Consistent Improvement Research Articles

IMPROVEMENT IN LV END-DIASTOLIC PRESSURE AFTER PRIMARY PCI AND ITS IMPACT ON PATIENTS’ RECOVERY

Left ventricular end-diastolic pressure (LVEDP) is a crucial indicator of cardiac function, particularly in patients with acute ST-segment elevation myocardial infarction (STEMI). Primary percutaneous coronary intervention (PCI) is the standard of care for STEMI, but its impact on LVEDP and patient recovery remains to be thoroughly studied. Objective: This study aimed to evaluate the improvement in LVEDP following primary PCI in patients with acute STEMI and to assess its impact on recovery and clinical outcomes. Methods: This prospective study included 100 patients with acute STEMI treated by primary PCI. LVEDP was recorded at four-time points: before PCI, and at one week, one month, and three months post-PCI. Demographic and clinical characteristics were also collected. Statistical analysis was performed to compare LVEDP values at different time intervals using paired t-tests and repeated measures ANOVA to assess significant changes over time. Results: The mean LVEDP significantly decreased from 18 ± 4 mmHg before PCI to 12 ± 3 mmHg at one week, 10 ± 2 mmHg at one month, and 9 ± 2 mmHg at three months post-PCI (p < 0.001). This demonstrated a consistent improvement in left ventricular function and hemodynamic status, suggesting favorable patient recovery post-intervention. Conclusion: Primary PCI significantly reduces LVEDP in patients with acute STEMI, leading to improved cardiac function and patient recovery. Monitoring LVEDP post-PCI can serve as a valuable predictor of patient prognosis and long-term outcomes. Further studies are warranted to explore additional therapies that may further enhance recovery and improve the quality of life in STEMI patients.

Novel hybrid arithmetic-equilibrium optimizer as robust tuner for power system stabilizer (PSS) parameters in interconnected electrical power system

Nowadays, the metaheuristic approaches become popular in the optimal tuning parameters of power system controllers, especially Power System Stabilizers (PSS). Besides the easiness, the stochastic behavior in metaheuristic approaches needs further investigation to increase the quality of the offered optimal parameters. Thus, this paper proposes A Novel Hybrid Arithmetic-Equilibrium Optimizer (HAEO) as a robust tuner for PSS in the interconnected electrical power system. The algorithms are hybridized in unique ways to utilize the features in both Arithmetic Optimizer (AO) and Equilibrium Optimizer (EO). Hybridization is performed to improve the exploration ability by providing the widest optimal parameters possible. In benchmarking by the Friedman Ranking Test, the proposed algorithm shows a significant improvement in consistency and accuracy over the basic AO and EO. A wider-distributed optimal solution and better convergence are also offered by the proposed algorithm. Besides that, the application in the optimal tuning shows that the proposed algorithm can provide the best PSS parameters in different objective functions with better average and standard deviation values. The HAEO-PSS gives a significant overshoot suppression of 35 % to 57 %, while the settling time of the system is also improved by 7 % to 13 %. Overall, the HAEO-PSS is proven to improve the stability response of the interconnected electrical power system both in local and interarea responses.

Enhanced gastric cancer classification and quantification interpretable framework using digital histopathology images

Recent developments have highlighted the critical role that computer-aided diagnosis (CAD) systems play in analyzing whole-slide digital histopathology images for detecting gastric cancer (GC). We present a novel framework for gastric histology classification and segmentation (GHCS) that offers modest yet meaningful improvements over existing CAD models for GC classification and segmentation. Our methodology achieves marginal improvements over conventional deep learning (DL) and machine learning (ML) models by adaptively focusing on pertinent characteristics of images. This contributes significantly to our study, highlighting that the proposed model, which performs well on normalized images, is robust in certain respects, particularly in handling variability and generalizing to different datasets. We anticipate that this robustness will lead to better results across various datasets. An expectation-maximizing Naïve Bayes classifier that uses an updated Gaussian Mixture Model is at the heart of the suggested GHCS framework. The effectiveness of our classifier is demonstrated by experimental validation on two publicly available datasets, which produced exceptional classification accuracies of 98.87% and 97.28% on validation sets and 98.47% and 97.31% on test sets. Our framework shows a slight but consistent improvement over previously existing techniques in gastric histopathology image classification tasks, as demonstrated by comparative analysis. This may be attributed to its ability to capture critical features of gastric histopathology images better. Furthermore, using an improved Fuzzy c-means method, our study produces good results in GC histopathology picture segmentation, outperforming state-of-the-art segmentation models with a Dice coefficient of 65.21% and a Jaccard index of 60.24%. The model’s interpretability is complemented by Grad-CAM visualizations, which help understand the decision-making process and increase the model’s trustworthiness for end-users, especially clinicians.

