bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring susceptibility and therapeutic targets for kidney stones through proteome-wide Mendelian randomization
Authors: Jiang Qinhong , Su Xiaozhe , Liao Wenbiao , He Ziqi , Wang Yunhan , Jiang Rong , Dong Caitao , Yang Sixing 
Published: November 2024

Abstract
Given the high recurrence rate of kidney stones, surgical lithotripsy and stone removal are not the ultimate treatments for kidney stones. There’s an urgent need to explore the genetic mechanisms behind the susceptibility to kidney stones and to identify potential targets for prevention, to reduce the renal damage caused by recurrent stone formation. In this study, we screened 4548 circulating proteins using proteome-wide Mendelian Randomization (MR) to find proteins with a causal relationship to kidney stone risk. Additionally, proteome-wide association study (PWAS) and colocalization analysis were used to validate and prioritize candidate proteins. Moreover, downstream analyses including single-cell analysis, enrichment analysis, protein–protein interaction (PPI), and druggability analysis were conducted on the proteins causally related to kidney stones, to further explore the genetic mechanisms of susceptibility and the potential of proteins as drug targets. Ultimately, 22 target proteins associated with the risk of kidney stones were identified. Six plasma proteins (COLGALT1, CLMP, LECT1, ITIH1, CDHR3, CPLX2) were negatively correlated with kidney stone risk, while the genetic overexpression of 16 target proteins (GJA1, STOM, IRF9, F9, TMPRSS11D, ADH1B, SPINK13, CRYBB2, TNS2, DOCK9, OXSM, MST1, IL2, LMAN2, ITIH3, KLRF1) increased the risk of kidney stones. Based on the PWAS and colocalization analysis results, the 22 target proteins were classified into 3 tiers: IL2, CPLX2, and LMAN2 as tier 1 proteins with the most compelling evidence, MST1, ITIH1, and ITIH3 as tier 2 proteins, and the rest as tier 3 proteins. Enrichment analysis and PPI showed that target proteins mainly affect the occurrence of kidney stones through leukocyte activation and cell junction assembly. Druggability analysis suggested that IL2, MST1, and ITIH1 have potential as drug targets, and potential drugs were evaluated through molecular docking. In summary, this study employed multiple analytical methods to screen plasma proteins related to susceptibility to kidney stones, providing new insights into the genetic mechanisms of kidney stones and potential targets for treatment and prevention.
Two novel alleles of the MYB transcription factor BjA06.GL1 and BjB02.GL1 control leaf trichomes and enhance resistance to aphids in Brassica juncea
Authors: Heng Shuangping , Li Xiaolin , Li Man , Jiang Lulu , Li Meng , Zeng Wei , Mao Guangzhi , Xing Feng , Wan Zhengjie , Wen Jing , Shen Jinxiong , Fu Tingdong 
Published: November 2024

Abstract
Leaf trichome formation is a very important agronomic trait as it confers resistance to biotic and abiotic stresses, but the causal genes involved in this process in Brassica juncea remain largely unexplored. In this study, we first characterized the haplotypes of BjB02.GL1 among different inbred lines with leaf trichomes or glabrous leaves. A comparative analysis of the number and density of leaf trichomes between the two mustard inbred lines was then performed. BSA analysis of leaves with trichomes and glabrous pools from the F2 segregating population mapped the candidate genes on Chr.A06 and Chr.B02. Two candidate genes, BjA06.GL1 and BjB02.GL1, were subsequently cloned. After sequence alignment of the BjGL1 genes, both single-nucleotide polymorphisms (SNPs) and indel were identified in the BjA06.GL1 and BjB02.GL1 genes. And quantitative real-time polymerase chain reaction (qRT-PCR) analysis further confirmed that both the BjA06.GL1 and BjB02.GL1 genes were more highly expressed in leaves with trichomes than in glabrous leaves. As the leaf size increased, the leaf trichome density decreased. Gene editing of both BjA06.GL1 and BjB02.GL1 changed the leaf trichome to a glabrous leaf phenotype in mustard. In addition, plants with leaf trichomes presented greater resistance to aphids. Taken together, our results revealed that both BjA06.GL1 and BjB02.GL1 positively regulate leaf trichome formation and help increase aphid resistance in mustard. This study provides valuable resources and helps to elucidate the molecular mechanism of leaf trichome formation in B. juncea.
Optimization planning of distributed photovoltaic integration in distribution networks using combinatorial search algorithm
Authors: Wang Yong , Hu Yahan , Wang Zhe , Liu Mengchen , Li Tao 
Published: November 2024

