Search Results (162)

Functional foods like flax (Linum usitatissimum L.) are rich sources of specialized metabolites that contribute to their nutritional and health-promoting properties. Understanding the biosynthesis of these compounds is essential for improving their quality and potential applications. However, dissecting complex metabolic networks in plants remains challenging due to the dynamic nature and interconnectedness of biosynthetic pathways. In this study, we present a synergistic approach combining stable isotopic labeling (SIL), Candidate Substrate–Product Pair (CSPP) networks, and a time-course study with high temporal resolution to reveal the biosynthetic fluxes shaping phenylpropanoid metabolism in young flax seedlings. By feeding the seedlings with ¹³C₃-p-coumaric acid and isolating isotopically labeled metabolization products prior to the construction of CSPP networks, the biochemical validity of the connections in the network was supported by SIL, independent of spectral similarity or abundance correlation. This method, in combination with multistage mass spectrometry (MSⁿ), allowed confident structural proposals of lignans, neolignans, and hydroxycinnamic acid conjugates, including the presence of newly identified chicoric acid and related tartaric acid esters in flax. High-resolution time-course analyses revealed successive waves of metabolite formation, providing insights into distinct biosynthetic fluxes toward lignans and early lignification intermediates. No evidence was found here for the involvement of chlorogenic or caftaric acid intermediates in chicoric acid biosynthesis in flax, as has been described in other species. Instead, our findings suggest that in flax seedlings, chicoric acid is synthesized through successive hydroxylation steps of p-coumaroyl tartaric acid esters. This work demonstrates the power of combining SIL and CSPP strategies to uncover novel metabolic routes and highlights the nutritional potential of flax sprouts rich in chicoric acid. Full article

Random Forests are powerful machine learning models widely applied in classification and regression tasks due to their robust predictive performance. Nevertheless, traditional Random Forests face computational challenges during tree construction, particularly in high-dimensional data or on resource-constrained devices. In this paper, a novel node-splitting algorithm, BayesSplit, is proposed to accelerate decision tree construction via a Bayesian-based impurity estimation framework. BayesSplit treats impurity reduction as a Bernoulli event with Beta-conjugate priors for each split point and incorporates two main strategies. First, Dynamic Posterior Parameter Refinement updates the Beta parameters based on observed impurity reductions in batch iterations. Second, Posterior-Derived Confidence Bounding establishes statistical confidence intervals, efficiently filtering out suboptimal splits. Theoretical analysis demonstrates that BayesSplit converges to optimal splits with high probability, while experimental results show up to a 95% reduction in training time compared to baselines and maintains or exceeds generalization performance. Compared to the state-of-the-art MABSplit, BayesSplit achieves similar accuracy on classification tasks and reduces regression training time by 20–70% with lower MSEs. Furthermore, BayesSplit enhances feature importance stability by up to 40%, making it particularly suitable for deployment in computationally constrained environments. Full article

Background: Belantamab mafodotin (belamaf) is a BCMA-targeting antibody–drug conjugate used in triple-class refractory multiple myeloma. Despite its efficacy, keratopathy remains a significant dose-limiting toxicity. Following its withdrawal from the U.S. market in 2022, its use in Austria is limited to clinical trials or compassionate use. Methods: In this real-world, retrospective study, we analyzed 36 relapsed/refractory, BCMA-naïve multiple myeloma patients treated at the University Hospital of Vienna (January 2020–June 2024); 42% received a reduced dose (1.9 mg/kg) throughout all treatment cycles. The primary objective was to assess adverse events, particularly keratopathy, and the impact of dose modifications on toxicity and efficacy. Results: The overall response rate was 64%, with responders having significantly fewer prior therapy lines (median 3 vs. 4.5, p = 0.015). Median PFS was 7.3 months, significantly longer in responders (11.1 vs. 1.6 months, p < 0.0001); median OS was 20.1 months, also longer in responders (not reached vs. 18 months, p = 0.031). Keratopathy occurred in 75% of patients; 33% experienced grade 3–4 events. Dose reduction significantly decreased grade 3–4 keratopathy (7% vs. 52%, p = 0.004) and thrombocytopenia (33% vs. 67%, p = 0.048) without compromising efficacy. Conclusions: Belamaf dose reductions improved tolerability without loss of efficacy, supporting reduced dosing in practice. Full article

Logistic regression is often used to solve classification problems. This article combines the advantages of Bayesian methods and spike-and-slab Lasso to select variables in high-dimensional logistic regression. The method of introducing a new hidden variable or approximating the lower bound is used to solve the problem of logistic functions without conjugate priors. The Laplace distribution in spike-and-slab Lasso is expressed as a hierarchical form of normal distribution and exponential distribution, so that all parameters in the model are posterior distributions that are easy to deal with. Considering the high time cost of parameter estimation and variable selection in high-dimensional models, we use the variational Bayesian algorithm to perform posterior inference on the parameters in the model. From the simulation results, it can be seen that it is an adaptive prior that can perform parameter estimation and variable selection well in high-dimensional logistic regression. From the perspective of algorithm running time, the method proposed in this article also has high computational efficiency in many cases. Full article