Enhancing chatbot performance for imaging recommendations: Leveraging GPT-4 and context-awareness for trustworthy clinical guidance

PurposeTo investigate if GPT-4 improves the accuracy, consistency, and trustworthiness of a context-aware chatbot to provide personalized imaging recommendations from American College of Radiology (ACR) appropriateness criteria documents using semantic similarity processing: In addition, we sought to enable auditability of the output by revealing the information source the decision relies on. Material and MethodsWe refined an existing chatbot that incorporated specialized knowledge of the ACR guidelines by upgrading GPT-3.5-Turbo to its successor GPT-4 by OpenAI, using the latest version of LlamaIndex, and improving the prompting strategy. This chatbot was compared to the previous version, generic GPT-3.5-Turbo and GPT-4, and general radiologists regarding the performance in applying the ACR appropriateness guidelines. ResultsThe refined context-aware chatbot performed superior to the previous version using GPT-3.5-Turbo, generic chatbots GPT-3.5-Turbo and GPT-4, and general radiologists in providing “usually or may be appropriate” recommendations according to the ACR guidelines (all p < 0.001). It also outperformed GPT-3.5-Turbo and general radiologists in respect to “usually appropriate” recommendations (both p < 0.001). Moreover, the consistency in correct answers was higher with 78 % consistent correct “usually appropriate” answers and 94 % for “usually or may be appropriate” recommendations. In all cases, the same source documents were chosen, ensuring transparency. ConclusionOur study demonstrates the significance of context awareness in ensuring the use of appropriate knowledge and proposes a strategy to enhance trust in chatbot-based outputs to provide transparency. The improvements in accuracy, consistency, and source transparency address trust issues and enhance the clinical decision support process.Abbreviations: ACR, American College of Radiology; accGPT, appropriateness criteria context aware GPT; accGPT-4, appropriateness criteria context aware GPT using GPT-4; GPT, generative pre-trained transformer; LLM, Large Language Model.

Randomised Controlled Trial for the Evaluation of the Efficacy of the IDA's "Living Well" Online Counselling Tool in First-Time Adult Users with Hearing Loss.

Effective management of hearing loss through the use of modern hearing aids significantly improves communication and the quality of life for individuals experiencing auditory impairment. Complementary counselling of patients with hearing loss who will be fitted with hearing aids for the first time should be evidence-based and adapted to their individual needs. To date, several counselling protocols and tools have been developed. The aim of this randomised controlled trial study was to investigate the efficacy of the application of the IDA's "Living Well" counselling tool in first-time hearing aid users in terms of the degree of their hearing related handicap (using the Hearing Handicap Inventory (HHI)), their communication coping strategies (using the Communication Profile for the Hearing Impaired (CPHI)) and their overall satisfaction of the hearing aids (using a Likert scale). Both groups (the IDA and the control group) were fitted with hearing aids and received counselling for their hearing aids by the same audiologist. The IDA group attended an additional counselling session about communication coping strategies with the use of the "Living Well" tool. Both groups' participants were seen for their hearing aid fittings 4-6 weeks, 3 and 6 months after their fitting when the HHI and the CPHI were measured. Although there was not a statistically significant difference between the two groups for the primary and secondary outcomes, the IDA group did show a more consistent improvement of their HHI score and less frequent use of maladaptive strategies. The "Living Well" counselling tool proved to be a favourably received and helpful counselling tool in first-time hearing aid users.

How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?

Abstract Large language models have been shown to behave inconsistently in response to meaning-preserving paraphrastic inputs. At the same time, researchers evaluate the knowledge and reasoning abilities of these models with test evaluations that do not disaggregate the effect of paraphrastic variability on performance. We propose a metric, PC, for evaluating the paraphrastic consistency of natural language reasoning models based on the probability of a model achieving the same correctness on two paraphrases of the same problem. We mathematically connect this metric to the proportion of a model’s variance in correctness attributable to paraphrasing. To estimate PC, we collect ParaNlu, a dataset of 7,782 human-written and validated paraphrased reasoning problems constructed on top of existing benchmark datasets for defeasible and abductive natural language inference.1 Using ParaNlu, we measure the paraphrastic consistency of several model classes and show that consistency dramatically increases with pretraining but not fine-tuning. All models tested exhibited room for improvement in paraphrastic consistency.

