bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel crossover and recombination hotspots massively spread across human genome
Authors: Ohadi Mina , Arabfard Masoud , Khamse Safoura , Alizadeh Samira , Vafadar Sara , Bayat Hadi , Tajeddin Nahid , Maddi Ali M.A. , Delbari Ahmad , Khorshid Hamid R Khorram 
Published: May 2024

Abstract

Background
The recombination landscape and subsequent natural selection have vast consequences in evolution and speciation. However, most of the recombination hotspots in the human genome are yet to be discovered. We previously reported hotspot colonies of CG-rich trinucleotide two-repeat units (CG-TTUs) across the human genome, several of which were shared, with extensive dynamicity, as phylogenetically distant as in mouse.
Results
Here we performed a whole-genome analysis of AT trinucleotide two-repeat units (AT-TTUs) in human and found that the majority (96%) resided in approximately 1.4 million colonies, spread throughout the genome. In comparison to the CG-TTU colonies, the AT-TTU colonies were significantly more abundant and larger in size. Pure units and overlapping units of the pure units were readily detectable in the same colonies, signifying that the units are the sites of unequal crossover. Subsequently, we analyzed several of the AT-TTU colonies in several primates and mouse. We discovered dynamic sharedness of several of the colonies across the primate species, which mainly reached maximum complexity and size in human.
Conclusions
We report novel crossover and recombination hotspots of the finest molecular resolution, and evolutionary relevance in human. In respect of crossover and recombination, the human genome is far more dynamic than previously envisioned.
Experimental investigation on the hydraulic fracture initiation and propagation of temporary plugging and acid fracturing in a large-scale true triaxle simulation
Authors: Kong Xiangwei , Huang Hao , Sun Tengfei 
Published: May 2024

Abstract

The study investigates the initiation and propagation of multi-fractures during temporary plugging and diverting acid fracturing in deep carbonate reservoir rocks with tight formations. An orthogonal experiment using prepared carbonate outcrop rock mass simulated a genuine triaxle scenario for temporary plugging multi-fracture network acid fracturing. Analysis of 3D section scans revealed the roughness of fractured surfaces caused by acidization, helping understand the effects of different types and amounts of temporary plugging agents combined with changes in acid injection displacement on initiation process and morphological complexity during propagation when forming these temporarily plugged fractures. Design parameters for temporary plugging acid fracturing were optimized based on criteria such as fracture pressure, transformed area, and pre- and post-plug acid fracturing transformation indexes. The concentration of the temporary plug agent affects the pressure-bearing capacity of the plug layer, but excessive pumping or rapid compression can damage fibers. Rigid particle plugs allow for quicker steering, while flexible particle plugs enable slower steering. The turning and propagation of acid fracturing fractures show unsteady behavior. The sensitivity factors affecting temporary plugging acid fracturing are ranked as follows: type of temporary plugging agent > acid injection displacement > dosage of temporary plugging agent. For optimal design parameters in a temporary plugging acid fracturing process, it is recommended to use H-type particle temporary plugging agent at a dosage of 10 g and an acid injection displacement rate of 400 mL/min. Increasing both the concentration and pumping displacement rate can enhance its steering ability; however, incorporating fibers and particles into the mixture is advisable to improve stability within the plugged layer as well as throughout acid fractures.
PCL Injury Following High Energy Trauma: Associated Injuries and Postoperative Complications “Insights from a National Registry Study”
Authors: Bingol Izzet , Oktem Umut , kaymakoglu mehmet , Kolac Ulas Can , Kamaci Saygin , Korkmaz Izzet , Fidanci Ali Aykut , Ata Naim , Ulgu M. Mahir , Birinci Suayip , Karaaslan Fatih , turhan egemen , Atay Ozgur Ahmet , Kocaoglu Baris 
Published: May 2024

