bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploration of the causal relationship between obesity and sepsis and investigation of the mechanism of anoikis in sepsis
Authors: Zhou Wenyan , Feng kai , Zhang Xusheng , Zhang Xiaoya , Chen Bendong 
Published: September 2024

Abstract

Objective To explore the causal relationship between common obesity indicators (body mass index, hip circumference, waist circumference) and sepsis based on Mendelian randomization analysis. Furthermore, the mechanism of the role of anoikis in sepsis was explored based on the bioinformatics mining. Methods In the first part, SNPs strongly associated with body mass index, Hip circumference, and Waist circumference were downloaded from the genome-wide association study(GWAS) database and screened as instrumental variables, and sepsis was used as an outcome variable. IVW was used as the primary analysis method to assess causal associations, with Weighted median and Mr-Egger as complementary methods. Heterogeneity among genetic variants was detected using Cochran's Q test and funnel plot analysis, horizontal pleiotropy was detected using Mr-Egger-intercept, and sensitivity analyses were performed using the "leave-one-out" method. In the second part, the biological functions and mechanisms of anoikis in sepsis were investigated based on R-analysis downloaded from the GEO database. Resuts The body mass index(BMI), hip circumference(HC), and waist circumference (WC) were risk factors for sepsis. The core ARDEGs SERPINB1, MERTK and CEACAM8 were significantly up-regulated in sepsis and showed good diagnostic efficacy. The risk model based on ARDEGs showed good potential for clinical application. SERPINB1 may be involved in the regulation of inflammatory responses in sepsis through the NLRC4/CASP1-inflammatory effects signaling pathway. Conclusion There is a causal association between obesity and sepsis and obesity is a risk factor for sepsis. The anoikis genes SERPINB1, MERTK and CEACAM8 are potential diagnostic targets for sepsis. And SERPINB1 may be involved in the regulation of inflammatory effects in sepsis through the NLRC4/CASP1- inflammatory effects signaling pathway.
Integrative taxonomy of Janirella (Isopoda: Asellota: Janirellidae), with descriptions of two new species and an amended classification of the genus
Authors: Ohta Mizuki , Kakui Keiichi , Kojima Shigeaki , Shimomura Michitaka 
Published: September 2024

Abstract

We describe two new Janirella species, Janirella scutum sp. nov. and Janirella spinoscutum sp. nov., collected at depths of 2893–3176 m on the landward slope of the Japan Trench, northwestern Pacific. These species differ from congeners in having an ovoid body with dorsal spines on each pereonite; the pleotelson with two pairs of short and one pair of long lateral projections; and the posterior projection on the pleotelson shorter than pleotelson length. They differ from one another in the number and size of dorsal spines on the pereonites. We determined partial sequences for the cytochrome c oxidase subunit I (COI) gene for the two new species and seven other Janirella species and constructed a COI-based maximum-likelihood tree of Janirella. In the tree, the subgenus Parjanirella was monophyletic but embedded within a paraphyletic group of species in the subgenus Janirella. Based on this result, we propose the elimination of subgenus ranks in Janirella.
Structural Perceptual Local Feature Pattern
Authors: Xu Jie , Deng Yizhi , Chen Jianping 
Published: September 2024

Abstract

This paper introduces a novel feature extraction technique, named Structural Perceptual Local Feature Pattern (SPLFP). The SPLFP method integrates Fechner's law into a compact encoding scheme, aiming to mimic the human perception of external stimuli and extract features from images that conform to human visual habits. At the same time, under the framework of the famous Petersen graph, SPLFP extracts spatial structure information from four different directions within the 5×5 neighborhood of each pixel. The effectiveness of SPLFP and its single-scale methods, SPLFPv and SPLFPh, were rigorously evaluated on several face data sets. The results demonstrated that SPLFP and its single-scale methods exhibit remarkable performance, consistency, and stability across all tested datasets. This indicates that SPLFP enables the extraction of highly discriminative features, positioning it as a strong candidate for face classification tasks.
A developmental classification system for the comparison of Puya raimondii giant Andean rosettes
Authors: Suni Mery , Vadillo Giovana , Prado Gerson , Tumi Liscely , Ramsay Paul Michael 
Published: September 2024

