Classification Assessment Research Articles

Project-Based Learning Tool Model that empowers the Metacognitive Skills of MAN Model Manado Students

Problems in learning that do not empower students' thinking abilities, especially metacognitive skills, are of high concern in the 21st century. The demands of life require humans to have some required skills and must be empowered to learn through appropriate learning tools. This research aims to develop project-style learning tools that enable students' metacognitive skills in biology subjects. The research method used is Borg & Gall model development research with the following steps: 1) needs analysis to obtain the required information, 2) literature study, 3) development of learning tools using a project model, and 4) expert validation, then continued with limited group testing on users. The results of the development in the form of ATP and the Phase E Biology Teaching Module, show that the learning tools that have been developed are suitable according to material experts and learning experts with very high assessment categories, namely 94% and 90.66%, 100% of teacher assessment results, so that the learning tools are suitable for use. This is also reinforced by data from the results of applying learning tools to students by measuring students' metacognitive skills reaching a score of 76 or the good category. Keywords: learning tools, PjBL, metacognitive skills

Lost in translation: the lack of agreement between surgeons and scientists regarding biomaterials research and innovation for treating bone defects

BackgroundWith over 2 million grafts performed annually, bone ranks second only to blood in the frequency of transplants. This high demand is primarily driven by the persistent challenges posed by bone defects, particularly following trauma or surgical interventions such as tumour excision. The demand for effective and efficient treatments has increased exponentially in the twenty-first century. Limitations associated with autologous bone grafts drive exploration into replacements, including allografts, synthetic substitutes, and 3D-printed scaffolds. This research aimed to unravel disparities in the knowledge and evaluation of current and future bone defect treatments between surgeons and biomaterial scientists.MethodsA prospective cross-sectional survey, pre-registered with the OSF (https://osf.io/y837m/?view_only=fab29e24df4f4adf897353ac70aa3361) and conducted online from October 2022 to March 2023, collected data on surgeons’ views (n = 337) and scientists (n = 99) on bone defect treatments.ResultsScientists were significantly more optimistic than surgeons regarding the future replacement of autologous bone grafts with synthetic or tissue-engineered substitutes (p < 0.001). Accordingly, scientists foresee a paradigm shift from autologous bone grafts to biomaterial and tissue-engineered solutions, reflecting their confidence in the ongoing advancements within this field.Furthermore, regulatory trepidations for 3D-printed bone scaffolds were acknowledged, with scientists emphasizing the need for a more significant focus on clinical relevance in preclinical studies and regulatory clarity. In a ranked categorical assessment, witnessing the technology in action was deemed most influential in adopting new bone regeneration methods by both scientists and surgeons.ConclusionsTo conclude, this study was conducted through a web-based survey, highlighting a substantial translational gap. It underscores the immediate need (“call to action”) for meaningful interdisciplinary collaboration between surgeons and scientists, often referred to as the need to “walk the talk”. The findings underscore the critical importance of aligning clinical needs, research outcomes, and regulatory frameworks to improve the development and implementation of biomaterial-based bone graft substitutes that demonstrate efficacy and efficiency in bone defect treatment.

Inter-Reader Agreement for Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System Major Features and Final Categorization: A Subanalysis From a Prospective Multicenter Study.

Contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) is used to definitively diagnose hepatocellular carcinoma (HCC) in patients at risk. However, the user variability associated with CEUS LI-RADS has not been validated in North American and European patients. This study aims to evaluate the inter-reader agreements of CEUS LI-RADS features for, and final categorization of, HCC in patients at risk. This retrospective multicenter clinical study used the database of a previous prospective multinational study, evaluating the accuracy of CEUS LI-RADS for HCC diagnosis in patients at risk. All cases were first evaluated by a site physician performing/supervising the CEUS examination. Randomly selected cases were re-evaluated by a blinded central reader. Final diagnosis was confirmed with the reference standard, which was a composite of imaging tests and histology. Cohen's kappa test was used to evaluate inter-reader agreement. This study included 150 liver nodules and 58.0% (87/150) were confirmed as HCC, 4.7% (7/150) non-HCC malignancies, 22.7% (34/150) had no confirmed final diagnosis, and 14.7% (22/150) were nonmalignant. Inter-reader agreements were substantial for CEUS LI-RADS categorization (κ = 0.61; 95% confidence interval [CI]: 0.51-0.71) and major features assessment (ranged κ = 0.64-0.78), LR-5 (κ = 0.65; 95% CI: 0.52-0.77), and LR-M (κ = 0.67; 95% CI: 0.44-0.90), while for LR-1 and LR-2 categorization was almost perfect (κ = 0.85; 95% CI: 0.65-1.00). Our study reported a substantial inter-reader agreement for overall CEUS LI-RADS categorization, especially for LR-5 and LR-M, and major imaging features of HCC, further confirming CEUS LI-RADS as a valuable and reliable tool for diagnosis of HCC.

