bluuebunny/crossref_metadata_2025_split huggingface dataset:
State expansion of Supplemental Nutrition Assistance Program eligibility and rates of firearm-involved deaths in the United States
Authors: Sokol Rebeccah Lyn , Austin Anna E 
Published: February 2024

IntroductionPoverty is a consistent correlate of firearm-involved mortality, yet little work has considered the effects of social and economic policies on these deaths. This study examined associations of state elimination of the asset test and increases in the income limit for Supplemental Nutrition Assistance Program (SNAP) eligibility with rates of firearm-involved suicide and homicide deaths in the United States.MethodsThis ecological repeated cross-sectional study used 2015–2019 data from the SNAP Policy Database and death certificate data from the National Vital Statistics System. The exposures were (1) state elimination of the asset test for SNAP eligibility and (2) state elimination of the asset test and increases in the income limit for SNAP eligibility, compared with (3) state adoption of neither policy. The outcomes were firearm-involved suicide deaths and firearm-involved homicide deaths. The research team conducted mixed-effects regressions to estimate associations.ResultsState elimination of the asset test for SNAP eligibility (incidence rate ratio (IRR), 0.67; 95% CI, 0.48 to 0.91) and state adoption of both eliminating the asset test and increasing the income limit for SNAP eligibility (IRR, 0.68; 95% CI, 0.49 to 0.92) were associated with decreased rates of firearm-involved suicide deaths compared with state adoption of neither policy. There were no associations with state firearm-involved homicide rates.ConclusionsSNAP is an important social safety net programme that addresses food insecurity, and the present results suggest it may also contribute to reducing firearm-involved suicide.
Evaluation of branch sampling, ocular assessments, and aerial surveys for estimating spruce budworm defoliation
Authors: Donovan Shawn , MacLean David A. 
Published: February 2024

We compared three methods for estimating current-year spruce budworm ( Choristoneura fumiferana (Clem.)) defoliation from 2014 to 2021 using a network of 99 permanent sample plots in central Gaspé Peninsula, Québec. Percent current-year defoliation was measured by assessing shoots from mid-crown branches, ocular ratings of all individual trees using binoculars, and provincial government aerial surveys. Ocular survey defoliation differed from branch sample defoliation in 5–6 out of 7 years, consistently underestimating defoliation, across the full range of defoliation severity observed. Nested mixed-effect models for fir–spruce combined, balsam fir, white spruce, and black spruce ocular survey defoliation bias resulted in marginal R2 of 0.40, 0.47, 0.82, and 0.86, respectively. Current defoliation severity and its interaction with previous year defoliation and weather conditions significantly affected ocular survey bias. Correspondence of aerial survey estimates and mean plot defoliation occurred in only 43% of all plot-years and ranged from 14%–58% in individual years. Differences between aerial survey defoliation and plot values mainly resulted from assigning an adjacent class (e.g., light <30% assigned as moderate 31%–70% defoliation) or misplaced defoliation polygon boundaries, suggesting that assignment of aerial survey defoliation to plots or specific ground areas needs ground truth sampling.
Triple Primary Cancers: An Analysis of Genetic and Environmental Factors
Authors: Borja Nicholas A. , Silva-Smith Rachel , Calfa Carmen , Sussman Daniel A. , Tekin Mustafa 
Published: February 2024

Abstract

The occurrence of multiple primary cancers (MPC) is thought to reflect increased cancer susceptibility in patients due to a combination of genetic and environmental factors. Here we conducted a retrospective review of 2,894 consecutive patients evaluated at a single institution and identified 31 (1.14%) individuals with a history of three or more primary cancers, then analyzed the genetic and environmental influences associated with their propensity for developing malignancies. We found that 35.5% of patients had a hereditary cancer syndrome (HCS), with high penetrance HCS in 72.7% of cases, suggesting that monogenic causes underly a significant proportion of triple primary cancer risk. Analysis of cancer frequencies found that the diagnosis of breast cancer was associated with a significantly lower likelihood of HCS, while the diagnosis of colorectal, prostate, and pancreas cancer was associated with a significantly higher likelihood of HCS. Comparison of HCS-positive and HCS-negative patients revealed similar demographic characteristics, mean age at first diagnosis, and family history of cancer. Moreover, no significant differences in lifestyle behaviors, occupational exposures, chronic health conditions, or treatment with chemotherapy and radiation were observed between HCS-positive and -negative groups, though outliers in tobacco smoking, as well as systemic treatment after both first and second primary cancers were observed. These findings indicate a robust contribution of HCS to cancer susceptibility among patients with triple primary cancers while environmental influences were less evident. This emphasizes the need for larger MPC cohorts incorporating additional genetic and environmental factors to more comprehensively characterize drivers of cancer risk.

