Assessment Methods Research Articles

Peran Alat Pembelajaran Edukatif dalam Peningkatan Akademik di SDN 3 Bluluk Lamongan

Academics include teaching and learning, knowledge, skills and achievements obtained in the field of education. Educational learning tools are a development of educational game tool products (APE). An educational learning tool that aims to improve students' ability to absorb the subjects given at school in order to obtain increased grades in the academic world. SDN III Bluluk Lamongan has the problem of improving the effective teaching process in order to improve the quality of teaching and learning and grades. academics at school. The implementation method used in community service activities this time has 5 stages, the first is the observation method, the second is the introduction method, the third is the learning method, the fourth is the assessment method and the fifth is the sustainability method. The result of the service is an educational learning tool in the form of a modified snakes and ladders game that can improve students' grades and enthusiasm for learning and the role of this educational learning is to help students absorb lessons using a game method that can be played individually or in groups, and can be applied in various subjects.

An Embodied Intelligence System for Coal Mine Safety Assessment Based on Multi-Level Large Language Models

Artificial intelligence (AI), particularly through advanced large language model (LLM) technologies, is reshaping coal mine safety assessment methods with its powerful cognitive capabilities. Given the dynamic, multi-source, and heterogeneous characteristics of data in typical mining scenarios, traditional manual assessment methods are limited in their information processing capacity and cost-effectiveness. This study addresses these challenges by proposing an embodied intelligent system for mine safety assessment based on multi-level large language models (LLMs) for multi-source sensor data. The system employs a multi-layer architecture implemented through multiple LLMs, enabling not only rapid and effective processing of multi-source sensor data but also enhanced environmental perception through physical interactions. By leveraging the tool invocation and reasoning capabilities of LLM in conjunction with a coal mine safety knowledge base, the system achieves logical inference, anomalous data detection, and potential safety risk prediction. Furthermore, its memory functionality ensures the learning and utilization of historical experiences, providing a solid foundation for continuous assessment processes. This study established a comprehensive experimental framework integrating numerical simulation, scenario simulation, and real-world testing to evaluate the system through embodied intelligence. Experimental results demonstrate that the system effectively processes sensor data and exhibits rapid, efficient safety assessment capabilities during embodied interactions, offering an innovative solution for coal mine safety.

Life cycle assessment research and application in Nigeria

Abstract Purpose Life cycle assessment (LCA) methodology is becoming increasingly popular in developing countries, however, challenges such as lack of local data, spatial and temporal differentiation of impact categories, and uncertainty in the data and impact assessment methods remain. In this comprehensive review, we systematically conduct a literature review of LCA research in Nigeria, including a thorough assessment of the LCA studies according to ISO 14040 and 14044 standards. Methods A total of 30 peered reviewed and conference papers on LCA papers Nigeria as the study area of authors affiliated to institutions in the country were assessed. The assessment focused on functional unit, system boundary, data quality, allocation, impact assessment methods, database and LCA software used and interpretation methods. Results and discussion The results of the review showed that LCA is still in its infancy in Nigeria with 30 papers on the subject matter published between 2010–2023. These peer reviewed publications came from universities and research institutions, none from companies or government. In terms of the methodological choices, different functional units, system boundaries, impact assessment methods, allocation, data choices, databases and software were used. The Ecoinvent database is one of the most widely used for background data for potential environmental impacts while SimaPro and GaBi are the softwares of choice for most of the studies. Climate Change was the most assessed impact category at the midpoint level for life cycle impact assessment (LCIA). To ensure that uncertainties in LCA results are reduced, studies should ensure transparency in inventories, consider all the life cycle stages, use primary data and adapt local characterisation factors. Local impacts such as gas flaring, biodiversity, oil spills, soil erosion, and desertification should be the focus of LCA method developers in Nigeria as they are the prevailing environmental challenges affecting different parts of the country. Conclusions and recommendations Different methodological choices are used by researchers, they highlight a challenge that was noticeable in all the papers – a general lack of primary data. The studies are not equally distributed amongst the sectors of the economy. Most of them are concentrated in the agriculture, energy and transportation sectors. Based on our findings, the authors recommend the development of an LCI database for Nigeria and Nigeria-specific impact pathways, normalisation and weighting factors to enhance the reproducibility of the results. This study lays the foundation for the development of an integrated master plan for the development of LCA in Nigeria, with the potential to significantly contribute to improving environmental assessment and sustainable development.

