RANKL/RANK contributes to the pathological process of type 2 diabetes mellitus through TRAF3 activation of NIK.

Diabetic osteoporosis is a complication of diabetes mellitus (DM). Denosumab (DMB) is an effective anti-osteoporotic drug functions by inhibiting NF-κB ligand receptor-activating factor (RANKL). Previous study found that osteoprotegerin (OPG) regulated ßcell homeostasis through the RNAK/RANKL pathway. The present study aimed to investigate the effect of RANKL/RANK on the pathological process of DM and the underlying mechanism. We used D-glucose-induced RINm5F cells to construct in vitro type 2 diabetes models (T2DM). A high-fat diet combined with intraperitoneal injection of streptozotocin (STZ) was used to establish a T2DM model in SD rats. The apoptosis of ß-cells was determined by TdT-mediated dUTP nick-end labeling (TUNEL) analysis. qRT-PCR and western blotting assays were used to explore the mRNA and protein expression of the TRAF3 (Tumor necrosis factor receptor-associated factor)/NIK (NF-κB-inducible kinase) pathway. Furthermore, insulin expression was detected by ELISA and immunohistochemistry assay. The islet morphology was analyzed by H&E. In vivo experiments demonstrated that sRANKL-IN-3 down-regulated insulin secretion levels by significantly ameliorating pancreatic tissue damage and mitigating apoptosis of high glucose induced ß-cells. Subsequently, sRANKL-IN-3, acting as an inhibitor of RANKL, mitigated functional decline in ß-cells induced by high glucose, mainly manifested by the low expression of PDX-1 (pancreatic duodenal homeobox 1), BETA2 (beta-2 adrenoceptors), INS-1 (insulin 1), and INS-2 (insulin 2). Mechanistic studies revealed that deletion of TRAF3 combined with sRANKL-IN-3 administration reduced the activity of NIK, NF-κB2, and RelB in RINm5F cells. In addition, our study demonstrated that inhibition of either RANKL or TRAF3 had a protective effect on high glucose induced apoptosis. Moreover, the combined action of sRANKL-IN-3 and shTRAF3 had a more pronounced inhibitory effect on high glucose-induced apoptosis. In summary, RANKL/RANK deficiency may attenuate apoptosis of ß-cells, a phenomenon associated with the TRAF3/NIK pathway. Therefore, RANKL/RANK could be regarded as a potential therapeutic strategy for DM.

QRAGE-Simultaneous multiparametric quantitative MRI of water content, T1, T2*, and magnetic susceptibility at ultrahigh field strength.

PURPOSE: To introduce quantitative rapid gradient-echo (QRAGE), a novel approach for the simultaneous mapping of multiple quantitative MRI parameters, including water content, T1, T2*, and magnetic susceptibility at ultrahigh field strength. METHODS: QRAGE leverages a newly developed multi-echo MPnRAGE sequence, facilitating the acquisition of 171 distinct contrast images across a range of inversion and TE points. To maintain a short acquisition time, we introduce MIRAGE2, a novel model-based reconstruction method that exploits prior knowledge of temporal signal evolution, represented as damped complex exponentials. MIRAGE2 minimizes local Block-Hankel and Casorati matrices. Parameter maps are derived from the reconstructed contrast images through postprocessing steps. We validate QRAGE through extensive simulations, phantom studies, and in vivo experiments, demonstrating its capability for high-precision imaging. RESULTS: In vivo brain measurements show the promising performance of QRAGE, with test-retest SDs and deviations from reference methods of < 0.8% for water content, < 17 ms for T1, and < 0.7 ms for T2*. QRAGE achieves whole-brain coverage at a 1-mm isotropic resolution in just 7 min and 15 s, comparable to the acquisition time of an MP2RAGE scan. In addition, QRAGE generates a contrast image akin to the UNI image produced by MP2RAGE. CONCLUSION: QRAGE is a new, successful approach for simultaneously mapping multiple MR parameters at ultrahigh field.

Analysing lapsing rates among first-time blood donors at a blood centre in Zimbabwe using survival analysis.

