bluuebunny/crossref_metadata_2025_split huggingface dataset:
A model-free variable screening method for optimal treatment regimes with high-dimensional survival data
Authors: Yang Cheng-Han , Cheng Yu-Jen 
Published: May 2024

Summary
We propose a model-free variable screening method for the optimal treatment regime with high-dimensional survival data. The proposed screening method provides a unified framework to select the active variables in a prespecified target population, including the treated group as a special case. Based on this framework, the optimal treatment regime is exactly the optimal classifier that minimizes a weighted misclassification error rate, with weights associated with survival outcome variables, the censoring distribution and a prespecified target population. Our main contribution involves reformulating the weighted classification problem into a classification problem within a hypothetical population, where the observed data can be viewed as a sample obtained from outcome-dependent sampling, with the selection probability inversely proportional to the weights. Consequently, we introduce the weighted Kolmogorov–Smirnov approach for selecting active variables in the optimal treatment regime, extending the conventional Kolmogorov–Smirnov method for binary classification. Additionally, the proposed screening method exhibits two levels of robustness. The first level of robustness is achieved because the proposed method does not require any model assumptions for the survival outcome on treatment and covariates, whereas the other is attained as the form of treatment regimes is allowed to be unspecified even without requiring convex surrogate loss, such as logit loss or hinge loss. As a result, the proposed screening method is robust to model misspecifications, and nonparametric learning methods such as random forests and boosting can be applied to those selected variables for further analysis. The theoretical properties of the proposed method are established. The performance of the proposed method is examined through simulation studies and illustrated by a lung cancer dataset.
Histone deacetylase 3-specific inhibitor RGFP966 attenuates oxidative stress and inflammation after traumatic brain injury by activating the Nrf2 pathway
Authors: Xu Lanjuan , An Tingting , Jia Baohui , Wu Qiong , Shen Jinggui , Jin Jie , Liu Jing , Li Chengjian 
Published: May 2024

Abstract

Background
Oxidative stress (OS) and inflammatory reactions play pivotal roles in secondary brain injury after traumatic brain injury (TBI). Histone deacetylase 3 (HDAC3) controls the acetylation of histones and non-histones, which has a significant impact on the central nervous system’s reaction to damage. This research determined the implications of RGFP966, a new and specific inhibitor of HDAC3, for the antioxidant (AO) systems mediated by nuclear factor erythroid2-related factor 2 (Nrf2) and the Nod-like receptor protein 3 (NLRP3) inflammasome in TBI. The study also studied the underlying mechanisms of RGFP966’s actions. Our objective was to examine the impacts and underlying RGFP966 mechanisms in TBI.

Methods
In vitro, a rat cortical neuron OS model was induced by H2O2, followed by the addition of RGFP966 to the culture medium. Neurons were collected after 24 h for western blot (WB), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) and 2′-7′-dichlorodihydrofluorescein diacetate staining. In vivo, RGFP966 (10 mg/kg) was administered post-TBI. Brain tissue water content and modified neurological severity scores were assessed 72 h post-injury. Cortical tissues surrounding the focal injury were subjected to western blot, TUNEL staining, Nissl staining and immunofluorescence/immunohistochemistry staining, and malondialdehyde level, hindered glutathione content and superoxide dismutase activity were measured. Serum was collected for the enzyme-linked immunosorbent assay. Nrf2-specific shRNA lentivirus was injected into the lateral ventricle of rats for 7 days, and cerebral cortex tissue was analyzed by WB and real-time polymerase chain reaction.

Results
During in vitro and in vivo experiments, RGFP966 suppressed HDAC3 expression, promoted Nrf2 nuclear translocation, activated downstream AO enzymes, mitigated excessive reactive oxygen species production and alleviated nerve cell apoptosis. RGFP966 effectively reduced brain edema and histological damage and enhanced neurological and cognitive function in rats with TBI. RGFP966 markedly inhibited NLRP3 inflammasome activation mediated by high-mobility group box 1 (HMGB1)/toll-like receptor 4 (TLR4). Nrf2 knockdown in TBI rats attenuated the AO and anti-inflammatory, neuroprotective impacts of RGFP966.

