bluuebunny/crossref_metadata_2025 huggingface dataset:
Abnormally Low HbA1c Caused by Hemolytic Anemia, a Case Report and Literature Review
Authors: Bakhtiari Sajjad , Timbrell Nathan E. , D’Almeida Sènan M.
Published: January 2025

Hemoglobin A1c is a widely used diagnostic tool for monitoring glycemic control in diabetes management. However, its accuracy can be influenced by various factors. We present a case of a 17-year-old boy with abnormally low Hemoglobin A1c levels caused by warm autoantibody-induced hemolytic anemia. This case highlights the importance of considering conditions that may affect erythrocyte survival, and the potential interferences when interpreting Hemoglobin A1c results to ensure accurate diagnosis and effective management of diabetes.
The manipulation of odor availability of training aids used in detection canine training
Authors: Sloan Katylynn B. , Maughan Michele N. , Sharpes Caitlin E. , Greubel Robin R. , Gallegos Shawna F. , Miklos Aleksandr E. , Waldrop Lindsay D.
Published: January 2025

Detection canines can identify numerous substances for which they have been trained. Historically, and a point of ongoing contention, detection canine threshold (i.e., sensitivity or limit of detection) training has primarily focused on changing the weight of the training aid substance used. There has been minimal focus on other principles, such as surface area, confinement, and temperature, which can be manipulated to affect odor availability. That said, trainers have been manipulating odor availability for years without necessarily understanding the governing scientific principles. The aim of this review is to highlight the principles that control odor availability of a substance and how an end user can apply these principles for operational detection canine training needs.
Sensitivity analysis of a mathematical model for malaria transmission accounting for infected ignorant humans and relapse dynamics
Authors: Haile Getahun Tadesse , Koya Purnachandra Rao , Mosisa Legesse Fekadu
Published: January 2025

This article presents and analyzes a deterministic model for malaria transmission that incorporates infected individuals who are unaware of their infectious status (ignorant infected humans) and accounts for relapse dynamics. We explore the invariant region and positivity of the model and calculate the effective reproduction number using the next-generation matrix method. We demonstrate the local and global stability of disease-free equilibrium points using the Routh-Hurwitz criterion and Lyapunov function, respectively. The proposed model shows that a disease-free equilibrium point is globally asymptotically stable when the basic reproduction number Re < 1. We conducted a sensitivity analysis on the effective reproduction number to identify which basic parameter most significantly influences the increase or decrease of malaria cases. This study focuses on individuals who have been treated and cured but continue to carry dormant Plasmodium parasites in their blood, which can potentially cause relapse or reinfection. Additionally, we introduce a protected compartment to carefully evaluate how preventive measures influence the spread and persistence of malaria within the population.
A robust, exponentially fitted higher-order numerical method for a two-parameter singularly perturbed boundary value problem
Authors: Agmas Adisie Fenta , Gelu Fasika Wondimu , Fino Meselech Chima
Published: January 2025

This study constructs a robust higher-order fitted operator finite difference method for a two-parameter singularly perturbed boundary value problem. The derivatives in the governing ordinary differential equation are substituted by second-order central finite difference approximations, after which the fitting parameter is introduced and determined. The resulting system of linear equations may then be solved using the Thomas method. The stability, consistency, and convergence of the current method have been thoroughly validated. To enhance accuracy and achieve a higher-order numerical solution, a post-processing technique was employed to upgrade the method from second-order to fourth-order convergence. Finally, three test examples were used to confirm the method's appropriateness. The numerical results demonstrate that the proposed technique is stable, consistent, and produces a higher-order numerical solution than the existing ones in the literature.
Estimated genetic trends in the lysine requirements of growing-finishing pigs and reproductive sows due to genetic trends in production traits
Authors: Knap Pieter W.
Published: January 2025

The requirements for standardized ileal digestible (SID) lysine due to lean tissue growth rate (LTGR) in growing-finishing pigs were quantified on the basis of data from the literature. The same was done for those requirements due to LTGR; protein deposition in mammary tissue, uterine tissue, fetal tissue and placental tissue; and colostrum and milk protein synthesis in gestating and lactating sows. These processes were expressed in terms of LTGR, litter size, piglet birth weight, preweaning survival rate, litter weaning weight and teat number. The 2013--2023 genetic trends of those traits in the PIC-L02, PIC-L03, PIC-L65 and PIC-L800 populations were estimated and converted to genetic trends in lysine requirements. On this basis, the daily SID lysine requirement of Camborough (i.e., PIC-L02 × PIC-L03) sows increases by 0.47 g/d (i.e., by 2% of the current mean level) per year: 0.10 g/d per year and 0.37 g/d per year for gestational and lactational processes, respectively. The daily SID lysine requirement of growing-finishing progeny of Camborough sows and either PIC-L65 or PIC-L800 boars increases by 0.09 g/d (i.e., by 0.6% of the current mean level) per year.
Microfluidic organ-on-chip systems for periodontal research: advances and future directions
Authors: Sriram Gopu , Makkar Hardik
Published: January 2025