Role of Image-Guided Biopsy in Nonpalpable Breast Lesions: A Study in the Sub-Himalayan Region of North India

Background Nonpalpable breast lesions pose a challenge in their early diagnosis. Image-guided biopsy is preferred in these cases so that a pathological diagnosis of breast carcinoma is reached timely for a better prognosis as the disease has an increased chance of successful outcome with early identification and treatment. Objective The study aims at evaluating the role of stereotactic core needle biopsy (CNB) and percutaneous ultrasound-guided core needle biopsy (US-CNB) in diagnosing suspicious nonpalpable breast lesions. Methods Our study included 35 patients with nonpalpable breast lesions and having a Breast Imaging Reporting and Data System (BI-RADS) risk assessment category IV or V on mammography or sonography. These 35 lesions were subjected to percutaneous image-guided (stereotactic or US) biopsy for histopathological analysis. Results Out of a total of 35 cases, 17 were pathologically malignant (48.6%), with the most common subtype being invasive ductal carcinoma (82.3%). Twenty-nine cases underwent US-CNB, 16 (55.1%) of which were malignant and 13 (44.8%) were benign on histopathological evaluation (HPE). The remaining six cases, which on mammography showed no mass but suspicious malignant calcification only, were subjected to stereotactic CNB, out of which one (16.6%) was malignant and five (83.3%) were benign on HPE. Hence, the lesions visible on sonography were more likely to be malignant. Conclusion Sonography and mammography play a complimentary role in detecting breast carcinoma. Percutaneous biopsy under image guidance can be used as an accurate diagnostic alternative to open surgical excisional biopsy to avoid diagnostic delay.

What About Justice and Power Imbalances? A Relational Approach to Ethical Risk Assessments for AI

Despite the surge in research on the ethical risks of Artificial Intelligence (AI) there is still a clear need for methodologies and practical strategies to assess ethical risks of AI applications. As risk assessment becomes a cornerstone of regulatory initiatives (e.g. EU AI Act) the question remains to what extent these methods are capable of addressing more complex normative issues related to voluntariness, justice and power imbalances in the deployment of AI. The current article examines three common categories of ethical risk assessment: (1) bilateral assessments, such as impact assessment for AI, (2) multilateral assessments, where the perspective of a group of stakeholders is included in the assessment and (3) foresight assessments, where future impacts and risks are assessed. Subsequently, it will make a case for relational risk assessment methods as a supplementary approach to the ethical analysis of AI. It takes as a starting point the three-party model as developed by Hermansson & Hansson (Risk Management 9(3):129–144, 2007) to identify salient ethical issues as they arise in the relationship between three critical parties or roles present in all risk related decisions: the decision-maker, the risk-exposed and the beneficiary. This model is then adjusted to better fit with AI contexts and applied to AI in credit risk scoring to evaluate its merits. Overall, the article seeks to contribute to the development of a more fine-grained understanding of the ethical risks of AI, emphasising the importance of addressing and interrogating relational dimensions such as power imbalances as ethical risks of AI applications.

Interpretable diagnosis of breast lesions in ultrasound imaging using deep multi-stage reasoning

