bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrative genomics identifies SHPRH as a tumor suppressor gene in lung adenocarcinoma that regulates DNA damage response
Authors: Nagelberg Amy L. , Sihota Tianna S. , Chuang Yu-Chi , Shi Rocky , Chow Justine L. M. , English John , MacAulay Calum , Lam Stephen , Lam Wan L. , Lockwood William W. 
Published: June 2024

Abstract
Background
Identification of driver mutations and development of targeted therapies has considerably improved outcomes for lung cancer patients. However, significant limitations remain with the lack of identified drivers in a large subset of patients. Here, we aimed to assess the genomic landscape of lung adenocarcinomas (LUADs) from individuals without a history of tobacco use to reveal new genetic drivers of lung cancer.

Methods
Integrative genomic analyses combining whole-exome sequencing, copy number, and mutational information for 83 LUAD tumors was performed and validated using external datasets to identify genetic variants with a predicted functional consequence and assess association with clinical outcomes. LUAD cell lines with alteration of identified candidates were used to functionally characterize tumor suppressive potential using a conditional expression system both in vitro and in vivo.

Results
We identified 21 genes with evidence of positive selection, including 12 novel candidates that have yet to be characterized in LUAD. In particular, SNF2 Histone Linker PHD RING Helicase (SHPRH) was identified due to its frequency of biallelic disruption and location within the familial susceptibility locus on chromosome arm 6q. We found that low SHPRH mRNA expression is associated with poor survival outcomes in LUAD patients. Furthermore, we showed that re-expression of SHPRH in LUAD cell lines with inactivating alterations for SHPRH reduces their in vitro colony formation and tumor burden in vivo. Finally, we explored the biological pathways associated SHPRH inactivation and found an association with the tolerance of LUAD cells to DNA damage.

Conclusions
These data suggest that SHPRH is a tumor suppressor gene in LUAD, whereby its expression is associated with more favorable patient outcomes, reduced tumor and mutational burden, and may serve as a predictor of response to DNA damage. Thus, further exploration into the role of SHPRH in LUAD development may make it a valuable biomarker for predicting LUAD risk and prognosis.
Reflections on the discovery GLP-1 as a satiety hormone: Implications for obesity therapy and future directions
Authors: Astrup Arne 
Published: June 2024

AbstractScientists were chasing an incretin hormone, and when GLP-1 was finally discovered, we found that it had a pronounced satiety effect, slowed down gastric emptying, and actually reduced postprandial insulin response. These mechanisms are the basis for the highly efficacious GLP-1 analogues that today offer safe and effective treatment in millions of people living with obesity. Moreover, the combined GLP-1 mechanisms of weight loss and delayed carbohydrate absorption may also be the key drivers of remission of type 2 diabetes and reduced cardiovascular events found by GLP-1 analogues.
A hybrid structure based on silk fibroin/PVA nanofibers and alginate/gum tragacanth hydrogel embedded with cardamom extract
Authors: Irantash Shadan , Gholipour-Kanani Adeleh , Najmoddin Najmeh , Varsei Mehdi 
Published: June 2024

AbstractHybrid structures made of natural-synthetic polymers have been interested due to high biological features combining promising physical–mechanical properties. In this research, a hybrid dressing consisting of a silk fibroin (SF)/polyvinyl alcohol (PVA) nanofibers and sodium alginate (SA)/gum tragacanth (GT) hydrogel incorporating cardamom extract as an antibacterial agent was prepared. Accordingly, SF was extracted from cocoons followed by electrospinning in blend form with PVA (SF/PVA ratio: 1:1) under the voltage of 18 kV and the distances of 15 cm. The SEM images confirmed the formation of uniform, bead free fibers with the average diameter of 199 ± 28 nm. FTIR and XRD results revealed the successful extraction of SF and preparation of mixed fibrous mats. Next, cardamom oil extract-loaded SA/GT hydrogel was prepared and the nanofibrous structure was placed on the surface of hydrogel. SEM analysis depicted the uniform morphology of hybrid structure with desirable matching between two layers. TGA analysis showed desired thermal stability. The swelling ratio was found to be 1251% after 24 h for the hybrid structure and the drug was released without any initial burst. MTT assay and cell attachment results showed favorable biocompatibility and cell proliferation on samples containing extract, and antibacterial activity values of 85.35% against S. aureus and 75% against E. coli were obtained as well. The results showed that the engineered hybrid nanofibrous-hydrogel film structure incorporating cardamom oil extract could be a promising candidate for wound healing applications and skin tissue engineering.
Next generation fatigue crack growth experiments of aerospace materials
Authors: Strohmann Tobias , Melching David , Paysan Florian , Dietrich Eric , Requena Guillermo , Breitbarth Eric 
Published: June 2024