Abstract

Purpose
The posterior cruciate ligament (PCL) is a vital knee stabilizer. While PCL injuries are rare, high-energy traumas can lead to total ruptures, with accompanying injuries requiring surgery. This study aims to investigate the demographics, concomitant injuries, and postoperative complications of patients who underwent PCL reconstruction due to high-energy trauma in a large patient sample.
Methods
Patients who underwent PCL reconstruction from 2016 to 2022 were retrospectively evaluated using data from a nationwide personal health recording system. Patient demographics, injury mechanisms, associated fractures, soft tissue injuries, and postoperative complications were collected from patient notes, clinical visits, and surgical notes. Individuals with a PCL injury following high-energy trauma (car accident, falls from height, motorcycle accident) with a minimum follow-up of 1 year were included in the study.
Results
The study included 416 patients with a mean age of 32.4 years. Isolated PCL injuries (n = 97, 23.3%) were observed less frequently than multiple-ligament injuries (n = 319, 76.7%). Most cases were treated with single-stage surgery (86.8%), while staged surgeries were performed in a minority of cases (13.2%). There was no relationship between trauma mechanisms and multiple-ligament involvement, accompanying injuries, or postoperative complications. Surgeries following car accidents were more likely to occur as staged surgeries (p = 0.014). Additionally, the complication rates for staged surgeries and younger patients (≤ 18 years) were significantly higher (p = 0.009).
Conclusion
High-energy trauma-induced PCL injuries are often associated with severe concurrent knee injuries with multiple ligament involvement. PCL reconstructions following car accidents are more likely to be staged. These findings highlight the importance of careful consideration in managing these cases to minimize complications, particularly in younger age groups.
Level of evidence: Level III
Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression
Authors: Benster Lindsay , Weissman Cory , Suprani Federico , Toney Kamryn , Afshar Houtan , Stapper Noah , Tello Vanessa , Stolz Louise , Poorganji Mohsen , Daskalakis Zafiris , Appelbaum Lawrence , Kohn Jordan 
Published: May 2024

Abstract

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (TRD). Leveraging electronic medical records (EMR), this retrospective cohort study applied supervised machine learning (ML) to sociodemographic, clinical, and treatment-related data to predict depressive symptom response (>50% reduction on PHQ-9) and remission (PHQ-9 < 5) following rTMS in 232 patients with TRD (mean age: 54.5, 63.4% women) treated at the University of California, San Diego Interventional Psychiatry Program between 2017 and 2023. ML models were internally validated using nested cross-validation and Shapley values were calculated to quantify contributions of each feature to response prediction. The best-fit models proved reasonably accurate at discriminating treatment responders (Area under the curve (AUC): 0.689 [0.638, 0.740], p < 0.01) and remitters (AUC 0.745 [0.692, 0.797], p < 0.01), though only the response model was well-calibrated. Both models were associated with significant net benefits, indicating their potential utility for clinical decision-making. Shapley values revealed that patients with comorbid anxiety, obesity, concurrent psychiatric medication use, and more chronic TRD were less likely to respond or remit following rTMS. Patients with trauma and former tobacco users were more likely to respond. Furthermore, delivery of intermittent theta burst stimulation and more rTMS sessions were associated with superior outcomes. These findings highlight the potential of ML-guided techniques to guide clinical decision-making for rTMS treatment in patients with TRD to optimize therapeutic outcomes.
Development of a predictive nomogram for sepsis in patients with urolithiasis-related obstructive pyelonephritis
Authors: Tsai Yi-Chun , Huang Yu-Hsuan , Niu Kuang-Yu , Yeh Hsin-Tzu , Lu Sz-Wei , Lo Yu-Tai , Tsai Yu-Chen , Chen Chen-Bin , Yen Chieh-Ching 
Published: May 2024