Introduction: blood centres are often faced with the problem of donor lapsing resulting in loss of donors from the already strained donor pool. In Zimbabwe, 70% of the donated blood comes from younger donors aged 40 years and below, who at the same time, have high attrition rates. This study seeks to apply the concept of survival analysis in analysing blood donor lapsing rates. Methods: in analysing the donor lapsing and retention rates, data on 450 first-time blood donors at the National Blood Service Zimbabwe, in Harare´s blood bank for the period 2014 to 2017 was extracted from the donors´ database. The Cox proportional hazards (Cox PH) and Kaplan-Meier methods were applied in the analysis. Donor demographic characteristics suspected of having effect on donor lapsing and retention were identified and analysed. Results: the study findings show that 56.9% of the donors had lapsed by the end of the four-year study period. Results from the multiple Cox PH model indicate that donor age had a significant effect on blood donor retention time (p = 0.000918 < 0.05). The hazard ratio (HR) = 0.615 with 95% CI: (0.461; 0.820) shows that the relatively older donors had a lower hazard (38.5% lower) of lapsing compared to the hazard for younger donors. The effect of gender, blood donor group and donation time interval on donor retention and attrition were not statistically significant. Male donors had HR = 1.03; 95% CI (0.537; 1.99) with (p = 0.922 > 0.05) and donors with a 4-month interval between donations had HR = 1.31; 95% CI (0.667; 2.59) with (p = 0.430 > 0.05). Conclusion: the study confirmed the problem of donor attrition faced by blood centres. The age of the donor had a significant effect on the retention time of blood donors before lapsing. The older the blood donor, the lower the risk of lapsing. The Zimbabwe National Blood Service (NBSZ) Blood Centre authorities should have a critical mass of individuals above 40 years as potential blood donors because of their reliability in blood donation according to the study findings.

Phylogenetic association analysis with conditional rank correlation.

Phylogenetic association analysis plays a crucial role in investigating the correlation between microbial compositions and specific outcomes of interest in microbiome studies. However, existing methods for testing such associations have limitations related to the assumption of a linear association in high-dimensional settings and the handling of confounding effects. Hence, there is a need for methods capable of characterizing complex associations, including nonmonotonic relationships. This article introduces a novel phylogenetic association analysis framework and associated tests to address these challenges by employing conditional rank correlation as a measure of association. The proposed tests account for confounders in a fully nonparametric manner, ensuring robustness against outliers and the ability to detect diverse dependencies. The proposed framework aggregates conditional rank correlations for subtrees using weighted sum and maximum approaches to capture both dense and sparse signals. The significance level of the test statistics is determined by calibration through a nearest-neighbour bootstrapping method, which is straightforward to implement and can accommodate additional datasets when these are available. The practical advantages of the proposed framework are demonstrated through numerical experiments using both simulated and real microbiome datasets.

RANK in cancer-associated fibroblasts: A valuable prognostic determinant for metastasis in early-stage breast cancer patients.

BACKGROUND: The molecular system of receptor activator of nuclear factor kappa-ß (RANK) and its ligand (RANKL) plays a role in a variety of physiological and pathological processes. These encompass the regulation of bone metabolism, mammary gland development, immune function, as well as their involvement and tumorigenesis. Nevertheless, limited knowledge exists regarding their function within the tumor microenvironment. METHODS AND RESULTS: We explored the significance of RANK expression in cancer-associated fibroblasts (CAFs) as a prognostic biomarker in early breast cancer patients (BCPs) by immunohistochemistry. Results reveal a significant correlation between high RANK expression in CAFs and an increased risk of metastasis (p= 0.006), shorter metastasis-free survival (MFS) [p= 0.007, OR (95%CI) = 2.290 (1.259-4.156)], and lower overall survival (OS) [p= 0.004, OR (95%CI) = 2.469 (1.343-4.541)]. Upon analyzing the phenotype of CD34(-) CAFs isolated from primary tumors in BCPs, we observed co-expression of RANK with CD105 marker by immunofluorescence and flow cytometry, characteristic of mesenchymal stem/stromal cells (MSCs), suggesting the possible cellular origin. Also RANKL-RANK system increase the OCT-4, SOX-2 and DKK-1 (dickkopf 1) gene expression in CD34(-) CAFs by RT-PCR. Moreover, this system plays a crucial role in the migration of these CD34(-) CAFs. CONCLUSIONS: These results support the clinical relevance of RANK in CAFs and propose its potential as a future therapeutic target in the treatment of early BCPs.

