bluuebunny/crossref_metadata_2025_split huggingface dataset:
High resolution fluorescence imaging of the alveolar scaffold as a novel tool to assess lung injury
Authors: Lindstedt Sandra , Wang Qi , Niroomand Anna , Stenlo Martin , Hyllen Snejana , Pierre Leif , Olm Franziska , Bechet Nicholas B. 
Published: March 2024

AbstractAcute lung injury (ALI) represents an aetiologically diverse form of pulmonary damage. Part of the assessment and diagnosis of ALI depends on skilled observer-based scoring of brightfield microscopy tissue sections. Although this readout is sufficient to determine gross alterations in tissue structure, its categorical scores lack the sensitivity to describe more subtle changes in lung morphology. To generate a more sensitive readout of alveolar perturbation we carried out high resolution immunofluorescence imaging on 200 μm lung vibratome sections from baseline and acutely injured porcine lung tissue, stained with a tomato lectin, Lycopersicon Esculentum Dylight-488. With the ability to resolve individual alveoli along with their inner and outer wall we generated continuous readouts of alveolar wall thickness and circularity. From 212 alveoli traced from 10 baseline lung samples we established normal distributions for alveolar wall thickness (27.37; 95% CI [26.48:28.26]) and circularity (0.8609; 95% CI [0.8482:0.8667]) in healthy tissue. Compared to acutely injured lung tissue baseline tissue exhibited a significantly lower wall thickness (26.86 ± 0.4998 vs 50.55 ± 4.468; p = 0.0003) and higher degree of circularityϕ≤ (0.8783 ± 0.01965 vs 0.4133 ± 0.04366; p < 0.0001). These two components were subsequently combined into a single more sensitive variable, termed the morphological quotient (MQ), which exhibited a significant negative correlation (R2 = 0.9919, p < 0.0001) with the gold standard of observer-based scoring. Through the utilisation of advanced light imaging we show it is possible to generate sensitive continuous datasets describing fundamental morphological changes that arise in acute lung injury. These data represent valuable new analytical tools that can be used to precisely benchmark changes in alveolar morphology both in disease/injury as well as in response to treatment/therapy.
Effects of kinect-based virtual reality training on bone mineral density and fracture risk in postmenopausal women with osteopenia: a randomized controlled trial
Authors: Riaz Saima , Shakil Ur Rehman Syed , Hafeez Sana , Hassan Danish 
Published: March 2024

AbstractOsteopenia is a condition characterized by low bone mineral density (BMD) that increases fracture risk, particularly among postmenopausal women (PMW). This study aimed to determine the effects of Kinect-based VRT on BMD and fracture risk in PMW with osteopenia. The study was a prospective, two-arm, parallel-design, randomized controlled trial. The study enrolled 52 participants, 26 randomly assigned to each group. In the experimental group, Kinect-based VRT was provided thrice weekly for 24 weeks for 45 min/session. Both groups were instructed to engage in a daily 30-min walk outdoors. The fracture risk assessment tool (FRAX) was used to calculate fracture risk, and dual-energy X-ray absorptiometry was used to measure lumbar spine and femur neck BMD. Both variables were assessed at baseline and 24 weeks afterwards. After 24 weeks of Kinect-based VRT, the experimental group showed significant BMD increases in the right and left femoral necks and lumbar spine (p value < 0.001). In the control group, the BMD at the right and left femoral necks showed fewer significant changes (p value < 0.022 and 0.004, respectively). In the control group, lumbar spine BMD did not change (p = 0.57). The experimental group showed significantly lower FRAX scores for hip fracture prediction (HFP) and hip prediction of major osteoporotic (HPMO) at both femoral necks (p value < 0.001) than the control group (p = 0.05 and p = 0.01, respectively), but no significant change at the left femoral neck for HFP (p = 0.66) or HPMO (p = 0.26). These findings indicate that a Kinect-based VRT intervention resulted in significantly increased BMD and a reduced fracture risk, as predicted by HFP and HPMO measurements. These improvements were more pronounced in the experimental group than in the control group. Thus, Kinect-based VRT may be utilized as an effective intervention to improve BMD and reduce fracture risk in postmenopausal women with osteopenia.
Caveolin-1 gene expression provides additional prognostic information combined with PAM50 risk of recurrence (ROR) score in breast cancer
Authors: Godina Christopher , Belting Mattias , Vallon-Christersson Johan , Isaksson Karolin , Bosch Ana , Jernström Helena 
Published: March 2024