Advances in tissue engineering and microfluidic technologies have enabled the development of sophisticated in vitro models known as organ-on-a-chip (OoC) or microphysiological systems. These systems enable to potential to simulate the dynamic interactions between host tissues and their microenvironment including microbes, biomaterials, mechanical forces, pharmaceutical, and consumer-care products. These fluidic technologies are increasingly being utilized to investigate host-microbe and host-material interactions in oral health and disease. Of interest is their application in understanding periodontal disease, a chronic inflammatory condition marked by the progressive destruction of periodontal tissues, including gingiva, periodontal ligament, and alveolar bone. The pathogenesis of periodontal disease involves a complex interplay between microbial dysbiosis and host immune responses, which can lead to a loss of dental support structures and contribute to systemic conditions such as cardiovascular disease, diabetes, and inflammatory bowel disease. This provides a comprehensive overview of the latest developments in millifluidic and microfluidic systems designed to emulate periodontal host-microbe and host-material interactions. We discuss the critical engineering and biological considerations in designing these platforms, their applications in studying oral biofilms, periodontal tissue responses, and their potential to unravel disease mechanisms and therapeutic targets in periodontal disease.
Effects of different warm-up methods on 50-meter breaststroke swimming performance
Authors: Lee Hsuan-Yen , Chao Te , Hsu Chi-Chieh , Chang Ning-Wei , Chen Yi-Liang , Tsai Yung-Shen
Published: January 2025

Purpose

To examine the effects of different warm-up methods on 50 m breaststroke performance in both breaststroke specialists and individual medley swimmers.

Methods

18 swimmers (breaststroke group: 9, individual medley group: 9) who met the qualification standards for the National Intercollegiate Athletic Games participated in this study. Each participant completed four different warm-up protocols (a conventional 1,400 m warm-up and a 700 m conventional warm-up that integrated tubing-assisted (TA), paddle (PD), or squat (SQ) warm-ups) over four separate days. Following each warm-up protocol, a 50 m breaststroke performance test was conducted with inertial measurement unit (IMU) sensors attached to specific body segments to evaluate and compare stroke performance, stroke length, stroke frequency, and the acceleration of the hands, sacrum, and feet across different warm-up methods.

Results

The breaststroke specialists who performed the TA warm-ups recorded significantly less time than those who performed the conventional 1,400 m warm-ups (35.31 ± 1.66 s vs. 35.67 ± 1.83 s, p = 0.006). There was a trend that individual medley specialists who performed the SQ warm-ups recorded less time than those who performed the PD warm-ups (34.52 ± 1.45 s vs. 34.92 ± 1.46 s, p = 0.043). The stroke length of breaststroke specialists following the TA warm-ups was shorter than that following the PD warm-ups, the SQ warm-ups, and the conventional 1,400 m warm-ups. Breaststroke specialists who engaged in the TA warm-ups had higher stroke frequency than those who engaged in the conventional 1,400 m warm-ups, the SQ warm-ups, and the PD warm-ups. During the TA warm-ups, breaststroke specialists exhibited a shorter stroke length and a higher stroke frequency than individual medley specialists. Acceleration data from the center of mass and limb segments, recorded by IMUs, were insufficient to fully explain the variations in stroke frequency, stroke length, and overall performance caused by the different warm-up protocols.