TBConvL-Net: A hybrid deep learning architecture for robust medical image segmentation

Deep learning has shown great potential for automated medical image segmentation to improve the precision and speed of disease diagnostics. However, the task presents significant difficulties due to variations in the scale, shape, texture, and contrast of the pathologies. Traditional convolutional neural network (CNN) models have certain limitations when it comes to effectively modelling multiscale context information and facilitating information interaction between skip connections across levels. To overcome these limitations, a novel deep learning architecture is introduced for medical image segmentation, which takes advantage of CNNs and vision transformers. Our proposed model, named TBConvL-Net, involves a hybrid network that combines the local features of a CNN encoder–decoder architecture with long-range and temporal dependencies using biconvolutional long-short-term memory (LSTM) networks and vision transformers (ViT). This enables the model to capture contextual channel relationships in the data and account for the uncertainty of the segmentation over time. Additionally, we introduce a novel composite loss function that considers both segmentation robustness and boundary agreement of the predicted output with the gold standard. Our proposed model shows consistent improvement over the state of the art on ten publicly available datasets of seven different medical imaging modalities.

Real-world Effectiveness of Sarilumab in RA: Results from the Open-label, Prospective, Single-arm Observational PROFILE Study.

The 1-year PROspective sarilumab (preFILled syringe/pen) multinational, obsErvational (PROFILE) study evaluated the real-world effectiveness and safety of sarilumab in patients with moderate-to-severe rheumatoid arthritis (RA). Safety endpoints included adverse events (AEs) and lab abnormalities. Effectiveness endpoints included the ACR core set. The primary endpoint was the change from baseline in Clinical Disease Activity Index (CDAI). All statistics are descriptive and pvalues were nominal. In total, 595 patients were treated, of whom 223 (37.5%) received sarilumab monotherapy and 372 (62.5%) received combination therapy. Upon initiation of sarilumab, an improvement in the mean (SD) CDAI score was observed at week 24 [11.4 (10.3)] and was maintained through week 52 [10.0 (10.5)], resulting in a mean [SD] reduction of -14.9 (12.7) and -14.4 (12.9), respectively. There were consistent improvements in disease activity that were similar for patients on monotherapy vs. combination therapy. An increase in the proportion of patients achieving remission and low disease activity was reported. By week 52, both groups had improved physical function and quality of life. There were no new safety signals. The proportions of any patients reporting a treatment-emergent adverse event (TEAE) or serious treatment-emergent AE (SAE) was 66.2% and 5.9%, respectively, and were similar between both treatment groups. Overall, 15.6% of patients discontinued sarilumab treatment due to TEAEs. The most commonly reported TEAE of interest was neutropenia (14.1%). In this 1-year, observational real-world study, sarilumab therapy resulted in improved clinical outcomes. The safety profile was consistent with that observed in sarilumab randomized clinical trials. This study was entered on the German website (Paul Ehrlich Institute) on January 11, 2018, with NIS No.: 423.

EuMAR stakeholder engagement: an analysis of medically assisted reproduction (MAR) data collection practices in EU countries†.

