bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of two MALDI-TOF MS systems and extraction methods for identification of filamentous fungi recovered from clinical specimens
Authors: Ransom Eric M. , Wallace Meghan A. , Wiederhold Nathan P. , Cañete-Gibas Connie , Burnham Carey-Ann D. 
Published: January 2025

ABSTRACT

Rapid and accurate identification of cultured molds is important to determine clinical significance and therapeutic decision-making. Conventional mold identification uses phenotypic macroscopic and microscopic characterization; however, this can take days or weeks for colony maturity and definitive microscopic structure formation, be limited to genus-level identification, and be misidentified due to morphologic mimics or similarities between closely related species. Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI–TOF MS) revolutionized bacterial and yeast identification but remains uncommon for molds in part because of limited reference libraries. Here, a retrospective 5-year review at a large teaching hospital found that 88.6% of identified molds were in the Bruker Filamentous Fungi Library 3.0 and 91.5% in the VITEK Knowledge Base Library 3.2.0. A prospective evaluation was also performed on early growth from 205 consecutive, working clinical isolates. Each mold was processed using the VITEK chemical extraction method and modified NIH chemical plus bead-beating extraction method; both extractions were tested on both systems. When compared to conventional identification, more molds were identified using VITEK extractions over NIH extractions using the VITEK (65 and 59%) and Bruker (56 and 54%) systems, respectively, using the ≥1.5 log Bruker threshold. VITEK MS identified more molds, regardless of the extraction method. Isolates without consensus agreement (
n
= 116) underwent sequence-based identification, which demonstrated that conventional identification had the highest genus-level (84%) but lowest species-level (3%) identification rates compared to VITEK (59 and 52%, respectively) and Bruker (52 and 36%) using VITEK extractions. Taken together, our findings suggest both MALDI-TOF systems can supplement conventional mold identification to optimize identification rates with species-level distinction.

IMPORTANCE
Mold identification using matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) remains uncommon in clinical laboratories. Contributing concerns include limited genus/species spectra in the MALDI-TOF MS libraries, varying success rates in the literature regarding extraction methods and instrumentation, and the lack of practical performance evaluations using early mold colony growth, which would be used in a clinical mycology laboratory. This study used multiple approaches to improve our understanding of the clinical utility and performance of MALDI-TOF MS mold identification.
Pulmonary granuloma formation during latent
Cryptococcus neoformans
infection in C3HeB/FeJ mice involves progression through three immunological phases
Authors: Betancourt Jovany J. , Ding Minna , Yoder J. Marina , Mutyaba Issa , Atkins Hannah M. , De la Cruz Gabriela , Meya David B. , Nielsen Kirsten 
Published: January 2025

ABSTRACT

Cryptococcus neoformans
is a fungal pathogen that can cause lethal disease in immunocompromised patients. Immunocompetent host immune responses, such as formation of pulmonary granulomas, control the infection and prevent disseminated disease. Little is known about the immunological conditions establishing the latent infection granuloma in the lungs. To investigate this, we performed an analysis of pulmonary immune cell populations, cytokine changes, and granuloma formation during infection with a latent disease-causing clinical isolate in C3HeB/FeJ mice over 360 days. We found that latently infected mice progress through three phases of granuloma formation where different immune profiles dominate: an early phase characterized by eosinophilia, high IL-4/IL-13, and
C. neoformans
proliferation in the lungs; an intermediate phase characterized by multinucleated giant cell formation, high IL-1α/IFNγ, granuloma expansion, and increased blood antigen levels; and a late phase characterized by a significant expansion of T cells, granuloma condensation, and decreases in lung fungal burden and blood antigen levels. These findings highlight a complex series of immune changes that occur during the establishment of granulomas that control
C. neoformans
in the lungs and lay the foundation for studies to identify critical beneficial immune responses to
Cryptococcus
infections.

