bluuebunny/crossref_metadata_2025_split huggingface dataset:
PDI inhibitor LTI6426 enhances panobinostat efficacy in preclinical models of multiple myeloma
Authors: Robinson Reeder M. , Basar Ashton P. , Reyes Leticia , Duncan Ravyn M. , Li Hong , Dolloff Nathan G. 
Published: April 2022

AbstractThe histone deacetylase inhibitor (HDACi), panobinostat (Pano), is approved by the United States Food and Drug Administration (FDA) and European Medicines Agency (EMA) for treatment of relapsed/refractory multiple myeloma (MM). Despite regulatory approvals, Pano is used on a limited basis in MM due largely to an unfavorable toxicity profile. The MM treatment landscape continues to evolve, and for Pano to maintain a place in that paradigm it will be necessary to identify treatment regimens that optimize its effectiveness, particularly those that permit dose reductions to eliminate unwanted toxicity. Here, we propose such a regimen by combining Pano with LTI6426, a first-in-class orally bioavailable protein disulfide isomerase (PDI) inhibitor. We show that LTI6426 dramatically enhances the anti-MM activity of Pano in vitro and in vivo using a proteasome inhibitor resistant mouse model of MM and a low dose of Pano that exhibited no signs of toxicity. We go on to characterize a transcriptional program that is induced by the LTI6426/Pano combination, demonstrating a convergence of the two drugs on endoplasmic reticulum (ER) stress pathway effectors ATF3 (Activating Transcription Factor 3), DDIT3/CHOP (DNA Damage Inducible Transcript 3, a.k.a. C/EBP Homologous Protein), and DNAJB1 (DnaJ homolog subfamily B member 1, a.k.a. HSP40). We conclude that LTI6426 may safely enhance low-dose Pano regimens and that ATF3, DDIT3/CHOP, and DNAJB1 are candidate pharmacodynamic biomarkers of response to this novel treatment regimen.
No evidence of differential impact of sunflower and rapeseed oil on biomarkers of coronary artery disease or chronic kidney disease in healthy adults with overweight and obesity: result from a randomised control trial
Authors: Nicol Katie , Mansoorian Bahareh , Latosinska Agnieszka , Koutroulaki Aimilia , Mullen Bill , Combet Emilie 
Published: April 2022

Abstract
Purpose
The perceived benefits and risks associated with seed oil intake remain controversial, with a limited number of studies investigating the impact of intake on a range of compounds used as cardiometabolic markers. This study aimed to explore the proteomic and cardiometabolic effects of commonly consumed seed oils in the UK, with different fatty acid profiles.

Methods
In a parallel randomised control design, healthy adults (n = 84), aged 25–72 with overweight or obesity were randomised to one of three groups: control (habitual diet, CON); 20 mL rapeseed oil per day (RO), or 20 mL sunflower oil per day (SO). Blood, spot urine and anthropometric measures were obtained at 0, 6 and 12 weeks. Proteomic biomarkers analysis was conducted for coronary arterial disease (CAD) and chronic kidney disease (CKD) using capillary electrophoresis coupled to mass spectrometry (CE-MS). Blood lipids, fasting blood glucose, glycative/oxidative stress and inflammatory markers were also analysed.

Results
No differences in change between time points were observed between groups for CAD or CKD peptide fingerprint scores. No change was detected within groups for CAD or CKD scores. No detectable differences were observed between groups at week 6 or 12 for the secondary outcomes, except median 8-isoprostane, ~ 50% higher in the SO group after 12-weeks compared to RO and CON groups (p = 0.03).

Conclusion
The replacement of habitual fat with either RO or SO for 12 weeks does not lead to an improvement or worsening in cardiovascular health markers in people with overweight or obesity.

