bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of deep-learning models for real-time anaerobic threshold and peak VO2 prediction during cardiopulmonary exercise testing
Authors: Watanabe Tatsuya , Tohyama Takeshi , Ikeda Masataka , Fujino Takeo , Hashimoto Toru , Matsushima Shouji , Kishimoto Junji , Todaka Koji , Kinugawa Shintaro , Tsutsui Hiroyuki , Ide Tomomi 
Published: December 2023

Abstract

Aims
Exercise intolerance is a clinical feature of patients with heart failure (HF). Cardiopulmonary exercise testing (CPET) is the first-line examination for assessing exercise capacity in patients with HF. However, the need for extensive experience in assessing anaerobic threshold (AT) and the potential risk associated with the excessive exercise load when measuring peak oxygen uptake (peak VO2) limit the utility of CPET. This study aimed to use deep-learning approaches to identify AT in real time during testing (defined as real-time AT) and to predict peak VO2 at real-time AT.

Methods and results
This study included the time-series data of CPET recorded at the Department of Cardiovascular Medicine, Kyushu University Hospital. Two deep neural network models were developed to: (i) estimate the AT probability using breath-by-breath data and (ii) predict peak VO2 using the data at the real-time AT. The eligible CPET contained 1472 records of 1053 participants aged 18–90 years and 20% were used for model evaluation. The developed model identified real-time AT with 0.82 for correlation coefficient (Corr) and 1.20 mL/kg/min for mean absolute error (MAE), and the corresponding AT time with 0.86 for Corr and 0.66 min for MAE. The peak VO2 prediction model achieved 0.87 for Corr and 2.25 mL/kg/min for MAE.

Conclusion
Deep-learning models for real-time CPET analysis can accurately identify AT and predict peak VO2. The developed models can be a competent assistant system to assess a patient’s condition in real time, expanding CPET utility.
Co-exposure to multiple air pollutants, genetic susceptibility, and the risk of myocardial infarction onset: a cohort analysis of the UK Biobank participants
Authors: Jiang Zhou , Zhang Shuo , Gao Tongyu , Chen Keying , Liu Yuxin , Liu Ying , Wang Ting , Zeng Ping 
Published: December 2023

Abstract

Aims
The relationship between the long-term joint exposure to ambient air pollution and incidence of myocardial infarction (MI) and modification by genetic susceptibility remain inconclusive.

Methods and results
We analysed 329 189 UK Biobank participants without MI at baseline. Exposure concentrations to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were obtained. Air pollution score assessing the joint exposure was calculated, and its association with MI was evaluated via Cox model under the P value aggregation framework. Genetic susceptibility to MI was evaluated by incorporating polygenic risk score (PRS) into models. Risk prediction models were also established. During a median follow-up of 13.4 years, 9993 participants developed MI. Per interquartile range increase of PM2.5, PM10, NO2, and NOx resulted in 74% [95% confidence intervals (CIs) 69%–79%], 67% (63%–72%), 46% (42%–49%), and 38% (35%–41%) higher risk of MI. Compared with the lowest quartile (Q1) of air pollution score, the multivariable adjusted hazard ratio (HR) (95%CIs) of Q4 (the highest cumulative air pollution) was 3.50 (3.29–3.72) for MI. Participants with the highest PRS and air pollution score possessed the highest risk of incident MI (HR = 4.88, 95%CIs 4.35–5.47). Integrating PRS, air pollution exposure, and traditional factors substantially improved risk prediction of MI.