AbstractToday’s societal challenges require rapid response and smart materials solutions in almost all technical areas. Driven by these needs, data-driven research has emerged as an enabler for faster innovation cycles. In fields such as chemistry, materials science and life sciences, automatic and even autonomous data generation and processing is already accelerating knowledge discovery. In contrast, in experimental mechanics, complex investigations like studying fatigue crack growth in structural materials have traditionally adhered to standardized procedures with limited adoption of the digital transformation. In this work, we present a novel infrastructure for data-centric experimental mechanics in the field of fatigue crack growth. Our methodology incorporates a robust code base that complements a multi-scale digital image correlation and robot-assisted test rig. Using this approach, the information-to-cost ratio of fatigue crack growth experiments in aerospace materials is significantly higher compared to traditional experiments. Thus, serves as a catalyst for discovering new scientific knowledge in the field of structural materials and structures.
The influence of existing piles on station settlement during the construction of a tunnel undercrossing under existing stations
Authors: Ma Baolin , Wu Shengzhi , Chen Qihui , Liang Erbin , Li Xiudong 
Published: June 2024

AbstractIn the construction of tunnels under existing stations, it is necessary to control their settlement. When there is a pile foundation in the existing station, the pile cutting has a significant impact on the settlement of the existing station. To determine the influence of existing piles on the settlement of subway stations, a reasonable pile-cutting time is proposed. Based on the Chengdu Metro Line 9 underpassing the existing Line 1 hatchery station, the settlement law of the tunnel underpassing the existing Line 1 station is analysed via a numerical simulation. Furthermore, the deformation and stress characteristics of the existing piles, pipe roofs, and tunnel linings and the supporting effect on the existing station are discussed. It is concluded that the cutting of existing piles causes a change in the tunnel bearing system, thus resulting in a certain deformation of the station. The influence of different pile cutting times on the settlement of the existing station is then analysed, and it is clarified that the tunnel support stiffness is significantly enhanced after the construction of the secondary lining. At this time, the settlement of the existing pile station is significantly reduced. Finally, through a field investigation, the effect of surface grouting, pipe shed, and multilayer lining on the settlement control of the existing station while the existing pile foundation exists is determined. This research can provide a reference for the settlement control and foundation underpinning of existing stations at ultra-small distances in underground excavation tunnels.
Enhancing germination and growth of canola (Brassica napus L.) through hydropriming and NaCl priming
Authors: BiBi Rahila , Elahi Nosheen Noor , Danish Subhan , Alahmadi Tahani Awad , Ansari Mohammad Javed 
Published: June 2024

AbstractThe excessive accumulation of sodium chloride (NaCl) in soil can result in soil salinity, which poses a significant challenge to plant growth and crop production due to impaired water and nutrient uptake. On the other hand, hydropriming (WP) and low level of NaCl priming can improve the germination of seeds, chlorophyll contents, oil and seed yield in plants. That’s why this study investigates the impact of hydro and different levels of NaCl (0.5, 1.0, 1.5 and 2.0%) priming, as pre-treatment techniques on canola seeds germination, growth and yield of two varieties Punjab and Faisal Canola. Results showed that, WP performed significant best for increase in germination (~ 20 and ~ 22%) and shoot length (~ 6 and ~ 10%) over non-priming (NP) in Punjab Canola and Faisal Canola respectively. A significant increase in plant height (~ 6 and ~ 7%), root length (~ 1 and ~ 7%), shoot fresh weight (~ 5 and ~ 7%), root fresh weight (~ 6 and ~ 7%) in Punjab Canola and Faisal Canola respectively. It was also observed that plants under WP and 0.5%NaCl priming were also better in production of seed yield per plant, oil contents, silique per plant, seeds per silique, and branches per plant chlorophyll contents and leaf relative water contents over NP. In conclusion, WP and 0.5%NaCl has potential to improve the germination, growth, yield and oil attributes of canola compared to non-priming, 1.0%NaCl priming, 1.5%NaCl priming and 2.0%NaCl priming.
GIS-based multi-criteria decision models for barite exploration in Nigeria’s Benue Trough
Authors: Gajere Jiriko N. , Adekeye Olabisi A. , Tende Andongma W. , Aminu Mohammed D. 
Published: June 2024