Conclusions
Overall, our findings demonstrate that RGFP966 can mitigate the first brain damage and neurological impairments in TBI. The underlying mechanism involves triggering the Nrf2-mediated AO system and negatively regulating the HMGB1/TLR4-mediated NLRP3 inflammasome pathway.
Development and Validation of the HPLC Method for Simultaneous Quantification of Glucose and Xylose in Sugar Cane Bagasse Extract
Authors: Jafari Saeedeh , Hematian Sourki Abdollah 
Published: May 2024

Abstract
A validated rapid high-performance liquid chromatography (HPLC)-refractive index (RI) method was developed for the identification and quantification of glucose and xylose in hydrolyzed bagasse extract. The separation of compounds was achieved on Eurokat® H column (300 × 8 mm, 10 μm) at 75°C, using 0.01 N sulfuric acid solution as mobile phase and 0.6 mL/min as flow rate. The method was validated based on accuracy, precision, linearity, robustness, uncertainty, limit of detection (LOD) and limit of quantification (LOQ). Total chromatographic analysis time per sample was ~11 min. Calibration plots were linear over the concentration ranges 11–100 μg/100 μL for glucose and xylose. The LOD was 0.8 ppm and LOQ was 2.5 ppm. The high recovery and low relative standard deviation confirm the suitability of the method for determination of glucose and xylose in bagasse extract. The proposed HPLC-RI method was accurate, fast and robust and required less run time due to less analytes retention times and allowed optimal energy consumption owing to lower column oven temperature.
Development of Response Surface Approach for Determination of Paracetamol, Chlorpheniramine Maleate, Caffeine and Ascorbic Acid by Green HPLC Method: A Desirability-Based Optimization
Authors: Mouhamed Aya A , Eltanany Basma M , Mostafa Nadia M , Nadim Ahmed H 
Published: May 2024

Abstract
Design of experiment is an efficient and cost-effective tool to optimize the chromatographic separation of a multicomponent mixture. The central composite design was conducted to develop and optimize a green high performance liquid chromatography (HPLC) method for simultaneous quantitation of a quaternary mixture of paracetamol, chlorpheniramine maleate, caffeine and ascorbic acid in their pharmaceutical dosage form as well as the determination of their dissolution profile. A five-level three-factor model was performed to investigate the effect of mobile phase composition, pH and flow rate on enhanced resolution and short run time. Analysis was performed using a Kinitex EVO C18 column and a mobile phase composed of methanol: 0.02 M phosphate buffer pH 3.3 (34:66, v/v) at 1.0 mL/min using photodiode array detection. Optimum chromatographic separation was achieved in &lt;6 min with a desirability of 0.999. Linearity was achieved over a range of 1.00–300.00, 1.00–50.00, 2.00–50.00 and 2.00–100.00 μg/mL for paracetamol, chlorpheniramine maleate, caffeine and ascorbic acid, respectively, with a limit of detection (&lt;0.1 μg/mL). The greenness profile was evaluated using the analytical eco-scale and Analytical GREEnness Metric Approach with values of 81 and 0.77, respectively.
Tor Trace in Images: A Novel Multi-Tab Website Fingerprinting Attack With Object Detection
Authors: Xu Yifan , Wang Liangmin , Chen Jie , Zhou Qiang 
Published: May 2024