Abstract

Puya raimondii Harms, an endangered giant bromeliad, has great ecological and cultural significance in the Central Andes. To help studies of population size structure in this species, this study aims to develop a rapid classification system based on plant developmental stages instead of using absolute size measurements, and applies it to three areas in or near Huascarán National Park, Peru. Plant height, stem height, total and photosynthetically-active rosette diameter and height to the base of the rosette were measured, to illustrate how the developmental stages compare, along with estimates of vegetation, rocks, and bare ground. Five plant developmental stages were identified in the study: juvenile, subadult, adult, reproductive adult, and senescent reproductive adult. The juvenile stage could, in future, be further divided into smaller, vulnerable plants and more established juveniles, but this requires more detailed study to determine appropriate distinguishing developmental criteria. Comparing locations, Puya plants in Queshque, were smaller than in the other locations, across all developmental stages. However, the environmental variables recorded in this study could not explain this difference, indicating the importance of other, unknown factors. This study provides an efficient and informative classification system for P. raimondii giant rosettes, using well-defined developmental stages, that can reveal important differences between populations and prompt the generation of new hypotheses about the ecology of these important plants. The classification system could be applied in populations across the species’ distributional range in the Central Andes to explore how age, size and environmental factors affect growth and development in this species.
Elucidating the binding specificity of interactive compounds targeting ATP binding cassette subfamily G member 2 (ABCG2)
Authors: Ray Pawan , Kumari Indu , Prasad Rajendra , Ray Shashikant , Banerjee Atanu , Prakash Amresh 
Published: September 2024

Abstract

The ATP-binding cassette (ABC) transporter superfamily plays a pivotal role in cellular detoxification and drug efflux. ATP binding cassette subfamily G member 2 (ABCG2) referred to as the Breast cancer resistance protein (BCRP) has emerged as a key member involved in multidrug resistance displayed by cancer cells. Understanding the molecular basis of substrate and inhibitor recognition, and binding within the transmembrane domain of ABCG2 is crucial for the development of effective therapeutic strategies. Herein, utilizing state-of-the-art molecular docking algorithms and molecular dynamic (MD) simulations, substrates and inhibitors molecular binding with ABCG2 are defined, distinctly. We performed extensive virtual screening of Drugbank to identify the potential candidates, and MD simulations of docked complexes were carried out in POPC lipid bound membrane. Further, the binding affinities of compounds were estimated by free binding energy employing MM-GBSA. Docking results show three compounds, Docetaxel > Tariquidar > Tezacaftor having highest binding affinities (> 12.00 Kcal/mol) for ABCG2. Remarkably, MM-GBSA results suggest the most stable binding of Tariquidar with ABCG2 as compared to the other inhibitors. These results provide valuable insights into the key residues that may govern substrate/inhibitor recognition, shedding light on the molecular determinants influencing substrate specificity, transport kinetics and ABCG2-mediated drug efflux. Hence, Tariquidar could serve as a potential candidate for the design of highly efficient inhibitors targeting ABCG2 in breast cancer therapy.
Experimental Study on the Effects of Water Retaining Agents in Ecological Substrates on Soil Properties
Authors: Yang Xuanyu , Wang Yong 
Published: September 2024

Abstract

With the deepening of sustainable development concepts, vegetation protection has become the primary method for highway slope protection and has seen widespread application. Among these, the type and properties of substrate materials significantly affect the protective effectiveness, making it a core issue in vegetation protection. In arid regions, where rainfall is scarce and evaporation rates are high, water retention becomes a key focus in the study of ecological substrates. This study, focusing on the semi-arid regions of the Northern Hemisphere, investigates the effects of varying water-retaining agent content on soil water retention and mechanical behavior through laboratory evaporation tests and triaxial compression tests. By examining crack development during the evaporation process, the study reveals the micro-mechanisms by which water-retaining agents influence soil properties. The findings are as follows: (1) Water-retaining agents can effectively reduce the evaporation rate, with higher contents leading to slower evaporation and stronger soil water retention capacity; (2) The agents have little effect on the overall strength of the soil but primarily alter the soil’s deformation behavior, reducing cohesion while having minimal impact on the internal friction angle; (3) The hydrological properties of soils containing water-retaining agents are unstable and prone to cracking under dry conditions. Therefore, the content of water-retaining agents should be carefully calibrated according to the geotechnical properties of the protective slope, and in the early stages of ecological protection, surface evaporation prevention measures should be implemented to avoid surface cracking.
Genome wide association analysis revealed novel candidate genes for body measurement traits in indigenous Gudali and crossbred Simgud in Cameroon
Authors: Matenchi Youchahou Poutougnigni , Hegarty Matthew , Baștanlar Evren Koban 
Published: September 2024