Conclusion

Breaststroke specialists exhibited significant improvement in their 50 m breaststroke performance after the TA warm-up. By contrast, individual medley specialists benefited more from the SQ warm-up.
Collaborative stress of concrete-filled steel tube tied-arch beam-column support based on the double-layer elastic foundation beam theory
Authors: Tong Jiazhu , Wang Hang , Xu Dalian , Tian Changjin
Published: January 2025

The construction of concrete-filled steel tube tied-arch bridges typically employs the “beam first and arch later” methodology. In this approach, tie beams are initially constructed on temporary supports, followed by the erection of the arch ribs. When post-construction loads—such as those from arch-rib supports and concrete-filled steel tubes—are applied, a synergistic force phenomenon occurs between the tie beam and temporary supports, which collectively bear these loads. To investigate the collaborative-force mechanism of the tie beam during construction, we developed a collaborative-force model based on Winkler’s double-layer elastic foundation beam theory. We derived equations for displacement, rotation angle, bending moment, and shear force of the tie beam under concentrated loads. Using a 72-m concrete-filled steel tube arch bridge as our research subject, we conducted a comparative analysis utilizing finite element methods. The results indicated that our derived formulas were consistent with those obtained through finite element meta-computing techniques. Under concentrated loading conditions, it was observed that the load increment at the location of the steel pipe column in the Bailey beam was significantly larger than what traditional averaging methods would predict. Conversely, load increments at both mid-span and pier locations of the Bailey beam were relatively small. Furthermore, it was found that variations in concrete strength grade had minimal impact on displacement, bending moment, and bearing ratio for both tie beams and Bailey beams. However, factors such as cross-sectional height of the tie beam and arrangement of sandwich buckle frames exerted considerable influence on both displacement and load-bearing ratios for these structural elements. Additionally, while arrangements within Bailey beams significantly affected displacements in both types of beams (tie beam and Bailey beam), their impact on bending moments and bearing ratios was comparatively less pronounced.
Pandemic one health clones of Escherichia coli and Klebsiella pneumoniae producing CTX-M-14, CTX-M-27, CTX-M-55 and CTX-M-65 ESβLs among companion animals in northern Ecuador
Authors: Gonzales-Zubiate Fernando A. , Tambor José Humberto M. , Valencia-Bacca Juan , Villota-Burbano María Fernanda , Cardenas-Arias Adriana , Esposito Fernanda , Moura Quézia , Fuga Bruna , Sano Elder , Pariona Jesus G. M. , Jacome Mishell Poleth Ortiz , Lincopan Nilton
Published: January 2025

From a One Health perspective, dogs and cats have begun to be recognized as important reservoirs for clinically significant multidrug-resistant bacterial pathogens. In this study, we investigated the occurrence and genomic features of ESβL producing Enterobacterales isolated from dogs, in the province of Imbabura, Ecuador. We identified four isolates expressing ESβLs from healthy and diseased animals. In this regard, two Escherichia coli strains producing CTX-M-55-like or CTX-M-65 ESβLs belonged to the international ST10 and ST162, whereas two Klebsiella pneumoniae producing CTX-M-14 or CTX-M-27 belonged to ST35 and ST661. Phylogenomic analysis clustered (95-105 SNP differences) CTX-M-55/ST10 E. coli from companion animal with food and human E. coli strains of ST10 isolated in 2016, in Australia and Cambodia, respectively; whereas CTX-M-27-positive K. pneumoniae ST661 was clustered (201-216 SNP differences) with human strains identified in Italy, in 2013 and 2017, respectively. In summary, we report the presence and genomic data of global human-associated clones of CTX-M-producing E. coli and K. pneumoniae in dogs, in Ecuador. The implementation of a national epidemiological surveillance program is necessary to establish future strategies to control the dissemination of antibiotic-resistant priority pathogens using a One Health approach.
Antibodies directed against bacterial antigens in sera of Polish patients with primary biliary cholangitis
Authors: Bauer Alicja , Habior Andrzej
Published: January 2025

Background

Primary biliary cholangitis (PBC) is a cholestatic, autoimmune liver disease with the presence of characteristic autoantibodies. The aim of the work was to determine the level of antibodies directed against bacterial antigens: Chlamydia pneumoniae (anti-Cpn), Yersinia enterolitica (anti-Y.e), Helicobacter pylori (anti-Hp), Mycoplasma pneumoniae (anti- Mp.) and Escherichia coli (E.coli) in sera of PBC patients. We also performed in vitro studies on the impact of the bacterial peptides on the specific antigen-antibody binding.

Method

We screened 92 Polish PBC patients and sera samples from healthy donors and pathological controls. Autoantibodies and anti-bacterial antibodies were determined by commercially available ELISA kits. Specific inhibition of antibody binding was also detected by the in house ELISA method.

