bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction Models for Post‐Stroke Hospital Readmission: A Systematic Review
Authors: Mao Yijun , Liu Qiang , Fan Hui , Li Erqing , He Wenjing , Ouyang Xueqian , Wang Xiaojuan , Qiu Li , Dong Huanni 
Published: October 2024

ABSTRACTObjectiveThis study aims to evaluate the predictive performance and methodological quality of post‐stroke readmission prediction models, identify key predictors associated with readmission, and provide guidance for selecting appropriate risk assessment tools.MethodsA comprehensive literature search was conducted from inception to February 1, 2024. Two independent researchers screened the literature and extracted relevant data using the CHARMS checklist.ResultsEleven studies and 16 prediction models were included, with sample sizes ranging from 108 to 803,124 cases and outcome event incidences between 5.2% and 50.0%. The four most frequently included predictors in the models were length of stay, hypertension, age, and functional disability. Twelve models reported an area under the curve (AUC) ranging from 0.520 to 0.940, and five models provided calibration metrics. Only one model included both internal and external validation, while six models had internal validation. Eleven studies were found to have a high risk of bias (ROB), predominantly in the area of data analysis.ConclusionThis systematic review included 16 readmission prediction models for stroke, which generally exhibited good predictive performance and can effectively identify high‐risk patients likely to be readmitted. However, the generalizability of these models remains uncertain due to methodological limitations. Rather than developing new readmission prediction models for stroke, the focus should shift toward external validation and the iterative adaptation of existing models. These models should be tailored to local settings, extended with new predictors if necessary, and presented in an interactive graphical user interface.Trial RegistrationPROSPERO registration number CRD42023466801
Gene markers generating polygenic resistance in melon–Fusarium wilt–FOM1.2 interaction pathosystem
Authors: Sadeghpour N. , Asadi‐Gharneh H. A. , Nasr‐Esfahani M. , Rahimiardkapan B. , Nasr‐Esfahani A. , Nasr‐Esfahani A. , Monazah M. 
Published: October 2024

Abstract
Developing melon genotypes with resistance to Fusarium oxysporum f. sp. Melonis‐(FOM) race1.2 is a major goal in any breeding program. In this study, we identified the role of 11 gene markers that contribute to polygenic resistance during the FOM1.2–melon interaction.
qRT‐PCR analysis elucidated upregulation of candidate marker genes AMT, DXPR, Fom‐2, GLUC, GalS, GRF3, MLO, PRK, RuBlsCo, TLP and WRKY in resistant ‘Shante‐F1’ and ‘Khatouni’, and susceptible ‘Shante‐T' and ‘Shahabadi’ at 7, 14 and 21 days post‐inoculation (dpi). We also studied changes in defence‐related enzyme activity: chitinase (CHI), β‐1,3‐glucanase (GLU) and peroxidase (POX) in melon roots.
AMT, GLUC and DXPR transcripts were upregulatied in leaf and root tissues of the resistant ‘Shante‐F1’ and ‘Shahabadi’. Transcript levels for GalS and GRF3 increased 6.77‐ and 6.83‐fold in roots of ‘Shante‐F1’ at 7 dpi, whereas in PRK, TLP and WRKY theye increased by 7.84‐, 5.15‐ and 12.26‐fold at 14 dpi, respectively. However, transcript levels increased by 5.18‐fold for Fom‐2 and 8.46‐fold for MLO at 21 dpi. Also, RBC transcript level peaked at 14 dpi with 4.9‐fold increase in leaves of resistant genotypes, whereas AMT increased 2.94‐fold at 21 dpi, and GLUC and DXPR increased 7.11‐ and 2.91‐fold at 14 dpi in ‘Shante‐F', respectively. Defence‐related‐enzyme activity was also upregulated three‐fold in resistant varieties.
The dynamic shifts in the melon transcriptome induced by FOM1.2 emphasize that resistance mechanisms are predominantly regulated through signalling pathways involving CHI, GLU, and POX defence response. Surprisingly, the AMT gene, basically resistant to downy mildew, Pseudoperonospora cubensis; GLUC, MLO and PRK resistant to powdery mildew (Sphaerotheca fusca); TLP and WRKY resistant to Phytophthora blight (Phytophthora capsici); and GRF3 and RBC resistant to root knot nematodes (Meloidogyne spp.) were upregulated in resistant genotypes, indicating a dual role of these genes in resistance to more than one disease at a time.
Estimation Stand Volume, Basal Area and Quadratic Mean Diameter Using Landsat 8 OLI and Sentinel‐2 Satellite Image With Different Machine Learning Techniques
Authors: Aksoy Hasan 
Published: October 2024

