bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recombinant human gelatin: expression and characterization
Authors: Song Xiaoping , Chu Tao , Shi Wanru , He Jingyan 
Published: April 2024

Abstract

Gelatin is a product obtained through partial hydrolysis and thermal denaturation of collagen, belonging to natural biopeptides. It possesses irreplaceable biological functions in the field of biomedical science and tissue engineering, and has been widely applied. The amino acid sequence of recombinant human gelatin was constructed using a newly designed hexamer composed of six protein monomer sequences in series, with the minimum repeating unit being the characteristic Gly-X-Y sequence found in type III human collagen α1 chain. The nucleotide sequence was subsequently integrated into the genome of Pichia pastoris, leading to successful expression through fermentation. As a result, a recombinant human collagen with a purity exceeding 95% and an expression level of 0.95mg/mL was achieved. Molecular weight determination and amino acid analysis confirmed that the obtained recombinant gelatin had an identical amino acid composition to the one of theoretically designed. Furthermore, scanning electron microscopy revealed that the water-based gel formed by recombinant gelatin exhibited a porous structure. After culturing cells continuously within these gel microspheres for two days followed by fluorescence staining and observation using confocal laser scanning microscopy, it was observed that cells clustered together within the gel matrix, exhibiting three-dimensional growth characteristics while maintaining good viability. This research presents promising prospects for developing recombinant human gelatin as a
Increasing loneliness among children and adolescents from 2018 to 2022: A representative survey before and after the COVID-19 pandemic
Authors: Schütz Raphael , Bilz Ludwig 
Published: April 2024

Abstract

Background: Loneliness is an increasingly present topic in scientific and public discourse, and has gained relevance, especially due to the COVID-19 pandemic. Nevertheless, there is a lack of representative studies examining the prevalence of loneliness among children and adolescents before and after the pandemic. Accordingly, the present study aimed to determine the prevalence of loneliness among 11- to 15-year-old students before (2018) and after (2022) the onset of the COVID-19 pandemic and to investigate subgroup differences.
Methods: In this cross-sectional Health Behaviour in School-aged Children (HBSC) study, the prevalence of loneliness was compared in representative samples in the German federal state of Brandenburg from 2018 and 2022. In 2018, data were collected from 3,057 (51.8% girls, Mage= 13.1, SD = 1.7) and, in 2022, from 3,801 (52.6% girls, Mage= 13.5, SD = 1.6) students in general education schools in grades 5, 7, and 9. Loneliness was assessed using a single item from the Center for Epidemiologic Studies Depression Scale (CES-D). The chi-square test was used to determine bivariate correlations. To validate the bivariate results, we performed a logistic regression in which we also added interaction effects to test whether loneliness developed differently depending on gender, grade, and family affluence.
Results: In total, 11.8% of the students reported being lonely in 2018, and 19.3% reported being lonely in 2022. Loneliness was more prevalent among girls, nonbinary students, older adolescents, and students with lower family affluence. The increase in loneliness did not differ depending on age, gender, or family affluence.
Conclusion: The findings highlight that loneliness among German children and adolescents is a widespread phenomenon that has increased significantly since 2018. The sharp increase in loneliness clarifies the need for prevention measures and further research into health-related associations of loneliness.
Implications of TP-positive CAFs as a possible inducer of bone invasion in the pathogenesis of oral squamous cell carcinoma
Authors: Gao Aihua , Kim Dong Wook , Pei Meiling , Kim Ki-Yeol , Park Young-Jin , Nam Woong , Kim Hyung Jun , Cha In-Ho , Zhang Xianglan 
Published: April 2024