IMPORTANCE

Cryptococcus neoformans
is a fungal pathogen that disseminates from the lungs to the brain to cause fatal disease. Latent C.
neoformans
infection in the lungs is controlled by organized collections of immune cells called granulomas. The formation and structure of
Cryptococcus
granulomas are poorly understood due to inconsistent human pathology results and disagreement between necrotic granuloma-forming rat models and non-necrotic granuloma-forming mouse models. To overcome this, we investigated granuloma formation during latent
C. neoformans
infection in the C3HeB/FeJ mouse strain which forms necrotic lung granulomas in response to other pathogens. We found that latent
C. neoformans
granuloma formation progresses through phases that we described as early, intermediate, and late with different immune response profiles and granulomatous characteristics. Ultimately, we show that C3HeB/FeJ mice latently infected with
C. neoformans
form non-necrotic granulomas and could provide a novel mouse model to investigate host immune response profiles.
Complete genome sequence of a novel classical swine fever virus subgenotype 1.1 detected from a live Japanese encephalitis virus vaccine in South Korea
Authors: Jang Guehwan , Lee Changhee 
Published: January 2025

ABSTRACT

A novel classical swine fever virus (CSFV) strain GNU-240601 was identified from a commercial live Japanese encephalitis virus (JEV) vaccine. The whole-genome sequence of GNU-240601 shared the highest similarity with strains belonging to subgenotype 1.1. This is the first identification and complete genome sequence of CSFV from the JEV vaccine.
A sensitivity analysis of methodological variables associated with microbiome measurements
Authors: Forry Samuel P. , Servetas Stephanie L. , Dootz Jennifer N. , Hunter Monique E. , Kralj Jason G. , Filliben James J. , Jackson Scott A. 
Published: January 2025

ABSTRACT

The experimental methods employed during metagenomic sequencing analyses of microbiome samples significantly impact the resulting data and typically vary substantially between laboratories. In this study, a full factorial experimental design was used to compare the effects of a select set of methodological choices (sample, operator, lot, extraction kit, variable region, and reference database) on the analysis of biologically diverse stool samples. For each parameter investigated, a main effect was calculated that allowed direct comparison both between methodological choices (bias effects) and between samples (real biological differences). Overall, methodological bias was found to be similar in magnitude to real biological differences while also exhibiting significant variations between individual taxa, even between closely related genera. The quantified method biases were then used to computationally improve the comparability of data sets collected under substantially different protocols. This investigation demonstrates a framework for quantitatively assessing methodological choices that could be routinely performed by individual laboratories to better understand their metagenomic sequencing workflows and to improve the scope of the datasets they produce.

IMPORTANCE
Method-specific bias is a well-recognized challenge in metagenomic sequencing characterization of microbiome samples, but rigorous bias quantification is challenging. This report details a full factorial exploration of 48 experimental protocols by systematically varying microbiome sample, iterations of material production, laboratory personnel, DNA extraction kit, marker gene selection, and reference databases. Quantification of the biases associated with each parameter revealed similar magnitudes of variation arising from real biological differences and from varied analysis procedures. Furthermore, these measurement biases varied substantially with taxa, even between closely related genera. However, computational correction of method bias using a reference material was demonstrated that significantly harmonized metagenomic sequencing results collected using different analysis protocols.
Primordial black holes from effective field theory of stochastic single field inflation at NNNLO
Authors: Choudhury Sayantan , Karde Ahaskar , Padiyar Pankaj , Sami M. 
Published: January 2025

