Composition Parameters Research Articles

Different cutoff values of the skeletal muscle mass and myosteatosis result in different clinical impact on overall survival in oncology. A subanalysis of a clinical trial

BackgroundBody composition analysis, particularly the assessment of sarcopenia and myosteatosis, has emerged as a potential prognostic tool in oncology. However, the clinical implication of body composition parameters remains inconsistent, largely due to the variability in cutoff values used across studies. This study examines the influence on prevalence and prognostic influence of different cutoff values for sarcopenia and myosteatosis in patients in a standardized cohort from a large clinical trial (SORAMIC).MethodsThis study included 179 patients with unresectable liver cancer from the palliative arm of the SORAMIC trial. Skeletal muscle index (SMI) was calculated by measuring the cross-sectional area of skeletal muscle at the third lumbar vertebra (L3) on baseline CT scans. We then applied 14 published cutoff definitions for sarcopenia (SMI) and 7 for myosteatosis (muscle attenuation) to determine their prevalence in this cohort. Cox regression models were used to analyze the relationship between sarcopenia, myosteatosis, and OS.ResultsThe prevalence of sarcopenia ranged from 8.9% (Van der Werf et al.) to 69.8% (Lanic et al.). Overall, 3 of the 14 cutoffs [Van Vledder et al. (HR = 1.53, p = 0.03), Coelen et al. (HR = 1.46, p = 0.03), and Derstine et al. (HR = 1.47, p = 0.04)] showed a relevant association with OS. Other cut off values were not associated with OS.The prevalence of myosteatosis varied between 10.1% (Nachit et al.) and 53.1% (Zhang et al.). One of the 7 cutoffs (Chu et al.) demonstrated a relevant association with OS (HR = 1.53, p = 0.03).ConclusionThe large variability in prevalence and prognostic impact observed across different cutoff definitions underscores the urgent need for standardized, cancer-specific cutoff values for SMI and muscle attenuation. Establishing uniform criteria will enhance the reliability and clinical applicability of body composition metrics as prognostic tools in oncology. Further research should focus on refining these cutoffs and validating them across diverse cancer populations.

Transformer-based skeletal muscle deep-learning model for survival prediction in gastric cancer patients after curative resection.

We developed and evaluated a skeletal muscle deep-learning (SMDL) model using skeletal muscle computed tomography (CT) imaging to predict the survival of patients with gastric cancer (GC). This multicenter retrospective study included patients who underwent curative resection of GC between April 2008 and December 2020. Preoperative CT images at the third lumbar vertebra were used to develop a Transformer-based SMDL model for predicting recurrence-free survival (RFS) and disease-specific survival (DSS). The predictive performance of the SMDL model was assessed using the area under the curve (AUC) and benchmarked against both alternative artificial intelligence models and conventional body composition parameters. The association between the model score and survival was assessed using Cox regression analysis. An integrated model combining SMDL signature with clinical variables was constructed, and its discrimination and fairness were evaluated. A total of 1242, 311, and 94 patients were assigned to the training, internal, and external validation cohorts, respectively. The Transformer-based SMDL model yielded AUCs of 0.791-0.943 for predicting RFS and DSS across all three cohorts and significantly outperformed other models and body composition parameters. The model score was a strong independent prognostic factor for survival. Incorporating the SMDL signature into the clinical model resulted in better prognostic prediction performance. The false-negative and false-positive rates of the integrated model were similar across sex and age subgroups, indicating robust fairness. The Transformer-based SMDL model could accurately predict survival of GC and identify patients at high risk of recurrence or death, thereby assisting clinical decision-making.

