bluuebunny/crossref_metadata_2025_split huggingface dataset:
SENP3 inhibition suppresses hepatocellular carcinoma progression and improves the efficacy of anti-PD-1 immunotherapy
Authors: Wang Peng , Qiu Jiannan , Fang Yuan , Li Songmao , Liu Kua , Cao Yin , Zhang Guang , Wang Zhongxia , Gu Xiaosong , Wu Junhua , Jiang Chunping 
Published: January 2025

Abstract
The importance of SUMOylation in tumorigenesis has received increasing attention, and research on therapeutic agents targeting this pathway has progressed. However, the potential function of SUMOylation during hepatocellular carcinoma (HCC) progression and the underlying molecular mechanisms remain unclear. Here, we identified that SUMO-Specific Peptidase 3 (SENP3) was upregulated in HCC tissues and correlated with a poor prognosis. Multiple functional experiments demonstrated that SENP3 promotes the malignant phenotype of HCC cells. Mechanistically, SENP3 deSUMOylates RACK1 and subsequently increases its stability and interaction with PKCβII, thereby promoting eIF4E phosphorylation and translation of oncogenes, including Bcl2, Snail and Cyclin D1. Additionally, tumor-intrinsic SENP3 promotes the infiltration of tumor-associated macrophages (TAMs) while reducing cytotoxic T cells to facilitate immune evasion. Mechanistically, SENP3 promotes translation of CCL20 via the RACK1 /eIF4E axis. Liver-specific knockdown of SENP3 significantly inhibits liver tumorigenesis in a chemically induced HCC model. SENP3 inhibition enhances the therapeutic efficacy of PD-1 blockade in an HCC mouse model. Collectively, SENP3 plays cell-intrinsic and cell-extrinsic roles in HCC progression and immune evasion by modulating oncogene and cytokine translation. Targeting SENP3 is a novel therapeutic target for boosting HCC responsiveness to immunotherapy.
Rnd3 protects against doxorubicin-induced cardiotoxicity through inhibition of PANoptosis in a Rock1/Drp1/mitochondrial fission-dependent manner
Authors: Ge Wen , Zhang Xiaohua , Lin Jie , Wang Yangyang , Zhang Xiao , Duan Yu , Dai Xinchun , Zhang Jiye , Zhang Yan , Jiang Mengyuan , Qiang Huanhuan , Zhao Zhijing , Zhang Xuebin , Sun Dongdong 
Published: January 2025

AbstractDoxorubicin, a representative drug of the anthracycline class, is widely used in cancer treatment. However, Doxorubicin-induced cardiotoxicity (DIC) presents a significant challenge in its clinical application. Mitochondrial dysfunction plays a central role in DIC, primarily through disrupting mitochondrial dynamics. This study aimed to investigate the impact of Rnd3 (a Rho family GTPase 3) on DIC, with a focus on mitochondrial dynamics. Cardiomyocyte-specific Rnd3 transgenic mice (Rnd3-Tg) and Rnd3LSP/LSP mice (N-Tg) were established for in vivo experiments, and adenoviruses harboring Rnd3 (Ad-Rnd3) or negative control (Ad-Control) were injected in the myocardium for in vitro experiments. The DIC model was established using wild-type, N-Tg, and Rnd3-Tg mice, with subsequent intraperitoneal injection of Dox for 4 weeks. The molecular mechanism was explored through RNA sequencing, immunofluorescence staining, co-immunoprecipitation assay, and protein-protein docking. Dox administration induced significant mitochondrial injury and cardiac dysfunction, which was ameliorated by Rnd3 overexpression. Further, the augmentation of Rnd3 expression mitigated mitochondrial fragmentation which is mediated by dynamin-related protein 1 (Drp1), thereby ameliorating the PANoptosis (pyroptosis, apoptosis, and necroptosis) response induced by Dox. Mechanically, the interaction between Rnd3 and Rho-associated kinase 1 (Rock1) may impede Rock1-induced Drp1 phosphorylation at Ser616, thus inhibiting mitochondrial fission and dysfunction. Interestingly, Rock1 knockdown nullified the effects of Rnd3 on cardiomyocytes PANoptosis, as well as Dox-induced cardiac remodeling and dysfunction elicited by Rnd3. Rnd3 enhances cardiac resilience against DIC by stabilizing mitochondrial dynamics and reducing PANoptosis. Our findings suggest that the Rnd3/Rock1/Drp1 signaling pathway represents a novel target for mitigating DIC, and modulating Rnd3 expression could be a strategic approach to safeguarding cardiac function in patients undergoing Dox treatment.
Connecting genomic results for psychiatric disorders to human brain cell types and regions reveals convergence with functional connectivity
Authors: Yao Shuyang , Harder Arvid , Darki Fahimeh , Chang Yu-Wei , Li Ang , Nikouei Kasra , Volpe Giovanni , Lundström Johan N. , Zeng Jian , Wray Naomi R. , Lu Yi , Sullivan Patrick F. , Hjerling-Leffler Jens 
Published: January 2025