Abstract

Background: In patients with urolithiasis-related obstructive pyelonephritis (UROP), sepsis represents a critical and concerning complication that can substantially increase the mortality rate. This study aimed to identify the risk factors for sepsis in UROP patients and to develop a predictive nomogram model.
Methods: We analyzed data from 148 patients who met the UROP criteria and were admitted to Chang Gung Memorial Hospital between January 1, 2016, and December 31, 2021. The primary outcome evaluated was the incidence of sepsis, as defined by the most recent Sepsis-3 guidelines. To identify potential risk factors for sepsis, we employed the Least Absolute Shrinkage and Selection Operator (LASSO) regression technique. Subsequently, we utilized multivariable logistic regression to construct the predictive model.
Results: There were a total of 102 non-sepsis cases and 46 sepsis cases. The sepsis group showed significantly lower systolic blood pressure (p < 0.001), a higher heart rate (p = 0.002), a higher shock index (SI) (p < 0.001), a more prevalent history of diabetes mellitus (DM) (p = 0.015), and the mean hospital length of stay was significantly longer (p < 0.001). The laboratory results indicated a higher rate of positive blood culture in the sepsis group (60.9% vs 33.3%, p = 0.002), increased serum white blood cell counts (17.2 ± 10.9 103/uL vs 12.8 ± 6.4 103/uL, p = 0.014), a higher proportion of bandemia (26.1% vs 4.1%, p < 0.001), elevated CRP levels (19.9 ± 9.8 mg/dL vs 9.9 ± 9.9 mg/dL, p < 0.001), and a higher neutrophil to lymphocyte ratio (NLR) (23.6 ± 20.3 vs 12.9 ± 10.1, p < 0.001). Risk factors for sepsis in multivariable analysis were a history of DM (OR = 4.24, p = 0.007), SI (x10-1) (OR = 1.55, p < 0.001), CRP (mg/dL) (OR = 1.08, p = 0.005), and NLR (x10) (OR = 1.58, p = 0.007).
Conclusions: Our study demonstrated that patients with UROP who have DM, higher SI, higher NLR, and elevated CRP levels are significantly more likely to develop sepsis. These insights may aid in risk stratification, and it is imperative that clinicians promptly initiate treatment for those identified as high risk.
The effect of miR-20b on breast cancer cell proliferation and related mechanism
Authors: Li Wei , He Pengjuan , Cui Xiaochen , Zhang Taotao 
Published: May 2024

Abstract

Background and Purpose
Breast cancer is the the most common malignant tumor of women, and contributes to the main cause of death of female malignant tumors. Although there are many mutated oncogenes and anti-oncogenes during the course of breast cancer formation, it is not clear that the specific molecular mechanism to maintain the malignant proliferation of tumor cells. Studies have shown that microRNAs (miRNAs) display specific expression in different tumor tissues and play an important role in the development of tumors. The purpose of this paper is to explore the influences of miR-20b on the breast cancer cell proliferation and the regulation function of miR-20b to the targeted genes.It will provide evidence for diagnosis and treatment of breast cancer and lay a foundation for its clinical targeted diagnosis and treatment.
Methods
We analyzed the expressive levels of miR-20b within cancer tissue and corresponding normal tissue adjacent to carcinoma of 10 breast cancer patients, as well as the normal breast epithelial cell lines MCF-10A and SKBR3, MCF-7, and MDA-MB-231 breast cancer cell lines through quantitative PCR (qPCR). MDA-MB-231 breast cancer cell line was up-regulated by miR-20b, and the effect of miR-20b on proliferation ability of breast cancer cells were detected by MTT and colony formation assay. The effect of miR-20b on the tumor formation ability of 231 breast cancer cells was detected by the breast cancer model of BALB/c mice. we used the bioinformatics to predict the possible downstream target genes, and verified it through luciferase experiment. Finally, the regulation effect of miR-20b on target genes was detected by qPCR and western blot in mRNA and protein levels.
Results
The present study confirmed that the expressive level of miR-20b were significantly reduced in breast cancer tissue and cells. MTT and colony formation data showed that miR-20b inhibited the proliferation ability of 231 breast cancer cells, and the breast cancer model of BALB/c nude mice showed that miR-20b inhibited the tumor formation ability of 231 breast cancer cells. The luciferase experiment confirmed that hypoxia inducible factor-α(HIF-α)was a potential downstream target gene of miR-20b. Finally we found by qPCR and western blot that miR-20b could inhibit the expression of target gene HIF-α in mRNA and protein levels.
Conclusions
MiR-20b can inhibit the proliferation of breast cancer cells. MiR-20b can inhibit the expression of target gene HIF-α in mRNA and protein levels.
Modeling the Interaction of L-Hydroxyproline, a Constituent of Collagen, with a Hydrated TiO2 lattice at Varied Concentrations: Examining Surface and Long-Range Effects
Authors: Valentini Maria , Caboni Pierluigi , Sanna Giovanni , Pisu Massimo , Pieroni Enrico 
Published: May 2024