Abstract
Objectives Recently, cancer-associated fibroblasts (CAFs) have been suggested as key cellular components of bone invasion in oral squamous cell carcinoma (OSCC). However, the underlying molecular mechanisms, as well as the subtypes related to their bone invasive function, are largely unknown. In this study, we aimed to investigate the implications of thymidine phosphorylase (TP)-positive CAFs (TP+CAFs) in OSCC bone invasion.Materials and Methods TP expression was determined in 116 patients with OSCC using immunohistochemistry. The influence of TP expression on the biological behavior of CAFs was investigated in vitro. The possible impact of TP+CAFs on bone invasion in OSCC was further evaluated using patient-derived xenograft (PDX) mouse models.Results In bone-invasive OSCC tissues, we found that TP+CAFs were mainly distributed on the surface of resorbed bone tissue rather than on the tumor side. High TP+CAFs were significantly associated with higher T-stage (p = 0.002) and bone invasion (p < 0.001), as well as worsened overall survival (p = 0.013) and recurrence-free survival (p = 0.029), in our study cohort. Multivariate analysis using variable clinicopathologic factors—with tumoral TP and TP+CAFs as cofactors—revealed that high TP+CAFs (hazard ratio: 3.140; p = 0.005) had independent impacts on worsened recurrence-free survival. Recombinant human TP promoted the proliferative and invasive abilities of CAFs and increased matrix metalloproteinase-9 mRNA expression in vitro, which is related to bone resorption. In the PDX mouse models, TP+CAFs were found in early bone resorption on the surface of resorbed bony tissues. Moreover, bone resorption occurred more frequently in the PDX models with TP+CAFs than in those without.Conclusion TP+CAFs were significantly associated with bone invasion and the prognosis of OSCC. This study provides information about cellular and molecular targets for the early diagnosis and treatment of bone-invasive OSCC.
PCR-positive meningococcal CSF infection without pleocytosis but high IL-6 and IL-8
Authors: Dyckhoff-Shen Susanne , Pfister Hans-Walter , Koedel Uwe , Klein Matthias 
Published: April 2024

Abstract

Background
Meningococcal meningitis is still a severe disease causing high mortality and morbidity rates. Early diagnosis is crucial to ensure prompt antibiotic therapy. However, identification of the pathogen can be challenging.
Case presentation
: A 32-year-old male patient with systemic lupus erythematosus (SLE) presented to the emergency room with fever, nausea, vomiting, headache and lower back pain as well as multiple petechial bleedings. On suspicion of meningococcal infection, the emergency doctor had already administered one dose of ceftriaxone before arrival to the clinic. Blood works showed massive inflammation due to bacterial infection. Cerebrospinal fluid (CSF) analysis showed normal cell count, protein and glucose levels but PCR was positive for Neisseria meningitis and IL-6 as well as IL-8 were elevated. On antibiotic therapy with ceftriaxone, the patient’s condition improved quickly.
Conclusions
We present a rare case of meningococcal infection of the CSF in a SLE patient without further CSF abnormalities. We discuss the involvement of early antibiotic treatment and the role of the patient’s immune status in the normal CSF findings of this case. Moreover, this case demonstrates the importance of early antibiotic therapy in bacterial meningitis for the clinical outcome.
Assessing the relationship between gut microbiota ( family, orders, classes,and phyla) and gestational diabetes mellitus : a two-sample Mendelian randomization analysis
Authors: Tong Yan , liu zhao xia , weng shiqi , zhou yan , wu bo , wang xiaohong , hu hui , xiao qin , tan xiao , lai zhiqing 
Published: April 2024