Trial registration
Trial registration clinicaltrials.gov NCT04867629, retrospectively registered 30/04/2021.
Volcano infrasound: progress and future directions
Authors: Watson Leighton M. , Iezzi Alexandra M. , Toney Liam , Maher Sean P. , Fee David , McKee Kathleen , Ortiz Hugo D. , Matoza Robin S. , Gestrich Julia E. , Bishop Jordan W. , Witsil Alex J. C. , Anderson Jacob F. , Johnson Jeffrey B. 
Published: April 2022

Abstract
Over the past two decades (2000–2020), volcano infrasound (acoustic waves with frequencies less than 20 Hz propagating in the atmosphere) has evolved from an area of academic research to a useful monitoring tool. As a result, infrasound is routinely used by volcano observatories around the world to detect, locate, and characterize volcanic activity. It is particularly useful in confirming subaerial activity and monitoring remote eruptions, and it has shown promise in forecasting paroxysmal activity at open-vent systems. Fundamental research on volcano infrasound is providing substantial new insights on eruption dynamics and volcanic processes and will continue to do so over the next decade. The increased availability of infrasound sensors will expand observations of varied eruption styles, and the associated increase in data volume will make machine learning workflows more feasible. More sophisticated modeling will be applied to examine infrasound source and propagation effects from local to global distances, leading to improved infrasound-derived estimates of eruption properties. Future work will use infrasound to detect, locate, and characterize moving flows, such as pyroclastic density currents, lahars, rockfalls, lava flows, and avalanches. Infrasound observations will be further integrated with other data streams, such as seismic, ground- and satellite-based thermal and visual imagery, geodetic, lightning, and gas data. The volcano infrasound community should continue efforts to make data and codes accessible and to improve diversity, equity, and inclusion in the field. In summary, the next decade of volcano infrasound research will continue to advance our understanding of complex volcano processes through increased data availability, sensor technologies, enhanced modeling capabilities, and novel data analysis methods that will improve hazard detection and mitigation.
Nutritional management of the infant with chronic kidney disease stages 2–5 and on dialysis
Authors: Shaw Vanessa , Anderson Caroline , Desloovere An , Greenbaum Larry A. , Haffner Dieter , Nelms Christina L. , Paglialonga Fabio , Polderman Nonnie , Qizalbash Leila , Renken-Terhaerdt José , Stabouli Stella , Tuokkola Jetta , Vande Walle Johan , Warady Bradley A. , Shroff Rukshana 
Published: April 2022

AbstractThe nutritional management of children with chronic kidney disease (CKD) is of prime importance in meeting the challenge of maintaining normal growth and development in this population. The objective of this review is to integrate the Pediatric Renal Nutrition Taskforce clinical practice recommendations for children with CKD stages 2–5 and on dialysis, as they relate to the infant from full term birth up to 1 year of age, for healthcare professionals, including dietitians, physicians, and nurses. It addresses nutritional assessment, energy and protein requirements, delivery of the nutritional prescription, and necessary dietary modifications in the case of abnormal serum levels of calcium, phosphate, and potassium. We focus on the particular nutritional needs of infants with CKD for whom dietary recommendations for energy and protein, based on body weight, are higher compared with children over 1 year of age in order to support both linear and brain growth, which are normally maximal in the first 6 months of life. Attention to nutrition during infancy is important given that growth is predominantly nutrition dependent in the infantile phase and the growth of infants is acutely impaired by disruption to their nutritional intake, particularly during the first 6 months. Inadequate nutritional intake can result in the failure to achieve full adult height potential and an increased risk for abnormal neurodevelopment. We strongly suggest that physicians work closely with pediatric renal dietitians to ensure that the infant with CKD receives the best possible nutritional management to optimize their growth and development.
How Alpine seismicity relates to lithospheric strength
Authors: Spooner Cameron , Scheck-Wenderoth Magdalena , Cacace Mauro , Anikiev Denis 
Published: April 2022