Abstract

This study investigates the interaction between L-hydroxyproline (LHP), a key component of collagen, and a hydrated titanium dioxide (TiO2) lattice at various LHP concentrations. It represents the first step toward a broader project aimed at recycling agri-food wastes and byproducts, particularly mussel byssus, to enhance existing nano-coatings and design new ones. We performed gas chromatography-mass spectrometry analysis of byssus, which revealed 22 metabolites, confirming glycine, L-proline, and particularly LHP as key biomolecules. Subsequently, molecular dynamics (MD) simulations provided insights into LHP-lattice interaction mechanisms, revealing the TiO2 lattice's ability to align LHP rings near-perpendicular to the lattice surface and near-parallel to each other, facilitated by the LHP tail functional group. This indicates optimal LHP packing, particularly close to the surface, and the formation of durable bonds between LHPs and lattice atoms. The analysis, particularly radial distribution functions, indicates that lattice-driven organizing interactions extend from the surface region to the bulk liquid phase thanks to the LHP– and water–mediated contributions. Overall, the simulation provides a chemical-physics rationale to explain improved collagen adhesion to the TiO2 lattice, contributing to understanding collagen-TiO2 interactions, and offering valuable insights for nanomaterials, biomaterials, tissue engineering, and biomedical applications.
Nanocrystalline Boron Nitride Coating for High Conductivity, Low Temperature Proton Exchange Membrane Fuel Cells
Authors: Akinwande Deji , Kutagulla Shanmukh , Biswas Abhijit , Mutyala Devi , Terlier Tanguy , Le Nam , Caldino-Bohn Isabel , Favela Christopher , Vajtai Robert , Korgel Brian A. , Aluru Narayana , Ajayan Pulickel 
Published: May 2024

Abstract

Hydrogen fuel cells based on proton exchange membrane (PEM) technology are promising as an alternative to fossil fuel-based energy. Conventional PEMFC technology is operated at fully humidified conditions in a narrow temperature range (~ 80 oC) to maintain sufficient proton conductivity and power output, which necessitates high cost of operation. In this work, we demonstrate a scalable, room temperature coating of ultrathin boron nitride (BN) via pulsed laser deposition (PLD) that simultaneously increases conductivity of perfluorosulfonic acid (PFSA) based membranes while decreasing the crossover. Remarkably, BN coated membranes show a 20% increase in performance at current operational conditions (1.485 A/cm2 @ 0.6 V) and a 20% increase in power density (0.965 W/cm2) while exhibiting a maximum crossover current decrease of 32% (3.58 mA/cm2) relative to industry standard Nafion™ 211. Furthermore, we demonstrate a reduction of operational temperatures to as low as 60 oC with modified membranes without performance impact, thereby affording substantial reduction of the PEMFC operational cost. These observations are practically relevant for the development of next generation PEM technology by enabling more scalable and cost-effective high performance fuel cell stacks.
Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics
Authors: Su Shuquan , Ni Zhongran , Lan Tian , Ping Pengyao , Tang Jinling , Yu Zuguo , Hutvagner Gyorgy , Li Jinyan 
Published: May 2024

Abstract

Viral codon fitness (VCF) of the host and the VCF shifting path have been seldom studied under quantitative measurements, although they could be concepts vital to understand pathogen epidemiology. This study demonstrates that the relative synonymous codon usage (RSCU) of virus genomes together with other genomic properties are predictive to virus host codon fitness through tree-based machine learning. Analysis on the RSCU data matrix also revealed that the wobble position of the virus codons is critically important for the host codon fitness distinction. As the trained models can well characterise the host codon fitness of the viruses, the frequency and other details stored at the leaf nodes of these models can be reliably translated into human virus codon fitness score (HVCF score) as a readout of codon fitness of any virus infecting human. Specially, we evaluated and compared HVCF of virus genome sequences from human sources and others and evaluated HVCF of SARS-CoV-2 genome sequences from NCBI virus database, where we found no obvious shifting trend in host codon fitness towards human-non-infectious. We also developed a bioinformatics tool to simulate codon-based virus fitness shifting path using codon compositions of the viruses, and we found that Tylonycteris bat coronavirus HKU4 related viruses may have close relationship with SARS-CoV-2 in terms of human codon fitness. The finding of abundant synonymous mutations in the predicted codon fitness shifting path also provides new insights for evolution research and virus monitoring in environmental surveillance.
Time-Series Decomposition Model combined with pre-trained LSTM: Real-time prediction of dissolved oxygen concentration suitable for automated aquaculture feeding system
Authors: Kim Woojae , Jun Myoungjae , Cho Yeong-Jun , Jeong Hieyong 
Published: May 2024