Combining theory and usability testing to inform optimization and implementation of an online primary care depression management tool

BackgroundThe ‘Ottawa Depression Algorithm’ is an evidence-based online tool developed to support primary care professionals care for adults with depression. Uptake of such tools require provider behaviour change. Identifying issues which may impact use of an innovation in routine practice (i.e. barriers to and enablers of behaviour change) informs the selection of implementation strategies that can be deployed with the tool to support use. However, established theory-informed barriers/enablers assessment methods may be less well suited to identifying issues with tool usability. User testing methods can help to determine whether the tool itself is optimally designed. We aimed to integrate these two methodological approaches to i) identify issues impacting the usability of algorithm; and ii) identify barriers to and enablers of algorithm use in routine practice.MethodsWe conducted semi-structured interviews with primary care professionals in Ottawa, Canada. To evaluate usability, participants used a written patient scenario to work through the algorithm while verbalizing their thoughts (‘Think Aloud’). Participants were then asked about factors influencing algorithm use in routine practice (informed by the Theoretical Domains Framework). We used the codebook approach to thematic analysis to assign statements to pre-specified codes and develop themes pertaining to usability and routine use.ResultsWe interviewed 20 professionals from seven practices. Usability issues were summarised within five themes: Optimizing content and flow to align with issues faced in practice, Enhancing the most useful algorithm components, Interactivity of the algorithm and embedded tools, Clarity of presence, purpose, or function of components, and Navigational challenges and functionality of links. Barriers to and enablers of routine use were summarised within five themes: Getting to know the algorithm, Alignment with roles and pathways of influence, Integration with current ways of working, Contexts for use, and Anticipated benefits and concerns about patient communication.ConclusionsWhilst the Ottawa Depression Algorithm was viewed as a useful tool, specific usability issues and barriers to use were identified. Supplementing a theory-based barriers/enablers assessment with usability testing provided enhanced insights to inform optimization and implementation of this clinical tool. We have provided a methods guide for others who may wish to apply this approach.

Coasting related to taxane-induced peripheral neuropathy in patients with breast cancer: a systematic review

Background and purpose: Chemotherapy-induced peripheral neuropathy (CIPN) is a common dose limiting adverse effect that may be transient or become persistent after the treatment ended. The taxane paclitaxel induces CIPN in 57–83% of patients treated. The neuropathy may debut or progress after the end of treatment (EOT), known as coasting, but little is known about the incidence of this phenomenon. The aim of this review is to examine the incidence and severity of coasting in CIPN in patients with breast cancer. Patient/material and methods: MEDLINE, Embase, clinicaltrials.gov, and medrivx.org were searched using terms related to taxanes, adverse effects, and breast cancer. Studies had to have a follow-up time of at least 3 months after EOT and patients had to have received taxanes in monotherapy. Additionally, studies had to be longitudinal and describe the neuropathy assessment method and timing. Results: A total of 17 studies met the eligibility criteria, with 4,265 participants summarized. Of these, one study reported coasting events in 14.3% (n = 4) of patients. Eight studies reported no coasting events and eight were unclear. Interpretation: Few studies reported on coasting in CIPN. There may be several reasons for this, including the timing and choice of assessment methods, confounding factors, and the possible rarity of the phenomenon. More information is needed about coasting in CIPN to better characterize the neuropathies, guide patient and doctor decisions, and aid in the development of interventions toward CIPN.

Assessing heavy metal contamination in agricultural soils: a new GIS-based Probabilistic Pollution Index (PPI) – case study: Guarda Region, Portugal

ABSTRACT Soil contamination by heavy metals is a global agricultural problem, as these elements can be absorbed by plants and transferred to humans through the food pathway. Current contamination assessment methods rely on in situ sample collection, which restricts the evaluation process due to the number of samples that can be analysed and the associated costs. This study addresses the need for a more efficient and cost-effective approach to identifying areas at risk of heavy metal contamination without the logistical constraints of physical sampling. To meet this challenge, we developed a new Probabilistic Pollution Index (PPI), calculated by integrating GIS tools with an 8-parameter probability-risk matrix to identify agricultural areas potentially contaminated by heavy metals. The factors considered included roads, industrial sites, pH levels, soil organic matter content, terrain slope, soil texture, mining areas, and drainage. Each parameter was classified and reclassified to produce a contamination risk map, categorizing each pixel into five levels of risk. To test the PPI, data analysis, parameter classification, and reclassification were applied in the district of Guarda, Portugal. The PPI map revealed that the central portion of the Guarda municipality, along with specific zones in Celorico da Beira, Sabugal, Mêda, and Pinhel, exhibited a high-probability risk of contamination. Given the agricultural expanse within each municipality, enhanced monitoring of heavy metal levels was recommended for Mêda, Pinhel, and Vila Nova de Foz Côa. This index provides a scalable, cost-effective, and easily replicable tool for identifying potential contamination hotspots and the sources and processes of contamination. Designed as a first-line method for large-scale assessments, it supports governmental decision-making and facilitates targeted risk mitigation strategies through a low-cost approach.