Dietary patterns, inflammatory biomarkers and cognition in older adults: An analysis of three population-based cohorts.

BACKGROUND: Targeting effective strategies to prevent cognitive decline is key in the aging population. Some diets have been linked to a slower cognitive decline, potentially through reducing inflammation. We aimed at determining the effect of inflammatory dietary patterns (IDPs) on cognitive function in three population-based cohorts. METHODS: In this longitudinal study, we analyzed data from the Canadian Longitudinal Study of Aging, CoLaus|PsyCoLaus and Rotterdam Study. Our analytical sample included participants over 55 years old with baseline data on cognition, dietary intake, and inflammatory markers. IDPs were derived for each cohort using reduced rank regression to reflect maximal variation in three inflammatory markers. We calculated scores of consumption of the IDPs, higher scores indicating more IDP consumption. We used inverse probability of treatment and censoring weights in the marginal structural models to estimate associations of higher versus lower quarters of consumption of an IDP on general cognition (Mini-Mental State Evaluation) and four cognitive domains (memory, verbal fluency, verbal learning and processing speed and executive function) during at least 3 years of follow-up. RESULTS: We included 10,366 participants (mean age 68) followed-up for a mean of 5 years. Diet explained between 1 and 2% of the variation of the inflammatory markers. There were no differences in general cognition when comparing the highest to the lowest quarter of consumption of IDPs among the three cohorts. Mean differences for the four cognitive domains were of small magnitude across cohorts and not clinically relevant. CONCLUSION: Diet explained low variation in inflammatory markers. Consuming IDPs was not associated with mean differences in general or domain-specific cognitive function.

Topology-preserving segmentation of abdominal muscle layers from ultrasound images.

BACKGROUND: In clinical anesthesia, precise segmentation of muscle layers from abdominal ultrasound images is crucial for identifying nerve block locations accurately. Despite deep learning advancements, challenges persist in segmenting muscle layers with accurate topology due to pseudo and weak edges caused by acoustic artifacts in ultrasound imagery. PURPOSE: To assist anesthesiologists in locating nerve block areas, we have developed a novel deep learning algorithm that can accurately segment muscle layers in abdominal ultrasound images with interference. METHODS: We propose a comprehensive approach emphasizing the preservation of the segmentation's low-rank property to ensure correct topology. Our methodology integrates a Semantic Feature Extraction (SFE) module for redundant encoding, a Low-rank Reconstruction (LR) module to compress this encoding, and an Edge Reconstruction (ER) module to refine segmentation boundaries. Our evaluation involved rigorous testing on clinical datasets, comparing our algorithm against seven established deep learning-based segmentation methods using metrics such as Mean Intersection-over-Union (MIoU) and Hausdorff distance (HD). Statistical rigor was ensured through effect size quantification with Cliff's Delta, Multivariate Analysis of Variance (MANOVA) for multivariate analysis, and application of the Holm-Bonferroni method for multiple comparisons correction. RESULTS: We demonstrate that our method outperforms other industry-recognized deep learning approaches on both MIoU and HD metrics, achieving the best outcomes with 88.21%/4.98 ( p m a x = 0.1893 $p_{max}=0.1893$ ) on the standard test set and 85.48%/6.98 ( p m a x = 0.0448 $p_{max}=0.0448$ ) on the challenging test set. The best&worst results for the other models on the standard test set were (87.20%/5.72)&(83.69%/8.12), and on the challenging test set were (81.25%/10.00)&(71.74%/16.82). Ablation studies further validate the distinct contributions of the proposed modules, which synergistically achieve a balance between maintaining topological integrity and edge precision. CONCLUSIONS: Our findings validate the effective segmentation of muscle layers with accurate topology in complex ultrasound images, leveraging low-rank constraints. The proposed method not only advances the field of medical imaging segmentation but also offers practical benefits for clinical anesthesia by improving the reliability of nerve block localization.