Conclusion
Long-term joint exposure to air pollutants including PM2.5, PM10, NO2, and NOx is substantially associated with increased risk of MI. Genetic susceptibility to MI strengthens such adverse joint association. Air pollutions together with genetic and traditional factors enhance the accuracy of MI risk prediction.
A native phosphoglycolate salvage pathway of the synthetic autotrophic yeast Komagataella phaffii
Authors: Baumschabl Michael , Mitic Bernd M , Troyer Christina , Hann Stephan , Ata Özge , Mattanovich Diethard 
Published: December 2023

Abstract
Synthetic autotrophs can serve as chassis strains for bioproduction from CO2 as a feedstock to take measures against the climate crisis. Integration of the Calvin–Benson–Bassham (CBB) cycle into the methylotrophic yeast Komagataella phaffii (Pichia pastoris) enabled it to use CO2 as the sole carbon source. The key enzyme in this cycle is ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) catalyzing the carboxylation step. However, this enzyme is error prone to perform an oxygenation reaction leading to the production of toxic 2-phosphoglycolate. Native autotrophs have evolved different recycling pathways for 2-phosphoglycolate. However, for synthetic autotrophs, no information is available for the existence of such pathways. Deletion of CYB2 in the autotrophic K. phaffii strain led to the accumulation of glycolate, an intermediate in phosphoglycolate salvage pathways, suggesting that such a pathway is enabled by native K. phaffii enzymes. 13C tracer analysis with labeled glycolate indicated that the yeast pathway recycling phosphoglycolate is similar to the plant salvage pathway. This orthogonal yeast pathway may serve as a sensor for RuBisCO oxygenation, and as an engineering target to boost autotrophic growth rates in K. phaffii.
Proportion of Nonindustrial Private Forest Lands That Potentially Can Be Leased to Bioenergy Enterprises to Grow Short Rotation Woody Crops
Authors: Hussain Anwar , Munn Ian A , Grala Robert K 
Published: December 2023

AbstractDetermining how much nonindustrial private forest (NIPF) land could potentially be allocated to growing short rotation woody crops (SRWCs) is critical for estimating the future supply of woody biomass for biofuels and overall bioenergy production. This study estimated the proportion of the land NIPF landowners would be willing to allocate to SRWC cultivation. In view of the bounded nature of the dependent binary variable [0,1] and model performance, a fractional logit regression model was used to estimate model parameters. The estimated proportion of land allocated to SRWCs was positively influenced by the rental rate per acre, owning land for investment or fee-access hunting purposes, and the landowner’s age. In contrast, size of the ownership, owning land for the production of agricultural products, and residing on the land negatively influenced the proportion of land allocated to SRWCs. Lease contract duration, location of the largest tract owned, owning land for personal recreation or ecosystem services, and landowner familiarity with the concept of alternative fuels production did not influence the proportion of land allocated to SRWCs. These results will contribute to a better understanding of SRWC biomass supply from NIPF land and provide important benchmark information for conducting feasibility analyses of biofuel and biopower manufacturing in Mississippi and other states with abundant woody feedstocks.Study Implications: To achieve targeted levels of bioenergy production and carbon dioxide (CO2) emission reductions and diversify NIPF landowner income, participation of NIPF landowners in woody biomass feedstock production will be critical, because they own a majority of forestland in the region. Moreover, they have diverse reasons for owning land which has extensive implications not only in terms of incentive types or monetary compensation levels they might require for cultivating SRWCs but also policies related to the development of the bioenergy sector in Mississippi, the location of individual bioenergy processing facilities, and feedstock types that will be developed. Thus, forest managers and biomass procurement foresters might need to decide whether to focus their efforts on maximizing the land area allocated to growing SRWCs or considering a mix of SRWCs at lower lease rates per acre and material obtained from thinnings, which might be more amenable to landowners who value environmental amenities.
Leaping through Tree Space: Continuous Phylogenetic Inference for Rooted and Unrooted Trees
Authors: Penn Matthew J , Scheidwasser Neil , Penn Joseph , Donnelly Christl A , Duchêne David A , Bhatt Samir 
Published: December 2023