Abstract

As part of automation in land-based aquaculture facilities, the widespread adoption of automated feed supply systems is actively taking place. The automated feed supply system must be capable of determining the appropriate feed quantity to supply at arbitrary feeding times based on the hunger level of cultured fish. However, the decline in dissolved oxygen concentration due to feed supply can pose a high mortality risk if not managed properly. Therefore, there is a need to ensure safety in real-time before the feed supply occurs. In this study, we proposed a method to predict dissolved oxygen concentration in real-time, even when feeding occurs at arbitrary times, and aimed to validate its performance. We combined a time-series data decomposition model with a pre-trained deep-learning model. We can obtain trend components for long-term changes in dissolved oxygen concentration through the time-series data decomposition method. Using two models, we predict seasonal components for short-term changes caused by feed supply at arbitrary times. Regular changes can be obtained through the time-series data decomposition model, while irregular changes can be obtained through the pre-trained deep learning model. Experimental results validate the performance of the proposed model by comparing the predicted results of regular and irregular feed supply with those of other deep learning models. Lastly, we discuss how the proposed model structure reduces complexity by simplifying the deep learning model's weight matrix elements, achieving good performance with fewer learning parameters.
Enhancing in Situ Conservation of Crop Wild Relatives for Food and Agriculture in Lithuania
Authors: Labokas Juozas , Lisajevičius Mantas , Uogintas Domas , Karpavičienė Birutė 
Published: May 2024

Abstract

The crop and CWR checklist of Lithuania was created containing 2,630 taxa. The checklist comprises 1,384 native taxa including archaeophytes and 1,246 neophytes. In total, 699 taxa (26.6%) could be quite strictly defined as of food or forage use. A list of 144 CWR priority species with 135 native species and archaeophytes and 9 naturalized species was generated. In total, 53 genera of food and forage species belonging to 15 families are represented by the priority CWR. Two approaches for CWR genetic reserve selection have been employed in this study: (1) CWR-targeted evaluation of preselected sites, including Natura 2000 sites, national protected areas, and other effective area-based conservation measures (OECMs), such as ancient hillfort sites and ecological protection zones of water bodies; and (2) analysis of large georeferenced plant databases. Forty-five potential genetic reserve sites have been selected by the first approach covering 83 species or 57.6% of the national CWR priority list. With the second approach, the in situ CWR National Inventory database has been created by combining data from the Database of EU habitat mapping in Lithuania (BIGIS), Herbarium Database of the Nature Research Centre (BILAS), Lithuanian Vegetation Database (EU-LT-001), and Global Biodiversity Information Facility (GBIF). Hotspot analysis of CWR species richness and number of observations suggested that higher CWR diversity is more likely to be found in protected areas. However, Shannon diversity and Shannon equitability indices showed that the areas outside of the protected areas are also suitable for CWR genetic reserve establishment.
Occurrence of blueberry virus L in Japan and its aphid transmission and pathogenicity in highbush blueberry
Authors: ISOGAI Masamichi , Yamamura Misaki , Sakamoto Hijiri , Yaegashi Hajime , Watanabe Manabu 
Published: May 2024

Abstract

In this first report of the occurrence of blueberry virus L (BlVL) in Japan, BlVL was detected using reverse transcription-polymerase chain reaction in 35 of 52 highbush blueberry shrubs in a field and in aphids (Aphis gossypii) on a BlVL-infected blueberry shrub. In the aphid transmission test of BlVL, the aphids transmitted the virus to uninfected blueberry bushes. No symptoms were observed in shrubs infected with the virus by aphid inoculation or by graft inoculation, suggesting that BlVL causes latent infection in highbush blueberry.
Increasing access, equitability, and rigor in the assessment of Neighborhood Mortgage Discrimination
Authors: Moubadder Leah , Bliss Maya , Maliniak Maret , Waddel Hannah , Switchenko Jeffery , Chang Howard , Kramer Michael , McCullough Lauren 
Published: May 2024

Abstract

Mortgage discrimination alters the distribution of investment, opportunity, and economic advantage—key contributors of health disparities. Leveraging Home Mortgage Disclosure Act data, we assessed mortgage denial risk in 380 U.S. urban areas. We estimated the risks by census tract–relative to the urban-specific average—using a Bayesian spatial model with conditionally autoregressive distributions fitted with integrated nested Laplace approximation. This approach borrows information through spatial and non-spatial smoothing, resulting in stable estimates in the presence of sparse data. The method, publicly accessible, allows researchers to apply our approach, fostering deeper insights into mortgage lending discrimination and systematic neighborhood disinvestment.