Prioritizing test cases for deep learning-based video classifiers.

The widespread adoption of video-based applications across various fields highlights their importance in modern software systems. However, in comparison to images or text, labelling video test cases for the purpose of assessing system accuracy can lead to increased expenses due to their temporal structure and larger volume. Test prioritization has emerged as a promising approach to mitigate the labeling cost, which prioritizes potentially misclassified test inputs so that such inputs can be identified earlier with limited time and manual labeling efforts. However, applying existing prioritization techniques to video test cases faces certain limitations: they do not account for the unique temporal information present in video data. Unlike static image datasets that only contain spatial information, video inputs consist of multiple frames that capture the dynamic changes of objects over time. In this paper, we propose VRank, the first test prioritization approach designed specifically for video test inputs. The fundamental idea behind VRank is that video-type tests with a higher probability of being misclassified by the evaluated DNN classifier are considered more likely to reveal faults and will be prioritized higher. To this end, we train a ranking model with the aim of predicting the probability of a given test input being misclassified by a DNN classifier. This prediction relies on four types of generated features: temporal features (TF), video embedding features (EF), prediction features (PF), and uncertainty features (UF). We rank all test inputs in the target test set based on their misclassification probabilities. Videos with a higher likelihood of being misclassified will be prioritized higher. We conducted an empirical evaluation to assess the performance of VRank, involving 120 subjects with both natural and noisy datasets. The experimental results reveal VRank outperforms all compared test prioritization methods, with an average improvement of 5.76% ∼ 46.51% on natural datasets and 4.26% ∼ 53.56% on noisy datasets.

Serum 25(OH) vitamin D deficiency among young adults in the East Khasi Hills district of Meghalaya and its influence on bone mineral density: Investigating the involvement of the RANKL/RANK/OPG system.

Introduction: Vitamin D's precise role in bone mineral density regulation remains elusive. Nevertheless, its deficiency is linked to increased bone turnover through the upregulation of RANK ligands by osteoblasts. This study aimed to (i) evaluate vitamin D status in young adults and (ii) assess the association between vitamin D deficiency and bone turnover markers receptor activator of nuclear factor-κB ligand (RANKL), RANK, and the osteoprotegerin (OPG) in determining bone mineral density. Materials and Methods: This cross-sectional study involved 474 participants from the East Khasi Hills district, Meghalaya. Vitamin D levels were measured using the UniCel DxI 800 system, while OPG, RANK, and RANKL were assessed through enzyme-linked immunosorbent assay (ELISA). Additionally, a whole-body dual X-ray absorptiometry (DEXA) scan determined bone mineral density. Vitamin D deficiency was categorised as <20 ng/ml, insufficiency as 20-29 ng/ml, and sufficiency as ≥30 ng/ml. Results: Findings indicated 54.6% vitamin D deficiency and 35.4% insufficiency in young adults. Osteoporosis affected 26%, and 67% exhibited osteopenia. A weak positive correlation was found between vitamin 25(OH) D and bone mineral density T score (r = 0.16, r2 = 0.02, P = 0.44). Additionally, moderately weak correlations were observed between serum vitamin D and OPG (r = -0.42, r2 = 0.18, P < 0.001) and between vitamin D and RANKL (r = -0.13, r2 = 0.01, P = 0.18). Conclusion: The study suggests that vitamin D deficiency diminishes bone mineral density by promoting RANKL-RANK osteoclastogenesis and upregulating OPG expression. As young adults form a significant workforce, creating awareness is crucial for maintaining optimal health.

Publications and ranking in orthopaedics and sports medicine of European countries during the last three decades: A bibliometric analysis.

