bluuebunny/crossref_metadata_2025_split huggingface dataset:
Organ Donation by the Imminently Dead: Addressing the Organ Shortage and the Dead Donor Rule
Authors: Chen Sarah , Sade Robert M , Entwistle John W 
Published: May 2024

Abstract
The dead donor rule (DDR) has facilitated the saving of hundreds of thousands of lives. Recent advances in heart donation, however, have exposed how DDR has limited donation of all organs. We propose advancing the moment in the dying process at which death can be determined to increase substantially the supply of organs for transplantation. We justify this approach by identifying certain flaws in the Uniform Determination of Death Act and proposing a modification of that law that permits earlier procurement of healthier organs in greater numbers.
A positive correlation of serum SFRP1 levels with the risk of developing type 2 diabetes mellitus: a case-control study
Authors: Alhilfi Ahmed Salim Najm , Afrisham Reza , Sefidan Alireza Monadi , Fadaei Reza , Moradi Nariman , Saed Lotfollah , Einollahi Nahid 
Published: May 2024

Abstract

Objective
Secreted frizzled-related protein 1 (SFRP1) is an adipokine whose production is significantly altered in metabolic disorders. Considering the relationship between dysfunction of Wnt/β-catenin signaling and metabolic disorders as well as the inhibitory effects of SFRP1 on this signaling pathway, the present work aimed to investigate the correlation between serum SFRP1 levels and type 2 diabetes mellitus (T2DM) and its developing risk factors for the first time.

Methods
This case-control study measured serum levels of SFRP1, tumor necrosis factor (TNF)-α, interleukin (IL)-6, adiponectin, and fasting insulin using enzyme-linked immunosorbent assay kits in 80 T2DM patients and 80 healthy individuals. Biochemical parameters were determined using the AutoAnalyzer instrument.

Results
The T2DM group had higher levels of SFRP1 compared with the controls (146.8100 ± 43.61416 vs 81.9531 ± 32.78545 pg/mL; P &lt; .001). There was a positive correlation between SFRP1 and insulin (r = 0.327, P = .003), TNF-α (r = 0.420, P &lt; .001) as well as homeostatic model assessment for insulin resistance (r = 0.328, P = .003) in the T2DM group. In addition, 10-unit changes in SFRP1 levels showed the risk of T2DM in both the unadjusted (odds ratio [OR] [95% CI] = 1.564 [1.359-1.800]) and adjusted models accounting for age, gender, and body mass index (OR [95% CI] = 1.564 [1.361-1.799]; P &lt; .001). A cut-off value of SFRP1 (105.83 pg/mL) was identified to distinguish between the T2DM patients and the healthy subjects, with sensitivity of 75.0% and specificity of 80.0%.

Conclusion
According to our research, there was a significant and positive link between the amount of SFRP1 and the likelihood of developing T2DM as well as the related factors like insulin resistance index and TNF-α. These results indicated that SFRP1 might have a potential role in the development of T2DM.
Impact of culture medium on the interpretation of qRT-PCR data in HepG2 incubated with lactobacilli
Authors: Nováková Mária , Vyletelová Veronika , Hlubinová Barbora , Kiňová Sepová Hana , Pašková Ľudmila 
Published: May 2024

Abstract
Recently, an increasing number of studies have investigated the mechanism of action of lactobacilli in the treatment of non-alcoholic fatty liver disease. Using four computational tools (NormFinder, geNorm, Delta Ct, and BestKeeper), six potential reference genes (RGs) were analyzed in the human liver cell line HepG2 cultivated 24 h in the presence of two strains of heat-killed lactobacilli, Limosilactobacillus reuteri E and Lactiplantibacillus plantarum KG4, respectively, in different cultivation media [Dulbecco´s Modified Eagle´s Medium (DMEM) high glucose or Roswell Park Memorial Institute (RPMI)]. The analysis revealed that the suitability of RG was similar between the two lactobacilli but quite different between the two media. The commonly used RGs, 18S rRNA and glyceraldehyde-3-phosphate dehydrogenase were the most unstable in DMEM high glucose. Normalization of the mRNA expression of the target gene encoding sterol regulatory element-binding protein 1c (SREBP-1c) to different RGs resulted in different expression profiles. This demonstrates that validation of candidate RGs under specific experimental conditions is crucial for the correct interpretation of quantitative polymerase chain reaction data. In addition, the choice of media has a profound impact on the effect of lactobacilli on lipogenesis at the gene expression level, as shown by the transcription factor SREBP-1c.
Dynamic superiorities in Defeasible Logic
Authors: Olivieri Francesco 
Published: May 2024