Background: Metastatic prostate cancer (mPrC), with a median survival of under 2 years, represents an important unmet medical need which may benefit from the development of more effective targeted drug delivery systems. Several cell surface receptors have been identified as candidates for targeted drug delivery to mPrC cells; however, these receptors were selected for their overabundance on PrC cells rather than for their suitability for targeted delivery and uptake of cytotoxic drug payloads. Methods: We describe a novel, unbiased strategy to isolate peptides that fulfill functional criteria required for effective intracellular drug delivery and the specific cytotoxicity of PrC cells without prior knowledge of the targeted receptor. Phage clones displaying 7-mer cyclic peptides were negatively selected in vivo and then positively biopanned through a series of parent and drug-resistant mPrC cells. Peptides from the internalized clones were then subjected to a panel of biochemical and functional tests that led to the selection of several peptide candidates. Results: The selected peptides do not bind PSMA. Peptide-drug conjugates (PDCs) incorporating one of the peptides selectively killed wild-type and drug-resistant PrC cell lines and patient PrC cells but not normal prostate tissue cells in vitro. The PDC also halted the growth of PC3 tumors in a xenograft model. Conclusions: Our study demonstrates that adding unbiased, functional criteria into drug carrier selection protocols can lead to the discovery of novel peptides with appropriate properties required for effective targeted drug delivery into target cancer cells. Full article

High aspect ratio (HAR) sample-induced aberrations seriously affect the topography measurement for the bottom of the microstructure by coherence scanning interferometry (CSI). Previous research proposed an aberration compensating method using deformable mirrors at the conjugate position of the pupil. However, it failed to compensate for the shift-variant aberrations introduced by the HAR hybrid trench array composed of multiple trenches with different parameters. Here, we propose a computational aberration correction method for measuring the topography of the HAR structure by the particle swarm optimization (PSO) algorithm without constructing a database and prior knowledge, and a phase filter in the spatial frequency domain is constructed to restore interference signals distorted by shift-variant aberrations. Since the aberrations of each sampling point are basically unchanged in the field of view corresponding to a single trench, each trench under test can be considered as a separate isoplanatic region. Therefore, a multi-channel aberration correction scheme utilizing the virtual phase filter based on isoplanatic region segmentation is established for hybrid trench array samples. The PSO algorithm is adopted to derive the optimal Zernike polynomial coefficients representing the filter, in which the interference fringe contrast is taken as the optimization criterion. Additionally, aberrations introduce phase distortion within the 3D transfer function (3D-TF), and the 3D-TF bandwidth remains unchanged. Accordingly, we set the non-zero part of the 3D-TF as a window function to preprocess the interferogram by filtering out the signals outside the window. Finally, experiments are performed in a single trench sample and two hybrid trench array samples with depths ranging from 100 to 300 μm and widths from 10 to 30 μm to verify the effectiveness and accuracy of the proposed method. Full article

To elucidate evolutionary characteristics of the surrounding rock failure mechanism in a double-roadway layout, this work is grounded on in the research context of the Jinjitan Coal Mine, focusing on the deformation and failure mechanisms of double roadways. This paper addresses the issue of resource wastage resulting from the excessive dimensions of coal pillars in prior periods by employing a research methodology that integrates theoretical analysis, numerical simulation, and field monitoring to systematically examine the movement characteristics of overlying rock in the working face. On that basis, the size of coal pillar is optimized. The advance’s stress transfer law and deformation distribution characteristics of the return air roadway and transport roadway are studied. The cause of the asymmetric deformation of roadway retention is explained. A differentiated design is conducted on the support parameters of double-roadway bolts and cables under strong dynamic pressure conditions. The study indicates that a 16 m coal pillar results in an 8 m elastic zone at its center, balancing stability with optimal resource extraction. In the basic top-sloping double-block conjugate masonry beam structure, the differing stress levels between the top working face’s transport roadway and the lower working face’s return air roadway are primarily due to the varied placements of key blocks. In the return air roadway, floor heave deformation is managed using locking anchor rods, while roof subsidence is controlled with a constant group of large deformation anchor cables. The displacement of surrounding rock increases under the influence of both leading and lagging pressures from the previous working face, although the change is minimal. There is a significant correlation between roadway deformation and support parameters and coal pillar size. With a 16 m coal pillar, differential support of the double roadway lowers the return air roadway deformation by 30%, which improves the mining rate and effectively controls the deformation of the roadway. Full article