What are the current national medically assisted reproduction (MAR) data collection systems across EU Member States, and how can these countries contribute to a unique, cycle-by-cycle registry for the European Monitoring of Medically Assisted Reproduction (EuMAR) project? The study identified significant variation in MAR data collection practices across Member States, with differences in data types, collection methods, and reporting requirements; the EuMAR project emerges as an opportunity to enhance data standardization and improve MAR data collection in the EU. There is a need for new approaches in MAR data collection that include long-term and cross border follow-up. The EuMAR project intends to establish a unified, cycle-by-cycle registry of data on MAR treatments in EU countries, from which accurate cumulative outcomes can be calculated. This cross-sectional study involved a survey and interviews with stakeholders from 26 EU Member States conducted in 2023 over a period of seven months. Representatives from national competent authorities and professional associations involved in MAR data collection in EU countries were invited to complete the survey and interviewed to assess current data flows, information requirements, and their interest in the EuMAR project. Half of the participating countries reported having a national MAR registry with cycle-by-cycle data (n = 13), while 31% reported having a national registry with aggregated data (n = 8) and 19% reported having no national registry (n = 5). Of the countries with a national cycle-by-cycle registry, eight countries collect identifiable data, five countries collect pseudonymized data, and one country collects fully anonymized data. Informed consent is required in 10 countries. The main advantages that participants expected from a European registry like EuMAR were the possibility of obtaining national statistics in the absence of a national registry and improving the calculation of cumulative outcomes. The results of the study are based on self-reported data, which may be subject to bias, however, the validity of the collected information was verified with different means, including follow-up calls for clarifications and sharing final transcript reports. The feasibility of the proposed data flow models will be tested in a pilot study. Despite the heterogeneity of data collection practices across EU countries, the results show that stakeholders have high expectations of the benefits that the EuMAR registry can bring, namely the improvement of data consistency, cross-border comparability, and cumulative live birth rates, leading to better information for patients, health care providers and policy makers. The EuMAR project was co-founded by ESHRE and the European Commission (101079865-EuMAR-EU4H-2021-PJ2). No competing interests were declared. N/A.

Assessing adequacy of surgical extent in CRSwNP: The Completion of Surgery Index.

Endoscopic sinus surgery (ESS) maximized for topical steroid irrigations is highly effective for polyp disease. As extent and completeness of ESS varies widely by situation and practitioner, it is important to understand when revision surgery is appropriate, particularly in the era of biologic treatments. A Completion of Surgery Index (CoSI) was developed to assess operative changes in polyp patients using pre- and postoperative computed tomography scans. The CoSI was then applied and tested in a cohort of consecutive chronic rhinosinusitis with nasal polyps (CRSwNP) patients, and examined within the context of quality-of-life improvements. The CoSI assesses surgical extent on a scale of 0-100, with 100 representing the highest possible degree of surgical completeness. Among 100 consecutive CRSwNP patients undergoing ESS in 2021 with postoperative topical steroid irrigations, including 75 revision surgeries, SNOT-22 scores improved at 6months postoperatively, with durable and consistent improvement at 24months (p<0.001). Preoperative CoSI scores in revision surgery patients were 49.4±26.0, improving to 91.0±8.1 postoperatively. SNOT-22 scores for primary ESS patients and patients with a preoperative CoSI score of less than 70 improved by 26.4 and 28.1 points, respectively, in contrast to patients with a preoperative CoSI of 70 or greater (14.1 points, p=0.029). It is important to define extent of surgery in CRSwNP to stratify postsurgical patients based on likelihood to benefit from revision surgery or alternative medications. The CoSI can be utilized to identify patients who are likely to improve significantly with revision surgical intervention.

Improving qualities of Kocho fermentation using Mandillo [Crassocephalum macropappum (Sch.Bip. ex. A.Rich.) S.Moore] as a starter culture ingredient

This study assessed the impact of adding Mandillo, an Ethiopian herbaceous plant, to the fermentation process of Kocho, a fermented food made from Enset plants. Mandillo has been traditionally used by the Shekacho people to enhance the quality and fermentation of Enset during Kocho production. Kocho samples were fermented with Mandillo stem (Kom) and without (Koki) for quality evaluation. Proximate composition, mineral content, water-holding capacity, phytic acid, tannin content, and sensory attributes were analyzed. Through comprehensive physicochemical and sensory analyses, we observed distinct improvements in Kocho quality. For Koki, the protein content increased from 5.1% to 6.0% with the use of LAB starter cultures, while Kom exhibited a 15% reduction in fermentation time (from 12 to 10 days). In terms of sensory evaluation, Koki had a 25% higher overall taste score compared to the control sample, whereas Kom demonstrated a 20% improvement in texture consistency. These findings indicate that tailored fermentation approaches can significantly enhance the nutritional and sensory qualities of both Koki and Kom. The results have important implications for improving and advancing traditional food fermentation practices in Ethiopia.

Analytics of feedback from members of accreditation subcommittees - participants in the «Accred-ROSOMED» study

The feedback data obtained in the process of questioning members of accreditation subcommittees is one of the significant components of the consistent improvement of the accreditation process. The article provides a comparison of data from the pilot and multicenter stages of the Accred-ROSOMED prospective study, dedicated to the analytics of a survey of members of accreditation subcommittees regarding the most important issues of the accreditation process in the 2022 and 2023. These studies emphasize the importance of the mentioned issues, forming the basis for subsequent research continuation in order to provide the most complete and detailed representation of the accreditation process in the regions of Russian Federation and compare it with international experience.