Prevention Relevance:
In patients with three or more primary cancers, genetic predisposition explained a significant proportion of cases; however, treatment history, lifestyle habits, and other exposures appeared to play a less significant role. This highlights the value of early genetic screening and the need to develop more sensitive markers of cancer susceptibility.
See related Spotlight, p. 193
Data from Pim Kinase Inhibitors Increase Gilteritinib Cytotoxicity in FLT3-ITD Acute Myeloid Leukemia Through GSK-3β Activation and c-Myc and Mcl-1 Proteasomal Degradation
Authors: Lee Jonelle K. , Chatterjee Aditi , Scarpa Mario , Bailey Christopher M. , Niyongere Sandrine , Singh Prerna , Mustafa Ali Moaath K. , Kapoor Shivani , Wang Yin , Silvestri Giovannino , Baer Maria R. 
Published: February 2024

<div>Abstract<p>Acute myeloid leukemia (AML) with <i>fms-</i>like tyrosine kinase 3 internal tandem duplication (FLT3-ITD) has poor outcomes. FLT3-ITD drives constitutive and aberrant FLT3 signaling, activating STAT5 and upregulating the downstream oncogenic serine/threonine kinase Pim-1. FLT3 inhibitors are in clinical use, but with limited and transient efficacy. We previously showed that concurrent treatment with Pim and FLT3 inhibitors increases apoptosis induction in FLT3-ITD–expressing cells through posttranslational downregulation of Mcl-1. Here we further elucidate the mechanism of action of this dual targeting strategy. Cytotoxicity, apoptosis and protein expression and turnover were measured in FLT3-ITD–expressing cell lines and AML patient blasts treated with the FLT3 inhibitor gilteritinib and/or the Pim inhibitors AZD1208 or TP-3654. Pim inhibitor and gilteritinib cotreatment increased apoptosis induction, produced synergistic cytotoxicity, downregulated c-Myc protein expression, earlier than Mcl-1, increased turnover of both proteins, which was rescued by proteasome inhibition, and increased efficacy and prolonged survival in an <i>in vivo</i> model. Gilteritinib and Pim inhibitor cotreatment of Ba/F3-ITD cells infected with T58A c-Myc or S159A Mcl-1 plasmids, preventing phosphorylation at these sites, did not downregulate these proteins, increase their turnover or increase apoptosis induction. Moreover, concurrent treatment with gilteritinib and Pim inhibitors dephosphorylated (activated) the serine/threonine kinase glycogen synthase kinase-3β (GSK-3β), and GSK-3β inhibition prevented c-Myc and Mcl-1 downregulation and decreased apoptosis induction. The data are consistent with c-Myc T58 and Mcl-1 S159 phosphorylation by activated GSK-3β as the mechanism of action of gilteritinib and Pim inhibitor combination treatment, further supporting GSK-3β activation as a therapeutic strategy in FLT3-ITD AML.</p>Significance:<p>FLT3-ITD is present in 25% of in AML, with continued poor outcomes. Combining Pim kinase inhibitors with the FDA-approved FLT3 inhibitor gilteritinib increases cytotoxicity <i>in vitro</i> and <i>in vivo</i> through activation of GSK-3β, which phosphorylates and posttranslationally downregulates c-Myc and Mcl-1. The data support efficacy of GSK-3β activation in FLT3-ITD AML, and also support development of a clinical trial combining the Pim inhibitor TP-3654 with gilteritinib.</p></div>
Cumulative Incidence, Risk Factors, and Overall Survival of Disease Recurrence after Curative Resection of Stage II–III Colorectal Cancer: A Population-based Study
Authors: Boute Tara C. , Swartjes Hidde , Greuter Marjolein J.E. , Elferink Marloes A.G. , van Eekelen Rik , Vink Geraldine R. , de Wilt Johannes H.W. , Coupé Veerle M.H. 
Published: February 2024