AbstractDespite the amount of research focussed on the Alpine orogen, different hypotheses still exist regarding varying spatial seismicity distribution patterns throughout the region. Previous measurement-constrained regional 3D models of lithospheric density distribution and thermal field facilitate the generation of a data-based rheological model of the region. In this study, we compute the long-term lithospheric strength and compare its spatial variation to observed seismicity patterns. We demonstrate how strength maxima within the crust (~ 1 GPa) and upper mantle (> 2 GPa) occur at temperatures characteristic of the onset of crystal plasticity in those rocks (crust: 200–400 °C; mantle: ~ 600 °C), with almost all seismicity occurring in these regions. Correlation in the northern and southern forelands between crustal and lithospheric strengths and seismicity show different patterns of event distribution, reflecting their different tectonic settings. Seismicity in the plate boundary setting of the southern foreland corresponds to the integrated lithospheric strength, occurring mainly in the weaker domains surrounding the strong Adriatic plate. In the intraplate setting of the northern foreland, seismicity correlates to modelled crustal strength, and it mainly occurs in the weaker and warmer crust beneath the Upper Rhine Graben. We, therefore, suggest that seismicity in the upper crust is linked to weak crustal domains, which are more prone to localise deformation promoting failure and, depending on the local properties of the fault, earthquakes at relatively lower levels of accumulated stress than their neighbouring stronger counterparts. Upper mantle seismicity at depths greater than modelled brittle conditions, can be either explained by embrittlement of the mantle due to grain-size sensitive deformation within domains of active or recent slab cooling, or by dissipative weakening mechanisms, such as thermal runaway from shear heating and/or dehydration reactions within an overly ductile mantle. Results generated in this study are available for open access use to further discussions on the region.
Adversarial classification via distributional robustness with Wasserstein ambiguity
Authors: Ho-Nguyen Nam , Wright Stephen J. 
Published: April 2022

AbstractWe study a model for adversarial classification based on distributionally robust chance constraints. We show that under Wasserstein ambiguity, the model aims to minimize the conditional value-at-risk of the distance to misclassification, and we explore links to adversarial classification models proposed earlier and to maximum-margin classifiers. We also provide a reformulation of the distributionally robust model for linear classification, and show it is equivalent to minimizing a regularized ramp loss objective. Numerical experiments show that, despite the nonconvexity of this formulation, standard descent methods appear to converge to the global minimizer for this problem. Inspired by this observation, we show that, for a certain class of distributions, the only stationary point of the regularized ramp loss minimization problem is the global minimizer.
Massive economic costs of biological invasions despite widespread knowledge gaps: a dual setback for India
Authors: Bang Alok , Cuthbert Ross N. , Haubrock Phillip J. , Fernandez Romina D. , Moodley Desika , Diagne Christophe , Turbelin Anna J. , Renault David , Dalu Tatenda , Courchamp Franck 
Published: April 2022

AbstractBiological invasions are one of the top drivers of the ongoing biodiversity crisis. An underestimated consequence of invasions is the enormity of their economic impacts. Knowledge gaps regarding economic costs produced by invasive alien species (IAS) are pervasive, particularly for emerging economies such as India—the fastest growing economy worldwide. To investigate, highlight and bridge this gap, we synthesised data on the economic costs of IAS in India. Specifically, we examine how IAS costs are distributed spatially, environmentally, sectorally, taxonomically, temporally, and across introduction pathways; and discuss how Indian IAS costs vary with socioeconomic indicators. We found that IAS have cost the Indian economy between at least US$ 127.3 billion to 182.6 billion (Indian Rupees ₹ 8.3 trillion to 11.9 trillion) over 1960–2020, and these costs have increased with time. Despite these massive recorded costs, most were not assigned to specific regions, environments, sectors, cost types and causal IAS, and these knowledge gaps are more pronounced in India than in the rest of the world. When costs were specifically assigned, maximum costs were incurred in West, South and North India, by invasive alien insects in semi-aquatic ecosystems; they were incurred mainly by the public and social welfare sector, and were associated with damages and losses rather than management expenses. Our findings indicate that the reported economic costs grossly underestimate the actual costs, especially considering the expected costs given India’s population size, gross domestic product and high numbers of IAS without reported costs. This cost analysis improves our knowledge of the negative economic impacts of biological invasions in India and the burden they can represent for its development. We hope this study motivates policymakers to address socio-ecological issues in India and launch a national biological invasion research programme, especially since economic growth will be accompanied by greater impacts of global change.
Dietary curcumin nanoparticles promoted the performance, antioxidant activity, and humoral immunity, and modulated the hepatic and intestinal histology of Nile tilapia fingerlings
Authors: Abdel-Tawwab Mohsen , Eissa El-Sayed Hemdan , Tawfik Wesam A. , Abd Elnabi Heba E. , Saadony Saadea , Bazina Walaa K. , Ahmed Ragaa A. 
Published: April 2022