Influence mechanism of process parameters on axial compressive response of CNTs reinforced filament‐wound riser with metal liner

AbstractCarbon nanotubes (CNTs) reinforced filament‐wound riser with metal liner face critical challenges in maintaining structural integrity under axial compressive loads, especially when subjected to the harsh conditions of deep‐sea environments. However, existing manufacturing processes for filament winding risers lack a comprehensive understanding of how key process parameters interact to influence axial compressive strength. This study aims to deeply explore the influence mechanism of process parameters on the axial compressive strength of CNTs reinforced filament‐wound riser with metal liner. The compressive strength model was constructed by using the multivariate nonlinear method, and the effectiveness of the model was ensured through verification. Meanwhile, the influence mechanism of a single process parameter was analyzed to reveal the internal relationship between the winding tension, feed rate, curing time, and the maximum axial compressive load. The coupling effects of process parameters were analyzed to elucidate the mechanism by which parameter interactions govern compression performance. Furthermore, the sensitivity analysis was carried out to determine the key sensitive parameters, divide the process window, and optimize the parameters. Finally, the optimal process parameters combination with the maximum axial compressive load of 88.4074 kN, 51.7448 N of winding tension, 14.8607 m/min of winding speed, and 6.3741 h of curing time was determined based on the PSO‐GWO algorithm. The research results can provide a novel approach for the manufacturing of high‐performance deep‐sea risers.Highlights Novel approach integrating multiple nonlinear regression and global–local sensitivity analysis. Stable region division method was adopted to determine the optimal ranges for composite wound risers. PSO‐GWO hybrid algorithm was employed to optimize the CNTs reinforced composite process parameters.

The effect of Ramadan fasting on anthropometric and body composition of healthy adults within different time points: A systematic review and meta-analysis.

To date, the effect of Ramadan fasting (RF) on anthropometric and body compositions remains inconsistent. This review aimed to investigate the impact of RF on anthropometric and body composition of healthy adults within different time points during and after RF. Qualified studies from MEDLINE, Web of Science, Embase, CINAHL Complete, ProQuest, and Scopus were included. We involved prospective observational studies with pre- and post-test design. The anthropometric and body composition parameters consist of weight, BMI, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), absolute fat mass (FM), fat percentage (FP), fat-free mass (FFM), and total body water (TBW). Fifty-four studies involving 2857 subjects were identified and conducted in 21 countries between 1987 and 2024. RF exerts a significant reduction in weight and BMI, starting within the second and third week of RF, peaking in the first week after RF, and gradually returning to the pre-Ramadan value in the weeks afterward. Meanwhile, WC, HC, and WHR were significantly alleviated within the last week of RF and the first week post-RF for HC. In body composition, RF elicits a significant but small reduction of absolute FM and FP within the third and fourth week of RF, while FFM and TBW were not affected. During Ramadan, anthropometric and body composition changes are transient and elicit only a short-term effect. Such leverages need to be maintained to achieve a long-term benefit of RF on the anthropometric and body composition of healthy adults.

The impact of immature granulocytes on the outcome of patients with decompensated cirrhosis.

Higher immature granulocyte levels have a predictive role in several clinical conditions, although data concerning cirrhosis are scarce. Reduced muscle mass is a known factor affecting the outcome of these patients. The aim of the study was to evaluate the association of immature granulocytes with muscle mass and their role in predicting the outcome (survival, death or liver transplantation) in patients with stable decompensated cirrhosis. We prospectively studied 210 patients with decompensated cirrhosis awaiting liver transplantation. Their clinical and laboratory characteristics were recorded, including complete blood count with immature granulocyte count and immature granulocyte percentage. The severity of liver disease was evaluated by estimating the Child-Turcotte-Pugh and MELD-sodium scores. Dual energy X-ray absorptiometry was used to quantify the total and regional lean mass, while mid-arm muscle circumference was used for the evaluation of upper limb muscle mass. Immature granulocyte percentage was proved to be the only factor independently associated with transplant-free survival (Hazard Ratio: 1.98, 95% confidence interval [1.03-3.81], p = .04). Stratification of our cohort based on the best discriminative cut-off values of immature granulocyte count and percentage revealed significant differences in the outcome based on Kaplan-Meier curves, while immature granulocyte count and percentage were significantly associated with parameters of body composition. Higher immature granulocyte count and percentage have a significant prognostic role and are associated with worse outcome in patients with stable decompensated cirrhosis.