The Relationship Between Body Mass Index, Waist Circumference, Neck Circumference and Cardiovascular Risk Factors

Background: This study aimed to estimate the correlation between body mass index, waist circumference and neck circumference and cardiovascular risk factors in healthy adult men and women with no history of any disease or chronic drug intake from Diyarbakır and Dicle University medical faculties. Materials and methods: The study included 199 subjects, 113 males (mean age 36.5 ± 11.3 years) and 86 females (mean age 33.8 ± 11.7 years) aged between 20 and 73 years. Age, height, weight, blood pressure, pulse rate, anthropometric methods; waist circumference (WC), body mass index (BMI), neck circumference (NC), blood glucose and insulin levels were determined. Insulin resistance was evaluated with the Homeostasis model assessment (HOMA-IR) formula. Total-cholesterol, triglyceride, LDL-cholesterol, HDL-cholesterol levels were measured. Pearson correlation and independent t-test were applied to the obtained study parameters. Results: 47.7% of women were obese, 1.2% were morbidly obese and 59.3% of men were obese. Waist circumference correlated with systolic blood pressure (r=0.426, p<0.001), diastolic blood pressure (r=0.414, p<0.001), total cholesterol (r=0.450, p<0.001), triglycerides (r=0.556, p<0.001) and LDL-cholesterol (i=0.486, p<0.001), and a negative correlation was found between waist circumference and HDL-cholesterol (r=0.261, p<0.001). In women, the relationship between BMI and HOMA-IR (r-0.415, p<0.001) was stronger than the relationship between waist circumference and HOMA-IR (r=0.333, p=0.02). In men, we found a positive correlation between waist circumference and HOMA-IR (r=0.271, p=0.04). In men, we found no correlation between BMI and HOMA-IR. Neck circumference was correlated with waist circumference (i=0.732), total cholesterol (r=0.534), triglycerides (r=0.365), LDL cholesterol (i=0.406), BMI (r=0.568), systolic blood pressure (r=0.200), diastolic blood pressure (r=0. 290), and glucose (r=0.280) (p < 0.001). Conclusions: Waist circumference was more tightly correlated with metabolic parameters. Waist circumference may better reflect the risk of cardiovascular disease than BMI. Neck circumference measurement, a new obesity indicator, can also be used as an obesity assessment method. Keywords: Cardiovascular risk factors, body mass index, waist circumference, neck circumference

Rapid Identification of Saline–Alkali Stress-Tolerant Peanut Varieties Based on Multimodal Data

The cultivation of saline–alkali-tolerant peanut (Arachis hypogaea L.) varieties can effectively increase grain yield in saline–alkali land. However, traditional assessment methods are often cumbersome and time consuming. To rapidly identify saline–alkali stress-tolerant peanut varieties, this research proposed a saline–alkali stress tolerance evaluation method based on deep learning and multimodal data. Specifically, the research first established multimodal datasets for peanuts at different growth stages and constructed a saline–alkali stress score standard based on unsupervised learning. Subsequently, a deep learning network called BO-MFFNet was built and its structure and hyperparameters were optimized by the Bayes optimization (BO) algorithm. Finally, the point prediction of the saline–alkali stress score were carried out by using the Gaussian process regression model. The experimental results show that the multimodal method is superior to the single-modal data and the BO algorithm significantly improves the performance of the model. The root mean squared error and relative percentage deviation of the BO-MFFNet model are 0.089 and 3.669, respectively. The model effectively predicted the salt–alkali stress tolerance of five varieties, and the predicted results were Huayu25, Yuhua31, Yuhua33, Yuhua32, and Yuhua164 from high to low. This research provides a new method for assessing crop tolerance under extreme environmental stress.