AbstractThe current study investigated the effects of dietary curcumin nanoparticles (C-NPs) on the performance, hemato-biochemical profile, digestive enzymes activities, antioxidant status, humoral immunity, and liver and intestinal histology of Nile tilapia (Oreochromis niloticus). Fish (4.3 ± 0.5 g) were fed with diets enriched with 0.0 (control), 15, 30, 45, and 60 mg C-NPs/kg diet up to apparent satiety thrice a day for 60 days. The growth-stimulating effects of dietary C-NPs were significantly observed in terms of final weight, weight gain %, specific growth rate, and feed intake. Compared with the control group, serum amylase, lipase, and proteases activities of Nile tilapia significantly (P < 0.05) increased alongside the increase in dietary levels of C-NPs in a dose-dependent manner. The counts of red blood cells and white blood cells as well as hemoglobin and hematocrit levels of Nile tilapia fed with 30–60 mg C-NPs/kg diet were statistically (P < 0.05) higher than fish in the control group with no significant differences among them (P > 0.05). Moreover, lymphocytes and monocytes significantly (P > 0.05) increased; meanwhile neutrophils significantly (P > 0.05) decreased as C-NPs levels in diets increased. In a similar trend, antioxidant (malondialdehyde, superoxide dismutase, catalase, and glutathione peroxidase) and humoral immunity (lysozyme and total immunoglobulin) biomarkers were significantly higher in C-NPs-fed fish. Liver histology showed improvements in the cell architecture of fish fed with C-NPs containing diets up to 45 mg/kg diet. Compared with the control diet, feeding Nile tilapia with C-NPs diets resulted in a higher villi length/width and absorption area. According to the regression curves, the current study recommends using the dietary C-NP with optimum values of 45–55 mg/kg diet to improve the performance, digestive enzymes, antioxidant activities, and immunity response of Nile tilapia.
A Quantitative Study of Locality in GPU Caches for Memory-Divergent Workloads
Authors: Lal Sohan , Varma Bogaraju Sharatchandra , Juurlink Ben 
Published: April 2022

AbstractGPUs are capable of delivering peak performance in TFLOPs, however, peak performance is often difficult to achieve due to several performance bottlenecks. Memory divergence is one such performance bottleneck that makes it harder to exploit locality, cause cache thrashing, and high miss rate, therefore, impeding GPU performance. As data locality is crucial for performance, there have been several efforts to exploit data locality in GPUs. However, there is a lack of quantitative analysis of data locality, which could pave the way for optimizations. In this paper, we quantitatively study the data locality and its limits in GPUs at different granularities. We show that, in contrast to previous studies, there is a significantly higher inter-warp locality at the L1 data cache for memory-divergent workloads. We further show that about 50% of the cache capacity and other scarce resources such as NoC bandwidth are wasted due to data over-fetch caused by memory divergence. While the low spatial utilization of cache lines justifies the sectored-cache design to only fetch those sectors of a cache line that are needed during a request, our limit study reveals the lost spatial locality for which additional memory requests are needed to fetch the other sectors of the same cache line. The lost spatial locality presents opportunities for further optimizing the cache design.
Exact and meta-heuristic approaches for the production leveling problem
Authors: Vass Johannes , Lackner Marie-Louise , Mrkvicka Christoph , Musliu Nysret , Winter Felix 
Published: April 2022