The impact of CT-based adipose tissue distribution and sarcopenia on treatment outcomes in patients with high-risk soft tissue sarcoma

BackgroundThe prognostic and predictive value of obesity and sarcopenia remains poorly defined in patients with high-risk soft tissue sarcoma (HR-STS). We sought to correlate clinical outcomes with CT-based body composition parameters in patients with HR-STS undergoing a multimodal preoperative therapy. The impact of radiologic and histopathologic response to preoperative treatment was correlated with individual fat and muscle distribution.MethodsPatients with locally advanced non-abdominal HR-STS and treatment with preoperative chemotherapy + regional hyperthermia (RHT) +/- radiotherapy (RT) followed by surgery between 2015 and 2022 were retrospectively evaluated. Body composition parameters measured on baseline CT scans were correlated with clinical outcomes including event-free survival (EFS) and overall survival (OS) as well as radiologic and histopathologic treatment response.ResultsA total of 85 patients were included. Body composition parameters showed no significant correlation with radiologic or histopathologic treatment response. High total fat indices such as the total fat index (TFI, HR 3.56, p = 0.005) and high total fat to muscle ratio (FMR, HR 3.22, p = 0.020) were strongly associated with poor OS. Parameters for sarcopenia including skeletal muscle index (SMI) were not significantly linked to survival outcomes.ConclusionHigh fat indices and a high FMR are strong predictors of poor OS in patients with HR-STS. Larger studies are warranted to further clarify the prognostic impact of sarcopenia and the predictive value of body composition parameters on preoperative treatment response.

FEATURES OF CHANGES IN STRUCTURAL AND COMPOSITION PARAMETERS OF KIDNEY STONES IN PATIENTS OF KHARKIV REGION IN WARTIME CONDITIONS

ANNOTATION. The article presents an analysis of changes in the structural and compositional parameters of kidney stones in patients of the Kharkiv region during the war. The mineral composition and structural state of kidney stones obtained as a result of minimally invasive interventions for urolithiasis were studied. The mineral composition was determined using the infrared spectroscopy method, the structural state of the stones was determined by conducting crystallooptical analysis on a polarizing microscope. The changes in the mineral composition and structural state of kidney stones are characterized by a decrease in the frequency of detection of phosphate-calcium compounds (hydroxylapatite), an increase in the quantitative presence of calcium oxalate monohydrate and dihydrate, a decrease in the degree of crystallinity, which may be a consequence of the effects of stress factors of wartime, changes in socio-economic living conditions and environmental parameters in front-line regions.

Morphometric Measurements Prior to Totally Endoscopic Mitral Valve Repair: Technical and Educational Aspects

Objective: The totally endoscopic approach is on the rise to become the new standard in mitral valve surgery. The aim of this study was to develop a morphometric measurement tool for educational purposes to predict operability with low conversion and high repair rates. Methods: From January 2020 to March 2023, 64 patients underwent totally endoscopic mitral valve repair (TE-MVR). Of these, 15 patients were deemed to be unsuitable for TE-MVR due to narrow space and/or anticipated complex repair techniques and underwent repair through sternotomy (MVR-open). Angio-CT scanning was performed for preoperative planning and measurements of the following: the distance between the sternum and the spine (DSS), the distance between the skin incision and the anterior anulus of the mitral valve (DNM) and the intercostal space at the level of the skin incision (ICS). Results: The repair rate for all patients was 98.7%. In the TE-MVR group, the conversion rate to sternotomy was 3.1%. The 30-day survival was 100%. The DSS was 130.4 ± 18.8 mm and 108.1 ± 17.3 mm, and the DSM 70.7 ± 12.1 mm and 58.5 ± 13.6 mm in the TE-MVR and MVR-open, respectively (p < 0.001). Twenty-one TE-MVR patients were found to be technically demanding due to friction and less freedom to move the instruments. The composite morphometric parameter DSS plus 4xICS minus DNM was 53.3, 39.8 and 25.6 for TE-TMReasy, TE-TMRdemanding and MVR-open, respectively (p < 0.05 and p < 0.01). Conclusions: Surgical skills and a long history of expertise are mandatory to achieve excellent results with a low conversion and high repair rate. The composite morphometric parameter may be an easy tool for educational demands to predict the ease and feasibility of TE-MVR.