AbstractSpatial predictive mapping using geographic information system (GIS) is considered an invaluable tool for reconnaissance-scale exploration of mineral resources. In this study, geospatial data on geophysics, remote sensing, and structural and lithological attributes were systematically integrated to prospect barite potential zones within the Mid-Nigerian Benue Trough (MBT). Correlation attribute evaluation was used to establish the relationship between mineral deposit occurrences and geospatial data, while data integration was implemented using the Multi-Objective Optimization by Ratio Analysis (MOORA), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Additive Ratio Assessment (ARAS) multi-criteria models. Here we show that the correlation attribute evaluation suggests that barite occurrences displayed a strong correlation with spatial data on lineament density, ferric iron alteration, and potassium to thorium (K/Th) ratio, whereas a weak correlation was observed with spatial data on the first vertical derivative (FVD), proximity to the host rock, and ferrous iron alteration. Here we report that the quantitative estimation of predictive models indicated that very high predictive zones for barite occurrences accounted for 19% of all the models. The accuracy assessment using Receiver Operating Characteristic (ROC)/Area Under the Curve (AUC) showed prediction levels above 78% for all models. The effectiveness of the spatial application of multi-criteria decision models makes them a reliable tool for barite exploration within the Mid-Nigerian Benue Trough (MBT) and other geologically similar environments.
Computational design of novel chimeric multiepitope vaccine against bacterial and viral disease in tilapia (Oreochromis sp.)
Authors: Pumchan Ansaya , Proespraiwong Porranee , Sawatdichaikul Orathai , Phurahong Thararat , Hirono Ikuo , Unajak Sasimanas 
Published: June 2024

AbstractRegarding several infectious diseases in fish, multiple vaccinations are not favorable. The chimeric multiepitope vaccine (CMEV) harboring several antigens for multi-disease prevention would enhance vaccine efficiency in terms of multiple disease prevention. Herein, the immunogens of tilapia’s seven pathogens including E. tarda, F. columnare, F. noatunensis, S. iniae, S. agalactiae, A. hydrophila, and TiLV were used for CMEV design. After shuffling and annotating the B-cell epitopes, 5,040 CMEV primary protein structures were obtained. Secondary and tertiary protein structures were predicted by AlphaFold2 creating 25,200 CMEV. Proper amino acid alignment in the secondary structures was achieved by the Ramachandran plot. In silico determination of physiochemical and other properties including allergenicity, antigenicity, glycosylation, and conformational B-cell epitopes were determined. The selected CMEV (OSLM0467, OSLM2629, and OSLM4294) showed a predicted molecular weight (MW) of 70 kDa, with feasible sites of N- and O-glycosylation, and a number of potentially conformational B-cell epitope residues. Molecular docking, codon optimization, and in-silico cloning were tested to evaluate the possibility of protein expression. Those CMEVs will further elucidate in vitro and in vivo to evaluate the efficacy and specific immune response. This research will highlight the new era of vaccines designed based on in silico structural vaccine design.
Research on machine learning forecasting and early warning model for rainfall-induced landslides in Yunnan province
Authors: Kang Jia , Wan Bingcheng , Gao Zhiqiu , Zhou Shaohui , Chen Huansang , Shen Huan 
Published: June 2024