Abstract
The current scenario sees the potential emergence of challenges such as power imbalances and energy dissipation upon the incorporation of distributed photovoltaic (PV) systems into distribution networks, impacting power quality and economic viability. To address these identified risks, this study introduces an innovative combinatorial search algorithm designed to autonomously derive optimal planning strategies for distribution networks. The process begins by establishing distinct planning models for distributed PVs and distribution network systems, followed by the application of the search algorithm to align these models and generate relevant Pareto datasets and multi-objective positioning criteria. By strategically combining and optimizing existing solutions to bolster the distribution network’s load-carrying capacity, the optimal strategy is progressively refined under the guidance of multiple objective constraints. Subsequent multiphase simulation experiments validate the efficacy of our approach in minimizing energy losses when compared to analogous methodologies. The distribution network integration planning strategies derived through our method showcase outstanding performance in reducing energy losses, conducting steady-state voltage safety assessments, optimizing installation capacity utilization rates, and enhancing economic returns, thus emphasizing the substantial potential of our approach in facilitating the seamless integration of distributed PVs into distribution networks.
Optimizing mountain railway alignments considering geo-hazard impacts based on a knowledge graph
Authors: Hu Ting , Song Taoran , Schonfeld Paul , Pu Hao , Hu Jianping 
Published: November 2024

Abstract
Alignment design is pivotal in determining the macroscopic hazard to a railway, especially in complex mountainous regions with dense geologic hazards. In this work, to apply the experience of handling geo-hazards that accumulated in manual alignment design, the related alignment design principles are summarized via an event tree. Based on this, a method is proposed to construct a knowledge graph (called GeRAD-KG) for mountain railway alignment design considering geo-hazard impacts of debris flows, landslides, and rockfalls, with which to structurally represent corresponding design principles. Then, a construction cost-geologic hazard bi-objective optimization model incorporating the knowledge-driven hazard assessment is constructed. To solve the model, a GeRAD-KG-guided distance transform algorithm integrating a multicriteria tournament decision is tailored. Finally, a real-world case indicates that the alternative generated by the proposed method can reduce the construction cost and geological hazard compared to the single-objective optimization alternative, which verifies the effectiveness of the proposed method for assisting actual railway design in a mountainous region with dense geo-hazards.
Comparison of six natural language processing approaches to assessing firearm access in Veterans Health Administration electronic health records
Authors: Trujeque Joshua , Dudley R Adams , Mesfin Nathan , Ingraham Nicholas E , Ortiz Isai , Bangerter Ann , Chakraborty Anjan , Schutte Dalton , Yeung Jeremy , Liu Ying , Woodward-Abel Alicia , Bromley Emma , Zhang Rui , Brenner Lisa A , Simonetti Joseph A 
Published: November 2024

Abstract

Objective
Access to firearms is associated with increased suicide risk. Our aim was to develop a natural language processing approach to characterizing firearm access in clinical records.

Materials and Methods
We used clinical notes from 36 685 Veterans Health Administration (VHA) patients between April 10, 2023 and April 10, 2024. We expanded preexisting firearm term sets using subject matter experts and generated 250-character snippets around each firearm term appearing in notes. Annotators labeled 3000 snippets into three classes. Using these annotated snippets, we compared four nonneural machine learning models (random forest, bagging, gradient boosting, logistic regression with ridge penalization) and two versions of Bidirectional Encoder Representations from Transformers, or BERT (specifically, BioBERT and Bio-ClinicalBERT) for classifying firearm access as “definite access”, “definitely no access”, or “other”.

Results
Firearm terms were identified in 36 685 patient records (41.3%), 33.7% of snippets were categorized as definite access, 9.0% as definitely no access, and 57.2% as “other”. Among models classifying firearm access, five of six had acceptable performance, with BioBERT and Bio-ClinicalBERT performing best, with F1s of 0.876 (95% confidence interval, 0.874-0.879) and 0.896 (95% confidence interval, 0.894-0.899), respectively.