Results

Anti-Cpn, anti-Y. enterolitica, anti-Hp, anti-M. pneumoniae and anti-E. coli antibodies were significantly more common in the group of PBC patients than in the pathological and healthy control groups: 74%, 40%, 84%, 39% and 69% respectively. The mean level of anti-Cpn, anti- Y.e, anti-Hp and anti- M.p in the PBC group was significantly higher than those in the healthy group (p < 0.001). and in patients with other liver diseases. In sera of patients with the presence of positive anti-mitochondrial antibodies (AMA), specific for PBC, anti-bacterial antibodies have been found in 80% vs. 50% in sera with AMA negative. We observed inhibition of specific antigen-antibody binding by the bacterial peptide: EClpP (E. coli caseinolytic protease) and adenine glycosylase from E. coli caseinolytic protease P, ClpP Y.e from peptide of Y. enterolitica, Mp PDC from M. pneumonia peptide and adenine glycosylase of E. coli. Bacterial factors influence the specific binding of antibodies to pyruvate dehydrogenase (PDC-E2), gp210 and KLHL12 (kelch-like peptide 12) antigens.

Conclusion

Microbial mimics may be the major targets of cross-reactivity with human pyruvate dehydrogenase, gp210, and KLHL12 in PBC.
Metagenomic next-generation sequencing for the clinical identification of spinal infection-associated pathogens
Authors: Shi Tengfei , Lin Yuhan , Zheng Xuexin , Ruan Hongliang , Zhang Rui , Liu Yinhuan , Xu Shaohan , Wang Huafeng
Published: January 2025

Background

This study aimed to evaluate the efficacy of metagenomic next-generation sequencing (mNGS) technology for identifying pathogens associated with spinal infection (SI).

Methods

A retrospective analysis was conducted on clinical data from 193 patients with suspected SI between August 2020 and September 2024. Based on histopathological results, the patients were divided into the SI group (n=162) and the non-SI group (n=31). The diagnostic performance of mNGS technology was compared with that of laboratory examination, imaging examination, and microbial culture.

Results

Among SI group, mNGS detected 135 pathogens in 77.78% (126/162) of the cases, including nine cases of multiple infections. One or more pathogens were detected using mNGS in 86 patients with SI and negative microbial cultures. Staphylococcus aureus (22.22%, n=30) and Mycobacterium tuberculosis (22.22%, n=30) were the major pathogens, while various rare pathogens such as anaerobes, Brucella, and Coxiella burnetii were also detected. For the 40 cases with positive results for both culture- and mNGS-based identification, high consistency (77.50%) was observed. Antibiotic use did not significantly affect the mNGS detection rate (P = 0.45). There was no significant difference in the positivity rate of mNGS between CT-guided needle biopsy (80.00%) and surgical sampling (77.17%) (P = 0.72). The sensitivity of mNGS (77.78%) was significantly higher than that of traditional microbial culture (27.16%), and the specificity was similar (90.32% vs. 96.77%). Although the sensitivities of erythrocyte sedimentation rate-based assay (91.36%), magnetic resonance imaging (88.27%), and C-reactive protein-based assay (87.65%) were better than those of mNGS, their specificities were generally low (20%-40%).

Conclusion

The pathogens responsible for SI are complex and diverse. As a novel diagnostic method, mNGS exhibits a high sensitivity and extensive pathogen coverage for SI diagnosis. When combined with imaging and laboratory indicators, mNGS can significantly improve the accuracy of SI diagnosis and provide strong support for clinical treatment.
The role of metagenomic next-generation sequencing in diagnosing and managing post-kidney transplantation infections
Authors: Wu Hao , Cao Hongliang , Gao Xin , Shi Chengdong , Wang Lei , Gao Baoshan
Published: January 2025

Kidney transplantation (KT) is a life-saving treatment for patients with end-stage renal disease, but post-transplant infections remain one of the most significant challenges. These infections, caused by a variety of pathogens, can lead to prolonged hospitalization, graft dysfunction, and even mortality, particularly in immunocompromised patients. Traditional diagnostic methods often fail to identify the causative organisms in a timely manner, leading to delays in treatment and poorer patient outcomes. This review explores the application of metagenomic next-generation sequencing (mNGS) in the diagnosis of post-KT infections. mNGS allows for the rapid, comprehensive detection of a wide range of pathogens, including bacteria, viruses, fungi, and parasites, without the need for culture-based techniques. We discuss the advantages of mNGS in early and accurate pathogen identification, its role in improving patient management, and the potential challenges in its clinical implementation. Additionally, we consider the future prospects of mNGS in overcoming current diagnostic limitations and its potential for guiding targeted therapies, particularly in detecting antimicrobial resistance and emerging pathogens. This review emphasizes the promise of mNGS as an essential tool in improving the diagnosis and treatment of infections in KT recipients.
Rising prevalence and drug resistance of Corynebacterium striatum in lower respiratory tract infections
Authors: Li Wei , Gao Mingyue , Yu Jinyan
Published: January 2025