Polyvinyl Alcohol-Based Membranes: A Review of Research Progress on Design and Predictive Modeling of Properties for Targeted Application

This review provides a comprehensive evaluation of the current state of polyvinyl alcohol (PVA)-based membranes, emphasizing their significance in membrane technology for various applications. The analysis encompasses both experimental and theoretical research articles, with a focus on recent decades, aiming to elucidate the potential and limitations of different fabrication approaches, structure–property relationships, and their applicability in the real world. The review begins by examining the advanced polymeric materials and strategies employed in the design and processing of membranes with tailored properties. Fundamental principles of membrane processes are introduced, with a focus on general modeling approaches for describing the fluid transport through membranes. A key aspect of discussion is the distinction between the membrane performance and process performance. Additionally, an in-depth analysis of PVA membranes in various applications is presented, particularly in environmental fields (e.g., fuel cell, water treatment, air purification, and food packaging) and biomedical domains (e.g., drug delivery systems, wound healing, tissue engineering and regenerative medicine, hemodialysis and artificial organs, and ophthalmic and periodontal treatment). Special attention is given to the relationship between membranes’ characteristics, such as material composition, structure, and processing parameters, and their overall performance, in terms of permeability, selectivity, and stability. Despite their promising properties, enhanced through innovative fabrication methods that expand their applicability, challenges remain in optimizing long-term stability, improving fouling resistance, and increasing process scalability. Therefore, further research is needed to develop novel modifications and composite structures that overcome these limitations and enhance the practical implementation of PVA-based membranes. By offering a systematic overview, this review aims to advance the understanding of PVA membrane fabrication, properties, and functionality, providing valuable insights for continued development and optimization in membrane technology.

Wear Characteristics and Optimization Measures of Disc Cutters During Large-Diameter Slurry Tunnel Boring Machine Advancing in Soil-Rock Composite Strata: A Case Study

The large-diameter slurry tunnel boring machine (TBM) is widely used in the construction of tunnels across rivers and seas. However, cutter wear has become a critical issue that severely limits the tunnelling efficiency. Taking the Qingdao Jiaozhou Bay Second Subsea Tunnel Project as the background, the wear patterns of disc cutters on the atmospheric cutterhead of a large-diameter slurry TBM under complex geological conditions were analyzed. The flat wear of disc cutters induced by factors such as rock chip accumulation in front of the cutterhead, the jump trajectory when changing disc cutters, alloy-insert disc cutter mismatch, cutter barrel clogging, and severe wear of scrapers is discussed. Furthermore, the impacts of measures such as slurry circulation to remove rock chips during TBM stoppage, clay dispersant injection into the slurry chamber, cutter barrel flushing, and the wear resistance optimization of cutters and cutter barrels on reducing cutter wear were investigated. Based on numerical simulations and field data, a methodology for determining the optimal timing for cutter replacement is proposed. The results indicate the following: The circulation system effectively reduces accumulation, minimizing secondary wear of the disc cutters and lowering the risk of clogging in the cutter barrel. Adopting measures such as shield shutdown, a circulation system to carry away the slag, cutter barrel flushing, and soaking in 2% dispersant for 8 h can effectively reduce the accumulation of rock chips and mud cakes on the cutterhead, which in turn reduces the flat wear of the disc cutter. Measures such as making the cutter body and cutter ring rotate together and adding wear-resistant plates to the cutter barrel greatly improve the life of the cutter. The sharp increase in composite parameters can serve as an effective marker for assessing cutter conditions. The findings of this study can provide valuable insights into reducing cutter wear in similar projects.

Looking at or beyond the tumor - a systematic review and meta-analysis of quantitative imaging biomarkers predicting pancreatic cancer prognosis.

