Sirtuins in intervertebral disc degeneration: current understanding.

BACKGROUND: Intervertebral disc degeneration (IVDD) is one of the etiologic factors of degenerative spinal diseases, which can lead to a variety of pathological spinal conditions such as disc herniation, spinal stenosis, and scoliosis. IVDD is a leading cause of lower back pain, the prevalence of which increases with age. Recently, Sirtuins/SIRTs and their related activators have received attention for their activity in the treatment of IVDD. In this paper, a comprehensive systematic review of the literature on the role of SIRTs and their activators on IVDD in recent years is presented. The molecular pathways involved in the regulation of IVDD by SIRTs are summarized, and the effects of SIRTs on senescence, inflammatory responses, oxidative stress, and mitochondrial dysfunction in myeloid cells are discussed with a view to suggesting possible solutions for the current treatment of IVDD. PURPOSE: This paper focuses on the molecular mechanisms by which SIRTs and their activators act on IVDD. METHODS: A literature search was conducted in Pubmed and Web of Science databases over a 13-year period from 2011 to 2024 for the terms "SIRT", "Sirtuin", "IVDD", "IDD", "IVD", "NP", "Intervertebral disc degeneration", "Intervertebral disc" and "Nucleus pulposus". RESULTS: According to the results, SIRTs and a large number of activators showed positive effects against IVDD.SIRTs modulate autophagy, myeloid apoptosis, oxidative stress and extracellular matrix degradation. In addition, they attenuate inflammatory factor-induced disc damage and maintain homeostasis during disc degeneration. Several clinical studies have reported the protective effects of some SIRTs activators (e.g., resveratrol, melatonin, honokiol, and 1,4-dihydropyridine) against IVDD. CONCLUSION: The fact that SIRTs and their activators play a hundred different roles in IVDD helps to better understand their potential to develop further treatments for IVDD. NOVELTY: This review summarizes current information on the mechanisms of action of SIRTs in IVDD and the challenges and limitations of translating their basic research into therapy.

Validation of the Minnesota Pectoralis Risk Score to predict mortality in the HeartMate 3 population.

BACKGROUND: The Minnesota Pectoralis Risk Score (MPRS) utilizes computed tomography-quantified thoracic muscle and clinical variables to predict survival after left ventricular assist device (LVAD) implantation. The model has not been prospectively tested in HeartMate 3 recipients. METHODS: A single-center HeartMate 3 cohort from July 2016 to July 2021 (n = 108) was utilized for this analysis. Cohort subjects with complete covariates for MPRS calculation (pectoralis muscle measures, Black race, creatinine, total bilirubin, body mass index, bridge to transplant status, and presence/absence of contrast) implanted after MPRS development were included. MPRS were calculated on each subject. Receiver operating characteristic curves were generated to test model discrimination at 30-day, 90-day, and 1-year mortality post-LVAD. Next, the performance of the 1-year post-LVAD outcome was compared to the HeartMate 3 survival risk score (HM3RS). RESULTS: The mean age was 58 (15 years), 80% (86/108) were male, and 26% (28/108) were destination therapy. The area under the curve (AUC) for the MPRS model to predict post-LVAD mortality was 0.73 at 30 days, 0.78 at 90 days, and 0.81 at 1 year. The AUC for the HM3RS for the 1-year outcome was 0.693. Each 1-unit point of the MPRS was associated with a significant increase in the hazard rate of death after LVAD (hazard ratio 2.1, 95% confidence interval 1.5-3.0, p < 0.0001). CONCLUSIONS: The MPRS had high performance in this prospective validation, particularly with respect to 90-day and 1-year post-LVAD mortality. Such a tool can provide additional information regarding risk stratification to aid informed decision-making.

Targeting signaling pathways in osteosarcoma: Mechanisms and clinical studies.