Abstract

Background: The genetics of Central African cattle have not been well-explored in terms of their potential for improved productivity. We therefore performed a genome wide association analysis (GWAS) on a total of 856 animals genotyped with the GGP Bovine 100K array, to identify genes or genomic regions of importance in body measurements in a local zebu (Gudali) and its crossbreed with the European Simmental (Simgud), using mixed linear model (MLM).
Results: SNP-based heritability of the four body traits under study varied between 0.23 ± 0.12 for the height at wither (HAW) to 0.44 ± 0.11 for the sacrum height (SH). The genetic correlation ranged from 0.19 ± 0.14 between HAW and ear length (EL), to 0.81 ± 0.06 between HAW and SH. For the phenotypic correlation, the ranges were 0.58 ± 0.00 between body length (BL) and EL to 0.90 ± 0.06 between HAW and BL. The maximum LD was 0.465 for Gudali and decreased by half (0.23) at a distance of 50,708 bp, while for the Simgud population the maximum LD was 0.47 and decreased to half (0.23) at 99,201 bp. Interestingly, we observed long ranges of LD throughout the Gudali and Simgud genome up to more than 1 mbp distant. These features are of great potential interest in association analysis and genetic improvement initiatives. We identified 59 SNPs associated to body traits. These SNPs were mapped within or near some 189 genes throughout the genome, with the CDCA2, EBF2, ADGRD1, NDUFAF1, DPPA4 and DPPA2 genes showing a pleiotropic effect since they were found associated with 2 or more traits.
Conclusions: This study identified a number of novel genes/loci associated with pathways influencing growth and body traits, disease resistance and immunity, reproduction and milk production. Overall, the identified genes could be considered as candidate genes in any attempt to improve growth, disease resistance and production in tropical cattle managed under extensive conditions. These genes or genomic regions should be targeted for any future cattle breeding in Cameroon.
Identifying Key Predictive Variables in Medical Records Using a Large Language Model (LLM)
Authors: Veigulis Zachary P. , Ware Anna D. , Hoover Peter J. , Blumke Terri L. , Pillai Malvika , Yu Li , Osborne Thomas F. 
Published: September 2024

Abstract

EHR systems are widely used, but leveraging their unstructured clinical notes for insights has been challenging. Large Language Models (LLMs) can offer scalable, precise extraction of pertinent information from clinical notes. This paper presents a novel framework for using LLMs to derive medical insights from EHRs, demonstrated through an assessment on female infertility within the Veterans Health Administration (VHA), combining unstructured and structured data for enhanced analysis.
Seasonal variations in net ecosystem exchange of CO 2 and conservation of water use efficiency of cotton in the Mississippi Delta
Authors: Anapali Saseendran , Bhandari Ammar B. , Adireddy Rajanna , Reddy Krishna N. 
Published: September 2024