ABSTRACTThe data required for sustainable forest planning is provided by traditional forest inventories, which are labor, time, and cost‐intensive. Providing this data quickly, reliably, and accurately is crucial for planners and researchers. The objective of this study was to predict stand basal area (BA), stand volume (V), and quadratic mean diameter (dq) by leveraging vegetation indices (VIs) and reflectance (R) derived from Landsat 8 OLI and Sentinel 2 satellite images, along with topographic (T) data obtained from ALOS‐PALSAR satellite imagery. Forest inventory data for a total of 250 sample plots were used for modeling in the study. Stand parameters were estimated using support vector machines (SVM), multiple linear regression (MLR), decision tree (DT), and random forest (RF) algorithms. In modeling V, BA, and dq, both individual and combinations of R, VIs, and T values obtained from satellite imagery were used as independent variables. Using the generated datasets, each of the stand parameters was modeled separately with MLR, SVM, RF, and DT algorithms, and the success of the models was compared to determine the modeling technique and dataset with the highest success for the relevant parameter. The results showed that for each stand parameter, the highest model success was achieved in the combined dataset, which was created by combining all datasets. However, in terms of modeling techniques, the highest success for each stand parameter was achieved with different modeling techniques. The highest success for V is obtained in the model using the SVM method (R2 = 0.78; RMSE = 0.28 m3/ha), the RF method yielded the highest model performance for BA (R2 = 0.70; RMSE = 2.53 m2/ha), and finally, the highest success for dq was obtained in the DT method (R2 = 0.74; RMSE = 0.02 cm). In general, the datasets obtained from Sentinel 2 images showed higher model success than the datasets obtained from Landsat 8 OLI images.
Derived deformation theory of crepant curves
Authors: Brown Gavin , Wemyss Michael 
Published: October 2024

AbstractThis paper determines the full, derived deformation theory of certain smooth rational curves in Calabi–Yau 3‐folds, by determining all higher ‐products in its controlling DG‐algebra. This geometric setup includes very general cases where does not contract, cases where the curve neighbourhood is not rational, all known simple smooth 3‐fold flops, and all known divisorial contractions to curves. As a corollary, it is shown that the non‐commutative deformation theory of is described via a superpotential algebra derived from what we call free necklace polynomials, which are elements in the free algebra obtained via a closed formula from combinatorial gluing data. The description of these polynomials, together with the above results, establishes a suitably interpreted string theory prediction due to Ferrari (Adv. Theor. Math. Phys. 7 (2003) 619–665), Aspinwall–Katz (Comm. Math. Phys.. 264 (2006) 227–253) and Curto–Morrison (J. Algebraic Geom. 22 (2013) 599–627). Perhaps most significantly, the main results give both the language and evidence to finally formulate new contractibility conjectures for rational curves in CY 3‐folds, which lift Artin's (Amer. J. Math. 84 (1962) 485–496) celebrated results from surfaces.
Investigating the Effect of Ammonia Addition on the Performance of a Heavy-Duty Natural Gas Spark Ignition Engine Operated at Stoichiometric Conditions
Authors: Yang Ruomiao , Yin Zibin , Yan Yuchao , Ou Juan , Xie Tianfang , Liu Zhentao , Liu Jinlong 
Published: October 2024