Corynebacterium striatum (C. striatum) is a Gram-positive bacterium commonly colonizing the skin and mucosa in healthy individuals and hospitalized patients. Traditionally regarded as a contaminant, C. striatum is now increasingly recognized as a potential cause of clinical infections, especially after the coronavirus disease pandemic. It has emerged as a pathogen implicated in severe infections, including pneumonia, bacteremia, meningitis, artificial joint infections, abdominal infections, and endocarditis. C. striatum has been reported in lower respiratory tract infections, mostly as a conditioned pathogen in immunocompromised individuals, particularly in those with chronic structural lung diseases, such as chronic obstructive pulmonary disease, leading to severe pneumonia or exacerbation of the existing disease and high mortality. Additionally, C striatum has been implicated in the community-acquired pneumonia among immunocompetent individuals and nosocomial lung infections, with evidence of person-to-person transmission through caregivers. C. striatum may exhibit multidrug resistance. Vancomycin, alone or in combination, is currently considered the most effective treatment for C. striatum. This review highlights the epidemiological characteristics, drug resistance mechanisms, diagnostics approaches, and treatment options for C. striatum lower respiratory tract infections to enhance clinician awareness and improve patient management strategies.
Experimental study on the correlation between pore evolution characteristics and seepage flow of loaded lignite
Authors: Zhang Xi , Ma Yankun , Hu Mingye , Zhao Aohan , Yang Wenwang
Published: January 2025

The pressure on coal affects the pore fracture structure, altering the seepage characteristics of fluids such as gas or water. A special pseudo-triaxial loading nuclear magnetic gripper was used for uniaxial compression testing of the coal body. The T2 map of the lignite was tested online, and MRI imaging was performed. The correlation between the pore fracture structure evolution and seepage characteristics of lignite was studied. The results show that (1) there are three stages, namely, compression, pore development, and post-peak failure, which promote the development and evolution of medium pore and macropores in lignite. (2) Under uniaxial compression, the permeability of the lignite sample shows a “V-shaped” trend, first decreasing and then increasing. When the axial pressure reaches approximately 3.0 MPa, the mutation of the MRI signal increases, and the enhancement of the MRI signal of the sample is due to the cumulative effect of mutation after aggregation. The aggregation of water image signals reflects the distribution area of pores that dominate seepage. (3) Under uniaxial compression, the pore change rate Si slightly decreased. The pore change rate Si of medium pores and macropores showed a positive correlation with axial pressure, which is consistent with the total pore change trend. The compressibility coefficient Cp of the porous pores (medium pores and macropores) and the permeability stress sensitivity coefficient Cf exhibited a linear correlation. The fractal dimension D2 and D3 values of pores in the medium and macropores scale range are close to 3, with the maximum value of D2 being 2.971. This indicates significant fractal characteristics, suggesting that medium pores are the most developed in this scale range. Researches show that that the middle pore has a greater stress sensitivity and shows obvious fractal characteristics during the load failure. The compressibility of the large pore is correlated with the permeability sensitivity, These results show can help elucidate the influence of the pores fracture structure on the seepage evolution of lignite.
Adapting amidst adversity: investigating medical educators’ attitudes towards change and resilience in the face of educational barriers during COVID-19 pandemic
Authors: Khojasteh Laleh , Karimian Zahra , Nasiri Elham , Kafipour Reza
Published: January 2025

Introduction

Resilience in the face of educational barriers refers to faculty members’ ability to effectively navigate, overcome, and adapt to challenges encountered in the educational environment. These challenges may include curriculum changes, transitions to online instruction, resource limitations, or disruptions caused by external factors, such as a pandemic. This study aims to explore the relationship between medical educators’ attitudes toward change and their resilience in overcoming these educational barriers.

Methods

This survey was conducted on 130 medical teachers of Shiraz University of Medical Sciences (SUMS) in 2021-2022. A standard questionnaire with 18 items was used to assess the teachers’ attitudes to change. A researcher-made questionnaire, including 36 items in eight components, was designed to assess the teachers’ resilience to educational barriers.

