 and older). Multivariate regression analysis was used to examine the association between digital front door arrangements and access to social care support, controlling for population size, dependency level, and financial need factors. Less than 20% (27/147) of local authorities provided an integrated digital easy-read format as part of their digital front door system with about 25% (37/147) adopting digital self-assessment within their system. We found that local authorities that offered an integrated digital easy-read information format showed higher rates of using OLLS (β coefficient=0.54; P=.03; but no statistically significant association with LTC and STC). The provision of an online self-assessment system was not associated with service use in the 1-year (2021) cross-sectional estimate, but when 2 years (2020 and 2021) of service-use data were analyzed, a significant positive association was found on OLLS rates (β coefficient=0.41; P=.21). Notably, these findings were consistent across different age groups. These findings are consistent with our hypothesis that digital systems with built-in easy-read and self-assessment may make access to (low-intensity) services easier for people. Adoption of these arrangements could potentially help increase the uptake of support among those who are eligible, with expected benefits for their care-related well-being. Given the limited adoption of the digital front door by local authorities in England, expanding their use could improve care-related outcomes and save social care costs.

Ion mobility mass spectrometry unveils conformational effects of drug lead EPI-001 on the intrinsically disordered N-terminal domain of the androgen receptor.

Intrinsically disordered proteins (IDPs) are important drug targets as they are key actors within cell signaling networks. However, the conformational plasticity of IDPs renders them challenging to characterize, which is a bottleneck in developing small molecule drugs that bind to IDPs and modulate their behavior. In relation to this, ion mobility mass spectrometry (IM-MS) is a useful tool to investigate IDPs, as it can reveal their conformational preferences. It can also offer important insights in drug discovery, as it can measure binding stoichiometry and unveil conformational shifts of IDPs exerted by the binding of small drug-like molecules. Herein, we have used IM-MS to investigate the effect of drug lead EPI-001 on the disordered N-terminal domain of the androgen receptor (AR-NTD). Despite structural heterogeneity rendering the NTD a challenging region of the protein to drug, this domain harbors most, if not all, of the transcriptional activity. We quantify the stoichiometry of EPI-001 binding to various constructs corresponding to functional domains of AR-NTD and show that it binds to separate constructs containing transactivation unit (TAU)-1 and TAU-5, respectively, and that 1-2 molecules bind to a larger construct containing both sequences. We also identify a conformational shift upon EPI-001 binding to the TAU-5, and to a much lesser extent with TAU-1 containing constructs. This work provides novel insight on the interactions of EPI-001 with the AR-NTD, and the structural alterations that it exerts, and positions IM-MS as an informative tool that will enhance the tractability of IDPs, potentially leading to better therapies.

Transforming English Language Education through Neuro-Linguistic Programming and Graphic Novels

As observed in the modern post-industrial world, the enshrinement of items of innovation in training is crucial in handling developments in the different sectors. Thus, this paper aims to analyse the introduction of Neuro Linguistic Programming and Language (NLP), the use of Graphic novels in teaching English, and the progressive integration of a bi-disciplinary approach in particular. This research offers a practical framework for educational practices and future research in the field by exploring the related literature in expressing the theoretical background of NLP, the educational value of graphic novels, and the approaches to teaching English efficiently. Since the method concentrates on such language characteristics as cognitive patterns and interacting communication strategies, NLP provides language learners with the opportunities to enhance their language learning much more effectively, considering the development of their affective learning aspects. Through disseminating Graphic novels as informative and creative tools, complex language concepts can be introduced effectively and attractively to the students. These approaches benefit second language learners, especially in academic vocabulary learning, by increasing constructive and contextual knowledge acquisition instead of mainly associative and repetitive learning. Through a mixed-methods approach involving quantitative assessments and qualitative case studies, this study evaluates the effectiveness of integrating NLP techniques and graphic novels in English language education. These findings assert the efficiency of the combined approaches, explaining the outcome definition of the changes in aspects such as students’ attendance, understanding, and knowledge retention. Whereas, according to the study, concerning students’ introduction to such methods, there was a rise in motivational levels and a decrease in language anxiety and usage errors. Teachers were able to notice augmented lesson engagement and amended discussions among students. It will be advantageous to educational management, information technology, sciences, and social sciences to justify the prospective of these innovative methodologies in mannering the developments in language education. These guidelines include the steps for using NLP and graphic novels in language curricula, as well as suggestions for further education for teachers and vast research on the long-term impact of the approaches in question on various learning environments and learners of different ages.

Exploring Jordanian university lecturers’ TPACK knowledge: Integrating ICT for teaching English pronunciation

This study investigates the technological knowledge (TK) of university lecturers in Jordan concerning the integration of information and communications technology (ICT) tools in teaching English pronunciation. Employing a mixed-methods approach, data were collected through questionnaires and semi-structured interviews to evaluate lecturers’ understanding and use of ICT for pronunciation instruction. The findings indicate moderate competence in technology integration, with nearly half of the participants feeling confident in using ICT for pronunciation teaching. However, a significant percentage reported insufficient knowledge, especially in selecting effective tools. Analysis revealed no statistically significant differences in TK based on gender or teaching experience, suggesting these factors do not influence technological competence. Challenges included limited access to specialized pronunciation software and a reliance on basic tools like PowerPoint and interactive whiteboards. Thematic analysis of interview data highlighted obstacles such as a lack of ICT training, unfamiliarity with pronunciation-specific tools, and difficulties in evaluating tool effectiveness. Many lecturers expressed a need for advanced resources and training, while others relied on peer support to address gaps. This study emphasizes the necessity for enhanced resources and targeted training initiatives to improve ICT integration in pronunciation teaching. Future research should explore strategies to strengthen lecturers’ TK, particularly regarding ICT’s role in higher education contexts.