Abstract
In many logical rule-based systems, it often happens that opposite statements can be concluded, hence superiorities (or priorities) among rules are needed to solve such conflicts. Since the specific circumstances describing the scenario at hand determine which rules may apply, we thus need a mechanism able to compute such superiorities dynamically, case-by-case. We formalise a non-monotonic logic able to dynamically compute superiorities over rules. Finally, we advance efficient algorithms to compute the (positive and negative) conclusions of such theories, and prove their computational properties.
AggreProt: a web server for predicting and engineering aggregation prone regions in proteins
Authors: Planas-Iglesias Joan , Borko Simeon , Swiatkowski Jan , Elias Matej , Havlasek Martin , Salamon Ondrej , Grakova Ekaterina , Kunka Antonín , Martinovic Tomas , Damborsky Jiri , Martinovic Jan , Bednar David 
Published: May 2024

Abstract
Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/.
Deep DNAshape webserver: prediction and real-time visualization of DNA shape considering extendedk-mers
Authors: Li Jinsen , Rohs Remo 
Published: May 2024

AbstractSequence-dependent DNA shape plays an important role in understanding protein–DNA binding mechanisms. High-throughput prediction of DNA shape features has become a valuable tool in the field of protein–DNA recognition, transcription factor–DNA binding specificity, and gene regulation. However, our widely used webserver, DNAshape, relies on statistically summarized pentamer query tables to query DNA shape features. These query tables do not consider flanking regions longer than two base pairs, and acquiring a query table for hexamers or higher-order k-mers is currently still unrealistic due to limitations in achieving sufficient statistical coverage in molecular simulations or structural biology experiments. A recent deep-learning method, Deep DNAshape, can predict DNA shape features at the core of a DNA fragment considering flanking regions of up to seven base pairs, trained on limited simulation data. However, Deep DNAshape is rather complicated to install, and it must run locally compared to the pentamer-based DNAshape webserver, creating a barrier for users. Here, we present the Deep DNAshape webserver, which has the benefits of both methods while being accurate, fast, and accessible to all users. Additional improvements of the webserver include the detection of user input in real time, the ability of interactive visualization tools and different modes of analyses. URL: https://deepdnashape.usc.edu
Survey Data and Subjective Beliefs in Business Cycle Models
Authors: Bhandari Anmol , Borovička Jaroslav , Ho Paul 
Published: May 2024

Abstract
This paper develops a theory of subjective beliefs that departs from rational expectations, and shows that biases in household beliefs have quantitatively large effects on macroeconomic aggregates. The departures are formalized using model-consistent notions of pessimism and optimism which are supported by extensive time-series and cross-sectional evidence from household surveys. The role subjective beliefs play in aggregate fluctuations is quantified in a business cycle model with goods and labour market frictions. Consistent with the survey evidence, an increase in pessimism generates upward biases in unemployment and inflation forecasts and lowers economic activity. The underlying belief distortions reduce aggregate demand and propagate through frictional goods and labour markets. As a by-product of the analysis, solution techniques that preserve the effects of time-varying belief distortions in the class of linear solutions are developed.
Matrotrophy and polyandry partially regulate postcopulatory mechanisms and sexual selection in a bimodal viviparous salamander
Authors: Alarcón-Ríos Lucía , Velo-Antón Guillermo 
Published: May 2024

Abstract
The evolution of matrotrophic viviparity creates new scenarios within which evolutionary processes can operate, including postcopulatory events, family conflicts, and selective processes, which are expected to intensify with polyandry. We evaluated the effect of matrotrophic viviparity and polyandry on the reproductive output and offspring fitness of a bimodal reproductive vertebrate, the fire salamander (Salamandra salamandra), which presents two forms of viviparity: larviparity (i.e. females deliver many aquatic larvae) and pueriparity (i.e. females deliver a few terrestrial juveniles). Polyandry is present in both strategies, but matrotrophy only occurs in pueriparity. Analyses of paternity and offspring life-history traits in 18 pueriparous and 13 larviparous mother–offspring arrays suggest the presence of sibling conflicts in pueriparous salamanders, especially with polyandry. However, these postcopulatory processes did not increase reproductive skew in the pueriparous strategy compared to the larviparous one or lead to fitness differences across sires within a clutch, suggesting other selective processes operating earlier in the reproductive sequence. Observed male–female pairs were found to be genetically more similar than other potential pairings, although no relationship between males’ genetic traits and reproductive success was detected. This work advances our understanding of how sibling conflicts and sexual selection affect the evolution of viviparous matrotrophy and mating strategies.
Postoperative Delirium Screening Characteristics in Pediatric Intestinal, Liver, and Renal Transplant Recipients: Single-Center Retrospective Cohort Study*
Authors: Patel Sagar , Pfeiffer Brent , Haddock De Jesus Rosa , Garcia Jennifer , Chandar Jayanthi , Alladin Amanda 
Published: May 2024