Abstract
Background
Previous studies have shown that gut microbiota (GM) are associated with gestational diabetes mellitus (GDM). Although it is unclear if the association is causative. This study used Mendelian randomization (MR) to systematically examine whether the gut microbiota was causally linked to GDM .There have been numerous Mendelian randomization (MR) studies that between the gut microbiota abundance (genus) and gestational diabetes mellitus (GDM). However, the gut microbiota abundance(family, orders, classes,and phyla)have yet to be fully investigated.This study used Mendelian randomization (MR) to systematically examine whether several gut microbiota taxa was causally linked to GDM.
Methods
Genetic instrumental variables for the gut microbiota were identified from a genome-wide association study (GWAS) involving 14306 participants. Summary statistics for gestational diabetes mellitus(GDM)were drawn from another GWAS, which included 6033 cases and 110330 controls.Maximum likelihood (ML), MR-Egger regression, weighted median, inverse variance weighted(IVW), and weighted model were used to investigate the causal association between gut microbiota and GDM. To examine the causal association, several methods were utilized, including inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS. We further conducted a series of sensitivity analyses to confirm the robustness of the primary results of the MR analyses.Reverse MR analysis was performed on the bacterial taxa that were reported to be causally linked to GDM risk in forwarding MR analysis to evaluate the possibility of reverse causation. Furthermore, sensitivity analyses were performed to identify any potential heterogeneity and horizontal pleiotropy.
Results
MR analysis revealed that phylum Tenericutes (OR: 0.717 95%CI: 0.573–0.896, P = 0.003), class Mollicutes (OR: 0.717, 95%CI: 0.573–0.896, P = 0.003)were related to a lower risk of GDM, and family Lactobacillaceae(OR: 1.303, 95%CI: 1.001–1.697, P = 0.049)were positively associated with the risk of GDM. Additional sensitivity analyses confirmed the robustness of the association between specific gut microbiota composition and GDM. In the reverse Mendelian randomization (MR) analysis, we did not find evidence that these was statistically significant associations between GDM and these three bacterial traits.
Conclusions
Our systematic analysis provides evidence to explore the causal associations among GM and GDM. More studies are needed to clarify how the gut microbiota(family, orders, classes,and phyla) affects the development of GDM.
Drivers of carbon stocks in Araucaria forests
Authors: Cysneiros Vinicius Costa , Pelissari Allan Libanio , Filho Afonso Figueiredo 
Published: April 2024

Abstract

Background Understanding the drivers of variations in carbon stocks is essential for developing the effective management strategies that contribute to mitigating climate change. Although a positive relationship between biodiversity and the aboveground carbon (AGC) has been widely reported for various Brazilian forest types, representing a win–win scenario for climate change mitigation, this association has not been commonly found in Brazilian subtropical forests. Therefore, in the present study, we aimed to evaluate the effects ofAraucaria angustifoliapopulations, stand structure and species diversity in shaping AGC stocks in Brazilian subtropical mixed forests. We hypothesized that the effects on the AGC of stand structure and diversity would be mediated byA. angustifolia. We also evaluated the expectation of higher carbon stocks in protected forests as a result of their positive correlation with biodiversity conservation. Results We found that stand structure, followed byA. angustifoliapopulation, played the most important role in shaping the AGC stock. Our hypothesis was partially confirmed, the direct and indirect effects ofA. angustifoliaon stand structure being found to have shaped the AGC. Similarly, our expectation was partially supported, with the higher AGC in the protected area being related not to diversity, but rather to the presence of larger trees, denser stands, and a greater abundance ofA. angustifolia. Conclusion Although the win–win strategy between diversity conservation and carbon storage is not a peculiarity of Araucaria forests, we highlight the potential of these forests as a nature-based climate solution, maintaining high levels of carbon storage in harmony with the provision of keystone resources.
Cell Escape Probabilities for Markov Processes on a Grid
Authors: Ingelaere T. , Maes V. , Samaey G. 
Published: April 2024

Abstract

Kinetic equations describe physical processes in a high-dimensional phase space and are often simulated using Markov process-based Monte Carlo routines. The quantities of interest are typically defined on the lower-dimensional position space and estimated on a grid (histogram). In several applications, such as the construction of diffusion Monte Carlo-like techniques and variance prediction for particle tracing Monte Carlo methods, the cell escape probabilities, i.e., the probabilities with which particles escape a grid cell during one step of the Markov process , are of interest. In this paper, we derive formulas to calculate the cell escape probabilities for common mesh elements in one, two, and three dimensions. Deterministic calculation of cell escape probabilities in higher dimensions becomes expensive and prone to quadrature errors due to the involved high-dimensional integrals. We therefore also introduce a stochastic Monte Carlo algorithm to calculate the escape probabilities, which is more robust at the cost of a statistical error. The code used to perform the numerical experiments and accompanying GeoGebra tutorials are openly available at https://gitlab.kuleuven.be/numa/public/escape-probabilities-markov-processes.
Robust Visual-based Method and New Datasets for Ego-lane Index Estimation in Urban Environment
Authors: Wang Dianzheng , Liang Dongyi , Li Shaomiao 
Published: April 2024