Stability Assessment and Reactive Power Compensation Strategies for Grid-Connected Wind Power Generations

With the acceleration of global economic integration and the rapid increase in population, the reserves of mineral resources on the earth are becoming increasingly scarce, and non-renewable resources are becoming increasingly scarce. Technological advances have significantly reduced the cost of photovoltaic and wind power, improved energy storage efficiency and smart grid technology, and solved the intermittent problem of new energy. How to boost the utilization rate of new energy and ensure its secure and reliable operation during grid connection is an important challenge that the current development of electric power technology must tackle. To serve as a guide for the creation of new wind power, this article analyses the two most widely used reactive power compensation devices, studies the method of restoring the stable state through reactive power compensation after the grid-connected wind power becomes unstable, and introduces several control methods for power compensation using reactive power compensation devices. The main objective of this article is to summarize the current mainstream stability assessment methods in the world and compare their benefits and drawbacks.

Filling the Gap in and Evaluation for Saturated Fluorine-Containing Derivatives With Machine Learning.

Lipophilicity and acidity/basicity are fundamental physical properties that profoundly affect the compound's pharmacological activity, bioavailability, metabolism, and toxicity. Predicting lipophilicity, measured by (1-octanol-water distribution coefficient logarithm), and acidity/basicity, measured by (negative of acid ionization constant logarithm), is essential for early drug discovery success. However, the limited availability of experimental data and poor accuracy of standard and assessment methods for saturated fluorine-containing derivatives pose a significant challenge to achieving satisfactory results for this compound class. To overcome this challenge, we compiled a unique dataset of saturated fluorinated and corresponding non-fluorinated derivatives with and experimental values. Aiming to create an optimal approach to acidity/basicity and lipophilicity prediction, we evaluated, trained from scratch, or fine-tuned more than 40 machine learning models, including linear, tree-based, and neural networks. The study was supplemented with a substructure mask explanation (SME), which confirmed the critical role of the fluorinated substituents on both physicochemical properties studied and testified to the consistency of the developed models. The results were open-sourced as a GitHub repository, pip, conda packages, and a KNIME node, allowing the public to perform the targeted molecular design of the proposed class of compounds.

Study on corrosion monitoring and assessment method of reinforced concrete based on multi-sensor fusion

Purpose The purpose of this paper is to investigate the accurate monitoring and assessment of steel bar corrosion in concrete based on deep learning multi-sensor information fusion method. The paper addresses the issue of traditional corrosion assessment models relying on sufficient data volume and low evaluation accuracy under small sample conditions. Design/methodology/approach A multi-sensor integrated corrosion monitoring equipment for reinforced concrete is designed to detect corrosion parameters such as corrosion potential, current, impedance, electromagnetic signal and steel bar stress, as well as environmental parameters such as internal temperature, humidity and chloride ion concentration of concrete. To overcome the small amount of monitoring data and improve the accuracy of evaluation, an improved Siamese neural network based on the attention mechanism and multi-loss fusion function is proposed to establish a corrosion evaluation model suitable for small sample data. Findings The corrosion assessment model has an accuracy of 98.41%, which is 20% more accurate than traditional models. Practical implications Timely maintenance of buildings according to corrosion evaluation results can improve maintenance efficiency and reduce maintenance costs, which is of great significance to ensure structural safety. Originality/value The corrosion monitoring equipment for reinforced concrete designed in this paper can realize the whole process of monitoring inside the concrete. The proposed corrosion evaluation model for reinforced concrete based on Siamese neural network has high accuracy and can provide a more accurate assessment model for structural health testing.

Anatomy-driven segmentation of parafoveal optical coherence tomography (OCT) measures may improve associations with clinical outcomes in multiple sclerosis.