AbstractWebsite fingerprinting (WF) attacks on Tor enable a passive adversary to predict the encrypted web browsing activity of a victim by matching the eavesdropped traffic with pretrained classifiers. Nowadays, deep learning-based methods have led to significant achievements in the single-tab Tor WF attack. However, the practical implementation of these single-tab methods is challenging due to most real-world Tor traffic involving multiple tabs. Existing single-tab methods hardly identify multi-tab WF due to the overlapping areas of the traffic trace confusing the original features. In this paper, we propose a Trace Image-based Object Detection model named TIOD as a novel multi-tab attacking model. Specifically, we model the traffic overlap in Tor as the object overlap in object detection tasks from the computer vision field. Besides, we propose a special S-matrix scheme to convert a trace into an image: (i) Retaining the original features by keeping the direction and order of the cells and (ii) Bringing cells of the same page closer together in space. We then utilize a specially designed object detection model for trace images, WF R-CNN, to extract features and identify potential destination websites within multi-tab traces. Comparative analysis with other multi-tab attacks is conducted, and the empirical results consistently underscore the superior performance of the proposed trace image model across diverse datasets. In the two-tab setting, TIOD achieves the best accuracy with more than 85% on both the first and second tabs.
Flight capacity and behavior of Ephestia kuehniella (Lepidoptera: Pyralidae) in response to kairomonal and pheromonal stimuli
Authors: Abshire Jennifer , Harman Rachel , Bruce Alexander , Gillette Samantha , Maille Jacqueline M , Ranabhat Sabita , Scully Erin D , Zhu Kun Yan , Gerken Alison R , Morrison William R 
Published: May 2024

Abstract
Flight behavior is an important component to understand in the context of pest management. However, because of their small size, little is known about the flight capacity of most stored-product insects, and when a flight has been assessed, it usually consists of a propensity for initiating flight. Despite a priori expectations of the importance of flight for moths, there are no data about the flight capacity and little on the flight behavior of the Mediterranean flour moth, Ephestia kuehniella Zeller (Lepidoptera: Pyralidae). As a result, the objective of the current study was to (i) characterize the baseline flight capacity of E. kuehniella and (ii) determine how flight capacity is affected by the presence of kairomonal, pheromonal, or no stimuli. We found adult E. kuehniella flew a mean of 24–34 km in a 24-h period, and the distance flown per bout increased from 91 to 207 m in the presence of pheromones but decreased to 41 m when food was nearby compared to a negative control. The total number of flight bouts was 1.6-fold higher in the presence of pheromone compared to the negative control, but E. kuehniella flew significantly slower with pheromone and food cues present, suggesting they may be exhibiting an optimal foraging strategy. Our data on flight capacity results in qualitatively and quantitatively different conclusions about flight than those conclusions formed if only flight initiation is considered. Overall, this novel information is useful for understanding the spread within facilities and in the landscape (between facilities), as well as parameterizing ecological modeling.
From data to discovery: AI-guided analysis of disease-relevant molecules in spinal muscular atrophy (SMA)
Authors: Tapken Ines , Kuhn Daniela , Hoffmann Nico , Detering Nora T , Schüning Tobias , Billaud Jean-Noël , Tugendreich Stuart , Schlüter Nadine , Green Jeff , Krämer Andreas , Claus Peter 
Published: May 2024

AbstractSpinal Muscular Atrophy is caused by partial loss of survival of motoneuron (SMN) protein expression. The numerous interaction partners and mechanisms influenced by SMN loss result in a complex disease. Current treatments restore SMN protein levels to a certain extent, but do not cure all symptoms. The prolonged survival of patients creates an increasing need for a better understanding of SMA. Although many SMN-protein interactions, dysregulated pathways, and organ phenotypes are known, the connections among them remain largely unexplored. Monogenic diseases are ideal examples for the exploration of cause-and-effect relationships to create a network describing the disease-context. Machine learning tools can utilize such knowledge to analyze similarities between disease-relevant molecules and molecules not described in the disease so far. We used an artificial intelligence-based algorithm to predict new genes of interest. The transcriptional regulation of 8 out of 13 molecules selected from the predicted set were successfully validated in an SMA mouse model. This bioinformatic approach, using the given experimental knowledge for relevance predictions, enhances efficient targeted research in SMA and potentially in other disease settings.
Solidarity as Foundation for Economic, Social and Cultural Rights
Authors: Casla Koldo , Sandner Marion 
Published: May 2024