Introduction: The present investigation examined the trend of publications and ranking in Orthopaedics and Sports Medicine of European countries during the years 1996 to 2022 and compared these with all the regions globally. Methods: In September 2023, the SCOPUS data of publications in Orthopaedics and Sports Medicine from the SCImago Journal & Country Rank website were retrieved. All the data from Western and Eastern Europe were extracted from the overall data of the global countries and merged into Excel files, for each of the years 1996-2022 and 2022. Results: Western European countries contributed significantly to the global share of publications in Orthopaedics and Sports Medicine with nearly 1/3rd of the total publications. Eastern European countries' contribution was minimal to the global publications and was almost 10 times less than the Western European countries. The total number of publications in the area of Orthopaedics and Sports Medicine from 1996 to 2022 at the European scale was led by the United Kingdom (N = 51510) and has maintained its supremacy until recently, in 2022. Amongst Western European countries, during the cumulative period of 1996-2022, the maximum contributions were made by the United Kingdom (N = 51510), and also in 2022, the United Kingdom contributed maximally (N = 3339). In the cumulative period of 1996-2022, Poland contributed maximally (N = 4049) among the Eastern European countries. In 2022, the maximum contribution from the Eastern European countries came from the Russian Federation (N = 462). Conclusion: The European continent is the major contributor to Orthopaedics and Sports Medicine research and publications, with almost 1/3rd of the global share of publications. Western European countries are far ahead in their contributions than Eastern European countries.

Income rank and depressive symptoms among employees in Germany - A 5-year cross-lagged panel analysis.

Background/Objective: Socioeconomic disparities in mental health are well-established. Previous research suggests that relative income rank is associated with depressive symptoms above and beyond absolute income. This study aimed to investigate the predictive value of income rank for future depressive symptoms while accounting for absolute income. Exploring potential reverse pathways from depressive symptoms to income rank was a secondary objective. Method: A two-wave cross-lagged panel design with a 5-year follow-up was used to analyze data for income rank, absolute income, and two dimensions of depressive symptoms (i.e., cognitive-affective and somatic symptoms) from initially 4,201 employees. Income rank was calculated for reference groups, based on the same gender, the same 5-year age band, and the same occupational skill level. Results: Lower income rank at baseline predicted a higher severity of cognitive-affective depressive symptoms at five-year follow-up, even after adjusting for absolute income. In contrast, income rank did not demonstrate a significant unique longitudinal association with somatic depressive symptoms when simultaneously taking absolute income into account. There was no evidence for the assumption that depressive symptoms are predictive for future income rank (i.e., reverse pathway). Conclusions: Cognitive-affective symptoms of depression might be particularly responsive to social comparisons and a relatively low social rank.

α-IRAK-4 Suppresses the Activation of RANK/RANKL Pathway on Macrophages Exposed to Endodontic Microorganisms.

Periapical lesions are common pathologies affecting the alveolar bone, often initiated by intraradicular lesions resulting from microbial exposure to dental pulp. These microorganisms trigger inflammatory and immune responses. When endodontic treatment fails to eliminate the infection, periapical lesions persist, leading to bone loss. The RANK/RANKL/OPG pathway plays a crucial role in both the formation and the destruction of the bone. In this study, the objective was to inhibit the RANK/RANKL pathway in vitro within exposed Thp-1 macrophages to endodontic microorganisms, specifically Enterococcus faecalis, which was isolated from root canals of 20 patients with endodontic secondary/persistent infection, symptomatic and asymptomatic, and utilizing an α-IRAK-4 inhibitor, we introduced endodontic microorganisms and/or lipoteichoic acid from Streptococcus spp. to cellular cultures in a culture plate, containing thp-1 cells and/or PBMC from patients with apical periodontitis. Subsequently, we assessed the percentages of RANK+, RANKL+, and OPG+ cells through flow cytometry and measured the levels of several inflammatory cytokines (IL-1ß, TNF-α, IL-6, IL-8, IL-10, and IL-12p70) in the cellular culture supernatant through a CBA kit and performed analysis by flow cytometry. A significant difference was observed in the percentages of RANK+RANKL+, OPG+ RANKL+ cells in thp-1 cells and PBMCs from patients with apical periodontitis. The findings revealed significant differences in the percentages of the evaluated cells, highlighting the novel role of the IRAK-4 inhibitor in addressing this oral pathology, apical periodontitis, where bone destruction is observed.