Previous investigations on optical coherence tomography (OCT) in multiple sclerosis (MS) focused on generalizable macular and peri-papillary regions without considering the anatomic variations of the retinal layer thickness. This study aimed to assess the utility of parafoveal retinal layer thickness measured by OCT, underscoring its relationships with clinical outcomes in MS. In this cross-sectional study, 214 people with MS (pwMS) and 57 age- and sex-matched healthy controls (HCs) were enrolled. Spectral domain OCT evaluation using 1, 3, 6mm Early Treatment Diabetic Retinopathy Study grid were conducted. The macular and parafoveal thickness (excluding the 1mm foveal/umbo contribution) of the retinal nerve fiber layer (RNFL), ganglion cell-inner plexiform layer (GCIPL), ganglion cell layer (GCL), inner plexiform layer (IPL), and the peri-papillary RNFL (pRNFL) were measured. Multivariable step-wise logistic, linear and generalized estimating equation (GEE) regression models were used to assess the association between the OCT parameters and clinical MS outcomes. The parafoveal RNFL thickness (d = 0.27, p = 0.023), GCL (d = 0.87, p < 0.001), IPL (d = 0.82, p < 0.001), and GCIPL (d = 0.85, p < 0.001) were all significantly lower in pwMS than HCs. Optic neuritis history [odds ratio (OR) = 0.84, p < 0.001] and progressive MS (PMS) status (OR = 0.92, p < 0.001) were bothbest predicted by parafoveal GCL. The Expanded Disability Status Scale (EDSS) was associated with the parafoveal thickness of GCL (standardized β = -0.472, p < 0.001) and pRNFL (standardized β = 0.187, p = 0.021). The parafoveal GCL thickness as predictor of MS disability was also confirmed by the GEE models. This investigation supports the potential use of parafoveal OCT segmentation as an alternative assessment method in detecting neuroinflammatory and neurodegenerative processes in MS. Averaging of the parafoveal retinal layer thickness into the OCT measures may increase the sensitivity of the standard macular OCT segmentation outcomes. Further studies should aim at exploring the reproducibility of this OCT outcome and its longitudinal responsiveness.

Incorporating circularity, sustainability, and systems thinking into an assessment framework for transformative food system innovation

The transition towards a circular economy in the food system is posited as way to harmonize the provision safe, ample and accessible food to a growing population with the reduction the food system’s widespread impact on natural resources, the environment, and human health. Within the context of circular food innovation, there is an abundance of assessment approaches allowing researchers to evaluate and guide new technologies, applications, and products. However, specialist circularity tools are underutilized. This research draws from wider circular economy discourse, sustainability assessment methods, and systems-transitions theory to propose a novel framework to appraise and guide circular food innovation. Through a systematic literature review and critical analysis, this work highlights the limitations of existing methods based on a multi-disciplinary lens. In lieu of robust circularity metrics, elaborations within the Life Cycle Assessment (LCA) methodology provide a comprehensive sustainability and circularity assessment, while cross-disciplinary approaches inform the development of technological trajectories in line with system-transitions theories. The proposed framework aims to bridge this gap by providing a holistic approach that incorporates systems perspectives and considers the wider dynamics of sustainability and circular economy via future scenario modelling. By integrating these perspectives, the framework facilitates earlier intervention and broader stakeholder engagement in the sustainability assessment process. Examined primarily within the context of food manufacturing, this work provides new tools for academic research and industrial practitioners, driving transformative change towards a more sustainable and circular food system.

Blood Biomarkers as a Non-Invasive Method for the Assessment of the State of the Fontan Circulation

The Fontan operation has become the primary palliative treatment for patients with a functionally univentricular heart. The population of patients with Fontan circulation is constantly growing and aging. As the number of Fontan patients surviving into adulthood increases, there is a clear need for research on how best to follow these patients and manage their complications. Monitoring blood biomarkers is a promising method for the non-invasive assessment of the Fontan circulation. In this article, we provide a comprehensive review of the available evidence on this topic. The following biomarkers were included: natriuretic peptides, red blood cell distribution width (RDW), cystatin C, high-sensitivity C-reactive protein, vitamin D, parathyroid hormone, von Willebrand factor, carbohydrate antigen 125, lipoproteins, hepatocyte growth factor, troponins, ST2 protein, galectin-3, adrenomedullin, endothelin-1, components of the renin–angiotensin–aldosterone system, norepinephrine, interleukin 6, tumor necrosis factor α, and uric acid. We did not find strong enough data to propose evidence-based recommendations. Nevertheless, significantly elevated levels of brain natriuretic peptide (BNP)/N-terminal prohormone of BNP (NT-proBNP) are most likely associated with the failure of the Fontan circulation. The use of the RDW is also promising. Several biomarkers appear to be useful in certain clinical presentations. Certainly, robust longitudinal, preferably multicenter, prospective studies are needed to determine the sensitivity, specificity, evidence-based cut-off values and overall predictive value of different biomarkers in monitoring Fontan physiology.