AbstractIdentifying cell types and brain regions critical for psychiatric disorders and brain traits is essential for targeted neurobiological research. By integrating genomic insights from genome-wide association studies with a comprehensive single-cell transcriptomic atlas of the adult human brain, we prioritized specific neuronal clusters significantly enriched for the SNP-heritabilities for schizophrenia, bipolar disorder, and major depressive disorder along with intelligence, education, and neuroticism. Extrapolation of cell-type results to brain regions reveals the whole-brain impact of schizophrenia genetic risk, with subregions in the hippocampus and amygdala exhibiting the most significant enrichment of SNP-heritability. Using functional MRI connectivity, we further confirmed the significance of the central and lateral amygdala, hippocampal body, and prefrontal cortex in distinguishing schizophrenia cases from controls. Our findings underscore the value of single-cell transcriptomics in understanding the polygenicity of psychiatric disorders and suggest a promising alignment of genomic, transcriptomic, and brain imaging modalities for identifying common biological targets.
The global implications of a Russian gas pivot to Asia
Authors: Pye Steve , Bradshaw Michael , Price James , Zhang Dan , Kuzemko Caroline , Sharples Jack , Welsby Dan , Dodds Paul E. 
Published: January 2025

AbstractRecent years have seen unprecedented shifts in global natural gas trade, precipitated in large part by Russia’s war on Ukraine. How this regional conflict impacts the future of natural gas markets is subject to three interconnected factors: (i) Russia’s strategy to regain markets for its gas exports; (ii) Europe’s push towards increased liquified natural gas (LNG) and the pace of its low carbon transition; and (iii) China’s gas demand and how it balances its climate and energy security objectives. A scenario modelling approach is applied to explore the potential implications of this geopolitical crisis. We find that Russia struggles to regain pre-crisis gas export levels, with the degrees of its success contingent on China’s strategy. Compared to 2020, Russia’s gas exports are down by 31–47% in 2040 where new markets are limited and by 13–38% under a pivot to Asia strategy. We demonstrate how integrating energy geopolitics and modelling enhances our understanding of energy futures.
Colorimetric identification of colorless acid vapors using a metal-organic framework-based sensor
Authors: Jang Wonhyeong , Yoo Hyejin , Shin Dongjun , Noh Seokjin , Kim Jin Yeong 
Published: January 2025

AbstractIn terms of safety and emergency response, identifying hazardous gaseous acid chemicals is crucial for ensuring effective evacuation and administering proper first aid. However, current studies struggle to distinguish between different acid vapors and remain in the early stages of development. In this study, we propose an on-site monitorable acid vapor decoder, MOF-808-EDTA-Cu, integrating the robust MOF-808 with Cu-EDTA, functioning as a proton-triggered colorimetric decoder that translates the anionic components of corrosive acids into visible colors. The sensor exhibits a cyan-to-yellow shift when exposed to HCl vapor and can visually differentiate various acidic vapors (HF, HBr, and HI) through unique color changes. Furthermore, the compatibility of the MOF-based sensor with multiple metal ions having atomic-level dispersion broadens its discrimination range, enabling the identification of six different colorless acid vapors within a single sensor domain. Additionally, by incorporating a flexible polymer, the MOF-808-EDTA-Cu has been successfully processed into a portable miniaturized acid sensor, exhibiting distinct color changes that can be easily monitored by the naked eye and camera sensors. This provides experimental validation as a practical sensor capable of on-site 24-hour monitoring in the real world.
Enhancing the growth and essential oil components of Lavandula latifolia using Malva parviflora extract and humic acid as biostimulants in a field experiment
Authors: El-Hefny Mervat , Hussien Mahmoud Khattab 
Published: January 2025