In the complex underwater environment, it is hard to obtain accurate system noise prior information. If uncertainty system noise model is used in state determination, the precision will decrease. To address the problem, this paper proposes a novel inverse-Wishart (IW) based variational Bayesian adaptive cubature Kalman filter (IW-VACKF), and the inverse-Wishart distribution is employed as the conjugate prior distribution of system noise covariance matrices. To improve the modeling accuracy, a mixing probability vector is introduced based on the inverse-Wishart distribution to better characterize the uncertainty and dynamic of state noise in underwater environments. Then, the state transition and the measurement process are derived as hierarchical Gaussian models. Subsequently, the posterior information of the system is jointly calculated by employing the variational Bayesian method. Simulations and real trials illustrate that the proposed IW-VACKF can improve the state estimation precision efficiently in the complex underwater environment. Full article

Background/Objectives: Breast cancer is the most common malignant neoplasm in women and the leading cause of cancer-related death. Approximately 50% of HER2-negative breast cancers exhibit low expression of this protein (HER2-low). Trastuzumab deruxtecan (T-DXd) is an antibody-drug conjugate targeting the HER2 receptor which has shown benefit in patients with HER2-low metastatic breast cancer in the DESTINY-Breast04 study. However, few data are available on its efficacy in real-world practice. Methods: We conducted a retrospective multicenter national study (eight centers) including patients with advanced HER2-low breast cancer (immunohistochemistry 1+ or 2+/ in situ hybridization negative) who started T-DXd treatment between January 2022 and March 2024. Patients had received at least one previous line of treatment. The primary endpoint was real-world progression-free survival (rwPFS) in patients with metastatic HER2-low breast cancer treated with T-DXd. The secondary endpoints were real-world overall survival (OS) and objective response rate (ORR). Results: The study included 35 patients (34 female and 1 male patient), with a median age of 54 years at the start of T-DXd. All patients had an ECOG-PS 0–1, and 26 patients (74%) had hormone receptor (HR)-positive disease. The median number of prior lines of treatment was 4 [1–7], and 23 patients (65.8%) had metastases in three or more sites. With a median follow-up of 7.8 months, rwPFS was 6 months (95% CI, 2.3–9.7), and OS was 15 months (95% CI, 4.7–25.3). In HR-positive patients, the median rwPFS was 6 months (95% CI, 1.2–10.7), compared to 4 months (95% CI, 2.1–5.9) in HR-negative patients. The overall ORR was 52.9%. Adverse events of grade 3 or higher were neutropenia (2.9%) and fatigue (2.9%). Conclusions: This study provides real-world data on T-DXd in the treatment of advanced HER2-low breast cancer. It is noteworthy that the population was heavily pre-treated and had a higher proportion of HR-negative patients, which may explain the lower efficacy compared to the DESTINY-Breast04 study. Full article

Background: Chemotherapy, a cornerstone treatment for Acute Lymphoblastic Leukemia (ALL), can compromise immune function, leading to impaired immune memory function and diminished responses to revaccination. This systematic review and meta-analysis sought to evaluate the impact of chemotherapy on the immunogenicity of prior vaccinations and subsequent revaccination responses in children with ALL. Methods: A comprehensive search was conducted through PubMed, Embase, Web of Science, and Medline. Search time was 9 January 2025. R 4.4.2 was employed for data analysis. Results: A total of 29 relevant studies were identified, with 8 undergoing meta-analysis. The pooled antibody seropositive rates (SPR) for vaccines against Hepatitis B Virus (HBV), Hepatitis A Virus (HAV), diphtheria, tetanus, pertussis, measles, mumps, rubella, varicella, and Pneumococcal Conjugate Vaccine (PCV) demonstrated a statistically significant decline after chemotherapy in ALL patients (p < 0.0001). Subgroup analysis further revealed marked and heterogeneous declines in SPR after chemotherapy, with the magnitude of reduction varying significantly across vaccines—tetanus, HBV, HAV, measles, mumps, and rubella (Subgroup differences, p = 0.0037). Conclusions: This review provides an updated assessment of this critical topic, representing the first meta-analysis specifically focused on the effects of chemotherapy on different vaccines’ immunogenicity in children with ALL. Full article

This paper considers Bayesian regularisation using global–local shrinkage priors in the multivariate general linear model when there are many more explanatory variables than observations. We adopt priors’ structures used extensively in univariate problems (conjugate and non-conjugate with tail behaviour ranging from polynomial to exponential) and consider how the addition of error correlation in the multivariate set-up affects the performance of these priors. Two different datasets (from drug discovery and chemometrics) with many covariates are used for comparison, and these are supplemented by a small simulation study to corroborate the role of error correlation. We find that structural assumptions of the prior distribution on regression coefficients can be more significant than the tail behaviour. In particular, if the structural assumption of conjugacy is used, the performance of the posterior predictive distribution deteriorates relative to non-conjugate choices as the error correlation becomes stronger. Full article