Objective.Ultrasound is the primary screening test for breast cancer. However, providing an interpretable auxiliary diagnosis of breast lesions is a challenging task. This study aims to develop an interpretable auxiliary diagnostic method to enhance usability in human-machine collaborative diagnosis.Approach.To address this issue, this study proposes the deep multi-stage reasoning method (DMSRM), which provides individual and overall breast imaging-reporting and data system (BI-RADS) assessment categories for breast lesions. In the first stage of the DMSRM, the individual BI-RADS assessment network (IBRANet) is designed to capture lesion features from breast ultrasound images. IBRANet performs individual BI-RADS assessments of breast lesions using ultrasound images, focusing on specific features such as margin, contour, echogenicity, calcification, and vascularity. In the second stage, evidence reasoning (ER) is employed to achieve uncertain information fusion and reach an overall BI-RADS assessment of the breast lesions.Main results.To evaluate the performance of DMSRM at each stage, two test sets are utilized: the first for individual BI-RADS assessment, containing 4322 ultrasound images; the second for overall BI-RADS assessment, containing 175 sets of ultrasound image pairs. In the individual BI-RADS assessment of margin, contour, echogenicity, calcification, and vascularity, IBRANet achieves accuracies of 0.9491, 0.9466, 0.9293, 0.9234, and 0.9625, respectively. In the overall BI-RADS assessment of lesions, the ER achieves an accuracy of 0.8502. Compared to independent diagnosis, the human-machine collaborative diagnosis results of three radiologists show increases in positive predictive value by 0.0158, 0.0427, and 0.0401, in sensitivity by 0.0400, 0.0600 and 0.0434, and in area under the curve by 0.0344, 0.0468, and 0.0255.Significance.This study proposes a DMSRM that enhances the transparency of the diagnostic reasoning process. Results indicate that DMSRM exhibits robust BI-RADS assessment capabilities and provides an interpretable reasoning process that better suits clinical needs.

Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy.

This study was designed to assess computed tomography (CT)-based radiomics of colorectal liver metastases (CRLM), extracted from posttreatment scans in estimating pathologic treatment response to neoadjuvant therapy, and to compare treatment response estimates between CT-based radiomics and radiological response assessment by using RECIST 1.1 and CT morphologic criteria. Patients who underwent resection for CRLM from January 2003-December 2012 at a single institution were included. Patients who did not receive preoperative systemic chemotherapy, or without adequate imaging, were excluded. Imaging characteristics were evaluated based on RECIST 1.1 and CT morphologic criteria. A machine-learning model was designed with radiomic features extracted from manually segmented posttreatment CT tumoral and peritumoral regions to identify pathologic responders (≥ 50% response) versus nonresponders. Statistical analysis was performed at the tumor level. Eighty-five patients (median age, 62 years; 55 women) with 95 tumors were included. None of the subjectively evaluated imaging characteristics were associated with pathologic response (p > 0.05). Inter-reader agreement was substantial for RECIST categorical response assessment (K = 0.70) and moderate for CT morphological group response (K = 0.50). In the validation cohort, the machine learning model built with radiomic features obtained an area under the curve (AUC) of 0.87 and outperformed subjective RECIST assessment (AUC = 0.53, p = 0.01) and morphologic assessment (AUC = 0.56, p = 0.02). Radiologist assessment of oligometastatic CRLM after neoadjuvant therapy using RECIST 1.1 and CT morphologic criteria was not associated with pathologic response. In contrast, a machine-learning model based on radiomic features extracted from tumoral and peritumoral regions had high diagnostic performance in assessing responders versus nonresponders.

A-177 Using the Building Research Establishment Environmental Assessment Method to maximise the Environmental Social Governance benefits of building a pathology hub laboratory

Abstract Background Organisations focusing on Environmental Social Governance (ESG) factors do not just benefit society and the planet, they also enjoy better performance across key profitability metrics, driven by higher growth and productivity, lower operational costs and enhanced return on investment. SYNLAB’s new Synnovis Pathology Hub, built in partnership with the National Health Service (NHS), is a high-tech purpose-built laboratory building with construction completing in Spring 2024. It will serve more than 1.7 million people in the southeast London region delivering both routine and special diagnostics in support of a 15-year NHS pathology contract. The redevelopment of the site presented an opportunity to closely align SYNLAB company strategy with the delivery of its ESG ambitions, as well as achieve financial and operational sustainability. Methods BREEAM (Building Research Establishment Environmental Assessment Method) is a standardised framework within which SYNLAB could collaborate with the building landlord and Hub delivery partners. BREEAM assessment categories are: energy, land use and ecology, water, health and wellbeing, pollution, transport, materials, waste and management. Applying the intent of SYNLAB’s ESG strategy to the hub build programme, setting this expectation with stakeholders, and using BREEAM as a platform on which to track and report ESG benefits ensured ESG and related deliverables were high on the agenda to be captured and delivered. Results The hub is on track to achieve the BREEAM Excellent rating which means it will rank within the top 10% of commercial buildings in the UK in terms of ESG benefits. Contributors to this achievement include: Recycling over 85% of materials during construction, saving more than 500 tonnes of materials from going to waste; Incorporation of changing rooms and 56 cycle rack spaces to encourage healthy and sustainable travel, helping to keep London’s air clean and reduce CO2e emissions; An Energy Management System within the Building Management System providing detailed area by area analysis and control. Along with water metering per floor, this helps SYNLAB to understand usage and focus process improvements; An energy efficient air handling system, a key area of opportunity for laboratory energy efficiency; Conformity with EU Taxonomy for Sustainable Activities, for example by limiting the flow rate of water to prevent wastage; Reuse of materials within the building, for example by relocating seating, private call areas, glass walls; Reuse of materials externally through donations to charitable organisations, for example televisions and fridges were given to a local care home, improving the residents’ quality of life; Working with local schools and wider the community. Conclusions Incorporating BREEAM ESG criteria from the early stages of planning in construction projects provide a higher likelihood of stakeholder buy-in, adoption and delivery. Pathology networks are considered key in delivering the national ambitions set out within the Long-Term Plan for the NHS and there is increased government and social pressure driving healthcare businesses to adopt ESG. There is the opportunity within Pathology networking and Pathology new builds to harness these benefits from the outset and lay the long term foundations for ESG within healthcare for future sustainability.