Abstract

Real-world data are necessitated to counsel patients about the risk for recurrent disease after curative treatment of colorectal cancer. This study provided a population-based overview of the epidemiology of recurrent disease in patients with surgically resected stage II/III colorectal cancer.
Patients diagnosed with stage II/III primary colorectal cancer between July and December 2015 were selected from the Netherlands Cancer Registry (N = 3,762). Cumulative incidence of recurrent disease was estimated, and multivariable competing risk regression was used to identify risk factors for recurrent disease in patients with primary colon and rectal cancer. Moreover, overall survival (OS) after diagnosis of recurrent colorectal cancer was estimated.
Median clinical follow-up was 58 months (Q1–Q3: 22–62). Five-year cumulative incidence of recurrent disease was 21.6% [95% confidence interval (CI): 20.0–23.2] and 30.0% (95% CI: 28.3–33.5) for patients with primary colon and rectal cancer, respectively. Stage III disease and incomplete resection margin in patients with primary colon cancer and extramural vascular invasion in patients with primary rectal cancer were strongly (HR ≥ 2) associated with recurrent disease. Median OS of patients with distant, locoregional, or the synchronous combination of distant and locoregional recurrent disease was 29, 27, and 13 months, respectively (P &lt; 0.001). Patients with distant recurrences limited to liver or lung showed a median OS of 46 and 48 months, respectively. The incidence of recurrent disease was higher in patients with rectal cancer than in patients with colon cancer, predominantly due to higher rates of distant recurrences. OS after recurrent disease was impaired, but subgroups of patients diagnosed with recurrent disease limited to one site showed statistically significantly longer OS.

Significance:
Population-based data on recurrent colorectal cancer are rare, but crucial for counseling patients and their physicians. This large nationwide, population-based study provides an up-to-date overview of the epidemiology of recurrent disease in patients with stage II and III primary colon and rectal cancer treated with surgical resection.
Cancer-associated Fibroblast–specific Expression of the Matricellular Protein CCN1 Coordinates Neovascularization and Stroma Deposition in Melanoma Metastasis
Authors: Hutchenreuther James , Nguyen John , Quesnel Katherine , Vincent Krista M. , Petitjean Louis , Bourgeois Sophia , Boyd Mark , Bou-Gharios George , Postovit Lynne-Marie , Leask Andrew 
Published: February 2024

Abstract

Melanoma is the leading cause of skin cancer–related death. As prognosis of patients with melanoma remains problematic, identification of new therapeutic targets remains essential. Matricellular proteins are nonstructural extracellular matrix proteins. They are secreted into the tumor microenvironment to coordinate behavior among different cell types, yet their contribution to melanoma is underinvestigated. Examples of matricellular proteins include those comprising the CCN family. The CCN family member, CCN1, is highly proangiogenic. Herein, we show that, in human patients with melanoma, although found in several tumor cell types, CCN1 is highly expressed by a subset of cancer-associated fibroblasts (CAF) in patients with melanoma and this expression correlates positively with expression of proangiogenic genes and progressive disease/resistance to anti-PD1 checkpoint inhibitors. Consistent with these observations, in a syngeneic C57BL6 mouse model of melanoma, loss of CCN1 expression from Col1A2-Cre-, herein identified as “universal,” fibroblasts, impaired metastasis of subcutaneously injected B16F10 tumor cells to lung, concomitant with disrupted neovascularization and collagen organization. Disruption of the extracellular matrix in the loss of CCN1 was validated using a novel artificial intelligence–based image analysis platform that revealed significantly decreased phenotypic fibrosis and composite morphometric collagen scores. As drug resistance is linked to matrix deposition and neoangiogenesis, these data suggest that CCN1, due to its multifaceted role, may represent a novel therapeutic target for drug-resistant melanoma. Our data further emphasize the essential role that cancer-associated, (universal) Col1A2-Cre-fibroblasts and extracellular matrix remodeling play in coordinating behavior among different cell types within the tumor microenvironment.