Abstract

Accurately quantifying the net ecosystem exchange of CO2 (NEE) is a critical prerequisite for developing alternative farm management strategies to enhance carbon sequestration in biological systems and reduce greenhouse gas emissions. A two-year study quantified the NEE of CO2 from cotton (Gossypium hirsutum L.) on silty clay in farm-scale fields using an eddy covariance approach (EC). On a seasonal scale, NEE and evapotranspiration (ET) were 8,836 kg CO2 ha− 1 and 367 mm, respectively, in 2017, and 10,759 kg CO2 ha− 1 and 430 mm, respectively, in 2018. Harvested cotton lint yields were 1,269 and 1,569 kg ha− 1 in 2017 and 2018, respectively. The water use efficiency (WUE) for lint production (WUElint) and ecosystem level WUE for NEE (WUENEE) across the two seasons was nearly constant. WUElint were 3.5 kg lint ha− 1 mm− 1 and 3.6 kg lint ha− 1 mm− 1, respectively, in 2017 and 2018, and WUENEE were 24 kg CO2 ha− 1 mm− 1 and 25 kg CO2 ha− 1 mm− 1. The NEE and WUE measured in this study can be used as a benchmark for comparing carbon sequestration potential in cotton production. However, further research is needed to understand NEE responses to long-term climate variability and to develop climate-smart crop-soil management strategies.
Assessment of Knowledge, Attitude and Practice towards Obesity among Medical Students in Jalalabad City, Afghanistan
Authors: Sherzad Abdul Ghafar , Shinwari Muhibullah , Zahirzai Mohammad Sediqe , Jabarkhil Abdul Nasir , Azimee Mohammad Azim , Mulavizada Habibullah , Zeng Qingchun 
Published: September 2024

Abstract

Background
Obesity is a global public health concern affecting individuals of all ages, sexes, and socioeconomic groups. It is generally linked to a greater risk of disability. Therefore, the present study aimed to determine the knowledge, attitudes, and practices of medical students toward obesity in Jalalabad city, Afghanistan.
METHODS
This institution-based, cross-sectional survey was conducted with 463 public and private medical university students in Jalalabad city, Afghanistan, from June 2023 to September 2023. The study participants were chosen via a nonprobability convenience sampling technique, and data were collected through structured questionnaires completed by all participants.
RESULTS
In this study, a total of 463 participants were enrolled. A total of 86.2% of them were male, and 13.8% were female. The majority (98.9%) had heard of term obesity. Body mass index (BMI) is the technique most commonly used to identify obesity. Ninety-five percent of the respondents were aware that obesity leads to cardiovascular diseases and diabetes mellitus. The participants’ attitudes toward obesity were satisfactory. Obesity was viewed as a disease by 86.6% and weight loss as a necessity by 99.1% of the participants. Only 24.6% of the respondents believed that obesity was inherited and could not be reduced. Among the respondents, 23.8% walked every day, and 28% participated in sports. Over half (53.6%) of the participants had never attempted to lose weight, and 43.2% reported eating junk food on a daily basis.
CONCLUSION
Most participants were aware of obesity and agreed that obesity is a serious health problem; however, they had inadequate practices compared with their knowledge and attitudes.
MLLM4Rec : Multimodal Information Enhancing LLM for Sequential Recommendation
Authors: Yuxiang Wang , Xin Shi , Xueqing Zhao 
Published: September 2024

Abstract

In recent years, With the advent of large language models (LLMs) such as GPT-4, LLaMA, and ChatGLM, leveraging multimodal information (e.g., images and audio) to enhance recommendation systems has become possible. To further enhance the performance of recommendation systems based on large language models (LLMs), we propose MLLM4Rec, a sequence recommendation framework grounded in LLMs. Specifically, our approach integrates multimodal information, with a focus on image data, into LLMs to improve recommendation accuracy. By employing a hybrid prompt learning mechanism combined with role-playing for model fine-tuning, MLLM4Rec effectively bridges the gap between textual and visual representations, enabling text-based LLMs to "read" and interpret images. Moreover, the fine-tuned LLM is utilized to rank retrieval candidates, thereby maintaining its generative capabilities while optimizing item ranking according to user preferences. Extensive experiments were conducted on three publicly available benchmark datasets to evaluate the proposed method. The results demonstrate that MLLM4Rec outperforms traditional sequence recommendation models and pre-trained multimodal models in terms of NDCG, MRR, and Recall metrics.
AutoML-based workflow for reliable DOE selection and reference studies for analyzing imprecise experimental data with machine learning
Authors: xu xukuan , li donghui , bi jinghou , Moeckel Michael 
Published: September 2024