Abstract
We present a study of the Effective Field Theory (EFT) generalization of stochastic inflation in a model-independent single-field framework and its impact on primordial black hole (PBH) formation. We show how the Langevin equations for the “soft” modes in quasi de Sitter background is described by the Infra-Red (IR) contributions of scalar perturbations, and the subsequent Fokker–Planck equation driving the probability distribution for the stochastic duration

$$\mathcal {N}$$

N

, significantly modify in the present EFT picture. An explicit perturbative analysis of the distribution function by implementing the stochastic-

$$\delta N$$

δ
N

formalism is performed up to the next-to-next-to-next-to-leading order (NNNLO) for both the classical-drift and quantum-diffusion dominated regimes. In the drift-dominated limit, we perturbatively analyse the local non-Gaussianity parameters

$$(f_\textrm{NL}, g_\textrm{NL}, \tau _\textrm{NL})$$

(

f
NL

,

g
NL

,

τ
NL

)

with the EFT-induced modifications. In the diffusion-dominated limit, we numerically compute the probability distribution featuring exponential tails at each order of perturbative treatment.
Observing pulsars with f(R) gravity and using van der Waals equation of state in model
Authors: Mardan S. A. , Khalid A. , Manzoor Rubab , Riaz Muhammad Bilal 
Published: January 2025

Abstract
This research focuses on the evolution of the universe and observes pulsars using modified gravitational theory. We computed the Einstein field equations for an anisotropic spherical structure with f(R) gravity. Furthermore, our density–pressure relationship is defined using the well-known van der Waals equation of state (VdW EoS). Graphs are used to investigate the behavior of physical parameters, and energy conditions are used to demonstrate the physical continuity of dense stars. Plotting the adiabatic index shows the model’s stability. The resulting figures of physical parameters confirm the model’s practical and conceptual feasibility. Under the effect of f(R) gravity, our work demonstrates regularity, viability and stability, supporting the presence of heavy pulsars such as PSR

$$J0348+0432$$

J
0348
+
0432

, PSR

$$J0740+6620$$

J
0740
+
6620

and PSR

$$J0030+0451$$

J
0030
+
0451

.
AVERAGE PATH LENGTH AND AVERAGE FERMAT DISTANCE OF A CLASS OF POLYGON NETWORKS
Authors: WANG DAOHUA , ZENG CHENG , XUE YUMEI 
Published: January 2025

The average path length of a network serves to elucidate the network’s fluency and coherence by providing insights into how efficiently and effectively information or interactions can traverse the network and it is extensively studied in the context of network science. The Fermat distance among three nodes [Formula: see text], [Formula: see text], and [Formula: see text], denoted as [Formula: see text], was defined as the shortest total path length between a node [Formula: see text] and nodes [Formula: see text], [Formula: see text], and [Formula: see text]. The corresponding average Fermat distance also plays an important role in describing the connectedness of a network. In this paper, we study a class of polygon networks with pseudo-fractal structure and analyze the average path length. Moreover, we derive the average Fermat distance in two ways. Interestingly, we find the ratio of asymptotic average Fermat distance to asymptotic average path length is exactly 3/2 and these metrics grow linearly with the order of the polygon networks.
Navigating Tabular Data Synthesis Research
Understanding User Needs and Tool Capabilities
Authors: Davila R. Maria F. , Groen Sven , Panse Fabian , Wingerath Wolfram 
Published: January 2025

In an era of rapidly advancing data-driven applications, there is a growing demand for data in both research and practice. Synthetic data have emerged as an alternative when there are not enough real data available or when these data may not be shared (e.g., due to privacy regulations). Synthesizing tabular data presents unique and complex challenges, especially handling (i) missing values, (ii) dataset imbalance, (iii) diverse column types, and (iv) complex data distributions, as well as preserving (v) column correlations, (vi) temporal dependencies, and (vii) integrity constraints (e.g., functional dependencies) present in the original dataset. Although significant progress has been made recently in the development of generational models, there is no one-size-fitsall solution for tabular data today and choosing the right tool for a particular use case remains a difficult task.
In this paper, we survey the state of the art in Tabular Data Synthesis (TDS) and examine user needs by defining a set of functional and non-functional requirements. We also evaluate the reported performance of 37 TDS research tools on these requirements, develop a tool selection guide to help users find a suitable TDS tool for their use case, and identify open challenges in TDS research, especially with respect to data management.
Mechanisms of Adaptive Resistance to Targeted Therapy in RET-Aberrant Cancers
Authors: Ortiz-Cuaran Sandra , Leonce Camille 
Published: January 2025