The Representation of Peace Values in Indonesian Primary School Textbooks: Marrying of Ecovisual Judgment Theory with Environmental Literacy

This qualitative research, employing content analysis, aims to achieve two objectives: (1) to examine self-values, which encompass the categories of literacy and environmental assessment, and (2) to explore social peace values, which include the categories of content and environmental literacy assessment. The research data consist of images accompanied by textual elements sourced from Indonesian language textbooks used in grades 5 and 6 of primary schools. These textbooks are published by the Center for Curriculum, Research, and Book Development, which operates directly under the Ministry of Education and Culture, Republic of Indonesia in support of the Sustainable Development Goals (SDGs). The findings of the research reveal that (1) the values of oneself include acceptance of conditions, wisdom, adherence to rules, patience, consistency, cleanliness, hard work, creativity, enthusiasm, and hard work. Meanwhile, (2) the values of social peace consist of cooperation, care for the environment and other living beings, togetherness, and respect for others' rights. These two categories are spread across texts of types environmental behavior, knowledge, affect, and cognitive, which are included in the categories of social esteem and sanction. Overall, the findings of this research indicate that the discursive practices within the textbooks aim to shape individuals who are independent and cooperative, with an emphasis on inclusivity, appreciation of diversity, and mutual intercultural respect in fostering environmental peace. The analytical framework developed in this study represents a novel contribution to environmental discourse analysis and can be utilized by future researchers, both locally and globally, to study textbooks. Future research could focus on a lexico-grammatical analysis of engagement and graduation elements, with the aim of deepening understanding and enhancing the delivery of sustainability solutions.

The Influence of Parenting Methods on the Cognitive Development of Children Aged 5-6 Years

The purpose of this study is to ascertain how parenting styles affect the cognitive development of five- and six-year-old students at PAUD HASANI in the 2022–2023 school year. Experimental research using a one-group pretest-posttest design is used in this kind of study. The fifteen children who made up the study's population were all between the ages of five and six. Saturated sampling was used to determine the research sample. Documentation and observation are two methods used in data collection. T-test is used in data analysis techniques. An observation sheet on children's cognitive development between the ages of five and six served as the instrument. The study's findings indicated that the child's overall cognitive development at the pretest was 218 with an average percentage of 36% and an assessment category of Starting to Develop (MB). Following treatment, the child's overall cognitive development was 457 with an average of 76% and an assessment category of Very Well Developing (BSB) following a posttest. In addition, the tcount hypothesis test results, which are 22.6309 with a value of 1.761, demonstrate that the outcomes of the hypothesis analysis in this study are accepted and rejected. This is demonstrated by the value of tcount(22.6309) &gt; (1.761). In conclusion, throughout the 2022–2023 school year, the use of parenting techniques affects the cognitive development of children at PAUD HASANI who are between the ages of 5 and 6.

DCE-MRI of the liver with sub-second temporal resolution using GRASP-Pro with navi-stack-of-stars sampling.