AbstractNatural extracts as biostimulants have the potential to enhance the productivity and growth of many medicinal and aromatic plants. This study aimed to enhance the growth, and essential oil (EO) content, as well as composition of Lavandula latifolia Medik. by using Malva parviflora L. extract (ME) as a biostimulant in combination with humic acid (HA) in a field experiment in two successive seasons of 2022 and 2023. The phenolic, flavonoid and water-soluble vitamins of the ME were analyzed using an HPLC. The protein amino acids of the ME were identified by an amino acid analyzer. The prepared concentrations of HA (0, 1, 2, and 4 g/L) were applied to the soil. While, they for ME (0, 2, 4, and 6 g/L) were added as a foliar spray. The EO compositions collected from the leaves of the treated L. latifolia plants were subjected to the hydro-distillation method and analyzed using GC-MS. The most prevalent vitamins found in ME were vitamin B12, vitamin C, and folic acid. Besides, several phenolic compounds were found in ME, such as catechol, cinnamic acid and syringic acid, while flavonoid chemicals, such as luteolin and quercetin. Also, alanine, ammonia, aspartic acid, glutamic acid, glycine, and tyrosine were the ME’s most prominent nitrogenous and amino acid components. The most effective treatments of HA and ME on the plant height, the number of branches/plant, and plant fresh weight were 4 + 6 g/L and 4 + 2 g/L for leaf area and chlorophyll content, it was 4 + 4 g/L; and for EO percentage were 4 + 0 g/L, 2 + 0 g/L, and 4 + 4 g/L, compared to the control treatment for each characteristic. The main EO compounds eucalyptol, camphor, α-pinene, β-pinene, Δ-elemene, germacrene D-4-ol, isoborneol, β-caryophyllene oxide, and tau.-cadinol identified in the leaves were found in the range of 28.74–46.19%, 15.34–30.49%, 3.39–7.16%, 0–5.08%, 0–5.18%, 0–3.20%, 0–3.31% and 0–3.40%, respectively. It can be concluded that a combination treatment of HA and ME as natural biostimulant compounds at 4 + 4 g/L could be recommended for good plant growth, and EO quantity of L. latifolia plants.
Enhancing electric vehicle battery lifespan: integrating active balancing and machine learning for precise RUL estimation
Authors: Sultan Yara A. , Eladl Abdelfattah A. , Hassan Mohamed A. , Gamel Samah A. 
Published: January 2025

AbstractElectric vehicles (EVs) rely heavily on lithium-ion battery packs as essential energy storage components. However, inconsistencies in cell characteristics and operating conditions can lead to imbalanced state of charge (SOC) levels, resulting in reduced capacity and accelerated degradation. This study presents an active cell balancing method optimized for both charging and discharging scenarios, aiming to equalize SOC across cells and improve overall pack performance. The proposed system includes two balancing strategies: a charging balance that redistributes excess charge from high-SOC cells to maximize capacity, and a discharging balance that addresses low-SOC cells to extend discharge duration. Experimental results confirm that this method effectively reduces SOC disparities, enhancing both charging and discharging capacities. Additionally, to accurately predict battery lifespan and remaining useful life (RUL), seven machine learning models are evaluated using R-squared (R2) and Mean Absolute Error (MAE) metrics. Among these, k-nearest Neighbors and Random Forest models deliver the highest accuracy, achieving R2 values of 0.996 and above with low MAE, demonstrating strong predictive capability. The integration of active balancing and RUL prediction enables a feedback loop where balanced SOC levels promote battery health, and RUL predictions inform optimal balancing strategies. This comprehensive approach advances EV battery management, enhancing lifespan and reliability through proactive balancing and predictive insights.
Scene categorization by Hessian-regularized active perceptual feature selection
Authors: Zhou Junwu , Ren Fuji 
Published: January 2025