Significance:
In human patients, the expression of proangiogenic matricellular protein CCN1 in CAFs correlates positively with expression of stroma and angiogenic markers and progressive disease/resistance to checkpoint inhibitor therapy. In an animal model, loss of CCN1 from CAFs impaired metastasis of melanoma cells, neovascularization, and collagen deposition, emphasizing that CAFs coordinate cellular behavior in a tumor microenvironment and that CCN1 may be a novel target.
Enhanced proportional integral controller for DSTATCOM with particle swarm optimization algorithm in power system
Authors: Datar Parag Vijay , Kulkarni Deepak Balkrishna 
Published: February 2024

Power system expansion planning is supported by using distributed generation (DG) instead of installing new main power system generators. The portability and autonomous operation of the DG make it capable of integrating into the distribution system. Power electronics devices for home loads, mainly electric vehicles, mobile phones, and laptops, introduce harmonics and related power quality issues to the distribution system. This load creates power quality issues like an increase in total harmonic distortion (THD) and a reduction in power factor. This paper uses the DG to supply important power electronics devices for the mitigation of power quality problems in distributed systems with non-linear loads, such as electric vehicles, called the “distributed static compensator (DSTATCOM)”. Wind and photovoltaic (PV) generators supply power to a common DC source. To improve power quality D-STATCOM powered by PV and wind energy systems at the DC link is incorporated. The direct axis/quadrature axis method (DQ method) controls the real and reactive components of the power. Proportional integral (PI) and particle swarm optimization (PSO) based PI controller parameter estimation are developed, and results are compared for power quality performance. In terms of improving power quality, the PSO-based parameter estimate of the PI controller performs better than the traditional PI controller.<br /><div class="extension_reset_css AnnotateNet_widget AnnotateReviewNotesButton" style="display: none; z-index: 2147483644;" data-id="ExtensionWidget"><div class="extension_reset_css AnnotateNet_widget annotateclickable" style="z-index: 8; display: none;" title="Resize" data-id="Widget"> </div></div>
Systematic cross-sectional age-associations in global fMRI signal topography
Authors: Nomi Jason S. , Bzdok Danilo , Li Jingwei , Bolt Taylor , Chang Catie , Kornfeld Salome , Goodman Zachary T. , Yeo B.T. Thomas , Spreng R. Nathan , Uddin Lucina Q. 
Published: February 2024

Abstract
The global signal (GS) in resting-state functional MRI (fMRI), known to contain artifacts and non-neuronal physiological signals, also contains important neural information related to individual state and trait characteristics. Here, we show distinct linear and curvilinear relationships between GS topography and age in a cross-sectional sample of individuals (6-85 years old) representing a significant portion of the lifespan. Subcortical brain regions such as the thalamus and putamen show linear associations with the GS across age. The thalamus has stronger contributions to the GS in older-age individuals compared with younger-aged individuals, while the putamen has stronger contributions in younger individuals compared with older individuals. The subcortical nucleus basalis of Meynert shows a u-shaped pattern similar to cortical regions within the lateral frontoparietal network and dorsal attention network, where contributions of the GS are stronger at early and old age, and weaker in middle age. This differentiation between subcortical and cortical brain activity across age supports a dual-layer model of GS composition, where subcortical aspects of the GS are differentiated from cortical aspects of the GS. We find that these subcortical-cortical contributions to the GS depend strongly on age across the lifespan of human development. Our findings demonstrate how neurobiological information within the GS differs across development and highlight the need to carefully consider whether or not to remove this signal when investigating age-related functional differences in the brain.
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks
Authors: Metzner Claus , Yamakou Marius E. , Voelkl Dennis , Schilling Achim , Krauss Patrick 
Published: February 2024

Abstract
Free-running recurrent neural networks (RNNs), especially probabilistic models, generate an ongoing information flux that can be quantified with the mutual information I[x→(t),x→(t+1)] between subsequent system states x→. Although previous studies have shown that I depends on the statistics of the network’s connection weights, it is unclear how to maximize I systematically and how to quantify the flux in large systems where computing the mutual information becomes intractable. Here, we address these questions using Boltzmann machines as model systems. We find that in networks with moderately strong connections, the mutual information I is approximately a monotonic transformation of the root-mean-square averaged Pearson correlations between neuron pairs, a quantity that can be efficiently computed even in large systems. Furthermore, evolutionary maximization of I[x→(t),x→(t+1)] reveals a general design principle for the weight matrices enabling the systematic construction of systems with a high spontaneous information flux. Finally, we simultaneously maximize information flux and the mean period length of cyclic attractors in the state-space of these dynamical networks. Our results are potentially useful for the construction of RNNs that serve as short-time memories or pattern generators.
Anatomy of the top 1% most highly cited publications: An empirical comparison of two approaches
Authors: Perianes-Rodriguez Antonio , Gomez-Nuñez Antonio J. , Olmeda-Gomez Carlos 
Published: February 2024