Sample Size Calculation Under Nonproportional Hazards Using Average Hazard Ratios.

Many clinical trials assess time-to-event endpoints. To describe the difference between groups in terms of time to event, we often employ hazard ratios. However, the hazard ratio is only informative in the case of proportional hazards (PHs) over time. There exist many other effect measures that do not require PHs. One of them is the average hazard ratio (AHR). Its core idea is to utilize a time-dependent weighting function that accounts for time variation. Though propagated in methodological research papers, the AHR is rarely used in practice. To facilitate its application, we unfold approaches for sample size calculation of an AHR test. We assess the reliability of the sample size calculation by extensive simulation studies covering various survival and censoring distributions with proportional as well as nonproportional hazards (N-PHs). The findings suggest that a simulation-based sample size calculation approach can be useful for designing clinical trials with N-PHs. Using the AHR can result in increased statistical power to detect differences between groups with more efficient sample sizes.

[Trends in the choice of internal medicine (and clinical immunology) at the end of the national ranking examination since 2010]. / Évolution du choix de la médecine interne (et immunologie clinique) à l'issue des épreuves classantes nationales depuis 2010.

INTRODUCTION: The 2017 reform of the third cycle of medical studies (R3C) was accompanied by modifications in the formats and number of specialty diplomas. The aim of this study was to investigate the evolution of the choice of the internal medicine and clinical immunology specialty before and after 2017. METHODS: We used the median ranking and its evolution, as well as incoming and outgoing remorse rights, as markers of attractiveness. Data on the number of position offered, rankings and affectation were collected from decrees published in the French "Journal Officiel" each year. A survey conducted by the "Amicale des Jeunes Internistes" investigated the reasons for the outgoing or incoming rights to remorse. RESULTS: Before 2017, internal medicine was accessible to 52% of students on average, with a median rank of 1118 [339-2640]. From 2017 onwards, the internal medicine specialty was accessible to an average of 76.6% of students, with a median rank of 2772 [1039-5155]. The balance of incoming and outgoing remorse rights was -4.7% before 2017 and varied between -4.1 and -12.4% from 2017. CONCLUSION: Since 2017, the median and cut-off ranks of students choosing internal medicine specialty have increased, and balance of incoming and outgoing remorse rights was increasingly negative. A reflection on the attractiveness of the internal medicine specialty is undertaken by the National College of Internal Medicine Teachers in order to make the richness of the specialty and its different modes of practice known to future residents.

Unveiling Medical Insights: Advanced Topic Extraction from Scientific Articles.

In the ever-evolving landscape of medical research and healthcare, the abundance of scientific articles presents both a treasure trove of knowledge and a daunting challenge. Researchers, clinicians, and data scientists grapple with vast amounts of unstructured information, seeking to extract meaningful insights that can drive advancements in the biomedical domain including, research trends, patient care, drug discovery, and disease understanding. This paper utilizes the topic extraction algorithms on Breast Cancer Research to shed light on the current trends and the path to follow in this field. We utilized TextRank and Large Language Models (LLM) using the TripleA tool to extract topics in the field, analyzing and comparing the results.

Testing the Significance of Ranked Gene Sets in Genome-wide Transcriptome Profiling Data Using Weighted Rank Correlation Statistics.