Discussion and Conclusion
Firearm-related terminology is common in the clinical records of VHA patients. The ability to use text to identify and characterize patients’ firearm access could enhance suicide prevention efforts, and five of our six models could be used to identify patients for clinical interventions.
Immunomodulatory potential of dietary soybean-derived saponins
Authors: White Cameron S , Dilger Ryan N 
Published: November 2024

Abstract
Soybeans are widely recognized as a valuable crop, often included as a high-quality protein source in production animal diets. In addition to contributing to the macronutrient composition of the diet, soybeans also contain many minor bioactive components which can influence the health and growth of animals. This review examined the immunomodulatory potential of soy saponins and their specific effects on the inflammatory response, oxidative stress, and intestinal barrier function. Saponins are amphiphilic molecules, a property imparted by their polar carbohydrate chains that attach to a nonpolar aglycone backbone. This structure also complicates their isolation, thus most research investigating soy saponins has been performed in models that only require small amounts of isolated material. Many experiments conducted in vitro or in rodents reported that saponins can reduce damage, particularly in conditions where a challenge was first introduced to stimulate inflammation or oxidative stress. It appears that saponins can exert their anti-inflammatory effects through modulation of the NF-κB pathway, reducing its activation and the release of pro-inflammatory molecules later in the cascade. Furthermore, soy saponins can influence levels of important anti-oxidative enzymes and reduce the generation of reactive oxygen species, thus attenuating levels of oxidative stress in the model. As these results were obtained from experiments done in vitro or in rodents, they neglect to provide a good representation of how soy saponins may affect some of the greatest consumers of soy-based products, with those being production animals. The work that has been done seems to indicate that soy saponins may exert similar anti-inflammatory and anti-oxidative effects in production animals as those observed in other research models along with immunostimulatory activity that may help boost host defense systems. Overall, there is a dearth of research regarding the effects of soy saponins on species that commonly consume soy products, which begins by developing more effective methods of saponin extraction.
Interleukin-10 inhibits important components of trained immunity in human monocytes
Authors: Röring Rutger J , Scognamiglio Flavia , de Jong Lisanne C , Groh Laszlo A , Matzaraki Vasiliki , Koeken Valerie A C M , Joosten Leo A B , Ziogas Athanasios , Netea Mihai G 
Published: November 2024

Abstract
Trained immunity induces antigen-agnostic enhancement of host defense and protection against secondary infections, but inappropriate activation can contribute to the pathophysiology of inflammatory diseases. Tight regulation of trained immunity is therefore needed to avoid pathology, but little is known about the endogenous processes that modulate it. Here, we investigated the potential of interleukin (IL)-10, a prototypical anti-inflammatory cytokine, to inhibit trained immunity. IL-10 induced tolerance and inhibited trained immunity in primary human monocytes at both functional and transcriptional levels. Inhibition of STAT3, a signaling route that mediates IL-10 signals, induced trained immunity. IL-10 downregulated glycolytic and oxidative metabolism in monocytes but did not impact the metabolic effects of β-glucan–induced trained immunity. Furthermore, IL-10 prevented increased reactive oxygen species production in Bacillus Calmette–Guérin (BCG)–induced training but did not influence phagocytosis upregulation. In a cohort study of healthy volunteers vaccinated with BCG, genetic variants that influenced IL-10 or its receptor modulated BCG-induced trained immunity. Furthermore, circulating IL-10 concentrations were negatively correlated with induction of trained immunity after BCG vaccination in a sex-specific manner. In conclusion, IL-10 inhibited several, albeit not all, immunological functions amplified after induction of trained immunity. Follow-up studies should explore the precise molecular mechanism that mediates the effects of IL-10 on trained immunity. Addressing these knowledge gaps is an important step toward optimizing IL-10's potential as a therapeutic target in diseases characterized by inappropriate induction of trained immunity.
Species distribution modeling of North American beavers from the late Pliocene into the future
Authors: Lubbers Kelly E , Samuels Joshua X , Joyner T Andrew 
Published: November 2024