For non-ignorable missing response variables, the mechanism of whether the response variable is missing can be modeled through logistic regression. In Bayesian computation, the lack of a conjugate prior for the logistic function poses a significant challenge. Introducing a new Pólya-Gamma variable and employing lower-bound approximation are two common methods for parameter inference in conjugate Bayesian logistic regression. It can be observed that these two methods yield essentially the same variational posterior in the calculation of the variational Bayesian posterior. This paper applies a popular Bayesian spike-and-slab LASSO prior for variable selection in quantile regression with non-ignorable missing response variables, which demonstrates good performance in both simulations and practical applications. Full article

Background: The aging of the population has increased the number of frail people living in long-term care facilities, underscoring the need for continuous updates in infectious diseases prevention strategies. The aim of this study was to analyze two pneumococcal disease outbreaks in elderly residences in Gipuzkoa, northern Spain, their impact on residents, and the containment measures implemented. Material and methods: The outbreaks took place in 2023 and in 2024 in two residences of 111 and of 155 residents, respectively. Diagnosis was based on clinical criteria, radiological findings, and microbiological techniques. Pneumococcal isolates were characterized by whole-genome sequencing. Results: The outbreaks involved five and six residents, respectively. Most residents in both facilities had been vaccinated with the pneumococcal polysaccharide 23-valent vaccine (PPV23) more than five years prior. The median attack rates were 4.5% and 3.9%, lower than those reported in similar outbreaks. The adopted infection transmission prevention measures successfully limited the spread of the outbreaks. Conclusions: PPV23 vaccination did not prevent invasive pneumococcal infection in the affected residents. The vaccination of elderly people living in long-term care facilities with 20-valent and 21-valent pneumococcal conjugated vaccines should be evaluated as a new preventive measure. Full article

A Bayes estimator for a mean parameter of an exponential distribution is calculated using Stein’s loss, which equally penalizes gross overestimation and underestimation. A corresponding Posterior Expected Stein’s Loss (PESL) is also determined. Additionally, a Bayes estimator for a mean parameter is obtained under a squared error loss along with its corresponding PESL. Furthermore, two methods are used to derive empirical Bayes estimators for the mean parameter of the exponential distribution with an inverse gamma prior. Numerical simulations are conducted to illustrate five aspects. Finally, theoretical studies are illustrated using Static Fatigue 90% Stress Level data. Full article

Background/Objectives: Sacituzumab govitecan (SG) is an antibody–drug conjugate targeting Trop-2, approved for use in metastatic triple-negative breast cancer (mTNBC) and more recently in the hormone receptor-positive/HER2-negative (mHRPBC) subtype. While clinical trials have demonstrated its efficacy, real-world data—especially those involving both molecular subtypes—remain scarce. This multicenter, retrospective study aimed to evaluate real-world observational data describing the clinical outcomes, safety, and prognostic factors associated with SG treatment in patients with mTNBC or mHRPBC. Methods: A total of 68 patients treated with SG between 2022 and 2025 were included from multiple oncology centers in Turkey. Patients with mTNBC were required to have received at least one prior chemotherapy line, while mHRPBC patients had received at least two prior chemotherapy lines in addition to cyclin-dependent kinase 4 and 6 inhibitors (CDK 4/6) plus hormone therapy. The clinical outcomes—including the progression-free survival (PFS), overall survival (OS), and objective response rate (ORR)—were evaluated. Univariate and multivariate analyses were performed to identify factors influencing outcomes. Adverse events (AEs) were also documented and graded according to National Cancer Institute Common Terminology Criteria for Adverse Events version 5 (NCI-CTCAE v5.0). Results: The cohort included 35 (51.5%) mTNBC and 33 (48.5%) mHRPBC patients. The median PFS was 6.1 months, and the median OS was 12.5 months, with no significant differences between subtypes. The ORR was 52.9%, with a complete response observed in 10.3% of patients. A high Eastern Cooperative Oncology Group Performance Status (ECOG PS) and liver metastasis were independent predictors of poorer PFS and OS. Prior immunotherapy did not negatively impact SG’s efficacy. SG was generally well tolerated; the most common AEs were alopecia, anemia, neutropenia, and diarrhea. Treatment discontinuation due to AEs was rare (2.9%). Conclusions: SG was associated with similar clinical outcomes and tolerability in both the mTNBC and mHRPBC subtypes. Although the real-world PFS and OS outcomes mirror those seen in clinical trials, the absence of a control group means that these findings should be interpreted descriptively rather than as confirmation of treatment efficacy. Importantly, this study provides one of the first real-world datasets evaluating SG in the mHRPBC subgroup, highlighting its potential role beyond clinical trials. These results support SG as a valuable therapeutic option in heavily pretreated patients, warranting further prospective and biomarker-driven studies. Full article