Abstract

Correct and robust ego-lane index estimation is crucial for autonomous in the absence of high-definition maps, especially in urban environments. Previous ego-lane index estimation approaches rely on feature extraction, which limited the robustness. To overcome these shortages, this study proposes a robust ego-lane index estimation framework upon only the original visual image. After optimization of processing route, the raw image was randomly cropped in height direction and then input into double supervised LaneLoc network to obtain the index estimations and confidences. A post process was also proposed to achieve the global ego-lane index from the estimated left and right indexes with total lane number. To evaluate our proposed method, we manually annotated the ego-lane index of public datasets which can work as an ego-lane index estimation baseline for the first time. The proposed algorithm achieved 96.48%/95.40% (precision/recall) on CULane dataset and 99.45%/99.49% (precision/recall) on TuSimple dataset, demonstrating the effectiveness and efficiency of lane localization in diverse driving environments. The code and datasets annotation results will be exposed publicly on https://github.com/haomo-ai/LaneLoc.
Post-earthquake rapid seismic demand estimation at unmonitored locations via Bayesian networks
Authors: Mesbahi Pooria , García-Macías Enrique , Breccolotti Marco , Ubertini Filippo 
Published: April 2024

Abstract

Post-earthquake safety assessment of buildings and infrastructure poses significant challenges, often relying on time-consuming visual inspections. To expedite this process, safety criteria based on a demand-capacity model are utilized. However, rapid assessment frameworks require accurate estimations of intensity measures (IMs) to estimate seismic demand and assess structural health. Unfortunately, post-earthquake IM values are typically only available at monitored locations equipped with sensors or monitoring systems, limiting broader assessments. Simple spatial interpolation methods, while possible, struggle to consider crucial physical factors such as earthquake magnitude, epicentral distance, and soil type, leading to substantial estimation errors, especially in areas with insufficient or non-uniform seismic station coverage. To address these issues, a novel framework, BN-GMPE, combining a Bayesian network (BN) and a ground motion prediction equation (GMPE), is proposed. BN-GMPE enables inference and prediction under uncertainty, incorporating physical parameters in seismic wave propagation. A further novelty introduced in this work regards the separation of the near and far seismic fields in the updating process to attain a clearer understanding of uncertainty and more accurate IM estimation. In the proposed approach, a GMPE is employed for the estimation, and the bias and standard deviation of the prediction error are updated after any new information is entered into the network. The proposed method is benchmarked against a classic Kriging interpolator technique, considering some recent earthquake shocks in Italy. The proposed BN framework can naturally extend for estimating the probability of failure of various structures in a targeted region, which represents the ultimate aim of this research.
Research on the revenue prospect for energy storage participation in electricity spot and FM auxiliary service markets —Considering capacity market mechanisms
Authors: Hu Junfeng , Zhao Qianqian , Zhang Deyu , Chang Mingxuan 
Published: April 2024

Abstract
The vigorous development of energy storage is significant in supporting new energy consumption and enhancing the power system regulation capability. The spot and auxiliary service markets are the core ways for energy storage to realize commercial value. This paper establishes a revenue prediction model for energy storage participation in the electricity spot and FM auxiliary service market from the perspective of the revenue outlook of energy storage investment, including electric energy spot revenue, spot response incentive revenue considering capacity market price, and FM capacity revenue and FM mileage revenue. Specifically, the BP neural network prediction model, the FM clearing prediction model, and the capacity market supply and demand model are used to combine a variety of influencing factors to predict the spot price spread of electric energy, the FM mileage price, and the capacity price, which are then solved by substituting other parameters into the model. The results show that the method proposed in this paper is favorable for energy storage investment cost recovery and has good economics.
Is the isolated bone change in advanced colorectal cancer a necessarily malignant metastasis? A case series
Authors: Sun Xin , Yang Xiaomei , Chen Wenjuan , Chen Juan , Qu Xiujuan , Qu Jinglei , Chen Ying 
Published: April 2024