AbstractLandslides are highly destructive geological disasters that pose a serious threat to the safety of people’s lives and property. In this study, historical records of landslides in Yunnan Province, along with eight underlying factors of landslide (elevation, slope, aspect, lithology, land cover type, normalized difference vegetation index (NDVI), soil type, and average annual precipitation (AAP)), as well as historical rainfall and current rainfall data were utilized. Firstly, we analyzed the sensitivity of each underlying factor in the study area using the frequency ratio (FR) method and obtained a landslide susceptibility map (LSM). Then, we constructed a regional rainfall-induced landslides (RIL) probability forecasting model based on machine learning (ML) algorithms and divided warning levels. In order to construct a better RIL prediction model and explore the effects of different ML algorithms and input values of the underlying factor on the model, we compared five ML classification algorithms: extreme gradient boosting (XGBoost), k-nearest neighbor (KNN), support vector machine (SVM), logistic regression (LR), and random forest (RF) algorithms and three representatives of the input values of the underlying factors. The results show that among the obtained forecasting models, the LSM-based RF model performs the best, with an accuracy (ACC) of 0.906, an area under the curve (AUC) of 0.954, a probability of detection (POD) of 0.96 in the test set, and a prediction accuracy of 0.8 in the validation set. Therefore, we recommend using RF-LSM model as the RIL forecasting model for Yunnan Province and dividing warning levels.
Follow-up study to explore the relationship between Neutrophil to lymphocyte ratio and impaired fasting glucose—using the group-based trajectory modeling
Authors: Liu Xuekui , Peng Gangshan , Liu Ran , Zang Xiu , Zou Caiyan , Sun Haojie , Zhu Qian , Geng Houfa , Liang Jun 
Published: June 2024

AbstractPrevious studies have indicated a link between neutrophil to lymphocyte ratio (NLR) and impaired fasting glucose (IFG), but the findings have been disputed. By conducting a real-world follow-up study, we can monitor the development of diseases and confirm the connection between NLR and IFG. A total of 1168 patients without IFG or T2DM were followed up for six years. At baseline, participants' NLR levels, fasting plasma glucose and other clinical characteristics were recorded. During the follow-up period, NLR levels and the prevalence of IFG were recorded. Ultimately, 45 individuals were lost to follow-up, leaving 1,123 participants for analysis. Using Group-Based Trajectory Modeling (GBTM), the sample was divided into three groups. The prevalence of IFG in the three groups was 12.1%, 19.4%, and 20.85%, respectively. Compared with the low-level NLR group, the hazard ratio of IFG in the moderate-level NLR group and high-level NLR group were 1.628 (1.109–2.390) and 1.575 (1.001–2.497), respectively. There was a significant interaction effect of BMI and NLR on the risk of IFG (P < 0.001). In this real-world follow-up study, we observed a positive association between NLR and the risk of IFG, with this relationship being exacerbated by obesity status.
Trajectory of mid-arm subcutaneous fat, muscle mass predicts mortality in hemodialysis patients independent of body mass index
Authors: Yang Yuqi , Li Qian , Qiu Wanting , Zhang Helin , Qiu Yuyang , Yuan Jing , Zha Yan 
Published: June 2024

AbstractAlthough decreasing body mass index (BMI) is associated with higher mortality risk in patients undergoing hemodialysis (HD), BMI neither differentiates muscle and fat mass nor provides information about the variations of fat distribution. It remains unclear whether changes over time in fat and muscle mass are associated with mortality. We examined the prognostic significance of trajectory in the triceps skinfold (TSF) thickness and mid-upper arm circumference (MUAC). In this multicenter prospective cohort study, 972 outpatients (mean age, 54.5 years; 55.3% men) undergoing maintenance HD at 22 treatment centers were included. We calculated the relative change in TSF and MUAC over a 1-year period. The outcome was all-cause mortality. Kaplan–Meier, Cox proportional hazard analyses, restricted cubic splines, and Fine and Gray sub-distribution hazards models were performed to examine whether TSF and MUAC trajectories were associated with all-cause mortality. During follow-up (median, 48.0 months), 206 (21.2%) HD patients died. Compared with the lowest trajectory group, the highest trajectories of TSF and MUAC were independently associated with lower risk for all-cause mortality (HR = 0.405, 95% CI 0.257–0.640; HR = 0.537; 95% CI 0.345–0.837; respectively), even adjusting for BMI trajectory. Increasing TSF and MUAC over time, measured as continuous variables and expressed per 1-standard deviation decrease, were associated with a 55.7% (HR = 0.443, 95% CI 0.302–0.649), and 97.8% (HR = 0.022, 95% CI 0.005–0.102) decreased risk of all-cause mortality. Reduction of TSF and MUAC are independently associated with lower all-cause mortality, independent of change in BMI. Our study revealed that the trajectory of TSF thickness and MUAC provides additional prognostic information to the BMI trajectory in HD patients.
Prediction of axial capacity of corrosion-affected RC columns strengthened with inclusive FRP
Authors: Kumar Prashant , Arora Harish Chandra , Kumar Aman , Radu Dorin 
Published: June 2024