AbstractDecoding the semantic categories of complex sceneries is fundamental to numerous artificial intelligence (AI) infrastructures. This work presents an advanced selection of multi-channel perceptual visual features for recognizing scenic images with elaborate spatial structures, focusing on developing a deep hierarchical model dedicated to learning human gaze behavior. Utilizing the BING objectness measure, we efficiently localize objects or their details across varying scales within scenes. To emulate humans observing semantically or visually significant areas within scenes, we propose a robust deep active learning (RDAL) strategy. This strategy progressively generates gaze shifting paths (GSP) and calculates deep GSP representations within a unified architecture. A notable advantage of RDAL is the robustness to label noise, which is implemented by a carefully-designed sparse penalty term. This mechanism ensures that irrelevant or misleading deep GSP features are intelligently discarded. Afterward, a novel Hessian-regularized Feature Selector (HFS) is proposed to select high-quality features from the deep GSP features, wherein (i) the spatial composition of scenic patches can be optimally maintained, and (ii) a linear SVM is learned simultaneously. Empirical evaluations across six standard scenic datasets demonstrated our method’s superior performance, highlighting its exceptional ability to differentiate various sophisticated scenery categories.
Integrating ecological and recreational functions to optimize ecological security pattern in Fuzhou City
Authors: Bai Junting , Sun Rui , Liu Yifan , Chen Jie , Li Xiaohe 
Published: January 2025

AbstractThe scientific establishment of the Ecological Security Pattern (ESP) is crucial for fostering the synergistic development of ecological and recreational functions, thereby enhancing urban ecological protection, recreational development, and sustainable growth. This study aimed to propose a novel method of constructing ESP considering both ecological and recreational functions, and to reconstruct ESP by weighing the relationship between ecological protection and recreational development. Utilizing Fuzhou City as a case study, a comprehensive application of methodologies including Morphological Spatial Pattern Analysis (MSPA), landscape connectivity analysis, ArcGIS spatial analysis, social network analysis (SNA), and circuit theory is employed to develop both the ESP and the Recreational Spatial Pattern (RSP). A trade-off matrix is created to facilitate the reconstruction of the ESP, delineate functional zones, and identify strategic points, followed by a thorough optimization and development strategy. The analysis revealed 36 ecological source areas (ESAs) within Fuzhou City, encompassing a total area of 5807.90 km², predominantly situated in the western and northern regions. Additionally, 98 ecological corridors (ECs) were identified, extending over 2500.55 km, alongside 100 ecological pinch points (EPPs) and 146 ecological barrier points (EBPs). The city also contains 57 recreational nodes (RNs),, which display a spatial distribution characterized by a “dense in the east, sparse in the west” pattern. Furthermore, 165 recreational corridors (RCs) were extracted, covering a distance of 3795.21 km. Based on the trade-off matrix, Fuzhou City was categorized into eight functional zones: ecological core zone, ecological important zone, eco-recreation key trade-off zone, eco-recreation secondary trade-off zone, recreational core zone, recreational important zone, recreational development zone, and elastic development zone.The study identified 95 key strategic points and 475 sub-strategic. A multifunctional and complex ESP was constructed, characterized by “one core, five districts, six corridors, and seven wedges”, and a tailored ecological and recreational planning and development strategy for Fuzhou City was proposed. This research contributes a theoretical framework for the construction and optimization of a multifunctional ESP and supports the coordinated high-quality development of ecological protection and recreational activities in urban environments.
The effect of fecal bile acids on the incidence and risk-stratification of colorectal cancer: an updated systematic review and meta-analysis
Authors: Yang Shaohui , Wang Yu , Sheng Lijuan , Cui Wei , Ma Chenyang 
Published: January 2025

AbstractRecent studies suggest the role of gut microbes in bile acid metabolism in the development and progression of colorectal cancer. However, the surveys of the association between fecal bile acid concentrations and colorectal cancer (CRC) have been inconsistent. We searched online to identify relevant cross-sectional and case-control studies published online in the major English language databases (Medline, Embase, Web of Science, AMED, and CINAHL) up to January 1, 2024. We selected studies according to inclusion and exclusion criteria and extracted data from them. RevMan 5.3 was used to perform the meta-analyses. In CRC risk meta-analysis, the effect size of CA (cholic acid), CDCA (chenodeoxycholic acid), DCA (deoxycholic acid), and UDCA (ursodeoxycholic acid) were significantly higher (CA: standardized mean difference [SMD] = 0.41, 95% confidence interval [CI]: 0.5–0.76, P = 0.02; CDCA: SMD = 0.35, 95% CI: 0.09–0.62, P = 0.009; DCA: SMD = 0.33,95% CI: 0.03–0.64, P = 0.03; UDCA: SMD = 0.46, 95% CI: 0.14–0.78, P = 0.005), and the combined effect size was significantly higher in the high-risk than the low-risk CRC group (SMD = 0.36, 95% CI: 0.21–0.51, P < 0.00001). In the CRC incidence meta-analysis, the effect sizes of CA and CDCA were significantly higher (CA: SMD = 0.42, 95% CI: 0.04–0.80, P = 0.03; CDCA: SMD = 0.61, 95% CI: 0.26–0.96, P = 0.00079), and their combined effect size was also significantly higher in the high-risk compared to low-risk CRC group (SMD = 0.39, 95% CI: 0.09–0.68, P = 0.01). Only one cross-sectional study suggested a higher concentration of CDCA, DCA, and UDCA in the stool of the CRC high-risk group than the low-risk group. These findings indicate that higher fecal concentrations of bile acid may be associated with a higher risk/incidence of CRC.
Electrical impedance-based tissue classification for bladder tumor differentiation
Authors: Veil Carina , Krauß Franziska , Amend Bastian , Fend Falko , Sawodny Oliver 
Published: January 2025