AbstractCombining information from the tumor microenvironment (TME) with PAM50 Risk of Recurrence (ROR) score could improve breast cancer prognostication. Caveolin-1 (CAV1) is a marker of an active TME. CAV1 is a membrane protein involved in cell signaling, extracellular matrix organization, and tumor-stroma interactions. We sought to investigate CAV1 gene expression in relation to PAM50 subtypes, ROR score, and their joint prognostic impact. CAV1 expression was compared between PAM50 subtypes and ROR categories in two cohorts (SCAN-B, n = 5326 and METABRIC, n = 1980). CAV1 expression was assessed in relation to clinical outcomes using Cox regression and adjusted for clinicopathological predictors. Effect modifications between CAV1 expression and ROR categories on clinical outcome were investigated using multiplicative and additive two-way interaction analyses. Differential gene expression and gene set enrichment analyses were applied to compare high and low expressing CAV1 tumors. All samples expressed CAV1 with the highest expression in the Normal-like subtype. Gene modules consistent with epithelial-mesenchymal transition (EMT), hypoxia, and stromal activation were associated with high CAV1 expression. CAV1 expression was inversely associated with ROR category. Interactions between CAV1 expression and ROR categories were observed in both cohorts. High expressing CAV1 tumors conferred worse prognosis only within the group classified as ROR high. ROR gave markedly different prognostic information depending on the underlying CAV1 expression. CAV1, a potential mediator between the malignant cells and TME, could be a useful biomarker that enhances and further refines PAM50 ROR risk stratification in patients with ROR high tumors and a potential therapeutic target.
Unraveling diffusion behavior in Cu-to-Cu direct bonding with metal passivation layers
Authors: Jeong Min Seong , Park Sang Woo , Kim Yeon Ju , Kim Ji Hun , Hong Seul Ki , Kim Sarah Eunkyung , Park Jong Kyung 
Published: March 2024

AbstractCu/SiO2hybrid bonding presents a promising avenue for achieving high-density interconnects by obviating the need for microbumps and underfills. Traditional copper bonding methods often demand temperatures exceeding 400 °C, prompting recent endeavors to mitigate bonding temperatures through investigations into metal passivation bonding. In this study, we scrutinized the diffusion behavior associated with various metal passivation layers (Platinum, Titanium, Tantalum, and Chromium) in the context of low-temperature direct copper bonding and delved into the essential bonding mechanisms. We observed a deviation from conventional metal–metal bonding factors, such as surface roughness and grain size, in the diffusion behavior. Remarkably, our analysis revealed a pronounced correlation between the crystallinity of the metal passivation layers and diffusion behavior, surpassing the influence of other experimental factors. Subsequent post-bonding examinations corroborated consistent diffusion behavior in Pt and Cr passivation samples with disparate crystallinities, reinforcing the significance of crystallinity in the bonding process. Our findings underscore crystallinity as a pivotal factor governing diffusion behavior, even under varied bonding conditions. These insights are instrumental in achieving exceptional bonding characteristics at lower temperatures in Cu/SiO2hybrid bonding. Implications of this study extend to the prospect of advancing highly integrated systems through die-to-wafer bonding, marking a substantial stride toward future applications.
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence
Authors: Eckardt Jan-Niklas , Hahn Waldemar , Röllig Christoph , Stasik Sebastian , Platzbecker Uwe , Müller-Tidow Carsten , Serve Hubert , Baldus Claudia D. , Schliemann Christoph , Schäfer-Eckart Kerstin , Hanoun Maher , Kaufmann Martin , Burchert Andreas , Thiede Christian , Schetelig Johannes , Sedlmayr Martin , Bornhäuser Martin , Wolfien Markus , Middeke Jan Moritz 
Published: March 2024