To evaluate the prognostic value of quantitative imaging biomarkers derived from computed tomography (CT) and magnetic resonance imaging (MRI) for pancreatic cancer (PC), with a particular focus on body composition parameters beyond the traditional intrinsic features of the tumor. PubMed, EMBASE, and Cochrane Library databases were searched for articles on quantitative imaging biomarkers obtained from CT or MRI in predicting PC prognosis published between January 2014 and August 2024. The Newcastle-Ottawa scale was used to assess the quality of the included studies. Survival outcomes, such as overall survival (OS) and recurrence-free survival (RFS), were evaluated. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using a random-effects model. In case of high heterogeneity, subgroup analyses and sensitivity analyses were performed to identify potential sources of heterogeneity among the studies. We performed a meta-analysis of ten imaging biomarkers investigated in 43 included studies. Larger tumor size, lower skeletal muscle radiodensity, lower skeletal muscle index (SMI), presence of sarcopenic obesity, lower psoas muscle index (PMI), higher visceral to subcutaneous adipose tissue area ratio, and lower visceral adipose tissue index were associated with significantly worse OS. In particular, lower SMI and lower PMI had relatively high HRs (1.65 for SMI, 95% CI 1.39-1.96, and 2.20 for PMI, 95% CI 1.74-2.78). Patients with lower SMI exhibited poorer RFS (HR 1.78, 95% CI 1.46-2.18). Subgroup analyses identified the origin region of the study and intervention type as potential factors of heterogeneity for SMI in predicting OS. Imaging biomarkers indicating body composition at PC diagnosis may play an important role in predicting patient prognosis. Further prospective multi-center studies with large sample sizes are needed for validation and translation into clinical practice.

Using body composition to predict treatment-related adverse events and disease-free survival in patients with gastrointestinal stromal tumors treated with imatinib: a retrospective cohort study

BackgroundImatinib (IM) is the primary treatment for Gastrointestinal stromal tumor (GIST), but it faces significant challenges with resistance and a high incidence of adverse events. This study aims to assess the predictive value of baseline body composition parameters on treatment-related adverse events and disease-free survival (DFS) in GIST patients treated with imatinib.Materials and MethodsA single-center retrospective analysis was conducted on 107 moderate or high-risk stratification GIST patients diagnosed from 2014 to 2020 at the First Affiliated Hospital of Nanjing Medical University. Body composition parameters, including skeletal muscle index (SMI), myosteatosis, cachexia index (CXI), and Fat-Free Mass (FFM), etc. were obtained using abdominal CT images and clinical data. Logistic and COX regression models were used to analyze the relationship between these indicators and treatment-related adverse events and DFS.ResultsMultivariate analysis revealed that myosteatosis (OR=7.640, P<0.001) and drug dose (OR=1.349, P=0.010) were independent risk factors for adverse events, while a higher CXI (OR=0.983, P=0.017) was protective. Additionally, LAMA/SMA% (OR=1.072, P=0.028) was identified as an independent risk factor for dose-limiting toxicity (DLT). Independent predictors of DFS included sarcopenia (HR=3.067, P=0.013), myosteatosis (HR=6.985, P=0.024), risk stratification (HR=9.562, high-risk vs. moderate-risk, P=0.003), and C-KIT mutation (HR=3.615, C-KIT exon 9 mutation vs. 11, P=0.013).ConclusionsBaseline body composition parameters, particularly myosteatosis, effectively predict the adverse events and DFS in patients taking imatinib. Personalized treatment, such as targeted nutritional and exercise interventions, and close monitoring of patients with myosteatosis or sarcopenia can enhance compliance and improve survival rates.

Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies

Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study, we developed and validated a flexible, open-access pipeline integrating available deep learning-based segmentation models with pre- and postprocessing steps to extract body composition measures from routine computed tomography (CT) scans. In 337 surgical oncology patients, total skeletal muscle tissue (SMtotal), psoas muscle tissue (SMpsoas), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were quantified both manually and using the pipeline. Automated and manual measurements showed strong correlations (SMpsoas: r = 0.776, VAT: r = 0.993, SAT: r = 0.984; all P < 0.001). Measurement discrepancies primarily resulted from segmentation errors, anatomical anomalies or image irregularities. SMpsoas measurements showed substantial variability depending on slice selection, whereas SMtotal, averaged across all L3 levels, provided greater measurement stability. Overall, SMtotal performed comparably to SMpsoas in predicting overall survival (OS). In summary, body composition measures derived from the pipeline strongly correlated with manual measurements and were prognostic for OS. The increased stability of SMtotal across vertebral levels suggests it may serve as a more reliable alternative to psoas-based assessments. Future studies should address the identified areas of improvement to enhance the accuracy of automated segmentation models.