OBJECTIVES:To describe and compare the results of delirium screening in the immediate post-transplant PICU admission for pediatric intestinal, liver, and renal transplant recipients. We also examined associations with known and suspected risk factors for pediatric delirium (PD).DESIGN:Retrospective analysis of a single-center cohort, 2016–2022.SETTING:Twenty-four-bed PICU in a high-volume transplant center.PATIENTS:All intestinal, liver, and renal transplant recipients under 23 years old admitted between July 2016 and August 2022.MEASUREMENTS AND MAIN RESULTS:We identified 211 pediatric transplant recipients: intestinal (n= 36), liver (n= 78), and renal (n= 97). Results of the Cornell Assessment for PD during the immediate post-transplant PICU admission were reviewed and patients were categorized into screen positive, screen negative, and unscreened. Corresponding data on known and suspected risk factors for PD were also collected. Data on delirium subtypes were not collected. Screens were available for 156 of 211 patients (74%) who were included in the final analysis. The prevalence of a positive screen by transplant category was: intestine 80% (24/30), liver 75% (47/63), and renal 14% (9/63). A positive screen was associated with younger age, greater duration of mechanical ventilation, and greater PICU length of stay (LOS) in bivariate analysis. In multivariable analysis, age and PICU LOS remained strongly correlated with a positive screen (p< 0.05). Deep sedation and agitation as categorized by the State Behavioral Scale was associated with a positive screen, as was significant iatrogenic withdrawal symptoms (p< 0.05). Most patients screened positive by post-transplant days 2 and 3 (58/80 [72%] and 64/80 [80%], respectively).CONCLUSIONS:In our 2016 to 2022 experience, we found a high prevalence of positive PD screens in pediatric intestinal and liver transplant recipients in the immediate post-transplant PICU admission. A positive screen was associated with younger age and greater PICU LOS.
A Randomized Controlled Trial of the Implementation of BREASTChoice, a Multilevel Breast Reconstruction Decision Support Tool With Personalized Risk Prediction
Authors: Politi Mary C. , Myckatyn Terence M. , Cooksey Krista , Olsen Margaret A. , Smith Rachel M. , Foraker Randi , Parrish Katelyn , Phommasathit Crystal , Brock Guy , Janse Sarah , Guglielmino Janine , Peled Anne , Mills Paul B. , Jackson Sherrill , Lee Clara N. 
Published: May 2024

Objective:
To implement the BREASTChoice decision tool into the electronic health record and evaluate its effectiveness.

Background:

BREASTChoice, is a multilevel decision tool that (1) educates patients about breast reconstruction, (2) estimates personalized risk of complications, (3) clarifies patient preferences, and (4) informs clinicians about patients’ risk and preferences.

Methods:
A multisite randomized controlled trial enrolled adult women with stage 0 to III breast malignancy undergoing mastectomy. Participants were randomized to BREASTChoice or a control website. A survey assessed knowledge, preferences, decisional conflict, shared decision-making, preferred treatment, and usability. We conducted intent-to-treat (ITT), per-protocol (PP) analyses (those randomized to BREASTChoice who accessed the tool), and stratified analyses.

Results:
A total of 23/25 eligible clinicians enrolled. A total of 369/761 (48%) contacted patients enrolled and were randomized. Patients’ average age was 51 years; 15% were older than 65. BREASTChoice participants had higher knowledge than control participants (ITT: mean 70.6 vs 67.4, P=0.08; PP: mean 71.4 vs 67.4, P=0.03), especially when stratified by site (ITT: P=0.04, PP: P=0.01), age (ITT: P=0.04, PP: P=0.02), and race (ITT: P=0.04, PP: P=0.01). BREASTChoice did not improve decisional conflict, match between preferences and treatment, or shared decision-making. In PP analyses, fewer high-risk patients using BREASTChoice chose reconstruction. BREASTChoice had high usability.

Conclusions:

BREASTChoice is a novel decision tool incorporating risk prediction, patient education, and clinician engagement. Patients using BREASTChoice had higher knowledge; older adults and those from racially minoritized backgrounds especially benefitted. There was no impact on other decision outcomes. Future studies should overcome implementation barriers and specifically examine decision outcomes among high-risk patients.
The formal demography of kinship VI: Demographic stochasticity, variance, and covariance in the kinship network
Authors: Caswell Hal 
Published: May 2024