AbstractClinical research relies on high-quality patient data, however, obtaining big data sets is costly and access to existing data is often hindered by privacy and regulatory concerns. Synthetic data generation holds the promise of effectively bypassing these boundaries allowing for simplified data accessibility and the prospect of synthetic control cohorts. We employed two different methodologies of generative artificial intelligence – CTAB-GAN+ and normalizing flows (NFlow) – to synthesize patient data derived from 1606 patients with acute myeloid leukemia, a heterogeneous hematological malignancy, that were treated within four multicenter clinical trials. Both generative models accurately captured distributions of demographic, laboratory, molecular and cytogenetic variables, as well as patient outcomes yielding high performance scores regarding fidelity and usability of both synthetic cohorts (n = 1606 each). Survival analysis demonstrated close resemblance of survival curves between original and synthetic cohorts. Inter-variable relationships were preserved in univariable outcome analysis enabling explorative analysis in our synthetic data. Additionally, training sample privacy is safeguarded mitigating possible patient re-identification, which we quantified using Hamming distances. We provide not only a proof-of-concept for synthetic data generation in multimodal clinical data for rare diseases, but also full public access to synthetic data sets to foster further research.
Common mouse models of chronic kidney disease are not associated with cachexia
Authors: Lair Benjamin , Lac Marlène , Frassin Lucas , Brunet Manon , Buléon Marie , Feuillet Guylène , Maslo Claire , Marquès Marie , Monbrun Laurent , Bourlier Virginie , Montastier Emilie , Viguerie Nathalie , Tavernier Geneviève , Laurens Claire , Moro Cedric 
Published: March 2024

AbstractThe 5/6 nephrectomy and adenine-induced nephropathy mouse models have been extensively used to study Chronic Kidney Disease (CKD)-related cachexia. One common caveat of these CKD models is the cross-sectional nature of comparisons made versus controls. We here performed a comprehensive longitudinal assessment of body composition and energy metabolism in both models. The most striking finding is that weight loss is largely driven by reduced food intake which promotes rapid loss of lean and fat mass. However, in both models, mice catch up weight and lean mass a few days after the surgery or when they are switched back to standard chow diet. Muscle force and mass are fully recovered and no sign of cachexia is observed. Our data demonstrate that the time-course of kidney failure and weight loss are unrelated in these common CKD models. These data highlight the need to reconsider the relative contribution of direct and indirect mechanisms to muscle wasting observed in CKD.
AKAP150-anchored PKA regulates synaptic transmission and plasticity, neuronal excitability and CRF neuromodulation in the mouse lateral habenula
Authors: Simmons Sarah C. , Flerlage William J. , Langlois Ludovic D. , Shepard Ryan D. , Bouslog Christopher , Thomas Emily H. , Gouty Kaitlyn M. , Sanderson Jennifer L. , Gouty Shawn , Cox Brian M. , Dell’Acqua Mark L. , Nugent Fereshteh S. 
Published: March 2024

AbstractThe scaffolding A-kinase anchoring protein 150 (AKAP150) is critically involved in kinase and phosphatase regulation of synaptic transmission/plasticity, and neuronal excitability. Emerging evidence also suggests that AKAP150 signaling may play a key role in brain’s processing of rewarding/aversive experiences, however its role in the lateral habenula (LHb, as an important brain reward circuitry) is completely unknown. Using whole cell patch clamp recordings in LHb of male wildtype and ΔPKA knockin mice (with deficiency in AKAP-anchoring of PKA), here we show that the genetic disruption of PKA anchoring to AKAP150 significantly reduces AMPA receptor-mediated glutamatergic transmission and prevents the induction of presynaptic endocannabinoid-mediated long-term depression in LHb neurons. Moreover, ΔPKA mutation potentiates GABAA receptor-mediated inhibitory transmission while increasing LHb intrinsic excitability through suppression of medium afterhyperpolarizations. ΔPKA mutation-induced suppression of medium afterhyperpolarizations also blunts the synaptic and neuroexcitatory actions of the stress neuromodulator, corticotropin releasing factor (CRF), in mouse LHb. Altogether, our data suggest that AKAP150 complex signaling plays a critical role in regulation of AMPA and GABAA receptor synaptic strength, glutamatergic plasticity and CRF neuromodulation possibly through AMPA receptor and potassium channel trafficking and endocannabinoid signaling within the LHb.
Folic acid supplementation prevents high body fat-induced bone loss through TGR5 signaling pathways
Authors: Zhang Yaxi , Wei Jieqiong , Feng Xiangling , Lin Qian , Deng Jing , Yuan Yuehan , Li Min , Zhai Bingfang , Chen Jihua 
Published: March 2024