Abstract
Beavers have occurred in North America since at least 7 Ma, but relatively little is known about their distribution across the continent. We modeled distributions of beavers in the late Pliocene (3.3 Ma), Pleistocene (130 ka and 21 ka), and recent Holocene (1970 to 2000) to understand their dispersal across North America, predict future distributions and predict their possible response to future climate and habitat changes. Occurrence data for Castor canadensis were derived from the Global Biodiversity Information Facility. Those data were used with both modern (1970 to 2000) and modeled future (EC-Earth-Veg 2081 to 2100) bioclimatic variables from WorldClim as well as past (Pliocene Marine Isotope Stage M2, Pleistocene Last Interglacial, and Pleistocene Last Glacial Maximum) bioclimatic variables from PaleoClim to model beaver distributions through time. Fossil locality points for Castor extracted from the New and Old Worlds Database of Fossil Mammals (NOW), NEOTOMA Paleoecology Database, and Paleobiology Database were overlain on past projection models to use as validation points. Models were run using MaxEnt with post-processing in ArcGIS. Accuracy for the 5 models ranged between 59.6% and 60.2%. Results for the present model (1970 to 2000) showed habitat suitability in areas beavers inhabit today. During the Pliocene MIS M2 cooling event (3.3 Ma) and Pleistocene Last Glacial Maximum (21 ka), habitat suitability shifted further south into Mexico and peninsular Florida and away from more periglacial northern regions. During the Last Interglacial period (130 ka) and modeled future (2081 to 2100) EC-Earth-Veg 2081 to 2100, habitat suitability was higher in coastal and central regions in North America and lower in southern regions compared to their present distribution. Distributions were most affected by precipitation seasonality, isothermality, and mean annual temperature. High variability in seasonal precipitation and temperatures is likely to influence surface water availability, vegetation type, and riparian vegetation composition, which consequently may reduce available food resources and habitat for beavers. Observed shifts during warmer periods may indicate areas in the late Miocene that facilitated dispersal into North America. Future models using other predicted climatic scenarios and shared socioeconomic pathways may provide better resolution of potential future shifts in beaver distribution with best- and worst-case climate scenarios, thereby permitting at-risk areas to be prioritized for conservation in the face of climate change.
Supporting evidence in phase 2 cancer trial protocols: a content analysis
Authors: Bicer Selin , Nelson Angela , Carayannis Katerina , Kimmelman Jonathan 
Published: November 2024

Abstract

Background
Phase 2 trials are instrumental for designing definitive efficacy trials or attaining accelerated approval. However, high attrition of drug candidates in phase 2 trials raises questions about their supporting evidence.

Methods
We developed a typology of supporting evidence for phase 2 cancer trials. We also devised a scheme for capturing elements that enable an assessment of the strength of such evidence. Using this framework, we content analyzed supporting evidence provided in protocols of 50 randomly sampled phase 2 cancer monotherapy trials between January 2014 and January 2019, available on ClinicalTrials.gov.

Results
Of the 50 protocols in our sample, 52% were industry funded. Most invoked supporting evidence deriving from trials against different cancers (n = 28, 56%) or preclinical studies (n = 48, 96%) but not from clinical studies involving the target drug-indication pairing (n = 23, 46%). When presenting evidence from models, only 1 (2%) protocol explained its translational relevance. Instead, protocols implied translatability by describing molecular (86%) and pathophysiological (84%) processes shared by model and target systems. Protocols often provided information for assessing the magnitude, precision, and risk of bias for supporting trials (n = 43; 93%, 91%, 47%, respectively). However, such information was often unavailable for preclinical studies (n = 49; 53%, 22%, 59%, respectively).

Conclusions
Supporting evidence is key to justifying the commitment of scientific resources and patients to a clinical hypothesis. Protocols often omit elements that would enable critical assessment of supporting evidence for phase 2 monotherapy cancer trials. These gaps suggest the promise of more structured approaches for presenting supporting evidence.
Human papillomavirus prophylactic vaccines: update on new vaccine development and implications for single-dose policy
Authors: Schuind Anne E , Balaji Kanduri Ananth , Du Anna , Yuan Yuan , Dull Peter 
Published: November 2024