Abstract
Radiation osteitis (RO) is one of the bone complications arising after radiotherapy (RT). Limited to atypical manifestation in imaging. RO is difficult to diagnose, and sometimes, it could be considered as an early bone metastasis (BM), resulting in improper treatment. Thus, it’s vital to provide reliable evidence to clarify the isolated bone changes. Herein, we reported two advanced colorectal cancer (CRC) patients with atypical, isolated bone change in imaging, and both had underwent postoperative chemotherapy and radiotherapy. After medical imaging and clinical laboratory tests, the isolated bone change was finally confirmed to be RO rather than BM. The case series presented precision assessment for differentiating RO from BM, which may change the treatment strategy of this subgroup of patients.
Keywords: Radiation osteitis, radiotherapy, pelvis, diagnosis, bone metastasis.
Identification and Track Improvement of Transmission Line Faults Using One Dimensional Complicated Neural Networks
Authors: Dhara Saumen , Shrivastav Alok Kumar , Sadhu Pradip Kumar , Datta Rudrajit , Naskar Shantanu 
Published: April 2024

Abstract

This paper focuses one dimensional-convolution neural networks (1D-CNN) with a snappy adaptive architecture to prevent fault removal complications and categorization into a computational analytics system by introducing a fast and consistent algorithm for fault identification, categorization, and instructions for transmission networks. The proposed algorithm can be implemented directly to source data, eliminating the need for a separate removal step and leading in a more powerful protected approach. The proposed approach related to the 3-phase voltages and currents at the relay position within the electric power line framework is considered as feedback for the recommended 1D-CNN algorithm. In order to provide the training and test statistics for the anticipated 1D-CNN approach, a 133 kV grid connected line is simulated using MATLAB/SIMULINK software. The suggested algorithm's test precision is contrasted with two additional neural and fuzzy neural network (FNN) standard techniques. The numerical outcomes of the test show that, in comparison to other conventional methods under several fault situations, the suggested diagnostic device is fast and efficient for categorizing and controlling the discrepancy of transmission line fault with greater accuracy.
Molecular investigation of ticks and tick-borne protozoan parasites (Apicomplexa: Cytauxzoon and Hepatozoon spp.) from Eurasian lynx (Lynx lynx) in northwestern China: first identification of Cytauxzoon manul in this host species
Authors: Cui Nannan , Su Lixin , Wang Ziqi , Hornok Sándor , Tang Lijuan , Yang Meihua , Zhang Yujiang , Zhao Guoyu , Wang Yuanzhi 
Published: April 2024

Abstract
Background: Multiple species of the genera Cytauxzoon and Hepatozoon can infect wild felines, but the diversity of these and other apicomplexan parasites in Eurasian lynx is scarelyknown. The aim of this study was to detect Cytauxzoon and Hepatozoon species with molecular methods in Eurasian lynxes and their ticks in northwestern China.
Methods: DNA was extracted from the heart, liver, spleen, lung and kidney samples of three Eurasian lynxes as well as from their five ixodid ticks. These DNA samples were screened with PCRs for Cytauxzoonwith the partial cytochrome b gene (CytB), cytochrome c oxidase subunit I gene (COI) and small subunit ribosomal RNA gene (18S rRNA), and Hepatozoon with three different fragments of small subunit ribosomal RNA gene (18S rRNA). PCR products were sequenced, aligned and phylogenetically analyzed.
Results: One adult female of Eurasian lynx (#1, adult female) was co-infected with Cytauxzoon manul and Hepatozoon felis genotype I, while an adult male lynx (#2) was infected with C. manul. Interestingly, H. felis genotype I was both detected in a male cub (#3) and two out of five infesting Hyalomma asiaticum ticks.
Conclusion: For the first time, Cytauxzoon manul is reported here from Eurasian lynx. In addition, H. felis has not been known to occur in this host species in China and Central Asia. Thus, findings of this study extend our knowledge on the geographical distribution and host range of these haemoprotozoan parasites. Moreover, this is also the first evidence of C. manul and H. felisco-infection in Eurasian lynx.