Abstract
Due to the pressing issue of global warming, there has been a significant focus on zero- and low-carbon fuels globally. Among hydrocarbon fuels, methane is widely used in spark ignition engines due to its abundance and relatively low-carbon footprint. However, to further reduce carbon emissions, interest is growing in the use of ammonia, a zero-carbon fuel, as a partial replacement for methane. Consequently, it is crucial to investigate the impact of ammonia addition on the performance of natural gas spark ignition engines. A key challenge in studying ammonia–methane engines is that the introduction of ammonia alters the formation mechanisms of nitrogen-based pollutants, resulting in the coupling of fuel-borne and airborne nitrogen pollutants. As a result, research on the nitrogen-based emissions of ammonia–methane engines has been limited. This study addresses this issue by differentiating between atmospheric nitrogen and fuel nitrogen elements, effectively decoupling fuel-borne and airborne nitrogen pollutants. This approach provides valuable insights into the effects of ammonia addition on the nitrogen-based pollutant characteristics of natural gas engines. The results indicate that ammonia addition introduces N2O, a species absent in pure methane engines. The N2O primarily originates from cold wall regions and the partial oxidation of ammonia released from engine crevices during the late oxidation process. Although NO remains the dominant nitrogen-based pollutant and the amount of N2O is small, the significant greenhouse gas potential of N2O warrants further attention. Furthermore, while ammonia addition increases the NO concentration in the burning zone, it slightly reduces the NO concentration at chemical equilibrium under stoichiometric conditions. As a result, engines operating with an ammonia energy substitution ratio of 0.4 exhibit lower nitrogen oxide (NOx) emissions compared to those fueled solely by methane. These findings underscore the need for further research into the combustion and emission characteristics of ammonia–methane spark ignition engines.
A Prediction Method of Oil Recovery for Hot Water Chemical Flooding in Heavy Oil Reservoirs: Semi-Analytical Stream Tube Model
Authors: Du Qingjun , Shen Jie , Shi Lina , Yu Jianmei , Hou Jian , Xue Yu , Wei Bei , Liu Yongge 
Published: October 2024

Abstract
Chemical agents (polymer and surfactant) assisted hot water flooding is an effective means of enhancing oil recovery in heterogeneous and heavy oil reservoirs. The rapid prediction of oil recovery through hot water chemical flooding is very important. The stream tube model is a fast analytical method for predicting water flooding recovery, but it is not suitable for hot water chemical flooding. In this paper, a permeability distribution model for multi-stream tubes is established based on permeability variation coefficient using normal distribution function for reservoir heterogeneity, using Gompertz growth function model to characterize the changes in stream tube temperature, polymer viscosity, and surfactant concentration with injection volume, using Brooks–Corey model to describe the influence of interfacial tension and temperature on the relative permeability curve. Finally, an analytical stream tube model for hot water chemical flooding of heavy oil reservoirs was established. The time-discrete method is used to solve the model, and then, the graphs of the relationship between oil recovery and water cut are obtained. Compared with numerical simulation methods, the prediction error of oil recovery is less than 2%, and the calculation time is reduced by 89%. This model has been successfully applied to X oilfield. Based on historical fitting, it is predicted that hot water chemical flooding can enhance oil recovery by 6.3% compared to water flooding. This paper provides a fast calculation method for predicting and evaluating the effectiveness of hot water chemical flooding in heavy oil reservoirs.
Physical Determinants of Sprint and Long Jump Performance in Male Youth Track-and-Field Athletes With Differing Maturity Statuses
Authors: Baker James , Read Paul , Graham-Smith Philip , Monaco Mauricio , Varamenti Evdokia , Cardinale Marco , Jones Thomas W. 
Published: October 2024