Abstract
Phylogenetics is now fundamental in life sciences, providing insights into the earliest branches of life and the origins and spread of epidemics. However, finding suitable phylogenies from the vast space of possible trees remains challenging. To address this problem, for the first time, we perform both tree exploration and inference in a continuous space where the computation of gradients is possible. This continuous relaxation allows for major leaps across tree space in both rooted and unrooted trees, and is less susceptible to convergence to local minima. Our approach outperforms the current best methods for inference on unrooted trees and, in simulation, accurately infers the tree and root in ultrametric cases. The approach is effective in cases of empirical data with negligible amounts of data, which we demonstrate on the phylogeny of jawed vertebrates. Indeed, only a few genes with an ultrametric signal were generally sufficient for resolving the major lineages of vertebrates. Optimization is possible via automatic differentiation and our method presents an effective way forward for exploring the most difficult, data-deficient phylogenetic questions.
Patchwork: Alignment-Based Retrieval and Concatenation of Phylogenetic Markers from Genomic Data
Authors: Thalén Felix , Köhne Clara G , Bleidorn Christoph 
Published: December 2023

Abstract
Low-coverage whole-genome sequencing (also known as “genome skimming”) is becoming an increasingly affordable approach to large-scale phylogenetic analyses. While already routinely used to recover organellar genomes, genome skimming is rather rarely utilized for recovering single-copy nuclear markers. One reason might be that only few tools exist to work with this data type within a phylogenomic context, especially to deal with fragmented genome assemblies. We here present a new software tool called Patchwork for mining phylogenetic markers from highly fragmented short-read assemblies as well as directly from sequence reads. Patchwork is an alignment-based tool that utilizes the sequence aligner DIAMOND and is written in the programming language Julia. Homologous regions are obtained via a sequence similarity search, followed by a “hit stitching” phase, in which adjacent or overlapping regions are merged into a single unit. The novel sliding window algorithm trims away any noncoding regions from the resulting sequence. We demonstrate the utility of Patchwork by recovering near-universal single-copy orthologs within a benchmarking study, and we additionally assess the performance of Patchwork in comparison with other programs. We find that Patchwork allows for accurate retrieval of (putatively) single-copy genes from genome skimming data sets at different sequencing depths with high computational speed, outperforming existing software targeting similar tasks. Patchwork is released under the GNU General Public License version 3. Installation instructions, additional documentation, and the source code itself are all available via GitHub at https://github.com/fethalen/Patchwork.
Opportunistic Bacteria of Grapevine Crown Galls Are Equipped with the Genomic Repertoire for Opine Utilization
Authors: Faist Hanna , Ankenbrand Markus J , Sickel Wiebke , Hentschel Ute , Keller Alexander , Deeken Rosalia 
Published: December 2023

Abstract
Young grapevines (Vitis vinifera) suffer and eventually can die from the crown gall disease caused by the plant pathogen Allorhizobium vitis (Rhizobiaceae). Virulent members of A. vitis harbor a tumor-inducing plasmid and induce formation of crown galls due to the oncogenes encoded on the transfer DNA. The expression of oncogenes in transformed host cells induces unregulated cell proliferation and metabolic and physiological changes. The crown gall produces opines uncommon to plants, which provide an important nutrient source for A. vitis harboring opine catabolism enzymes. Crown galls host a distinct bacterial community, and the mechanisms establishing a crown gall–specific bacterial community are currently unknown. Thus, we were interested in whether genes homologous to those of the tumor-inducing plasmid coexist in the genomes of the microbial species coexisting in crown galls. We isolated 8 bacterial strains from grapevine crown galls, sequenced their genomes, and tested their virulence and opine utilization ability in bioassays. In addition, the 8 genome sequences were compared with 34 published bacterial genomes, including closely related plant-associated bacteria not from crown galls. Homologous genes for virulence and opine anabolism were only present in the virulent Rhizobiaceae. In contrast, homologs of the opine catabolism genes were present in all strains including the nonvirulent members of the Rhizobiaceae and non-Rhizobiaceae. Gene neighborhood and sequence identity of the opine degradation cluster of virulent and nonvirulent strains together with the results of the opine utilization assay support the important role of opine utilization for cocolonization in crown galls, thereby shaping the crown gall community.
Using encrypted genotypes and phenotypes for collaborative genomic analyses to maintain data confidentiality
Authors: Zhao Tianjing , Wang Fangyi , Mott Richard , Dekkers Jack , Cheng Hao 
Published: December 2023