Summary
The success of targeted therapies in oncogene-driven cancer is limited by adaptive or acquired treatment resistance, leading to disease progression. A recent study reports that YAP-dependent human epidermal growth factor receptor 3 (HER3) activation constitutes a therapeutic vulnerability of adaptive resistance to RET-targeted therapies in RET-altered cancers, highlighting a promising strategy to improve RET inhibitor tumor responses.
See related article by Katayama et al., p. XX
PKCδ germline variants and genetic deletion in mice augment antitumor immunity through regulation of myeloid cells
Authors: Cron Kyle R. , Sivan Ayelet , Aquino-Michaels Keston , Ziblat Andrea , Higgs Emily F. , Sweis Randy F. , Tonea Ruxandra , Lee Seoho , Gajewski Thomas F. 
Published: January 2025

Abstract
Based on the notion that hypomorphic germline genetic variants are linked to autoimmune diseases, we reasoned that novel targets for cancer immunotherapy might be identified through germline variants associated with greater T-cell infiltration into tumors. Here, we report that while investigating germline polymorphisms associated with a tumor immune gene signature, we identified PKCδ as a candidate. Genetic deletion of PKCδ in mice resulted in improved endogenous antitumor immunity and increased efficacy of anti-PD-L1. Single-cell RNA sequencing revealed myeloid cell expression of Prkcd, and PKCδ deletion caused a shift in macrophage gene expression from an M2-like to an M1-like phenotype. Conditional deletion of PKCδ in myeloid cells recapitulated improved tumor control that was augmented further with anti-PD-L1. Analysis of clinical samples confirmed an association between PRKCD variants and M1/M2 phenotype, as well as between a PKCδ KO-like gene signature and clinical benefit from anti-PD-1. Our results identify PKCδ as a candidate therapeutic target that modulates myeloid cell states.
Early Versus Delayed Antihypertensive Treatment After Acute Ischemic Stroke by Hypertension History
Authors: Xie Xuewei , Zhong Chongke , Liu Xin , Pan Yuesong , Wang Aili , Wei Yufei , Liu Dacheng , Xu Tan , Jiang Yong , Wang Mengxing , Jing Jing , Meng Xia , Obst Katherine , Chen Chung-Shiuan , Wang David , Wang Yilong , Zhang Yonghong , He Jiang , Wang Yongjun , Liu Liping 
Published: January 2025

BACKGROUND:
We performed a prespecified subgroup analysis of the CATIS-2 trial (China Antihypertensive Trial in Acute Ischemic Stroke II) to compare the effect of early versus delayed antihypertensive treatment on death and disability in patients with and without medical history of hypertension.

METHODS:
CATIS-2 is a multicenter randomized clinical trial conducted in 106 hospitals in China. The trial randomized 4810 patients with acute ischemic stroke within 24 to 48 hours of symptom onset and elevated systolic blood pressure between 140 and <220 mm Hg to receive antihypertensive treatment immediately after randomization or to discontinue antihypertensive medications for 7 days and then receive treatment on day 8. The primary outcome was a combination of death or functional dependency (modified Rankin Scale score ≥3) at 90 days.

RESULTS:

At the 90-day follow-up, the primary outcome of death or functional dependency was not different between early- and delayed-treatment groups according to the history of hypertension; the odds ratios (95% CIs) associated with the early-treatment group were 1.11 (0.91–1.36) and 1.38 (0.92–2.08) for participants with and without a history of hypertension. However, the ordinal logistic regression showed that early antihypertensive treatment was associated with the odds of a higher modified Rankin Scale score in patients without hypertension (odds ratio, 1.35 [95% CI, 1.01–1.82]), but not in those with hypertension (odds ratio, 0.95 [95% CI, 0.82–1.10];
P
=0.04 for interaction).