AbstractIncluding sensor information in medical interventions aims to support surgeons to decide on subsequent action steps by characterizing tissue intraoperatively. With bladder cancer, an important issue is tumor recurrence because of failure to remove the entire tumor. Impedance measurements can help to classify bladder tissue and give the surgeons an indication on how much tissue to remove. Over the years of research, it became obvious that electrical impedance spectroscopy is a very promising tool for tissue differentiation, but also a very sensitive one. While differentiation in preliminary studies shows great potential, challenges arise when transferring this concept to real, intraoperative conditions, mainly due to the influence of preoperative radiotherapy, possibly different tumor types, and mechanical tissue deformations due to peristalsis or unsteady contact force of the sensor. This work proposes a patient-based classification approach that evaluates the distance of an unknown measurement to a healthy reference of the same patient, essentially a relative classification of the difference in impedance that is robust against inter-individual differences and systematic errors. A diversified dataset covering multiple disturbance scenarios is recorded. Two alternatives to define features from the impedance data are investigated, namely using measurement points and model-based parameters. Based on the distance of the feature vector of a unknown measurement to a healthy reference, a Gaussian process classifier is trained. The approach achieves a high classification accuracy of up to 100% on noise-free impedance data recorded under controlled conditions. Even when the differentiation is more ambiguous due to external disturbances, the presented approach still achieves a classification accuracy of 80%. These results are a starting point to tackle intraoperative bladder tissue characterization and decrease the recurrence rate.
Natural sampling and aliasing of marine geochemical signals
Authors: Curtis Andrew , Bloem Hugo , Wood Rachel , Bowyer Fred , Shields Graham A. , Zhou Ying , Yilales Mariana , Tetzlaff Daniel 
Published: January 2025

AbstractIt is well known that the sedimentary rock record is both incomplete and biased by spatially highly variable rates of sedimentation. Without absolute age constraints of sufficient resolution, the temporal correlation of spatially disjunct records is therefore problematic and uncertain, but these effects have rarely been analysed quantitatively using signal processing methods. Here we use a computational process model to illustrate and analyse how spatial and temporal geochemical records can be biased by the inherent, heterogenous processes of marine sedimentation and preservation. This confirms that sedimentary hiatuses can span a substantial proportion of geological time, caused by inherent geological processes. Moreover, even in marine geochemical records that are essentially spatially continuous and complete, the signal is irreversibly disguised in time as lower frequency signals by an aliasing effect. We demonstrate that Nyquist’s theorem correctly predicts these biased signatures, proving that aliasing can be caused by cyclical and multiscale relative sea-level changes - a natural sampling effect. Our combined results show that deeper marine records are significantly more likely to provide unaliased environmental signatures. Also, some proxy residence times will be sufficiently long that they average over aliased frequencies, cancelling these in the geochemical record. And field observations of changes in sedimentation rate (such as hiatuses, condensation, or lateral expansion) can be used to infer possible aliasing. Where aliasing by natural sampling occurs, this cannot be undone simply by increasing sample resolution (density): aliasing is caused by an absence of sedimentary record, which by definition cannot be sampled at all. To overcome these issues, we propose that spatially separated aliased records may still be correctly correlated in age, and true geochemical cycles inferred, if a paired-sampling strategy informed by local stratigraphy is adopted. In this, two (or more) closely-spaced samples are analysed at each sampling point instead of only one, after which aliased cycles are inferred from geochemical gradients.