Time for Change: A 3-Year Prospective Study on Mediterranean Diet Adherence and Body Composition in Kidney Transplant Recipients.

The aim of this prospective follow-up study was to evaluate changes in body composition parameters and Mediterranean diet (MeDi) adherence among kidney transplant recipients (KTRs) over a three-year period. Additionally, this study sought to investigate the associations between these changes and clinical parameters, including laboratory parameters, new onset of diseases, and death outcome. A total of 116 KTRs were initially assessed in 2019 and subsequently re-evaluated in 2022. The Mediterranean Diet Serving Score (MDSS) was used to assess dietary adherence to the MeDi at baseline and follow-up assessments. Bioelectrical impedance analysis was used to assess body composition and clinical outcomes were assessed by the data available from medical charts. After three years, MeDi adherence significantly decreased (p = 0.028) from 15 (18.29%) to 5 (6%), with dominantly lower adherence for vegetable, fruit, legume, red meat, olive oil and fish intake. Regarding body composition parameters, the most prominent change was seen in muscle mass, which deteriorated from 41.77% (IQR 6.46) to 39% (IQR 6.14; p = 0.004). However, changes in fat mass level were not significant in the follow-up period. Furthermore, cereal intake, fasting blood glucose (FBG), cholesterol level, level of low-density lipoprotein cholesterol (LDL), triglyceride leve and presence of diabetes mellitus lwere shown to be predictive for the decline of skeletal muscle mass. There were no significant changes in the estimated glomerular filtration rate (eGFR) or albuminuria level during the follow-up period. Associations with the death outcome were found for the MeDi-advised intake of eggs (β = -1.06, HR = 0.35, CI (0.14-0.87), p = 0.023), phase angle (PhA) (β = -2.68, HR = 0.07, CI (0.01-0.43), p = 0.004), cholesterol level (β = 0.95, HR = 2.60, CI (1.40-4.70), p = 0.001) and calcium level (β = -7.21, HR = 0.00, CI (0.00-1.50), p = 0.063). This study highlights a significant decline in MeDi adherence and skeletal muscle mass among KTRs over a three-year follow-up period, with no notable changes in fat mass or kidney function. The predictors of muscle mass loss and associations with mortality underscore the importance of dietary and clinical management in this population.

Expression Patterns of miR‐29b and miR‐148a in Colostrum of Awassi Sheep With Higher Immunoglobulin G Levels

ABSTRACTThis study aimed to investigate the compositional parameters and expression patterns of miR‐29b and miR‐148a in sheep colostrum containing low and high levels of Immunoglobulin G (IgG). Blood and colostrum samples were collected within the first 6 h following birth from 24 pregnant Awassi sheep. On the basis of the determined colostrum IgG levels, low (Low IgG [LIGG], 44.83 ± 4.97 mg/mL) and high (High IgG [HIGG], 80.71 ± 3.31 mg/mL) groups were formed. In addition to measuring colostrum compositional parameters, expressions of miR‐29b and miR‐148a were determined in plasma and colostrum. Although somatic cell score (SCS), pH and electrical conductivity (EC) were higher, fat‐free dry matter (FFDM), protein, lactose and freezing point were lower in HIGG group. Compared to LIGG, miR‐29b was downregulated approximately 5‐fold in the HIGG, whereas miR‐148a was downregulated more than 3‐fold in colostrum. There were negative correlations between colostrum miR‐148a and colostrum IgG, SCS and pH. Colostrum IgG was positively correlated with pH and freezing point and negatively correlated with FFDM, protein and lactose. Area under the curve (AUC) values of SCS, pH, FFDM, protein, lactose, freezing point, EC and miR‐148a (colostrum) were significant. Sensitivity and specificity of pH were 100% and 66.7%, of SCS were 81.8% and 66.7% and of miR‐148a (Colostrum) were 75% and 75% in HIGG and LIGG. According to the results, miR‐29b might be an important molecular target for lamb development, whereas miR‐148a could be a potential biomarker for colostrum quality. Moreover, the study showed that SCS and pH might be useful diagnostic parameters for IgG status because of higher sensitivity rates and AUC values.