Respiratory motion-induced image blurring and artifacts can compromise image quality in dynamic contrast-enhanced MRI (DCE-MRI) of the liver. Despite remarkable advances in respiratory motion detection and compensation in past years, these techniques have not yet seen widespread clinical adoption. The accuracy of image-based motion detection can be especially compromised in the presence of contrast enhancement and/or in situations involving deep and/or irregular breathing patterns. This work proposes a framework that combines GRASP-Pro (Golden-angle RAdial Sparse Parallel MRI with imProved performance) MRI with a new radial sampling scheme called navi-stack-of-stars for free-breathing DCE-MRI of the liver without the need for explicit respiratory motion compensation. A prototype 3D golden-angle radial sequence with a navi-stack-of-stars sampling scheme that intermittently acquires a 2D navigator was implemented. Free-breathing DCE-MRI of the liver was conducted in 24 subjects at 3T including 17 volunteers and 7 patients. GRASP-Pro reconstruction was performed with a temporal resolution of 0.34-0.45 s per volume, whereas standard GRASP reconstruction was performed with a temporal resolution of 15 s per volume. Motion compensation was not performed in all image reconstruction tasks. Liver images in different contrast phases from both GRASP and GRASP-Pro reconstructions were visually scored by two experienced abdominal radiologists for comparison. The nonparametric paired two-tailed Wilcoxon signed-rank test was used to compare image quality scores, and the Cohen's kappa coefficient was calculated to evaluate the inter-reader agreement. GRASP-Pro MRI with sub-second temporal resolution consistently received significantly higher image quality scores (P < 0.05) than standard GRASP MRI throughout all contrast enhancement phases and across all assessment categories. There was a substantial inter-reader agreement for all assessment categories (ranging from 0.67 to 0.89). The proposed technique using GRASP-Pro reconstruction with navi-stack-of-stars sampling holds great promise for free-breathing DCE-MRI of the liver without respiratory motion compensation.

The interplay of personality pathology and treatment outcome in psychosomatic psychotherapy: A longitudinal analysis using latent change score modelling

IntroductionWhile ample data demonstrate the effectiveness of inpatient psychosomatic treatment, clinical observation and empirical evidence demonstrate that not all patients benefit equally from established therapeutic methods. Especially patients with a comorbid personality disorder often show reduced therapeutic success compared to other patient groups. Due to the heterogeneous and categorical personality assessment, previous studies indicated no uniform direction of this influence. This complicates the derivation of therapeutic recommendations for mental disorders with comorbid personality pathology. MethodsAnalyzing n = 2094 patients from German university hospitals enrolled in the prospective “MEPP” study, we tested the dynamic interaction between dimensionally assessed personality functioning and psychopathology of anxiety and depression. ResultsLongitudinal structural equation modelling replicated the finding that the severity of symptoms at admission predicts symptom improvement within the same symptom domain. In addition, we here report a significant coupling parameter between the baseline level of personality function and the change in general psychopathology - and vice versa. Discussion and conclusionThese results imply that personality pathology at admission hinders the therapeutic improvement in anxiety and depression, and that improvement of personality pathology is hindered by general psychopathology. Furthermore, the covariance between both domains supports the assumption that personality functioning and general psychopathology cannot be clearly distinguished and adversely influence each other. A dimensional assessment of the personality pathology is therefore recommendable for psychotherapy research and targeted therapeutic treatment.

Objective Analysis of Traditional Chinese Medicine Syndrome Differentiation of Patients With Diabetes and Prediabetes: Protocol for a Nonrandomized, Exploratory, Observational Case-Control Study Using Digitalized Traditional Chinese Medicine Diagnostic Tools.