Effects of Supplementation with a Microalgae Extract from Phaeodactylum tricornutum Containing Fucoxanthin on Cognition and Markers of Health in Older Individuals with Perceptions of Cognitive Decline.

Forty-three males and females (64.3 ± 6.0 years, 79.8 ± 16.0 kg, 27.0 ± 4.0 kg/m2) with perceptions of cognitive and memory decline completed the double-blind, randomized, parallel-arm, placebo-controlled intervention clinical trial. Participants were counterbalanced by sex and BMI and randomly allocated to their respective 12-week supplementation interventions, which were either the placebo (PL) or 1100 mg/day of PT containing 8.8 mg of fucoxanthin (FX). Fasting blood samples were collected, and cognitive assessments were performed during the testing session at 0, 4, and 12 weeks of intervention. The data were analyzed by multivariate and univariate general linear model (GLM) analyses with repeated measures, pairwise comparisons, and mean changes from baseline analysis with 95% confidence intervals (CIs) to assess the clinical significance of the findings. FX supplementation significantly affected (p < 0.05) or exhibited tendencies toward significance (p > 0.05 to p < 0.10 with effect sizes ranging from medium to large) for word recall, picture recognition reaction time, Stroop color-word test, choice reaction time, and digit vigilance test variables. Additionally, FX supplementation promoted a more consistent clinical improvement from baseline values when examining mean changes with 95% CIs, although most differences were seen over time rather than between groups. The results demonstrate some evidence that FX supplementation can improve working and secondary memory, vigilance, attention, accuracy, and executive function. There was also evidence that FX promoted more positive effects on insulin sensitivity and perceptions about sleep quality with no negative effects on clinical blood panels or perceived side effects. Additional research should investigate how FX may affect cognition in individuals perceiving memory and cognitive decline. Registered clinical trial #NCT05759910.

Urban Flood Resilience Evaluation Based on Heterogeneous Data and Group Decision-Making.

In recent years, urban floods have occurred frequently in China. Therefore, there is an urgent need to strengthen urban flood resilience. This paper proposed a hybrid multi-criteria group decision-making method to assess urban flood resilience based on heterogeneous data, group decision-making methodologies, the pressure-state-response model, and social-economic-natural complex ecosystem theory (PSR-SENCE model). A qualitative and quantitative indicator system is formulated using the PSR-SENCE model. Additionally, a new weighting method for indicators, called the synthesis weighting-group analytic hierarchy process (SW-GAHP), is proposed by considering both intrapersonal consistency and interpersonal consistency of decision-makers. Furthermore, an extensional group decision-making technology (EGDMT) based on heterogeneous data is proposed to evaluate qualitative indicators. The flexible parameterized mapping function (FPMF) is introduced for the evaluation of quantitative indicators. The normal cloud model is employed to handle various uncertainties associated with heterogeneous data. The evaluations for Beijing from 2017 to 2021 reveal a consistent annual improvement in urban flood resilience, with a 14.1% increase. Subsequently, optimization recommendations are presented not only for favorable indicators such as regional economic status, drainability, and public transportation service capacity but also for unfavorable indicators like flood risk and population density. This provides a theoretical foundation and a guide for making decisions about the improvement of urban flood resilience. Finally, our proposed method shows superiority and robustness through comparative and sensitivity analyses.

Assessing the efficacy and safety of combined buspirone and venlafaxine treatment in late-life depression accompanied by cognitive impairment: A randomized controlled trial