Purpose: This study examined the physical determinants of 60-m sprint and long jump (LJ) performance and differences between maturity groups in physical characteristics in young male track-and-field athletes. Methods: Competition results, countermovement jump, isometric leg press, 10-5 repeated jump test, and 50-m sprint were collected over 3 seasons for 54 male athletes (age 13 [1] y; stature 160.0 [8.9] cm; body mass, 48.0 [9.8] kg; percentage predicted adult height 92.2% [5.5%]) grouped by maturity status: approaching- (n = 16), circa- (n = 19), and post-peak height velocity (PHV) (n = 19). Results: There were significant between-group differences in 60 m, LJ, and all physical testing variables (P < .001, g = 0.88–5.44) when comparing the approaching- and circa-PHV groups with the post-PHV group. Significant differences were identified between the approaching- and circa-PHV groups in 40-m (P = .033, g = 0.89), 50-m (P = .024, g = 1.64), and 60-m (P < .001, g = 0.89) sprint times. Countermovement jump and 50-m sprint variables were consistently important for projection of 60 m and LJ performance across the valid multivariate models. Conclusions: Large differences in performance across maturity groups highlight the importance of understanding athletes’ maturity status to accurately interpret performance. Several physical performance variables were important for projecting competition 60 m and LJ performance.
Sentinel Surveillance reveals phylogenetic diversity and detection of linear plasmids harboring
vanA
and
optrA
among enterococci collected in the United States
Authors: Kent Alyssa G. , Spicer Lori M. , Campbell Davina , Breaker Erin , McAllister Gillian A. , Ewing Thomas O. , Longo Cynthia , Balbuena Rocio , Burroughs Mark , Burgin Alex , Padilla Jasmine , Johnson J. Kristie , Halpin Alison Laufer , McKay Susannah L. , Rasheed J. Kamile , Elkins Christopher A. , Karlsson Maria , Lutgring Joseph D. , Gargis Amy S. 
Published: October 2024

ABSTRACT

Enterococcus faecalis
and
Enterococcus faecium
are frequent causes of healthcare-associated infections. Antimicrobial-resistant enterococci pose a serious public health threat, particularly vancomycin-resistant enterococci (VRE), for which treatment options are limited. The Centers for Disease Control and Prevention’s Division of Healthcare Quality Promotion Sentinel Surveillance system conducted surveillance from 2018 to 2019 to evaluate antimicrobial susceptibility profiles and molecular epidemiology of 205
E. faecalis
and 180
E. faecium
clinical isolates collected from nine geographically diverse sites in the United States. Whole genome sequencing revealed diverse genetic lineages, with no single sequence type accounting for more than 15% of
E. faecalis
or
E. faecium
. Phylogenetic analysis distinguished
E. faecium
from 19
E. lactis
(previously known as
E. faecium
clade B). Resistance to vancomycin was 78.3% among
E. faecium
, 7.8% among
E. faecalis
, and did not occur among
E. lactis
isolates. Resistance to daptomycin and linezolid was rare:
E. faecium
(5.6%, 0.6%, respectively),
E. faecalis
(2%, 2%), and
E. lactis
(5.3%, 0%). All VRE harbored the
vanA
gene. Three of the seven isolates that were not susceptible to linezolid harbored
optrA
, one chromosomally located and two on linear plasmids that shared a conserved backbone with other multidrug-resistant conjugative linear plasmids. One of these isolates contained
optrA
and
vanA
co-localized on the linear plasmid. By screening all enterococci, 20% of
E. faecium
were predicted to harbor linear plasmids, whereas none were predicted among
E. faecalis
or
E. lactis
. Continued surveillance is needed to assess the future emergence and spread of antimicrobial resistance by linear plasmids and other mechanisms.

IMPORTANCE

This work confirms prior reports of
E. faecium
showing higher levels of resistance to more antibiotics than
E. faecalis
and identifies that diverse sequence types are contributing to enterococcal infections in the United States. All VRE harbored the
vanA
gene. We present the first report of the linezolid resistance gene
optrA
on linear plasmids in the United States, one of which co-carried a
vanA
cassette. Additional studies integrating epidemiological, antimicrobial susceptibility, and genomic methods to characterize mechanisms of resistance, including the role of linear plasmids, will be critical to understanding the changing landscape of enterococci in the United States.
The point mutation A1387G in the 16S rRNA gene confers aminoglycoside resistance in
Campylobacter jejuni
and
Campylobacter coli
Authors: Zarske Michael , Werckenthin Christiane , Golz Julia C. , Stingl Kerstin 
Published: October 2024