Abstract
The potential of the principle of solidarity as an interpretative guide for the realisation of ESCR has, to date, been largely overlooked. Solidarity mediates between the individual and the community, and it has a collective dimension in relation to both burden- and benefit-sharing. The recognition of ESCR creates not only positive legal obligations on the state but also civic responsibilities on individuals to contribute, within their means, to the progressive realisation of ESCR. While the state is ultimately accountable for making progress on ESCR, taking these rights seriously will have implications for individual rights and responsibilities. We argue in this article that the principle of solidarity within society underpins ESCR as a whole and is essential for achieving sustainable progress on ESCR. This is because their progressive realisation requires not only that states' legal obligations are fulfilled but also that individual and collective contributions are made for the common good.
Sex and Gender in International Human Rights Law through the Prism of the ‘Women’ Category in Recent Case Law
Authors: Yahyaoui Krivenko Ekaterina 
Published: May 2024

Abstract
This article problematises the current understanding of sex and gender in international human rights law, especially as it manifests itself in its treatment of the ‘women’ category. The problematic nature of the current state of international human rights law in this regard came recently to light in two cases: the majority judgment in the Y v France case of the European Court for Human Rights and the dissenting opinions in the Vicky Hernández case of the Inter-American Court of Human Rights. Arguments and statements emerging from these two authoritative recent sources coming from two arguably progressive jurisdictions exemplify continuing inadequacies of the dominant approach. Through a critical engagement with these arguments, supplemented by the discussion of the broader framework of international human rights law, the article not only points out the precise nature of the existing shortcomings but also formulates strategies for overcoming them.
Repaired coarctation of the aorta does not affect four-dimensional flow metrics in bicuspid aortic valve disease
Authors: Kiljander Teemu , Kauhanen Petteri , Sillanmäki Saara , Lottonen-Raikaslehto Line , Husso Minna , Ylä-Herttuala Elias , Saari Petri , Kokkonen Jorma , Laukkanen Jari , Mustonen Pirjo , Hedman Marja 
Published: May 2024

Abstract

OBJECTIVES
The objective of this study was primarily to compare four-dimensional flow magnetic resonance imaging metrics in the ascending aorta (AA) of patients with right–left fusion type bicuspid aortic valve (RL-BAV) and repaired coarctation of the aorta (CoA) to RL-BAV without CoA. Metrics of patients with RL-BAV were also compared to the matched group of patients with common tricuspid aortic valve (TAV).

METHODS
Eleven patients with RL-BAV and CoA, 11 patients with RL-BAV without CoA and 22 controls with TAV were investigated. Peak velocity (cm/s), peak flow (ml/s) and flow displacement (%) were analysed at 5 pre-defined AA levels. In addition, regional wall shear stress (WSS, mN/m2), circumferential WSS (WSSc) and axial WSS (WSSa) at all levels were quantified in 6 sectors of the aortic circle. Averaged WSS values on each level (WSSavg, WSSc, avg and WSSa, avg) were calculated as well.

RESULTS
Peak velocity at the proximal tubular AA was significantly lower in BAV and CoA group (P = 0.047) compared to BAV without CoA. In addition, the WSSa, avg was found to be higher for the BAV and CoA group at proximal AA respectively (P = 0.040). No other significant differences were found between these groups. BAV group’s peak velocity was higher at every level (P &lt; 0.001–0.004) compared to TAV group. Flow displacement was significantly higher for the BAV group at every level (P &lt; 0.001) besides at the most distal level. All averaged WSS values were significantly higher in BAV patients in distal AA (P &lt; 0.001–0.018).

CONCLUSIONS
Repaired CoA does not relevantly alter four-dimensional flow metrics in the AA of patients with RL-BAV. However, RL-BAV majorly alters flow dynamics in the AA when compared to patients with TAV.