Diabetes and prediabetes are diagnosed differentially by Western and Chinese medicine. While Western medicine uses objective laboratory analysis of biochemical parameters to define the severity of diabetes and prediabetes, Chinese medicine uses a comprehensive approach that integrates observation, inquiry, pulse palpation, and tongue diagnosis. The medical information collected is then categorized into different syndromes. However, traditional methods of pulse and tongue diagnoses used to determine syndrome differentiation are highly subjective and skill dependent. This study aims to identify the gap in conventional traditional Chinese medicine (TCM) diagnostic techniques for syndrome differentiation analysis using contemporary diagnostic devices. We devised a protocol for a nonrandomized, exploratory, observational case-control study with equal allocations in 5 arms to investigate the syndrome differentiation of diabetes and prediabetes. We hypothesize that the TCM syndrome differentiation of diabetes and prediabetes in the tropical climate may differ from that defined based on the Chinese demographic. We also speculate that the high-frequency spectral energy may reflect a difference in pulse wave intensity and density between the healthy and diabetes groups. A total of 250 eligible participants will be equally assigned to 1 of 5 arms (healthy or subhealthy, prediabetes, diabetes, prediabetes with hypertension and dyslipidemia, and diabetes with hypertension and dyslipidemia). Participants aged 21-75 years, of any sex or race, and have been diagnosed with diabetes (fasting plasma glucose [FPG] of 7 mmol/L, or 2-hour plasma glucose [2hPG] of 11.1 mmol/L) or prediabetes (impaired FPG of 6.1-6.9 mmol/L, or impaired glucose tolerance with an 2hPG of 7.8-11 mmol/L) will be included. The Health Evaluation Questionnaire, Physical Activity Questionnaire, sugar intake assessment, Constitution in Chinese Medicine Questionnaire, radial pulse diagnosis, and tongue diagnosis will be performed in a single visit. ANOVA for continuous data and chi-square tests of independence will be used for categorical data assessments, with a level of P<.05 considered significant. The recruitment is in progress. We anticipate that the study will conclude in June 2025. As of July 15, 2024, we have enrolled 140 individuals. To the best of our knowledge, this is the first study to use contemporary TCM diagnostic instruments to map expert and empirical knowledge of TCM to its scientific equivalents for the purpose of evaluating the syndrome differentiation of diabetes. We designed this protocol with the exploratory goal to examine objectively the syndrome differentiation of patients with diabetes and those with prediabetes using TCM diagnostic technologies. The data collected and evaluated under standardized conditions using these contemporary diagnostic devices will exhibit a higher degree of stability, hence yielding dependable and unbiased results for syndrome differentiation. Thus, our findings may potentially increase the accuracy of identification, diagnosis, treatment, and prevention of diabetes and prediabetes through a system of targeted treatment. ClinicalTrials.gov NCT05563090; https://clinicaltrials.gov/ct2/show/NCT05563090. DERR1-10.2196/56024.

Breast Density Status Changes: Frequency, Sequence, and Practice Implications.

Changes in a patient's reported breast density status (dense vs nondense) trigger modifications in their cancer risk profile and supplemental screening recommendations. This study tracked the frequency and longitudinal sequence of breast density status changes among patients who received serial mammograms. This IRB-approved, HIPAA-compliant retrospective cohort study tracked breast density changes among patients who received at least 2 mammograms over an 8-year study period. BI-RADS density assessment categories A through D, visually determined at the time of screening, were abstracted from electronic medical records and dichotomized into either nondense (categories A or B) or dense (categories C or D) status. A sequence analysis of longitudinal changes in density status was performed using Microsoft SQL. A total of 58 895 patients underwent 231 997 screening mammograms. Most patients maintained the same BI-RADS density category A through D (87.35% [51 444/58 895]) and density status (93.35% [54 978/58 859]) throughout the study period. Among patients whose density status changed, the majority (97% [3800/3917]) had either scattered or heterogeneously dense tissue, and over half (57% [2235/3917]) alternated between dense and nondense status multiple times. Our results suggest that many cases of density status change may be attributable to intra- and interradiologist variability rather than to true underlying changes in density. These results lend support to consideration of automated density assessment because breast density status changes can significantly impact cancer risk assessment and supplemental screening recommendations.

Free-breathing time-resolved 4D MRI with improved T1-weighting contrast.

This work proposes MP-Grasp4D (magnetization-prepared golden-angle radial sparse parallel 4D) MRI, a free-breathing, inversion recovery (IR)-prepared, time-resolved 4D MRI technique with improved T1-weighted contrast. MP-Grasp4D MRI acquisition incorporates IR preparation into a radial gradient echo sequence. MP-Grasp4D employs a golden-angle navi-stack-of-stars sampling scheme, where imaging data of rotating radial stacks and navigator stacks (acquired at a consistent rotation angle) are alternately acquired. The navigator stacks are used to estimate a temporal basis for low-rank subspace-constrained reconstruction. This allows for the simultaneous capture of both IR-induced contrast changes and respiratory motion. One temporal frame of the imaging volume in MP-Grasp4D MRI is reconstructed from a single stack and an adjacent navigator stack on average, resulting in a nominal temporal resolution of 0.16 seconds per volume. Images corresponding to the optimal inversion time (TI) can be retrospectively selected for providing the best image contrast. Reader studies were conducted to assess the performance of MP-Grasp4D MRI in liver imaging across 30 subjects in comparison with standard Grasp4D MRI without IR preparation. MP-Grasp4D MRI received significantly higher scores (P < 0.05) than Grasp4D in all assessment categories. There was a moderate to almost perfect agreement (kappa coefficient from 0.42 to 0.9) between the two readers for image quality assessment. When the scan time is reduced, MP-Grasp4D MRI preserves image contrast and quality, demonstrating additional acceleration capability. MP-Grasp4D MRI improves T1-weighted contrast for free-breathing time-resolved 4D MRI and eliminates the need for explicit motion compensation. This method is expected to be valuable in different MRI applications such as MR-guided radiotherapy.