CONCLUSIONS:
Early antihypertensive treatment did not reduce the odds of dependency or death at 90 days by hypertension history among patients with ischemic stroke but worsened functional outcomes for patients without hypertension in the ordinal analysis.

REGISTRATION:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT03479554.
Improving Community College to University Transfer
Authors: Soliz Adela , Mesa Hidahis 
Published: January 2025

Abstract
Community college to university transfer (i.e., vertical transfer) is an important potential path to a bachelor's degree. However, community colleges may be particularly challenging for students to navigate. In this brief we argue that multiple transfer policies, combined with the complexity of community colleges, create a set of choices that are difficult for students to work through. Second, transfer-related policies may be weak or ineffective if they ignore policy mediators, such as the ways students access information to guide their decisions. We review the growing body of research on vertical transfer in order to make recommendations aimed at improving vertical transfer rates.
The Effects of At-Scale Career Pathway Investments on the Transition from High School to College
Authors: Bonilla Sade , Thim Alexander 
Published: January 2025

Abstract
In this study, we examine the impact of a large-scale effort in California aimed at establishing career pathways and estimate its causal effects on community college enrollment. By leveraging a discontinuous assignment rule for awarding grant funds, we obtain credibly causal estimates of a $500 million initiative to expand career and technical education (CTE) pathways between K-12 districts and community colleges. The competitive grant application process used a standardized rubric, and those receiving a score above a predetermined threshold were awarded funding (i.e., treatment group) while those just below received no funding (i.e., control group), allowing for a regression discontinuity design. We found no overall enrollment increases at partner community colleges for successful grantees. However, there were suggestive enrollment increases of 13.5 percent to 14.8 percent in CTE health sector, which was the primary career sector targeted for expansion. Other targeted programs, such as manufacturing and information communication technology, saw no increases in postsecondary enrollment. The health sector enrollment increases were concentrated among female students, aligning with earlier findings by Bonilla (2020) on reduced high school dropout rates for females. These findings suggest that K-12 postsecondary partnerships may be a viable avenue for aligning enrollment with high-growth sectors.
Delayed Bachelor's Degree Graduates Have Lower Graduate School Enrollment Rates
Authors: Bloem Michael D. 
Published: January 2025

Abstract
Using nationally representative data from the Baccalaureate and Beyond surveys, I establish a new descriptive finding: students who take longer than four years to complete their bachelor's degree have significantly lower graduate school enrollment rates compared to studentswhocomplete their bachelor's degree in four years, which is the standard for “on-time” graduation. Importantly, I show that students with a different time to degree report having similar expectations for earning a graduate degree in the future when asked during their final year of their bachelor's degree, suggesting differential graduate school goals do not explain the enrollment gaps. Additional analyses find that these enrollment patterns are driven entirely by differences in full-time enrollment in graduate programs within the first year after completing the bachelor's degree. Delayed graduates are not more or less likely to enroll in part-time graduate degree programs or to initially enroll between one and ten years after completing their bachelor's degree.
Family Background and College Major Choice: Evidence on Major Earnings Growth
Authors: Leighton Margaret , Speer Jamin D. 
Published: January 2025

Abstract
Expected earnings matter for college major choices, and majors differ in both their average earnings and the age profile of their earnings. We show that students' family background is strongly related to the earnings paths of the major they choose. Students with more educated parents, especially those who have graduate degrees, choose majors with lower early-career earnings but much stronger earnings growth. They are also less likely to choose safe majors with little early-career earnings or unemployment downside. These effects seem driven by students with more educated parents' propensity to eventually attend graduate school and increase later earnings, but not by the propensity to attend graduate school immediately after college, meaning these students are earning less in the years after college. Parental income has a weaker relationship with major choice and may operate partially through the type of institution the student attends.