Clinical trial registration number
https://www.clinicaltrials.gov/study/NCT05065996, Unique Protocol ID 5063566
Strong convergence of adaptive time-stepping schemes for the stochastic Allen–Cahn equation
Authors: Chen Chuchu , Dang Tonghe , Hong Jialin 
Published: May 2024

Abstract
It is known from Beccari et al. (2019) that the standard explicit Euler-type scheme (such as the exponential Euler and the linear-implicit Euler schemes) with a uniform timestep, though computationally efficient, may diverge for the stochastic Allen–Cahn equation. To overcome the divergence, this paper proposes and analyzes adaptive time-stepping schemes, which adapt the timestep at each iteration to control numerical solutions from instability. The a priori estimates in $\mathscr{C}(\mathscr{O})$-norm and $\dot{H}^{\beta }(\mathscr{O})$-norm of numerical solutions are established provided the adaptive timestep function is suitably bounded, which plays a key role in the convergence analysis. We show that the adaptive time-stepping schemes converge strongly with order $\frac{\beta }{2}$ in time and $\frac{\beta }{d}$ in space with $d$ ($d=1,2,3$) being the dimension and $\beta \in (0,2]$. Numerical experiments show that the adaptive time-stepping schemes are simple to implement and at a lower computational cost than a scheme with the uniform timestep.
A certified wavelet-based physics-informed neural network for the solution of parameterized partial differential equations
Authors: Ernst Lewin , Urban Karsten 
Published: May 2024

Abstract
Physics Informed Neural Networks (PINNs) have frequently been used for the numerical approximation of Partial Differential Equations (PDEs). The goal of this paper is to construct PINNs along with a computable upper bound of the error, which is particularly relevant for model reduction of Parameterized PDEs (PPDEs). To this end, we suggest to use a weighted sum of expansion coefficients of the residual in terms of an adaptive wavelet expansion both for the loss function and an error bound. This approach is shown here for elliptic PPDEs using both the standard variational and an optimally stable ultra-weak formulation. Numerical examples show a very good quantitative effectivity of the wavelet-based error bound.
Determination of Bovine Lactoferrin in Powdered Infant Formula and Adult Nutritionals by Heparin Affinity Extraction and Reverse-Phase High-Performance Liquid Chromatography/Ultraviolet Detection (HPLC/UV): Single-Laboratory Validation, First Action 2021.10
Authors: Frueh Jennifer L , Shu Peng , Vennard Thomas R , Gray Michael A , Phillips Shay C 
Published: May 2024

Abstract

Background
Infant formulas, and pediatric and adult nutritional products, are being fortified with bovine lactoferrin (bLF) due to its beneficial impacts on immune development and gut health. Lactoferrin supplementation into these products requires an analytical method to accurately quantify the concentrations of bLF to meet global regulatory and quality standards.

Objective
To develop and validate a lactoferrin method capable of meeting the AOAC INTERNATIONAL Standard Method Performance Requirements (SMPR®) 2020.005.

Methods
Powder formula samples are extracted using warm dibasic phosphate buffer, pH 8, then centrifuged at 4°C to remove insoluble proteins, fat, and other solids. The soluble fraction is further purified on a HiTrap heparin solid-phase extraction (SPE) column to isolate bLF from interferences. Samples are filtered, then analyzed by LC–UV using a protein BEH C4 analytical column and quantitated using an external calibrant.

Results
The LOQ (2 mg/100 g), repeatability (RSD: 2.0–4.8%), recovery (92.1–97.7%), and analytical range (4–193 mg/100 g) all meet the method requirements as stated in SMPR 2020.005 for lactoferrin.

Conclusion
The reported single-laboratory validation (SLV) results demonstrate the ability of this lactoferrin method to meet or exceed the method performance requirements to measure soluble, intact, non-denatured bLF in infant and adult nutritional powder formulas.

Highlights
The use of a heparin affinity column to isolate lactoferrin from bovine milk products combined with a selective analytical chromatographic column provides suitable analyte specificity without requiring proprietary equipment or reagents.