BackgroundLate-life depression, often accompanied by cognitive impairment, poses significant clinical challenges owing to its complex etiology and diverse manifestations. While antidepressants like venlafaxine and anxiolytics such as buspirone are effective for treating depression, their effects on cognitive function remain less well-understood. With the aging population increasingly experiencing geriatric depression, there is an urgent need for innovative treatment approaches that address both depressive symptoms and cognitive impairments. ObjectiveThis study aimed to evaluate the clinical efficacy and safety of combined buspirone and venlafaxine therapy in elderly patients diagnosed with geriatric depression accompanied by cognitive impairment. MethodsA 12-week, randomized controlled trial was conducted involving 170 elderly patients. Participants were randomized into two groups: one receiving venlafaxine alone (control group) and the other receiving a combination of venlafaxine and buspirone (experimental group). The primary analysis was performed using an Intent-to-Treat (ITT) approach with mixed-effects linear models to assess changes in depressive symptoms, cognitive function, and anxiety levels. A supplementary Per-Protocol (PP) analysis, utilizing repeated measures ANOVA, was also conducted. ResultsThe ITT analysis showed that the combination therapy significantly reduced depressive symptoms, as indicated by the HAMD-17 scores (p = 0.033 at week 12). Cognitive function, as measured by MoCA scores, also improved significantly in the experimental group by week 12 (p = 0.025). However, no statistically significant differences were observed in anxiety reduction between the groups (p = 0.127). The PP analysis confirmed these findings, demonstrating consistent improvements in depressive symptoms and cognitive function, particularly in those who completed the full course of treatment. The incidence of adverse events was comparable between groups, primarily mild and manageable symptoms like dry mouth, dizziness, and fatigue. ConclusionThe combination of buspirone and venlafaxine was found to be effective in reducing depressive symptoms and enhancing cognitive function in elderly patients with geriatric depression. However, the long-term benefits, especially regarding anxiety reduction, require further investigation. Future studies should consider larger sample sizes, longer follow-up periods, and the inclusion of placebo controls to fully assess the efficacy and safety of this treatment approach.

An assessment of ChatGPT’s responses to frequently asked questions about cervical and breast cancer

BackgroundCervical cancer (CC) and breast cancer (BC) threaten women’s well-being, influenced by health-related stigma and a lack of reliable information, which can cause late diagnosis and early death. ChatGPT is likely to become a key source of health information, although quality concerns could also influence health-seeking behaviours.MethodsThis cross-sectional online survey compared ChatGPT’s responses to five physicians specializing in mammography and five specializing in gynaecology. Twenty frequently asked questions about CC and BC were asked on 26th and 29th of April, 2023. A panel of seven experts assessed the accuracy, consistency, and relevance of ChatGPT’s responses using a 7-point Likert scale. Responses were analyzed for readability, reliability, and efficiency. ChatGPT’s responses were synthesized, and findings are presented as a radar chart.ResultsChatGPT had an accuracy score of 7.0 (range: 6.6-7.0) for CC and BC questions, surpassing the highest-scoring physicians (P < 0.05). ChatGPT took an average of 13.6 s (range: 7.6-24.0) to answer each of the 20 questions presented. Readability was comparable to that of experts and physicians involved, but ChatGPT generated more extended responses compared to physicians. The consistency of repeated answers was 5.2 (range: 3.4-6.7). With different contexts combined, the overall ChatGPT relevance score was 6.5 (range: 4.8-7.0). Radar plot analysis indicated comparably good accuracy, efficiency, and to a certain extent, relevance. However, there were apparent inconsistencies, and the reliability and readability be considered inadequate.ConclusionsChatGPT shows promise as an initial source of information for CC and BC. ChatGPT is also highly functional and appears to be superior to physicians, and aligns with expert consensus, although there is room for improvement in readability, reliability, and consistency. Future efforts should focus on developing advanced ChatGPT models explicitly designed to improve medical practice and for those with concerns about symptoms.

A comparative study of histotripsy parameters for the treatment of fibrotic ex-vivo human benign prostatic hyperplasia tissue

Histotripsy is a noninvasive focused ultrasound therapy that mechanically fractionates tissue to create well-defined lesions. In a previous clinical pilot trial to treat benign prostatic hyperplasia (BPH), histotripsy did not result in consistent objective improvements in symptoms, potentially because of the fibrotic and mechanically tough nature of this tissue. In this study, we aimed to identify the dosage required to homogenize BPH tissue by different histotripsy modalities, including boiling histotripsy (BH) and cavitation histotripsy (CH). A method for histotripsy lesion quantification via entropy (HLQE) analysis was developed and utilized to quantify lesion area of the respective treatments. These data were correlated to changes in mechanical stiffness measured by ultrasound shear-wave elastography before and after treatment with each parameter set and dose. Time points corresponding to histologically observed complete lesions were qualitatively evaluated and quantitatively measured. For the BH treatment, complete lesions occurred with > = 30 s treatment time, with a corresponding maximum reduction in stiffness of −90.9 ± 7.2(s.d.)%. High pulse repetition frequency (PRF) CH achieved a similar reduction to that of BH at 288 s (−91.6 ± 6.0(s.d.)%), and low-PRF CH achieved a (−82.1 ± 5.1(s.d.)%) reduction in stiffness at dose > = 144 s. Receiver operating characteristic curve analysis showed that a > ~ 75% reduction in stiffness positively correlated with complete lesions observed histologically, and can provide an alternative metric to track treatment progression.