Abstract
Scientific excellence is an ongoing object of quantitative analysis of science and technology literature. The most commonly adopted of the various criteria for such quantification is to define highly cited papers as the ones lying in the first percentile (top 1%) of citation counts. Wagner and colleagues have recently proposed a new method in which citation counts are determined as a whole, irrespective of discipline. This study analyzes the practical implications of the new approach compared to the traditional procedure in which papers are ranked bearing in mind the scientific field involved, with particular attention to the consequences for rankings by country and discipline. The results show that the new methodology favors countries with a predominance of polytechnical scientific production, technological development, and innovation and lowers the rank of countries where the social sciences, humanities, and basic research account for the lion’s share of output. An analysis of worldwide production confirms the growth of scientific output in technical and technological disciplines.
Lost in the Middle: How Language Models Use Long Contexts
Authors: Liu Nelson F. , Lin Kevin , Hewitt John , Paranjape Ashwin , Bevilacqua Michele , Petroni Fabio , Liang Percy 
Published: February 2024

Abstract
While recent language models have the ability to take long contexts as input, relatively little is known about how well they use longer context. We analyze the performance of language models on two tasks that require identifying relevant information in their input contexts: multi-document question answering and key-value retrieval. We find that performance can degrade significantly when changing the position of relevant information, indicating that current language models do not robustly make use of information in long input contexts. In particular, we observe that performance is often highest when relevant information occurs at the beginning or end of the input context, and significantly degrades when models must access relevant information in the middle of long contexts, even for explicitly long-context models. Our analysis provides a better understanding of how language models use their input context and provides new evaluation protocols for future long-context language models.
Environmental Justice and Lessons Learned from COVID-19 Outcomes—Uncovering Hidden Patterns with Geometric Deep Learning and New NASA Satellite Data
Authors: Zhen Zhiwei , Lee Huikyo , Segovia-Dominguez Ignacio , Huang Meichen , Chen Yuzhou , Garay Michael , Crichton Daniel , Gel Yulia R. 
Published: February 2024

Abstract
Virtually all aspects of our societal functioning—from food security to energy supply to healthcare—depend on the dynamics of environmental factors. Nevertheless, the social dimensions of weather and climate are noticeably less explored by the artificial intelligence community. By harnessing the strength of geometric deep learning (GDL), we aim to investigate the pressing societal question the potential disproportional impacts of air quality on COVID-19 clinical severity. To quantify air pollution levels, here we use aerosol optical depth (AOD) records that measure the reduction of the sunlight due to atmospheric haze, dust, and smoke. We also introduce unique and not yet broadly available NASA satellite records (NASAdat) on AOD, temperature, and relative humidity and discuss the utility of these new data for biosurveillance and climate justice applications, with a specific focus on COVID-19 in the states of Texas and Pennsylvania. The results indicate, in general, that the poorer air quality tends to be associated with higher rates for clinical severity and, in the case of Texas, that this phenomenon particularly stands out in Texan counties characterized by higher socioeconomic vulnerability. This, in turn, raises a concern of environmental injustice in these socioeconomically disadvantaged communities. Furthermore, given that one of NASA’s recent long-term commitments is to address such inequitable burden of environmental harm by expanding the use of Earth science data such as NASAdat, this project is one of the first steps toward developing a new platform integrating NASA’s satellite observations with deep learning (DL) tools for social good.

Significance Statement
By leveraging the strengths of modern deep learning models, particularly, graph neural networks to describe complex spatiotemporal dependencies and by introducing new NASA satellite records, this study aims to investigate the problem of potential environmental injustice associated with COVID-19 clinical severity and caused by disproportional impacts of poor air quality on disadvantaged socioeconomic populations.