Geographical Variations in Egg Nutrient Density: A Comparative Study of Sustainable Layer Hen Systems in Ohio and Indiana in Late Fall and Early Winter Months

Regenerative, pasture-raised layer hen systems create synergistic relationships between the hens, forage, soil, and weather, fostering a sustainable system. However, the influence of these factors on egg nutrient profile and quality may vary by region. This study took place over two years; samples were collected from a farm in Ohio during the first year and a farm in Indiana during the second year. Egg (n = 12) and forage (n = 3) samples were collected monthly from September to December. Fatty acids were quantified using gas chromatography-mass spectrometry, micronutrients were assessed in a commercial laboratory, and carotenoids and polyphenols were analyzed colorimetrically. Ohio eggs had significantly darker yolks (average yolk fan score: 8.5 ± 1.8 vs. 3.9 ± 2.0; p &lt; 0.0001), a higher beta carotene and carotenoid content, and a lower n-6:n-3 fatty acid ratio across the season. Indiana eggs had a lower average total phenolic content (0.07 ± 0.00 mg GAE/g vs. 0.14 ± 0.10 mg GAE/g) and lower average total cholesterol (5.35 ± 2.9 mg/g vs. 10.99 ± 1.54 mg/g). Forage composition and soil parameters varied between farms. Regional variations in forage composition, soil nutrients, and regional weather can significantly influence the nutrient density of eggs produced in sustainable, pasture-raising systems. This research highlights how local environmental factors can shape the nutritional profiles of eggs in different regions. Future studies should explore this relationship in more regions.

Study on the degradation mechanism of mechanical properties of red sandstone under static and dynamic loading after different high temperatures

To study the effect of high temperature on the mechanical properties of red sandstone, YNS600 electro-hydraulic servo universal testing machine and pneumatic separating Hopkinson press bar (SHPB) device were respectively used to conduct static and dynamic load loading tests on red sandstone after 500~1000 ℃ action, and X diffraction detection. The damage pattern and mechanical property index changes before and after high temperature action were compared, and the relationship between mineral composition, microstructure and mechanical parameters of the specimens and temperature was analyzed, and a theoretical model was constructed. With the increase of temperature, the peak strength and elastic modulus under static and dynamic loading decreased significantly, and compared with the static stress-strain curve, the dynamic stress-strain curve did not have an obvious compaction phase, and the mass loss rate, volume expansion rate, and longitudinal wave velocity attenuation rate increased above 600 ℃. Minerals such as zeolite and pyrite within the red sandstone specimen gradually reacted after high temperature. The theoretical model explains the degradation mechanism of the mechanical properties of red sandstone under the action of idealized high temperature. The research results can provide a reliable scientific basis for the assessment and prediction of rock engineering after high-temperature fire.

Neurofilament Light Chain Levels, Skeletal Muscle Loss, and Nutritional Decline: Key Prognostic Factors in Amyotrophic Lateral Sclerosis

ABSTRACTIntroduction/AimsHypermetabolism and weight loss are established negative prognostic factors in amyotrophic lateral sclerosis (ALS). However, the role of individualized body composition parameters in predicting ALS progression has been underexplored. This study aimed to investigate the correlation between nutritional parameters, neurofilament light chain (NfL) levels, and disease progression in ALS patients.MethodsThe Global Leadership Initiative on Malnutrition criteria were used to define malnutrition in this study. Nutritional status was assessed using body mass index and bioelectrical impedance analysis. The rate of disease progression was defined by the change in the Revised ALS Functional Rating Scale score (ΔFRS). NfL was quantified using single molecule array technology. Spearman's analyses were used to assess correlations.ResultsSixty of 110 ALS patients were classified as malnourished. There was a strong positive correlation between NfL and ΔFRS (r = 0.71), and a moderate negative correlation with disease duration (r = −0.55). The correlations between NfL and body composition parameters were statistically significant, although weak. NfL levels were significantly higher in fast progressors (p &lt; 0.0001 compared to slow progressors) and in malnourished patients (p = 0.0001). Of the 34 fast progressor patients, 28 (82%) exhibited some degree of malnutrition.DiscussionOur findings indicate that poor nutritional status, particularly reduced skeletal muscle mass—both independently and in combination with fat mass loss—is associated with elevated NfL levels and faster ALS progression. NfL, combined with nutritional parameters, could serve as a valuable biomarker for disease severity. Further research is warranted to clarify the role of skeletal muscle abnormalities in ALS progression.