Osteosarcoma (OS) is a highly prevalent bone malignancy among adolescents, accounting for 40% of all primary malignant bone tumors. Neoadjuvant chemotherapy combined with limb-preserving surgery has effectively reduced patient disability and mortality, but pulmonary metastases and OS cells' resistance to chemotherapeutic agents are pressing challenges in the clinical management of OS. There has been an urgent need to identify new biomarkers for OS to develop specific targeted therapies. Recently, the continued advancements in genomic analysis have contributed to the identification of clinically significant molecular biomarkers for diagnosing OS, acting as therapeutic targets, and predicting prognosis. Additionally, the contemporary molecular classifications have revealed that the signaling pathways, including Wnt/ß-catenin, PI3K/AKT/mTOR, JAK/STAT3, Hippo, Notch, PD-1/PD-L1, MAPK, and NF-κB, have an integral role in OS onset, progression, metastasis, and treatment response. These molecular classifications and biological markers have created new avenues for more accurate OS diagnosis and relevant treatment. We herein present a review of the recent findings for the modulatory role of signaling pathways as possible biological markers and treatment targets for OS. This review also discusses current OS therapeutic approaches, including signaling pathway-based therapies developed over the past decade. Additionally, the review covers the signaling targets involved in the curative effects of traditional Chinese medicines in the context of expression regulation of relevant genes and proteins through the signaling pathways to inhibit OS cell growth. These findings are expected to provide directions for integrating genomic, molecular, and clinical profiles to enhance OS diagnosis and treatment.

Association between calculated panel reactive antibody and waitlist outcomes in the 2018 heart allocation system.

BACKGROUND: The impact of heart transplant (HT) waitlist candidate sensitization on waitlist outcomes in the US is unknown. METHODS: Adult waitlist outcomes in OPTN (October 2018-September 2022) by calculated panel reactive antibody (cPRA) were modeled to identify thresholds of clinical significance. The primary outcome was the rate of HT by cPRA category (low: 0-35, middle: >35-90, high: >90) assessed using multivariable competing risk analysis (compete: waitlist removal for death or clinical deterioration). The secondary outcome was waitlist removal for death or clinical deterioration. RESULTS: The elevated cPRA categories were associated with lower rates of HT. Candidates in the middle (35-90) and high cPRA categories (>90) had an adjusted 24% lower rate (hazard ratio (HR) 0.86, 95% confidence interval (CI) 0.80-0.92) and 61% lower rate (HR 0.39 95% CI. 0.33-0.47) of HT than the lowest category, respectively. Waitlist candidates in the high cPRA category listed in the top acuity strata (Statuses 1, 2) had increased rates of delisting for death or deterioration compared to those in the low cPRA category (adjusted HR 2.9, 95% CI 1.5-5.5), however, elevated cPRA (middle, high) was not associated with an increased rate of death and delisting when the cohort was considered as a whole. CONCLUSIONS: Elevated cPRA was associated with reduced rates of HT across all waitlist acuity tiers. Among HT waitlist candidates listed at the top acuity strata, the high cPRA category was associated with increased rates of delisting due to death or deterioration. Elevated cPRA may require consideration for critically ill candidates under continuous allocation.

A flexible Bayesian framework for individualized inference via adaptive borrowing.

The explosion in high-resolution data capture technologies in health has increased interest in making inferences about individual-level parameters. While technology may provide substantial data on a single individual, how best to use multisource population data to improve individualized inference remains an open research question. One possible approach, the multisource exchangeability model (MEM), is a Bayesian method for integrating data from supplementary sources into the analysis of a primary source. MEM was originally developed to improve inference for a single study by asymmetrically borrowing information from a set of similar previous studies and was further developed to apply a more computationally intensive symmetric borrowing in the context of basket trial; however, even for asymmetric borrowing, its computational burden grows exponentially with the number of supplementary sources, making it unsuitable for applications where hundreds or thousands of supplementary sources (i.e., individuals) could contribute to inference on a given individual. In this article, we propose the data-driven MEM (dMEM), a two-stage approach that includes both source selection and clustering to enable the inclusion of an arbitrary number of sources to contribute to individualized inference in a computationally tractable and data-efficient way. We illustrate the application of dMEM to individual-level human behavior and mental well-being data collected via smartphones, where our approach increases individual-level estimation precision by 84% compared with a standard no-borrowing method and outperforms recently proposed competing methods in 80% of individuals.

Noncoding RNA PVT1 in osteosarcoma: The roles of lncRNA PVT1 and circPVT1.

Osteosarcoma (OS) is the most common primary malignant bone tumor in children and teenagers and is characterized by high malignant potential, rapid disease progression and high disability and mortality rates. Recently, noncoding RNAs (ncRNAs) have attracted the attention of many scholars due to their major regulatory roles in gene expression. Among them, lncRNA PVT1 and circPVT1 encoded by the PVT1 gene have been the focus of many studies; they are upregulated in OS, and abundant evidence indicates that lncRNA PVT1 and circPVT1 play key roles in the occurrence and development of OS. This review summarizes the mechanisms of action of lncRNA PVT1 and circPVT1 in regulating apoptosis, proliferation, glycolysis, invasion, migration and epithelial-mesenchymal transition (EMT) in OS and discusses their clinical applications in diagnosis, prognosis determination and drug resistance treatment, with the aim of helping researchers better understand the regulatory roles of lncRNA PVT1 and circPVT1 in OS progression and providing a theoretical basis for the development of early screening and accurate targeted treatment strategies and prognostic biomarkers for OS based on lncRNA PVT1 and circPVT1.