Abstract

Design of experiments (DOE) is an established method to allocate resources for efficient parameter space exploration.Model-based active learning (AL) data sampling strategies have shown potential for further optimization. This paper introduces a workflow for conducting DOE comparative studies using automated machine learning. Based on a practical definition of model complexity in the context of ML, the interplay of systematic data generation and model performance is examined considering various sources of uncertainty: this includes uncertainties caused by stochastic sampling strategies, imprecise data, suboptimal modeling, and model evaluation. Results obtained from electrical circuit models with varying complexity show that not all AL sampling strategies outperform conventional DOE strategies, depending on the available data volume, the complexity of the dataset, and data uncertainties. Trade-offs in resource allocation strategies, in particular between identical replication of data points for statistical noise reduction and broad sampling for maximum parameter space exploration, and their impact on subsequent machine learning analysis are systematically investigated. Results indicate that replication-oriented strategiesshould not be dismissed but may prove advantageous for cases with non-negligible noise impact and intermediate resource availability.
A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry
Authors: Riley William , Li Zhen , Marschmann Gianna , Karaoz Ulas , Shirley Ian , Wu Qiong , Bouskill Nicholas , Chang Kuangyu , Crill Patrick , Grant Robert , King Eric , Saleska Scott , Sullivan Matthew , Tang Jinyun , Varner Ruth , Woodcroft Ben , Wrighton Kelly , Brodie Eoin 
Published: September 2024

Abstract

Microbes drive the biogeochemical cycles of earth systems, yet the long-standing goal of linking emerging genomic information, microbial traits, mechanistic ecosystem models, and projections under climate change has remained elusive despite a wealth of emerging genomic information. Here we developed a general genome-to-ecosystem (G2E) framework for integrating genome-inferred microbial kinetic traits into mechanistic models of terrestrial ecosystems and applied it at a well-studied Arctic wetland by benchmarking predictions against observed greenhouse gas emissions. We found variation in genome-inferred microbial kinetic traits resulted in large differences in simulated annual methane emissions, quantitatively demonstrating that the genomically observable variations in microbial capacity are consequential for ecosystem functioning. Applying microbial community-aggregated traits via genome relative-abundance-weighting gave better methane emissions predictions (i.e., up to 54% decrease in bias) compared to ignoring the observed abundances, highlighting the value of combined trait inferences and abundances. This work provides the first example of integrating microbial functional trait-based genomics, mechanistic and pragmatic trait parameterizations of diverse microbial metabolisms, and mechanistic ecosystem modeling. The generalizable G2E framework will enable use of abundant microbial metagenomics data to improve predictions of microbial interactions in many complex systems, including oceanic microbiomes.
Interactive connections between the claustrum and lateral parabrachial nucleus participate in the regulation of nociceptive information and accompanying negative emotions
Authors: Li Yun-Qing , Qiu Xin-Tong , Ren Xiao , Zhou Lu-Xi , Ye Xiao-Ni , Gong Tao , Li Yi-Yao , Li Fei , Pan Lv-La , Xing Ke-Ke , Chen Tao , Li Hui , Huang Fensheng , Zhang Ming-Ming 
Published: September 2024

Abstract

The claustrum (CLA) is a widely connected brain area associated with pain sensation, but the underlying mechanism remains elusive. Here, we demonstrate that the activation of CLA vesicular glutamate transporter-2 (VGluT2) neurons promotes nociceptive and anxiety-like behaviors, whereas parvalbumin (PV) neurons in the core of the CLA inhibit the functional activity of VGluT2 neurons. Morphologically, the VGluT2 neurons in the shell of the CLA reciprocally communicate with the VGluT2 neurons in the lateral parabrachial nucleus (LPB). Manipulation of the LPBVGluT2–CLAVGluT2 pathway, LPBVGluT2–CLAPV pathway and CLA–LPB glutamatergic pathway results in bidirectional modulation of pain and emotions. Pharmacogenetic activation of the LPBVGluT2–CLAVGluT2–LPBVGluT2 circuit facilitates nociception and negative emotions, and vice versa, alleviates hyperalgesia and anxiety-like behaviors. These findings illuminate that the CLA plays a vital role in pain perception and emotional impacts and provide crucial insight to help researchers unveil the functions of the CLA.