AbstractThe primary cause behind the degradation of reinforced concrete (RC) structures is the propagation of corrosion in the steel-RC structures. Nowadays, numerous retrofitting techniques are available in the construction sector. Fiber-reinforced polymer (FRP) is one of the efficient rehabilitation measures that can be implemented on corroded structures to enhance structural capacities. However, the estimation of axial strength of FRP-strengthened columns affected by corrosion has been a challenging and tedious task in the laboratory as well as on the site. Considering such shortcomings, the prediction of axial capacity can be done using various analytical methods and artificial intelligence (AI) techniques. In this study, a comprehensive dataset of circular columns was extracted from the literature to predict the axial strength of FRP-wrapped and unstrengthened RC corroded columns. The laboratory results from the assembled dataset were compared to corresponding values estimated using relevant design codes provided by American Concrete Institute (ACI 440.2R-17 and ACI 318-19), and Bureau of Indian Standard (IS 456:2000). Five machine learning models were employed on columns to predict the axial load carrying capacity of FRP-strengthened and un-strengthened RC corroded columns. The results discovered that the extreme gradient boosting (XGBoost) model achieves superior accuracy with the least errors and could be used by the scientific community and FRP applicators to forecast the axial performance of corroded columns strengthened with and without FRP. The findings from the design codes revealed that prediction errors were available in high margins. Furthermore, feature importance analysis was conducted using the Shapley Additive exPlanation algorithm to know the contribution and influence of each input parameter on axial capacity. The feature analysis found that unconfined compressive strength of concrete plays an important role in deciding the axial capacity of columns. Moreover, to enhance the precision of axial capacity computation and improving the overall efficacy in engineering practice, a web-based user-friendly interface was developed for FRP applicators and engineers to simplify the process.
Candidate protein biomarkers in chronic kidney disease: a proteomics study
Authors: Makhammajanov Zhalaliddin , Kabayeva Assem , Auganova Dana , Tarlykov Pavel , Bukasov Rostislav , Turebekov Duman , Kanbay Mehmet , Molnar Miklos Z. , Kovesdy Csaba P. , Abidi Syed Hani , Gaipov Abduzhappar 
Published: June 2024

AbstractProteinuria poses a substantial risk for the progression of chronic kidney disease (CKD) and its related complications. Kidneys excrete hundreds of individual proteins, some with a potential impact on CKD progression or as a marker of the disease. However, the available data on specific urinary proteins and their relationship with CKD severity remain limited. Therefore, we aimed to investigate the urinary proteome and its association with kidney function in CKD patients and healthy controls. The proteomic analysis of urine samples showed CKD stage-specific differences in the number of detected proteins and the exponentially modified protein abundance index for total protein (p = 0.007). Notably, specific urinary proteins such as B2MG, FETUA, VTDB, and AMBP exhibited robust negative associations with kidney function in CKD patients compared to controls. Also, A1AG2, CD44, CD59, CERU, KNG1, LV39, OSTP, RNAS1, SH3L3, and UROM proteins showed positive associations with kidney function in the entire cohort, while LV39, A1BG, and CERU consistently displayed positive associations in patients compared to controls. This study suggests that specific urinary proteins, which were found to be negatively or positively associated with the kidney function of CKD patients, can serve as markers of dysfunctional or functional kidneys, respectively.