Application of Bioprinting in Ophthalmology.

Three-dimensional (3D) bioprinting is an emerging technology that is widely used in regenerative medicine. With the continuous development of the technology, it has attracted great attention and demonstrated promising prospects in ophthalmologic applications. In this paper, we review the three main types of 3D bioprinting technologies: Vat polymerization-based bioprinting, extrusion-based bioprinting, and jetting-based bioprinting. We also present in this review the analysis of the usage of both natural and synthesized hydrogels as well as the types of cells adopted for bioinks. Cornea and retina are the two main types of ocular tissues developed in bioprinting, while other device and implants were also developed for the ocular disease treatment. We also summarize the advantages and limitations as well as the future prospects of the current bioprinting technologies based on systematic reviews.

Optimal sample size determination for single-arm trials in pediatric and rare populations with Bayesian borrowing.

In many therapeutic areas with unmet medical needs, such as pediatric oncology and rare diseases, one of the deterrent factors for clinical trial interpretability is the limited sample size with less-than-ideal operating characteristics. Single arm is usually the only viable design due to feasibility and ethical concerns. For the trial results to be more interpretable and conclusive, the evaluation of operating characteristics, such as type I error rate and power, and the appropriate utilization of prior information for study design, shall be prespecified and fully investigated during the trial planning phase. So far, very few existing literature addressed optimal sample size determination issues for the planning of pediatric and rare population trials, with majority of research focusing on analysis perspective with focus on Bayesian borrowing. In practice, when a single-arm trial is designed for rare population, it is not uncommon that the only information available is from an earlier trial and/or a few clinical publications based on observational studies, often constituting mixed or uncertain conclusions. In light of this, an optimal Bayesian sample size determination method for single-arm trial with binary or continuous endpoint is proposed, where conflicting prior beliefs can be readily incorporated. Prior effective sample size can be calculated to assess the robustness as well as the prior information borrowed. Moreover, due to the lack of closed-form posterior distributions in general, an alternative approach for calculating Bayesian power is described. Simulation studies are provided to demonstrate the utility of the proposed methods. In addition, a case study in pediatric patients with leukemia is included to illustrate the proposed method with the existing approaches.

Momentary predictors of a broad range of food parenting practices within a population-based sample of parents of preschool-aged children.

Introduction: The current study sought to understand the influence of momentary factors within the home and family environment, including parent stress, parent and child mood and child behaviors, on parents' use of a broad range of food parenting practices later that same day. Methods: Ecological Momentary Assessment (EMA) was used to evaluate parents' use of coercive, indulgent, structured and autonomy support food parenting practices, as well as numerous potentially salient momentary predictors, including parental stress, parent and child mood, and child behavior. Data were collected from 109 parents of preschool aged children multiple times per day over the course of a ten-day data collection period, allowing for temporal sequencing of momentary predictors and use of food parenting practices. Results: With some notable exceptions, study findings align with study hypotheses in that parent stress, parent and child low mood, and child negative behaviors early in the day were found to be associated with the use of less supportive food parenting practices later that same day. For example, greater parent negative mood earlier in the day was associated with a decrease in use of feeding practices from within the structure domain later on that same day (-2.5%, p < 0.01), whereas greater parent positive mood earlier in the day was associated with an increase in use of structure later on that same day (+3.7%, p < 0.01). Greater parent stress earlier in the day was associated with an increase in the use of coercive control (+3.2%, p < 0.01) and indulgent (+3.0%, p < 0.01) practices later that same day; surprisingly, a similar increase in stress earlier in the day was also found to be associated with an increase in the use of autonomy support (5.6%, p < 0.01) feeding practices later on that same day. Discussion: Developing an understanding of the types of momentary factors that influence a parent's use of particular food parenting practices across multiple contexts is a crucial next step toward developing effective interventions aimed at teaching parents to use food parenting practices that are supportive of healthful child dietary intake and eating behaviors in a way that is responsive to shifting factors.