Abstract
To adhere to and capitalize on the benefits of the FAIR (findable, accessible, interoperable, and reusable) principles in agricultural genome-to-phenome studies, it is crucial to address privacy and intellectual property issues that prevent sharing and reuse of data in research and industry. Direct sharing of genotype and phenotype data is often prohibited due to intellectual property and privacy concerns. Thus, there is a pressing need for encryption methods that obscure confidential aspects of the data, without affecting the outcomes of certain statistical analyses. A homomorphic encryption method for genotypes and phenotypes (HEGP) has been proposed for single-marker regression in genome-wide association studies (GWAS) using linear mixed models with Gaussian errors. This methodology permits frequentist likelihood-based parameter estimation and inference. In this paper, we extend HEGP to broader applications in genome-to-phenome analyses. We show that HEGP is suited to commonly used linear mixed models for genetic analyses of quantitative traits including genomic best linear unbiased prediction (GBLUP) and ridge-regression best linear unbiased prediction (RR-BLUP), as well as Bayesian variable selection methods (e.g. those in Bayesian Alphabet), for genetic parameter estimation, genomic prediction, and GWAS. By advancing the capabilities of HEGP, we offer researchers and industry professionals a secure and efficient approach for collaborative genomic analyses while preserving data confidentiality.
Returning personalized, genetic health test results to individuals of African descent or ancestry in precision medicine research
Authors: Hendricks-Sturrup Rachele M , Emmott Nora , Nafie Maryam , Edgar Lauren , Johnson-Glover Tracey , Christensen Kurt D , Argetsinger Stephanie , Lu Christine Y 
Published: December 2023

Abstract
Today, many epidemiological studies and biobanks are offering to disclose individual genetic results to their participants, including the National Institutes of Health's All of Us Research Program. Returning hereditary disease risks and pharmacogenetic test results to study participants from racial/ethnic groups that are historically underrepresented in biomedical research poses specific challenges to those participants and the health system writ large. For example, individuals of African descent are underrepresented in research about drug–gene interactions and have a relatively higher proportion of variants of unknown significance, affecting their ability to take clinical action following return of results. In this brief report, we summarize studies published to date concerning the perspectives and/or attitudes of African Americans engaged in genetic research programs to anticipate factors in disclosure protocols that would minimize risks and maximize benefits. A thematic analysis of studies identified (n = 6) lends to themes centered on motivations to engage or disengage in the return of results and integrating research and care. Actionable strategies determined in reaction to these themes center on ensuring adequate system and health education support for participants and personalizing the process for participants engaging in return of results. Overall, we offer these themes and actionable strategies as early guidance to research programs, and provide recommendations to policy makers focused on fair and equitable return of genetic research results to underrepresented research participants.
Populus cathayana genome and population resequencing provide insights into its evolution and adaptation
Authors: Xiang Xiaodong , Zhou Xinglu , Zi Hailing , Wei Hantian , Cao Demei , Zhang Yahong , Zhang Lei , Hu Jianjun 
Published: December 2023