PROBLEMS OF ENVIRONMENTAL SECURITY AND WATER SUPPLY NEEDS IN THE CENTRAL ASIAN REGION

he last decade in the Central Asian region has been characterized by a steady trend of increasing fresh water needs due to the expansion of agricultural activities and the growth of population consumption. At the same time, the growth of consumption is ensured exclusively by increasing the anthropogenic load on available water resources, which causes a multiple increase in the risks of environmental disasters and problems with water supply and ensuring water security of the countries of the region. The article uses the method of complex assessment (balance method) of assessing the level of water resources availability in the context of countries, content analysis of regulation of water use of transboundary rivers, factor analysis of the growth of regulation of water flows of the main rivers (Amu Darya and Syr Darya basins, hereinafter abbreviated as BAM) and project analysis of the growth of anthropogenic pressure on the resource base of the region. The study notes that the uncoordinated use of water resources for national development and projects to overcome the environmental problems of shallowing of the Aral Sea only lead to an aggravation of the situation. The conclusions are based on the assessment of projects and strategies for overcoming the environmental catastrophe of the Aral Sea and the construction of new artificial water drainage infrastructure in the countries of the lower reaches of transboundary rivers.

Numerical investigation on degradation mechanism of reinforced concrete structures under close-in explosion

In current practice, the analysis of progressive collapse in building structures widely employs the alternate load path method. However, there are very few collapse tests that can be utilized under blast loads, especially for investigating the degradation mechanism of progressive collapse resistance in post-blast building structures. In this study, the degradation mechanisms and methods for damage assessment of reinforced concrete structures under blast loads were investigated through numerical analysis. A substructure model derived from explosion loads based on a drop-hammer testing machine was validated by comparing with test results, and the established model accurately captured three typical failure modes in the substructure columns and confirmed the axial tensile effects of the columns on the adjacent components. A substructure damage assessment method was used to assess the degree of damage in a 5-story reinforced concrete frame structure under different explosion scenarios. The results show that the degree of damage distribution of the reinforced concrete frame structure exhibited an S-shaped distribution under corner column blast scenarios while an arch-shaped distribution was observed for middle column blast scenarios. Furthermore, empirical formulas based on the explosive mass and distance ( M- R) curves were established. These empirical formulas can help to rapidly predict the damage levels of RC frame structures for a given explosion scenario within a certain scope.

Carbon Footprint of Masson Pine (Pinus massoniana) Seedlings in Southern China: A Life Cycle Inventory and Sensitivities

Masson pine is a crucial species for afforestation and timber production in China; it plays an important role in mitigating global climate warming and increasing carbon sinks. Previous studies have primarily focused on the carbon sequestration potential and carbon storage of mature Masson pine plantations, while studies on the carbon footprint have received little attention. China produces hundreds of millions of seedlings annually, and estimating the carbon footprint of seedling production is crucial for assessing the carbon sink of forestry. By surveying existing Masson pine nursery operations for primary data in Guangxi, southern China, a new process-based life cycle inventory (LCI) dataset per 4 × 8 cm seedling was created, covering all stages from seed collection to the transportation of seedlings to retailers. Incorporating the new LCI data into the life cycle assessment (LCA) method, the total global warming (GW) impact of Masson pine seedlings was estimated to be 0.0232 kg CO2eq, equivalent to 0.873 kg CO2eq per gallon seeding. In this case, the total environmental impact of the Masson pine seedling was dominated by energy consumption (25.76%), chemical fertilizer production and N₂O emissions generated from its application (34.84%), and woven bag use in seedling dispatch (10.77%). Our results indicated that optimizing energy structures and implementing efficient water and nutrient management strategies could significantly reduce carbon emissions during seedling cultivation. This study highlights the potential for optimizing Masson pine production as a model for low-carbon forestry practices globally.