ABSTRACT

Thermotolerant
Campylobacter
spp. are the most frequent cause of foodborne bacterial diarrhea and high-priority antibiotic-resistant pathogens, according to the World Health Organization (WHO). Monitoring revealed current low prevalence of gentamicin resistance in European
Campylobacter
spp. isolates but substantial presence of gentamicin modifying genes circulating globally. Using a combined approach of natural transformation and whole-genome sequencing, we revealed a novel gentamicin resistance mechanism, namely the point mutation A1387G in the 16S rRNA gene, originally identified in a
C. coli
isolate from turkey caecal content. The transformation rate of the resistance using genomic DNA of the resistant donor to sensitive recipient
C. jejuni
and
C. coli
was ~2.5 log
10
lower compared to the control
rpsL
-A128G point mutation conferring streptomycin resistance. Antimicrobial susceptibility tests showed cross-resistance to apramycin, kanamycin, and tobramycin, with transformants exhibiting more than 4- to 8-fold increased MICs to apramycin and tobramycin and over 64-fold higher MICs to kanamycin compared to wild-type isolates. Although transformants showed 177–1,235 variations relative to the recipient, only the A1387G point mutation in the 16S rRNA was in common. This mutation was causal for resistance, as transformation of a 16S rRNA_A1387G PCR fragment into susceptible isolates also led to resistant transformants. Sanger sequencing of the 16S rRNA genes and Oxford nanopore whole-genome sequencing of transformants identified clones harboring either all three copies with A1387G or a mixed population of wild-type and mutated 16S rRNA gene alleles. Within 15 passages on non-selective medium, transformants with mixed populations of the 16S rRNA gene copies partially reverted to wild type, both geno- and phenotypically. In contrast, transformants harboring the A1387G point mutation in all three 16S rRNA gene copies kept full resistance within at least 45 passages. We speculate that partial acquisition and rapid loss of the point mutation limited its spread among
C
. spp. isolates. In-depth knowledge on resistance mechanisms contributes to optimal diagnosis and preventative measures.
Discovery and synthesis of leaderless bacteriocins from the Actinomycetota
Authors: Hourigan David , Miceli de Farias Felipe , O’Connor Paula M. , Hill Colin , Ross R. Paul 
Published: October 2024

ABSTRACT

Leaderless bacteriocins are a unique class of bacteriocins that possess antimicrobial activity after translation and have few cases of documented resistance. Aureocin A53 and lacticin Q are considered two of the most well-studied leaderless bacteriocins. Here, we used
in silico
genome mining to search for novel aureocin A53-like leaderless bacteriocins in GenBank and MGnify. We identified 757 core peptides across 430 genomes with 75 species found currently without characterized leaderless bacteriocin production. These include putative novel species containing bacteriocin gene clusters (BGCs) from the genera
Streptomyces
(sp. NBC_00237) and
Agrococcus
(sp. SL85). To date, all characterized leaderless bacteriocins have been found within the phylum Bacillota, but this study identified 97 core peptides within the phylum Actinomycetota. Members of this phylum are traditionally associated with the production of antibiotics, such is the case with the genus
Streptomyces
. Actinomycetota is an underexplored phylum in terms of bacteriocin production with no characterized leaderless bacteriocin production to date. The two novel leaderless bacteriocins arcanocin and arachnicin from Actinomycetota members
Arcanobacterium
sp. and
Arachnia
sp., respectively, were chemically synthesized and antimicrobial activity was verified. These peptides were encoded in human gut (PRJNA485056) and oral (PRJEB43277) microbiomes, respectively. This research highlights the biosynthetic potential of Actinomycetota in terms of leaderless bacteriocin production and describes the first antimicrobial peptides encoded in the genera
Arcanobacterium
and
Arachnia
.

IMPORTANCE
Bacteriocins are gathering attention as alternatives to current antibiotics given the increasing incidence of antimicrobial resistance. Leaderless bacteriocins are considered a commercially attractive subclass of bacteriocins due to the ability to synthesize active peptide and low levels of documented resistance. Therefore, in this work, we mined publicly available data to determine how widespread and diverse leaderless bacteriocins are within the domain of bacteria. Actinomycetota, known for its antibiotic producers but lacking described and characterized bacteriocins, proved to be a rich source of leaderless bacteriocins—97 in total. Two such peptides, arcanocin and arachnicin, were chemically synthesized and have antimicrobial activity. These bacteriocins may provide a novel source of novel antimicrobials that could aid in the development of future alternative antimicrobials and highlight that the Actinomycetota are an underexplored resource of bacteriocin peptides.