Background: Popular gene set enrichment analysis approaches assumed that genes in the gene set contributed to the statistics equally. However, the genes in the transcription factors (TFs) derived gene sets, or gene sets constructed by TF targets identified by the ChIP-Seq experiment, have a rank attribute, as each of these genes have been assigned with a p-value which indicates the true or false possibilities of the ownerships of the genes belong to the gene sets. Objectives: Ignoring the rank information during the enrichment analysis will lead to improper statistical inference. We address this issue by developing of new method to test the significance of ranked gene sets in genome-wide transcriptome profiling data. Methods: A method was proposed by first creating ranked gene sets and gene lists and then applying weighted Kendall's tau rank correlation statistics to the test. After introducing top-down weights to the genes in the gene set, a new software called "Flaver" was developed. Results: Theoretical properties of the proposed method were established, and its differences over the GSEA approach were demonstrated when analyzing the transcriptome profiling data across 55 human tissues and 176 human cell-lines. The results indicated that the TFs identified by our method have higher tendency to be differentially expressed across the tissues analyzed than its competitors. It significantly outperforms the well-known gene set enrichment analyzing tools, GOStats (9%) and GSEA (17%), in analyzing well-documented human RNA transcriptome datasets. Conclusions: The method is outstanding in detecting gene sets of which the gene ranks were correlated with the expression levels of the genes in the transcriptome data.

Sample size calculation for mixture cure model with restricted mean survival time as a primary endpoint.

It is not uncommon for a substantial proportion of patients to be cured (or survive long-term) in clinical trials with time-to-event endpoints, such as the endometrial cancer trial. When designing a clinical trial, a mixture cure model should be used to fully consider the cure fraction. Previously, mixture cure model sample size calculations were based on the proportional hazards assumption of latency distribution between groups, and the log-rank test was used for deriving sample size formulas. In real studies, the latency distributions of the two groups often do not satisfy the proportional hazards assumptions. This article has derived a sample size calculation formula for a mixture cure model with restricted mean survival time as the primary endpoint, and did simulation and example studies. The restricted mean survival time test is not subject to proportional hazards assumptions, and the difference in treatment effect obtained can be quantified as the number of years (or months) increased or decreased in survival time, making it very convenient for clinical patient-physician communication. The simulation results showed that the sample sizes estimated by the restricted mean survival time test for the mixture cure model were accurate regardless of whether the proportional hazards assumptions were satisfied and were smaller than the sample sizes estimated by the log-rank test in most cases for the scenarios in which the proportional hazards assumptions were violated.

Comprehensive evaluation of global health cities development levels.

Introduction: How to scientifically assess the health status of cities and effectively assist in formulating policies and planning for health city development remains a profound challenge in building a global "health community." Methods: This study employs the Building Research Establishment's International Healthy Cities Index (BRE HCI), encompassing ten environmental categories and fifty-eight indicators, to guide and support the scientific development of healthy cities. The entropy weight-TOPSIS method and the rank sum ratio (RSR) method were applied to comprehensively rank and categorize the health development levels of fifteen global cities. Furthermore, through cluster analysis, this research identifies universal and unique indicators that influence the development of healthy cities. Results: The results indicate that: (1) Within the scope of 58 evaluation indicators, the precedence in weight allocation is accorded to the kilometres of bicycle paths and lanes per 100,000 population (0.068), succeeded by m2 of public indoor recreation space per capita (0.047), and kilometres of bicycle paths and lanes per 100,000 population (0.042). (2) Among the ten environmental categories, the top three in terms of weight ranking are transport (0.239), leisure and recreation (0.172), and resilience (0.125). Significant disparities exist between different cities and environmental categories, with the issue of uneven health development within cities being particularly prominent. (3) The study categorizes the development levels of healthy cities into three tiers based on composite scores: it classifies Singapore, Shanghai, and Amsterdam at an excellent level; places Dubai and Johannesburg at a comparatively poor level; and situates the remaining ten cities at a moderate level. (4) The analysis identifies 53 international common indicators and 5 characteristic indicators from the 58 indicators based on the significance of the clustering analysis (p < 0.05). Discussion: The study proposes four strategic recommendations based on these findings: establishing a comprehensive policy assurance system, refining urban spatial planning, expanding avenues for multi-party participation, and augmenting distinctive health indicators. These measures aim to narrow the developmental disparities between cities and contribute to healthy global cities' balanced and sustainable growth. However, due to existing limitations in sample selection, research methodology application, and the control of potential confounding variables, further in-depth studies are required in the future.