Folic acid intake was correlated with BMD, and the association may be mediated by BFR. Meanwhile, folic acid supplementation can improve bone loss in high-body fat mice, and its mechanism may be related to LCA and TGR5 signaling pathways.
The complement system in neurodegenerative diseases
Authors: Nimmo Jacqui , Byrne Robert A.J. , Daskoulidou Nikoleta , Watkins Lewis M. , Carpanini Sarah M. , Zelek Wioleta M. , Morgan B. Paul 
Published: March 2024

Abstract
Complement is an important component of innate immune defence against pathogens and crucial for efficient immune complex disposal. These core protective activities are dependent in large part on properly regulated complement-mediated inflammation. Dysregulated complement activation, often driven by persistence of activating triggers, is a cause of pathological inflammation in numerous diseases, including neurological diseases. Increasingly, this has become apparent not only in well-recognized neuroinflammatory diseases like multiple sclerosis but also in neurodegenerative and neuropsychiatric diseases where inflammation was previously either ignored or dismissed as a secondary event. There is now a large and rapidly growing body of evidence implicating complement in neurological diseases that cannot be comprehensively addressed in a brief review. Here, we will focus on neurodegenerative diseases, including not only the ‘classical’ neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease, but also two other neurological diseases where neurodegeneration is a neglected feature and complement is implicated, namely, schizophrenia, a neurodevelopmental disorder with many mechanistic features of neurodegeneration, and multiple sclerosis, a demyelinating disorder where neurodegeneration is a major cause of progressive decline. We will discuss the evidence implicating complement as a driver of pathology in these diverse diseases and address briefly the potential and pitfalls of anti-complement drug therapy for neurodegenerative diseases.
Temporal convex combination‐based secure distributed estimation against cyberattacks and noisy input
Authors: Zhang Zhanxi , Jia Lijuan , Peng Senran , Yang Zi‐Jiang , Tao Ran 
Published: March 2024

AbstractThis paper proposes a new secure distributed estimation for cyber‐physical systems against adversarial attacks with noisy input. To mitigate the effect of attacks, a novel distributed attack detection based on a reliable reference estimation obtained by temporal convex combination is proposed. Furthermore, for more effective and robust performance, an adaptation rule to adjust convex combination weights is presented, in which the generalized correntropy method with nonlinear loss function and stochastic gradient descent are utilized. Besides, to eliminate input noise, a bias‐compensation method in local adaptation of the secure distributed estimation is proposed. Simulations show superior dynamic and real‐time adaptability of the proposed algorithm under complex attacking scenarios.
Accelerated thermal ageing on performance of polypropylene‐based semiconducting screen for high voltage direct current cable applications—Effect of antioxidants
Authors: Wang Haitian , Luo Yi , Zhou Mingyu , Ren Xintong , Chen George 
Published: March 2024

AbstractThe potential of using eco‐friendly thermoplastic polypropylene (PP)‐based insulation for high voltage direct current (HVDC) cable has been widely investigated but much less work on the PP‐based semiconducting screen (SC). Considering a long service life (>30 years) under high temperature and high electrical stress is required for typical HVDC cables, and investigations on the effect of antioxidant (AO) concentration and thermal oxidative stability, mechanical, and electrical properties of PP‐based SCs have been conducted. It has been demonstrated that an appropriate combination and amounts of AOs are critical for achieving high thermal stability and maintaining the mechanical properties of SC after ageing in a harsh environment (150°C, with Cu, in air, 7 days). Although higher amounts of space charges have been observed in SC/PP/SC samples with higher AO concentrations, the impact on space charge behaviours is less after ageing, suggesting that ageing (or operating at high temperature) leads to microstructure evolution in SC and can potentially mitigate space accumulation in PP‐based insulating materials.
A Delaunay triangulation based dynamic pricing approach to profit‐driven crowdsourced package delivery
Authors: Zhou Zhifeng , Chen Rong , Deng Wu 
Published: March 2024