Abstract
Human papillomavirus (HPV) prophylactic vaccines were first licensed in 2006 with the primary goal of preventing HPV-related cancers, with cervical cancer accounting for the highest morbidity and mortality globally. Six HPV vaccines have been licensed; 4 of these have been prequalified by the World Health Organization, and additional products are in the pipeline. This article provides an overview of HPV vaccine coverage and current and anticipated vaccine supply vs expected demand. Given that the 2022 World Health Organization position paper on HPV vaccines includes a 1-dose regimen as an alternate schedule, we will discuss the evidence for using licensed vaccines in single-dose regimens and the approach to generating similar supportive data for other current and future vaccines. The broad adoption of a single-dose HPV vaccine regimen would expand access to vaccines by improving the supply-demand balance, increasing affordability, and simplifying logistics, which will ultimately impact HPV-related morbidity and mortality.
Leveraging single-dose human papillomavirus vaccination dose-efficiency to attain cervical cancer elimination in resource-constrained settings
Authors: Man Irene , Georges Damien , Basu Partha , Baussano Iacopo 
Published: November 2024

Abstract

Background
In low- and middle-income countries, resource constraints remain a critical factor limiting access to cervical cancer preventive measures. The option of single-dose immunization could help improve access to human papillomavirus vaccination and attain cervical cancer elimination.

Methods
With simulation models adapted to country-specific data and scenarios for single-dose protection derived from International Agency for Research on Cancer India vaccine trial data, we estimated the expected impact of single-dose vaccination in India, Rwanda, and Brazil, three countries with varying profiles of cervical cancer risk and vaccination timelines. In combination with single-dose vaccination, we explored different resource reallocation strategies based on dose efficiency, elimination attainment, and cervical cancer cases prevented, with the existing 2-dose program as a comparator.

Results
Assuming lifelong single-dose protection, switching from 2-dose to 1-dose vaccination and reallocating resources to female catch-up could prevent 467-1336, 94-194, and 15-207 additional cervical cancer cases (per 100 000 women born) in cohorts aged 11-30 years in India, Rwanda, and Brazil, respectively. Resource reallocation to improve the current routine coverage could help eliminate cervical cancer in India and across all Brazilian states but not in Rwanda. For each country, we found a dose-efficient reallocation strategy (or a combination of strategies) together with 1-dose vaccination that could prevent more cervical cancers vs 2-dose vaccination, even in the worst-case scenario of single-dose protection.

Conclusion
Adopting single-dose vaccination with resource reallocation is a resource-efficient approach to enhance progress toward cervical cancer elimination. The overall impact of vaccination can be maximized by fine-tuning resource reallocation to a country’s needs.
Population-level health impact of hypothetical waning 1-dose human papillomavirus vaccination and 2-dose mitigation strategies in a high cervical cancer burden setting
Authors: Burger Emily A , Laprise Jean-François , Portnoy Allison , Spencer Jennifer C , Sy Stephen , Regan Mary Caroline , Bénard Élodie , Drolet Mélanie , Brisson Marc , Kim Jane J 
Published: November 2024

Abstract

Background
We simulated the impact of hypothetical waning scenarios of a 1-dose human papillomavirus (HPV) vaccination paired with switching to 2-dose mitigation strategies guided by empirical vaccine trial reporting timelines.

Methods
Using 2 independent mathematical models fitted to a high-burden setting, we projected the cumulative cervical cancer cases averted over 85 years for alternative HPV vaccination scenarios under 2 program adoption timelines: 1) de novo introduction of a 1-dose HPV vaccination and 2) a switch from an existing 2-dose HPV vaccination program to a 1-dose vaccination. We assumed 80% vaccination coverage with the bivalent vaccine and an average duration of a 1-dose HPV vaccine protection of either 30 or 25 years with 100% efficacy. We varied the eligible age group(s) at program introduction and the 2-dose mitigation (single-age cohort or multi-age cohort). If needed for mitigation, reintroduction of 2-dose vaccination was assumed to occur in 2036 (ie, 30 years after initiation of the Costa Rica Vaccine Trial).

Results
Under both vaccine adoption timelines, the models projected that countries could achieve the same level of health benefits by switching to 2 doses in 2036 using a multi-age cohort approach as with initiating a 2-dose or 1-dose vaccination program with no waning. With only a single-age cohort 2-dose mitigation approach, 98%-99% of cases would be prevented compared with the health benefits of 2 doses or a noninferior, durable 1 dose.

Conclusions
Countries hesitant to adopt a 1-dose HPV vaccination program may have opportunities to leverage the benefits and efficiency of a 1-dose schedule while awaiting longer-term reporting from 1-dose durability studies, including Costa Rica Vaccine Trial.