The Role of Receptor Activator of Nuclear Factor-κB Ligand/Osteoprotegerin Ratio in Synovial Fluid as a Potential Marker for Periprosthetic Osteolysis Following Total Ankle Arthroplasty.

Background: Periprosthetic osteolysis is a prevalent complication following total ankle arthroplasty (TAA), implicating various cytokines in osteoclastogenesis as pivotal in this process. This study aimed to evaluate the relationship between osteolysis and the concentrations of osteoclastogenesis-related cytokines in synovial fluid and investigate its clinical value following TAA. Methods: Synovial fluid samples from 23 ankles that underwent revision surgery for osteolysis following TAA were analyzed as the osteolysis group. As a control group, we included synovial fluid samples obtained from 23 ankles during primary TAA for osteoarthritis. The receptor activator of nuclear factor-κB ligand (RANKL)/osteoprotegerin (OPG) ratio in these samples was quantified using sandwich enzyme-linked immunosorbent assay techniques, and a bead-based multiplex immunoassay facilitated the detection of specific osteoclastogenesis-related cytokines. Results: RANKL levels averaged 487.9 pg/mL in 14 of 23 patients in the osteolysis group, with no detection in the control group's synovial fluid. Conversely, a significant reduction in OPG levels was observed in the osteolysis group (p = 0.002), resulting in a markedly higher mean RANKL/OPG ratio (0.23) relative to controls (p = 0.020). Moreover, the osteolysis group had increased concentrations of various osteoclastogenesis-related cytokines (tumor necrosis factor-α, interleukin [IL]-1ß, IL-6, IL-8, IP-10, and monocyte chemotactic protein-1) in the synovial fluid relative to the control group. Conclusions: Our results demonstrated that periprosthetic osteolysis was associated with osteoclastogenesis activation through an elevated RANKL/OPG ratio following TAA. We assume that RANKL and other osteoclastogenesis-related cytokines in the synovial fluid have clinical value as a potential marker for the development and progression of osteolysis following TAA.

Aromatase inhibitor-induced bone loss osteosarcopenia in older patients with breast cancer: effects of the RANK/RANKL system's inhibitor denosumab vs. bisphosphonates.

The raising number of older patients who are diagnosed with breast cancer represents a significant medical and societal challenge. Aromatase inhibitors (AI), which are commonly utilized to treat this condition in these patients have significant adverse events on bone and muscle health. Falling estrogen production leads to an increase in RANKL secretion by osteoblasts with accelerated bone remodeling due to osteoclast activity. Furthermore, estrogen deficiency reduces skeletal muscle strength and mass. The humanized monoclonal antibody, denosumab, neutralizes RANKL, thereby inhibiting osteoclast formation, function and survival and ultimately exerting powerful anti-resorptive effects.. In this study, we report on the efficacy of denosumab in mitigating aromatase inhibitor-induced bone loss (AIBL) and sarcopenia in older women with breast cancer. From January 2022 to January 2023, we enrolled 30 patients (female sex, ≥ 65 years) diagnosed with non-metastatic breast cancer undergoing adjuvant endocrine therapy; patients received, as per clinical practice, primary bone prophylaxis with denosumab (60 mg via subcutaneous injection every 6 months) according to oncologic guidelines. This group was matched with 30 patients with non-metastatic breast cancer, who were treated with biphosphonates (BF) therapy (oral alendronate 70 mg/week). For each patient bone mineral density (BMD) and bone quality in terms of trabecular bone score (TBS) in addition to body composition and Relative Skeletal Muscle Index (RSMI) was assessed by bone densitometry at baseline and after one year of treatment. Significant improvements in TBS at the lumbar spine, RSMI and whole-body composition (arms, legs, and trunk) were observed in the denosumab group compared with the BF group. These findings underscore the role of denosumab as an effective strategy in managing AIBL and osteosarcopenia in older women with breast cancer and undergoing adjuvant endocrine therapy, which is crucial for improving quality of life, preventing functional decline, and optimizing treatment outcomes.