52650 Dupilumab Treatment Shows Rapid and Consistent Improvement in Atopic Dermatitis in All Anatomical Regions in Patients Aged 6 Months to 17 Years: Results From an Open-Label Extension Study

52650 Dupilumab Treatment Shows Rapid and Consistent Improvement in Atopic Dermatitis in All Anatomical Regions in Patients Aged 6 Months to 17 Years: Results From an Open-Label Extension Study

Subcutaneous efgartigimod PH20 in generalized myasthenia gravis: A phase 3 randomized noninferiority study (ADAPT-SC) and interim analyses of a long-term open-label extension study (ADAPT-SC+)

ADAPT-SC (NCT04735432) was designed to evaluate noninferiority of subcutaneous (SC) efgartigimod PH20 to intravenous (IV) efgartigimod in participants with generalized myasthenia gravis (gMG). ADAPT-SC+ (NCT04818671) is an open-label extension study designed to assess long-term safety, tolerability, and efficacy of efgartigimod PH20 SC. Adult participants in ADAPT-SC were randomly assigned to receive a treatment cycle of 4 once-weekly administrations of efgartigimod PH20 SC 1000 ​mg or efgartigimod IV 10 ​mg/kg, followed by 7 weeks of follow-up. Primary endpoint was percentage change from baseline in total immunoglobulin G (IgG) level at week 4 (1 week after the fourth administration). Secondary efficacy endpoints assessed number and percentage of Myasthenia Gravis Activities of Daily Living (MG-ADL) and Quantitative Myasthenia Gravis (QMG) responders and mean change from baseline in total score for each measure. The primary endpoint was met, demonstrating noninferiority in total IgG reduction between efgartigimod PH20 SC 1000 ​mg and efgartigimod IV 10 ​mg/kg. Clinically meaningful improvements were seen as early as 1 week following the first administration in both treatment arms, with maximal improvements at week 4. Continued treatment cycles of efgartigimod PH20 SC in ADAPT-SC+ have demonstrated long-term safety and consistent improvements in MG-ADL total score. Findings from ADAPT-SC and ADAPT-SC+ demonstrate similar safety and efficacy as observed in the placebo-controlled ADAPT study. Collectively, these findings support noninferiority between efgartigimod PH20 SC 1000 ​mg and efgartigimod IV 10 ​mg/kg, as well as long-term safety, tolerability, and efficacy of efgartigimod PH20 SC for treatment of a broad population of patients with gMG.

Single-cell RNA sequencing reveals microenvironmental infiltration in non-small cell lung cancer with different responses to immunotherapy.

Immunotherapy represents a groundbreaking and monumental achievement in the field of cancer therapy, marking a significant advancement in fighting against this devastating disease. Lung cancer has showed consistent clinical improvements in response to immunotherapy treatments, yet, it is undeniable that challenges such as limited response rates acquire resistance, and the unclear fundamental mechanisms were inevitable problems. The cellular composition was defined and distinguished through single-cell RNA sequencing (scRNA-seq) analysis of MPR (major pathologic response) and NMPR (non-major pathologic response) samples in GSE207422, including four primary MPR samples and eight primary NMPR samples. We found obvious difference in CD8+ T cell population between MPR and NMPR samples, with high expression of TYMS, RRM2, and BIRC5 in NPMR samples. Meanwhile, the proportion of macrophages and tumor epithelial cells infiltration increased in the NMPR samples. We discovered biomarkers (ACTN4, ATF3, BRD2, CDKN1A, and CHMP4B) in epithelial cells which were potentially represented worse outcomes. By exploring the difference of tumor microenvironment (TME) in samples with different corresponding degrees of neoadjuvant immunotherapy, this research introduces a number of novel biomarkers for predicting the response of treatment and a theoretical basis for overcoming immunotherapy resistance.