AbstractCrowdsourced package delivery (CPD) has gained great interest from the logistics industry and academe due to its signficant economic and environmental impact. A number of progresses have been reported; however, dynamic pricing, as a special and significant part of the uncertain CPD markets, is far less explored. To address the problem, a novel Delaunay Triangulation (DT) based pricing strategy is proposed for dealing with the imbalanced demand and supply in local markets with the aim to maximizing the profit of the CPD platform. To cater to drivers’ wishes further, the hyperbolic temporal discounting function is applied to estimate their psychological rewards in order to increase the possibility of package acceptance. A three‐stage framework consisting of the DT‐based pricing, the matching pruning and the package assigning algorithm is proposed, to figure out the best‐possible package‐driver matching. With the dataset generated by Brinkhoff road network generator in the city of Jinan and Luoyang, China, a series of experiments is conducted to evaluate the proposed approach against several representative baseline approaches. Experimental results show that the approach significantly outperforms the other approaches in terms of effectiveness and efficiency.
Analysis and optimization of the automated TIG welding process parameters on SS304 incorporating Taguchi optimization technique
Authors: Thangavel Subramaniam , Maheswari Chenniappan , Priyanka Elanthakadu Bhaskaran , Stonier Albert Alexander , Peter Geno , Ganji Vivekananda 
Published: March 2024

AbstractThe present research work focused on optimizing the input parameters of the automated TIG welding process of SS304 metal. Since SS304 possesses high inter‐granular toughness and corrosion resistance with increased lifespan in the pressure vessel and automobile sector, SS304 is mainly referred for gas arc welding compared with SS 202. The SS304 workpieces of 60 mm × 40 mm × 4 mm with dimension are utilized in the experiment and the same metal has been used as the filler material. The TIG welding experimental lab‐scale setup utilizes a 2‐axis servo workbench programmed with PLC to perform an automatic trajectory path using Taguchi design of optimization to obtain the optimal welding parameters for the SS304 welding process. To analyze the influence of welding current, welding speed, gas flow rate, and welding arc length on the tensile strength and hardness based on predicted R‐squared, p‐value and co‐efficient of the sum of squares from are verified. From the regression analysis, the predicted model R‐squared value holds 95.78% and 94.83% for the hardness and tensile strength respectively associating with the actual coefficient confirming the model which has maximum precision. Further, it is inferred that on increasing welding current and welding speed, the hardness of the welded joints seems to increase whereas when the minimum gas flow rate is maintained, the tensile strength of the SS304 decreases drastically. Overall, among the four input factors, the welding current is a major influencing parameter on the SS304 which is directly proportional to tensile strength and hardness.
20.2.4.2 Alkanedioic Acids and Derivatives (Update 2024)
Authors: Yang Z. , Dong K. 
Published: March 2024

AbstractThiocarboxylic acid S-esters are synthetically versatile building blocks that can be smoothly interconverted into a wide array of valuable functional groups including aldehydes, ketones, carboxylic acids, and amides. This review, which is an update to an earlier Science of Synthesis contribution (Section 20.8), covers synthetic strategies to access thiocarboxylic acid S-esters and other derivatives, and primarily focuses on the literature published between 2006 and 2023. Additionally, robust methods to prepare seleno- and tellurocarboxylic acid esters, which are becoming widely used synthons in total synthesis and peptide chemistry, are highlighted.
20.8.13 Thiocarboxylic S-Acid, Selenocarboxylic Se-Acid, and Tellurocarboxylic Te-Acid Derivatives (Update 2024)
Authors: Cellnik T. , Jo W. , Healy A. 
Published: March 2024

AbstractThiocarboxylic acid S-esters are synthetically versatile building blocks that can be smoothly interconverted into a wide array of valuable functional groups including aldehydes, ketones, carboxylic acids, and amides. This review, which is an update to an earlier Science of Synthesis contribution (Section 20.8), covers synthetic strategies to access thiocarboxylic acid S-esters and other derivatives, and primarily focuses on the literature published between 2006 and 2023. Additionally, robust methods to prepare seleno- and tellurocarboxylic acid esters, which are becoming widely used synthons in total synthesis and peptide chemistry, are highlighted.
22.4.9.2 Amidines (Imidamides) N-Substituted by Metals, Halogens, Oxygen, and Other Heteroatoms (Update 2024)
Authors: Huang H. , Deng G.-J. , Ji X. 
Published: March 2024

AbstractThe amidine (or imidamide) group is an important structural unit of organic molecules, including numerous bioactive naturally occurring products, drugs, pesticides, functional materials, and others. Substituted amidines have the general formula R1C(NR2)NR3R4, where R2, R3, and R4 can be metal or halogen atoms, or amino, hydroxy, or silyl groups, or others. These compounds also have wide applications in the construction of complex functionalized molecules. Herein, we showcase new synthetic methodologies developed between 2005 and 2022 for the preparation of amidines that are substituted at one of the nitrogen atoms by metals, halogens, oxygen, or other heteroatoms.