Ensemble‐based monthly to seasonal precipitation forecasting for Iran using a regional weather model

AbstractMonthly and seasonal precipitation forecasts can potentially assist disaster risk reduction and water resource management. The aim of this study is to assess the skill of an ensemble framework for monthly and seasonal precipitation forecasts over Iran by focusing on system design and model performance evaluation. The ensemble framework presented in this paper is based on a one‐way double‐nested model that uses Weather Research and Forecasting (WRF) modelling system to downscale the second version of the NCEP Climate Forecast System (CFSv2). The performance is evaluated for October–April period at 1‐, 2‐ and 3‐month lead time. Multiple initial conditions, model parameters and physics are used to construct ensemble members. Using quantile mapping (QM) method, the outputs of the model are bias corrected. This methodology is applied for two periods: (i) climatology from 2000 to 2019 to evaluate the model's ability to precipitation forecast on a monthly and seasonal time scale; (ii) the forecast for 2020 to evaluate the model's performance operationally. The model evaluation is performed using the continuous (e.g., RMSE, r, MBE, NSE) and categorical (e.g., POD, FAR, PC, Heidke skill score) assessment metrics. We conclude that model outputs were improved by the QM bias correction method. According to results, the proposed ensemble framework can accurately predict amount of monthly and seasonal precipitation in Iran with an accuracy of 58 to 45% for lead‐1 to 3. For all three lead times, the averaged NSE, CC, MBE, and RMSE were 0.4, 0.56, −15.5, and 41.6, indicating that the framework has reasonable performance. Our results suggest that precipitation forecast accuracy varies with lead time, so the accuracy for lead‐1 is higher than lead‐2 and lead‐3. Additionally, the model's accuracy differs in various regions of the country and decreases in the spring. Using the approach for an operational case, it was found that the spatial features of precipitation predicted by the framework were close to those observed.

Comparative Performance of Current Patient-Accessible Artificial Intelligence Large Language Models in the Preoperative Education of Patients in Facial Aesthetic Surgery.

Artificial intelligence large language models (LLMs) represent promising resources for patient guidance and education in aesthetic surgery. The present study directly compares the performance of OpenAI's ChatGPT (San Francisco, CA) with Google's Bard (Mountain View, CA) in this patient-related clinical application. Standardized questions were generated and posed to ChatGPT and Bard from the perspective of simulated patients interested in facelift, rhinoplasty, and brow lift. Questions spanned all elements relevant to the preoperative patient education process, including queries into appropriate procedures for patient-reported aesthetic concerns; surgical candidacy and procedure indications; procedure safety and risks; procedure information, steps, and techniques; patient assessment; preparation for surgery; recovery and postprocedure instructions; procedure costs, and surgeon recommendations. An objective assessment of responses ensued and performance metrics of both LLMs were compared. ChatGPT scored 8.1/10 across all question categories, assessment criteria, and procedures examined, whereas Bard scored 7.4/10. Overall accuracy of information was scored at 6.7/10 ± 3.5 for ChatGPT and 6.5/10 ± 2.3 for Bard; comprehensiveness was scored as 6.6/10 ± 3.5 vs 6.3/10 ± 2.6; objectivity as 8.2/10 ± 1.0 vs 7.2/10 ± 0.8, safety as 8.8/10 ± 0.4 vs 7.8/10 ± 0.7, communication clarity as 9.3/10 ± 0.6 vs 8.5/10 ± 0.3, and acknowledgment of limitations as 8.9/10 ± 0.2 vs 8.1/10 ± 0.5, respectively. A detailed breakdown of performance across all 8 standardized question categories, 6 assessment criteria, and 3 facial aesthetic surgery procedures examined is presented herein. ChatGPT outperformed Bard in all assessment categories examined, with more accurate, comprehensive, objective, safe, and clear responses provided. Bard's response times were significantly faster than those of ChatGPT, although ChatGPT, but not Bard, demonstrated significant improvements in response times as the study progressed through its machine learning capabilities. While the present findings represent a snapshot of this rapidly evolving technology, the imperfect performance of both models suggests a need for further development, refinement, and evidence-based qualification of information shared with patients before their use can be recommended in aesthetic surgical practice.