Modified Endothelial Activation and Stress Index: A New Predictor for Survival Outcomes in Classical Hodgkin Lymphoma Treated with Doxorubicin-Bleomycin-Vinblastine-Dacarbazine-Based Therapy

Background: Although the cure rates of classical Hodgkin Lymphoma (cHL) are as high as 90% using the current treatment protocols, the prognosis is poor for primary refractory patients. Thus, a biomarker that can predict patients with early progression at the time of diagnosis is an unmet clinical need. Endothelial activation and stress index (EASIX) and its variant modified EASIX (mEASIX) is a scoring system currently used for the prediction of prognosis in hematologic malignancies. This study aimed to investigate the prognostic value of the mEASIX score in newly diagnosed cHL patients. Methods: Data from 206 patients who underwent positron emission tomography (PET)-guided doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) therapy for cHL between January 2007 and November 2023 were retrospectively analyzed. The prognostic value of the mEASIX score was evaluated using the receiver operating characteristic (ROC) analysis, Cox regression analysis, and the Kaplan–Meier method, and then compared with standard risk assessment methods. Results: The median age at diagnosis was 33 years, and the rate of patients in the advanced stage was 67%. ROC analysis determined an optimal mEASIX score cut-off of 17.28, categorizing patients into mEASIXhigh (47%) and mEASIXlow (53%) groups. The 5-year progression-free survival (PFS) (60% vs. 84.3%) and overall survival (OS) (79.6% vs. 95.8%) were significantly lower in the mEASIXhigh group (p &lt; 0.001). Additionally, multivariate analysis showed that the independent variables affecting PFS included the nodular sclerosing subtype (HR: 0.4), bone marrow involvement (HR: 2.6), and elevated mEASIX (HR: 3.1). Independent variables, which had an effect on OS included elevated mEASIX (HR:3.8) and higher IPS-3 scores (HR:1.9). Furthermore, a higher mEASIX score (≥17.28) was identified as an independent variable indicating primary refractory disease (OR: 6.5). Conclusions: mEASIX is a powerful and easy-to-access marker for the detection of primary refractory disease and prognosis in newly diagnosed cHL cases.

Using Transorbital Sonography for Assessing Traumatic Brain Injury in Patients With Periorbital Hematoma.

The aim of this study is to assess the comparative effectiveness of transorbital sonography (TOS) and the pupillary penlight visual assessment method in patients with traumatic brain injury (TBI) and periorbital hematoma. A total of 140 patients with traumatic brain injury (TBI), meeting the inclusion and exclusion criteria, were selected from a tertiary hospital in Zhejiang Province between January 2022 and December 2023. Pupillary function in all patients was assessed using both TOS and the pupillary penlight visual assessment method on the first, third, and seventh day after admission. The stability and consistency of the measurement results were compared. Stability was determined using the coefficient of variation, whereas consistency was assessed using the intraclass correlation coefficient. The coefficients of variation for the pupillary transverse diameter values measured by TOS were 29.84% (left) and 29.55% (right) on day 1, 27.81% (left) and 26.88% (right) on day 3, and 26.80% (left) and 25.51% (right) on day 7. These values were consistently lower than those obtained through the pupillary penlight visual assessment method, indicating superior stability with the TOS measurement. In addition, the intraclass correlation coefficient analysis demonstrated consistency between the 2 methods, with values ranging from 0.562 to 0.809 (P<0.05), indicating good consistency. TOS represents an innovative tool for neurological assessment. It has been validated that the presence or absence of eyelid edema does not compromise the accuracy of ultrasound-based pupillary function measurements. The 2 methods of measurement exhibit good consistency, with the TOS method demonstrating superior stability in monitoring data. This approach provides a more accurate means of assessing pupillary function in patients with TBI who have periorbital hematoma or facial swelling, particularly when opening the eyelid is challenging, thereby addressing a significant clinical nursing challenge.

Facial assessment methods for inhibiting glycation and aging effects and the correlation between glycation and aging parameters

This study aimed to develop in vivo methods for assessing facial anti-glycation and anti-aging effects and to investigate the link between glycation and aging signs. We utilized an AGE reader to measure AGEs levels on the face and arms, establishing a correlation to validate the reader’s use for facial AGEs detection. Then the product’s 7-day anti-glycation effect was evaluated. And its 56-day anti-aging effects were evaluated using non-invasive probes and VISIA CR, assessing skin tone (skin brightness L* and yellowness b*, skin gloss), texture (skin elasticity R2 and firmness F4, skin pores), and hydration (skin moisture content). Correlations between facial AGEs levels and aging parameters were analyzed. Results indicated a strong correlation between facial and arm AGEs after product application, supporting facial AGEs level as an assessment parameter. The product demonstrated substantial anti-glycation and anti-aging effects, suggesting the methods’ efficacy for cosmetic evaluation. A stronger overall correlation was found between AGEs levels and skin tone than with skin texture and hydration, highlighting glycation’s impact on skin color.