AbstractBackgroundThe matrix model for kinship networks includes many demographic processes but is deterministic, projecting expected values of age-stage distributions of kin. It provides no information on (co)variances. Because kin populations are small, demographic stochasticity is expected to create appreciable inter-individual variation.ObjectivesTo develop a stochastic kinship model to project (co)variances of kin age-stage distributions, and functions thereof, including demographic stochasticity.MethodsKin populations are described by multitype branching processes. Means and covariances are projected using matrices that are generalizations of the deterministic model. The analysis requires only an age-specific mortality and fertility schedule. Both linear and non-linear transformations of the kin age distribution are treated as outputs accompanying the state equations.ResultsThe stochastic model follows the same mathematical framework as the deterministic model, modified to treat initial conditions as mixture distributions. Variances in numbers of most kin are compatible with Poisson distributions. Variances for parents and ancestors are compatible with binomial distributions. Prediction intervals are provided, as are probabilities of having at least one or two kin of each type. Prevalences of conditions are treated either as fixed or random proportions. Dependency ratios and their variances are calculated for any desired group of kin types. An example compares Japan under 1947 rates (high mortality, high fertility) and 2019 rates (low mortality, low fertility).ContributionPrevious versions of the kinship model have acknowledged their limitation to expected values. That limitation is now removed; means and variances are easily and quickly calculated with minimal modification of code.
A generative foundation model for antibody sequence understanding
Authors: Barton Justin , Gaspariunas Aretas , Yadin David A. , Dias Jorge , Nice Francesca L. , Minns Danielle H. , Snudden Olivia , Povall Chelsea , Valle Tomas Sara , Dobson Harry , Farmery James H. R. , Leem Jinwoo , Galson Jacob D. 
Published: May 2024

AbstractHere we introduce FAbCon, a generative antibody-specific language model comprising 2.4 billion parameters. A commonly accepted wisdom in developing large language models is that increasing model scale will translate to higher performance on downstream tasks. Starting from a 144-million parameter setup, we show that progressively larger models achieve greater accuracy in predicting antigen binding and can also be used to design new antibodies with good predicted developability potential. FAbCon is available onhuggingface.co/alchemab.
The maternal vGluT2 and embryonic mGluR3 signaling relay system controls offspring wing dimorphism in pea aphid
Authors: Yuan Yiyang , Wang Yanyan , Ye Wanwan , Xie Liqiang , Yuan Erliang , Guo Huijuan , Wang Shifan , Dong Fang , Zhu-Salzman Keyan , Ge Feng , Sun Yucheng 
Published: May 2024

AbstractTransgenerational phenotypic plasticity (TPP) refers to the phenomenon that environmental conditions experienced by one generation can influence the phenotype of subsequent generations to adapt to the environment without modification of their DNA sequences. Aphid wing dimorphism is a textbook example of TPP by which a maternal aphid perceives the environmental cues to decide the wing morph of her offspring. However, the signaling mechanism from mother to daughter remains unclear. In this study, we showed that the population density and physical contact caused high proportion of winged offspring in the pea aphidAcyrthosiphon pisum. Itsvesicular glutamate transporter 2(ApvGluT2) andmetabotropic glutamate receptor 3(ApmGluR3) were identified by tissue-specific RNA-seq as differentially expressed genes in the head and embryo respectively between solitary and more densely housed maternal aphids. Elevated expression of brainApvGluT2and embryonicApmGluR3led to increases in the winged proportion. Knockdown of either gene inhibited phosphorylation of ApFoxO in embryos. Furthermore, EMSA showed that dephosphorylated ApFoxO directly bound to the promotor ofhedgehog(ApHh), a morphogen gene for wing development, to repress its transcription in stage 20 embryos, causing a lower winged proportion. Our results demonstrated that brainvGluT2and embryonicmGluR3coordinately relayed the maternal physical contact signals and control wing development in offspring, showcasing a novel regulatory mechanism underlying physical contact-dependent, transgenerational wing dimorphism in aphids.
Genesis: A modular protein language modelling approach to immunogenicity prediction
Authors: O’Brien Hugh , Salm Max , Morton Laura T , Szukszto Maciej , O’Farrell Felix , Boulton Charlotte , King Laurence , Bola Supreet Kaur , Becker Pablo , Craig Andrew , Nielsen Morten , Samuels Yardena , Swanton Charles , Mansour Marc R , Hadrup Sine Reker , Quezada Sergio A 
Published: May 2024

AbstractNeoantigen immunogenicity prediction is a highly challenging problem in the development of personalised medicines. Low reactivity rates in called neoantigens result in a difficult prediction scenario with limited training datasets. Here we describe Genesis, a modular protein language modelling approach to immunogenicity prediction for CD8+ reactive epitopes. Genesis comprises of a pMHC encoding module trained on three pMHC prediction tasks, an optional TCR encoding module and a set of context specific immunogenicity prediction head modules. Compared with state-of-the-art models for each task, Genesis’ encoding module performs comparably or better on pMHC binding affinity, eluted ligand prediction and stability tasks. Genesis outperforms all compared models on pMHC immunogenicity prediction (Area under the receiver operating characteristic curve=0.619, average precision: 0.514), with a 7% increase in average precision compared to the next best model. Genesis shows further improved performance on immunogenicity prediction with the integration of TCR context information. Genesis performance is further analysed for interpretability, which locates areas of weakness found across existing immunogenicity models and highlight possible biases in public datasets.