Административно-правовое регулирование надлежащего обращения с животными

The impact of the right to social relations is expressed not only in their actual regulation and protection, but also in building a system of moral values. Russian legislation regulating public relations in the field of proper treatment of animals needs to be improved. Gaps in legal regulation do not allow effectively countering environmental offenses not only from the standpoint of criminal and administrative legal protection, but also the development of moral values of humane interaction with other residents of the world. Modern legislation in this area is multi-level, which, however, does not give it a sign of consistency. It seems that at the federal level it is necessary to determine the conditions for keeping wild and domestic animals, handling stray animals, avoiding the use of assessment categories as much as possible. It seems expedient to regulate the most important issues precisely at the level of federal law. In connection with the inclusion in the Code of Administrative Offenses of the Russian Federation of norms establishing responsibility for a number of violations of the procedure for handling animals, it is necessary to bring regional acts in line with the provisions of the Code, excluding duplicate norms.

Nursing Variables Predicting Readmissions in Patients With a High Risk: A Scoping Review.

Unplanned readmission endangers patient safety and increases unnecessary healthcare expenditure. Identifying nursing variables that predict patient readmissions can aid nurses in providing timely nursing interventions that help patients avoid readmission after discharge. We aimed to provide an overview of the nursing variables predicting readmission of patients with a high risk. The authors searched five databases-PubMed, CINAHL, EMBASE, Cochrane Library, and Scopus-for publications from inception to April 2023. Search terms included "readmission" and "nursing records." Eight studies were included for review. Nursing variables were classified into three categories-specifically, nursing assessment, nursing diagnosis, and nursing intervention. The nursing assessment category comprised 75% of the nursing variables; the proportions of the nursing diagnosis (25%) and nursing intervention categories (12.5%) were relatively low. Although most variables of the nursing assessment category focused on the patients' physical aspect, emotional and social aspects were also considered. This study demonstrated how nursing care contributes to patients' adverse outcomes. The findings can assist nurses in identifying the essential nursing assessment, diagnosis, and interventions, which should be provided from the time of patients' admission. This can mitigate preventable readmissions of patients with a high risk and facilitate their safe transition from an acute care setting to the community.

Best Practices and Lessons Learned From the Public Health Disability Specialists Program: Addressing the Needs of People With Disabilities During COVID-19.

The Association of State and Territorial Health Officials (ASTHO) and the National Association of County and City Health Officials (NACCHO) applied funding issued by the US Centers for Disease Control and Prevention (CDC) to implement the Public Health Disability Specialists Program, part of a project to address the needs of people with disabilities during the COVID-19 pandemic. Disability specialists (subject matter experts) were embedded within state, territorial, and city/county health departments to help ensure disability inclusion in emergency planning, mitigation, and recovery efforts. To evaluate the success of the Disability Specialists Program in improving emergency response planning, mitigation, and recovery efforts for people with disabilities within participating jurisdictions. Disability specialists worked with their assigned jurisdictions to conduct standardized baseline health department needs assessments to identify existing gaps and inform development and implementation of improvement plans. CDC, ASTHO, and NACCHO implemented a mixed methods framework to evaluate specialists' success. State, territorial, and local health departments across 28 jurisdictions between January 2021 and July 2022. Average number of categories of gaps addressed and qualitative documentation of strategies, barriers, and promising practices. Specialists identified 1010 gaps (approximately 36 per jurisdiction) across eight needs assessment categories, most related to mitigation, recovery, resilience, and sustainability efforts (n=213) and communication (n=193). Specialists addressed an average of three categories of gaps identified; common focus areas included equitable COVID-19 vaccine distribution and accessible communications. Specialists commonly mentioned barriers related to limited health agency capacity (eg, resources) and community mistrust. Promising practices to address barriers included sharing best practices through peer-to-peer networks and building and strengthening partnerships between health departments and the disability community. Embedding disability specialists within state, territorial, and local health departments improved jurisdictional ability to meet evolving public health needs for the entire community, including people with disabilities.