AbstractIn this paper, we introduce a new problem in the field of production planning, called the production leveling problem. The task is to assign orders to production periods such that the load in each period and for each product type is balanced, capacity limits are not exceeded, and the orders’ priorities are taken into account. Production leveling is an important intermediate step between long-term planning and the final scheduling of orders within a production period, as it is responsible for selecting good subsets of orders to be scheduled within each period. We provide a formal model of the problem and study its computational complexity. As an exact method for solving moderately sized instances, we introduce a mixed integer programming (MIP) formulation. For solving large problem instances, metaheuristic local search is investigated. A greedy heuristic and two neighborhood structures for local search are proposed in order to apply them using simulated annealing. Furthermore, three possible extensions that arise from the application in practice are described and implemented, both within the MIP model and within simulated annealing. We make publicly available a set of realistic problem instances from the industry as well as from random instance generators. The experimental evaluation on our test sets shows that the proposed MIP model is well suited for solving instances with up to 250 orders. Simulated annealing produces solutions with less than $$3\%$$

3
%

average optimality gap on small instances, and scales well up to thousands of orders and dozens of periods and product types. The metaheuristic method presented herein is already being successfully used in the industry.
Effect of silicon on morpho-physiological attributes, yield and cadmium accumulation in two maize genotypes with contrasting root system size and health risk assessment
Authors: An Tingting , Gao Yamin , Kuang Qiqiang , Wu Yujie , Zaman Qamar uz , Zhang Yi , Xu Bingcheng , Chen Yinglong 
Published: April 2022

Abstract
Background and aims
Cadmium (Cd) contamination is a serious threat to plants and humans. Silicon (Si) was reported to have some alleviative effects on Cd stress in plants. However, whether Si alleviates Cd toxicity in maize genotypes with contrasting root system size are unknown.

Methods
Effects of Si application (200 mg kg−1 soil) on shoot and root growth, Cd uptake and transportation under Cd stress (20 mg kg−1 soil) were assessed at the silking and maturity stages of maize genotypes Zhongke11 (deep-rooted) and Shengrui999 (shallow-rooted) in a pot experiment.

Results
Application of Si significantly increased root dry weight, plant height and root length. Root volume and average root diameter were significantly positively correlated with root Cd concentration, bioaccumulation and translocation factor, respectively, of two maize genotypes at the silking stage. Addition of Si significantly increased Cd concentration, content, bioconcentration and translocation factor in roots of Zhongke11, but reduced the values of these parameters in Shengrui9999 at both growth stages. Grain Cd concentration in the combined Cd and Si treatment was decreased by 14.4% (Zhongke11) and 21.4% (Shengrui999) than that in Cd treatment. Grain yield was significantly negatively correlated with root Cd accumulation. Moreover, addition of Si significantly reduced Cd daily intake and health risk index in maize.

Conclusions
This study demonstrated that addition of Si reduced health risk by eliminating Cd accumulation in maize shoot and grain, and alleviated Cd stress with more profound effects in the shallow-rooted genotype Shengrui999.
The influence of the subcortex and brain stem on overeating: How advances in functional neuroimaging can be applied to expand neurobiological models to beyond the cortex
Authors: Kung Po-Han , Soriano-Mas Carles , Steward Trevor 
Published: April 2022

AbstractFunctional neuroimaging has become a widely used tool in obesity and eating disorder research to explore the alterations in neurobiology that underlie overeating and binge eating behaviors. Current and traditional neurobiological models underscore the importance of impairments in brain systems supporting reward, cognitive control, attention, and emotion regulation as primary drivers for overeating. Due to the technical limitations of standard field strength functional magnetic resonance imaging (fMRI) scanners, human neuroimaging research to date has focused largely on cortical and basal ganglia effects on appetitive behaviors. The present review draws on animal and human research to highlight how neural signaling encoding energy regulation, reward-learning, and habit formation converge on hypothalamic, brainstem, thalamic, and striatal regions to contribute to overeating in humans. We also consider the role of regions such as the mediodorsal thalamus, ventral striatum, lateral hypothalamus and locus coeruleus in supporting habit formation, inhibitory control of food craving, and attentional biases. Through these discussions, we present proposals on how the neurobiology underlying these processes could be examined using functional neuroimaging and highlight how ultra-high field 7-Tesla (7 T) fMRI may be leveraged to elucidate the potential functional alterations in subcortical networks. Focus is given to how interactions of these regions with peripheral endocannabinoids and neuropeptides, such as orexin, could be explored. Technical and methodological aspects regarding the use of ultra-high field 7 T fMRI to study eating behaviors are also reviewed.