Abstract
Populus cathayana Rehder, an indigenous poplar species of ecological and economic importance, is widely distributed in a high-elevation range from southwest to northeast China. Further development of this species as a sustainable poplar resource has been hindered by a lack of genome information the at the population level. Here, we produced a chromosome-level genome assembly of P. cathayana, covering 406.55 Mb (scaffold N50 = 20.86 Mb) and consisting of 19 chromosomes, with 35 977 protein-coding genes. Subsequently, we made a genomic variation atlas of 438 wild individuals covering 36 representative geographic areas of P. cathayana, which were divided into four geographic groups. It was inferred that the Northwest China regions served as the genetic diversity centers and a population bottleneck happened during the history of P. cathayana. By genotype–environment association analysis, 947 environment-association loci were significantly associated with temperature, solar radiation, precipitation, and altitude variables. We identified local adaptation genes involved in DNA repair and UV radiation response, among which UVR8, HY5, and CUL4 had key roles in high-altitude adaptation of P. cathayana. Predictions of adaptive potential under future climate conditions showed that P. cathayana populations in areas with drastic climate change were anticipated to have greater maladaptation risk. These results provide comprehensive insights for understanding wild poplar evolution and optimizing adaptive potential in molecular breeding.
Quantifying income inequality in years of life lost to COVID-19: a prediction model approach using Dutch administrative data
Authors: Issa Jawa , Wouterse Bram , Milkovska Elena , van Baal Pieter 
Published: December 2023

Abstract

Background
Low socioeconomic status and underlying health increase the risk of fatal outcomes from COVID-19, resulting in more years of life lost (YLL) among the poor. However, using standard life expectancy overestimates YLL to COVID-19. We aimed to quantify YLL associated with COVID-19 deaths by sex and income quartile, while accounting for the impact of individual-level pre-existing health on remaining life expectancy for all Dutch adults aged 50+.

Methods
Extensive administrative data were used to model probability of dying within the year for the entire 50+ population in 2019, considering age, sex, disposable income and health care use (n = 6 885 958). The model is used to predict mortality probabilities for those who died of COVID-19 (had they not died) in 2020. Combining these probabilities in life tables, we estimated YLL by sex and income quartile. The estimates are compared with YLL based on standard life expectancy and income-stratified life expectancy.

Results
Using standard life expectancy results in 167 315 YLL (8.4 YLL per death) which is comparable to estimates using income-stratified life tables (167 916 YLL with 8.2 YLL per death). Considering pre-existing health and income, YLL decreased to 100 743, with 40% of years lost in the poorest income quartile (5.0 YLL per death). Despite individuals in the poorest quartile dying at younger ages, there were minimal differences in average YLL per COVID-19 death compared with the richest quartile.

Conclusions
Accounting for prior health significantly affects estimates of YLL due to COVID-19. However, inequality in YLL at the population level is primarily driven by higher COVID-19 deaths among the poor. To reduce income inequality in the health burden of future pandemics, policies should focus on limiting structural differences in underlying health and exposure of lower income groups.
Strategies to overcome low MHC-I expression in paediatric and adult tumours
Authors: Guillaume J , Perzolli A , Boes M 
Published: December 2023

Summary
Immunotherapy has made significant advancements in cancer treatments, improving patients’ survival rates and quality of life. Several challenges still need to be addressed, which include the considerable fraction of incomplete curative responses in cancer patients, the development of therapy resistance by tumours, and the occurrence of adverse effects, such as inflammatory and autoimmune complications. Paediatric tumours usually exhibit lower responsiveness to immunotherapies compared to adult tumours. Although the underlying reasons are not yet fully understood, one known mechanism by which tumours avoid immune recognition is through reduced cell surface expression of major histocompatibility complex class I (MHC-I) complexes. Accordingly, the reduced presentation of neoantigens by MHC-I hinders the recognition and targeting of tumour cells by CD8+ T cells, impeding T-cell-mediated cytotoxic anti-tumour responses. MHC-I downregulation indeed often correlates with a poorer prognosis and diminished response to immunotherapy. Understanding the mechanisms underlying MHC-I downregulation in different types of paediatric and adult tumours is crucial for developing strategies to restore MHC-I expression and enhance anti-tumour immune responses. We here discuss progress in MHC-I-based immunotherapies against cancers.