Accuracy of anthropometric-based predictive equations for tracking fat mass over a competitive season in elite female soccer players: a validation study

Background and aimsBody fat is a key body composition parameter monitored in soccer. Identifying reliable alternatives to laboratory techniques for assessing body fat during the competitive period is essential. This study aimed to evaluate the cross-sectional and longitudinal validity of anthropometric prediction equations in elite female soccer players.MethodsEighteen female soccer players (age: 26.6 [3.8] years; height: 168 [6.3] cm; body mass: 64.1 [7.4] kg; body mass index: 22.7 [1.9] kg/m²) from an Italian Serie A team were assessed at four time points during a competitive season. Fat mass was estimated using anthropometric equations by Evans and Warner and compared to dual-energy X-ray absorptiometry (DXA), which served as the reference method.ResultsCross-sectional agreement analysis revealed a bias of -4.5% with Warner’s equation, while Evans’s equation showed no bias compared to DXA, with coefficient of determination (R²) values of 0.69 and 0.70, respectively. Both methods showed a negative association (Evans: r = -0.53, Warner: r = -0.63) when the difference between the values and the mean with DXA were correlated. Longitudinal agreement analysis showed no significant differences in fat mass changes between the anthropometric equations and DXA, with R² values ranging from 0.68 to 0.83. The 95% limits of agreement between the methods for individual changes in fat mass ranged from − 3.3 to 3.2%. Furthermore, no significant changes (p > 0.05) in fat mass were observed over the season with any method.ConclusionsAt the group level, Evans’s equation provides valid estimates of fat mass, whereas it may overestimate values in players with low body fat and underestimate them in those with high fat mass. The Warner equation showed the same trend as Evans at the individual level, also resulting in poor accuracy at the group level. Despite this, both anthropometric equations are valid alternatives to DXA for monitoring fat mass changes during the season, with Evans’s equation showing superior overall performance.

Clinical and Radiological Fusion: A New Frontier in Predicting Post-Transplant Diabetes Mellitus

This study developed a predictive model for Post-Transplant Diabetes Mellitus (PTDM) by integrating clinical and radiological data to identify at-risk kidney transplant recipients. In a retrospective analysis across three Mayo Clinic sites, clinical metrics were combined with deep learning analysis of pre-transplant CT images, focusing on body composition parameters like adipose tissue and muscle mass instead of BMI or other biomarkers. Among 2,005 nondiabetic kidney recipients, 335 (16.7%) developed PTDM within the first year. PTDM patients were older, had higher BMIs, elevated triglycerides, and were more likely to be male and non-White. They exhibited lower skeletal muscle area, greater visceral adipose tissue (VAT), more intermuscular fat, and higher subcutaneous fat (all p &amp;lt; 0.001). Multivariable analysis identified age (OR: 1.05, 95% CI: 1.03–1.08, p &amp;lt; 0.0001), family diabetes history (OR: 1.55, CI: 1.14–2.09, p = 0.0061), White race (OR: 0.43, CI: 0.28–0.66, p &amp;lt; 0.0001), and VAT area (OR: 1.37, CI: 1.14–1.64, p = 0.0009) as predictors. The combined model achieved C-statistic of 0.724 (CI: 0.692–0.757), outperforming the clinical-only model (C-statistic 0.68). Patients with PTDM in the first year had higher mortality than those without PTDM. This model improves predictive precision, enabling accurate identification and intervention for at risk patients.