Results

Based on findings, teachers’ attitudes towards change were moderate in the affective and behavioral aspects but strongly positive in the cognitive aspect (p < 0.001). Teachers with more positive attitudes, compared to those with weaker attitudes, reported significantly fewer barriers in areas such as previous readiness (p = 0.025) and technical support (p = 0.005). Faculty members with better computer skills (p < 0.001) not only perceived fewer barriers but also exhibited more positive attitudes toward change (p = 0.002).

Conclusion

Attitudinal barriers are influenced by a person’s knowledge and skills, affecting their attitude toward change and willingness to face challenges. Involving teachers in diverse online education experiences and improving their competencies can enhance their acceptance of technological changes.
The predictive effect of cultural orientations on Chinese gifted students’ growth mindsets
Authors: Jiang Huifei
Published: January 2025

The study examined the predictive effect of cultural orientations on Chinese gifted students’ growth mindsets. This study encompassed 378 gifted students from universities in mainland China. Gifted students’ growth mindset beliefs and cultural orientations were assessed by using Dweck’s growth mindset inventory and Hofstede’s cultural value scale, respectively. Data analysis mainly leveraged Pearson correlation analysis and hierarchical multiple regression analysis to test the hypothesize role of gifted students’ cultural orientations in predicting their growth mindsets. Pearson correlation analysis was used to assess the bivariate correlation between growth mindset and cultural orientations. Subsequently, Hierarchical multiple regression analysis was conducted to test the predictive effects of cultural orientations on growth mindset beliefs of gifted students. The results revealed that the cultural dimensions of long-term orientation can positively predict gifted students’ growth mindset, but power distance and uncertainty avoidance negatively predict their growth mindsets. Collectivism (or individualism) and femininity (or masculinity) cannot predict growth mindsets. Theoretically, this study underscores the necessity of accounting for cultural contexts when applying the growth mindset framework. Practically, it highlights the need to incorporate cultural factors into growth mindset interventions targeted at gifted students.
Predictive and prognostic nomogram models for liver metastasis in colorectal neuroendocrine neoplasms: a large population study
Authors: Lei Xiao , Su Yanwei , Lei Rui , Zhang Dongyang , Liu Zimeng , Li Xiangke , Yang Minjie , Pei Jiaxin , Chi Yanyan , Song Lijie
Published: January 2025

Background

In recent years, the incidence of patients with colorectal neuroendocrine neoplasms (CRNENs) has been continuously increasing. When diagnosed, most patients have distant metastases. Liver metastasis (LM) is the most common type of distant metastasis, and the prognosis is poor once it occurs. However, there is still a lack of large studies on the risk and prognosis of LM in CRNENs. This study aims to identify factors related to LM and prognosis and to develop a predictive model accordingly.

Methods

In this study, the Surveillance, Epidemiology, and End Results (SEER) database was used to collect clinical data from patients with CRNENs. The logistic regression analyses were conducted to identify factors associated with LM in patients with CRNENs. The patients with LM formed the prognostic cohort, and Cox regression analyses were performed to evaluate prognostic factors in patients with liver metastasis of colorectal neuroendocrine neoplasms (LM-CRNENs). Predictive and prognostic nomogram models were constructed based on the multivariate logistic and Cox analysis results. Finally, the capabilities of the nomogram models were verified through model assessment metrics, including the receiver operating characteristic (ROC) curves, calibration curve, and decision curve analysis (DCA) curve.

Results

This study ultimately encompassed a total of 10,260 patients with CRNENs. Among these patients, 501 cases developed LM. The result of multivariate logistic regression analyses indicated that histologic type, tumor grade, T stage, N stage, lung metastasis, bone metastasis, and tumor size were independent predictive factors for LM in patients with CRNENs (p < 0.05). Multivariate Cox regression analyses indicated that age, primary tumor site, histologic type, tumor grade, N stage, tumor size, chemotherapy, and surgery were independent prognostic factors (p < 0.05) for patients with LM-CRNENs. The predictive and prognostic nomogram models were established based on the independent factors of logistic and Cox analyses. The nomogram models can provide higher accuracy and efficacy in predicting the probability of LM in patients with CRNENs and the prognosis of patients with LM.

Conclusion

The factors associated with the occurrence of LM in CRNENs were identified. On the other hand, the relevant prognostic factors for patients with LM-CRNENs were also demonstrated. The nomogram models, based on independent factors, demonstrate greater efficiency and accuracy, promising to provide clinical interventions and decision-making support for patients.
Influence of steady and turbulent wind on motions, mooring tension, and fatigue performance of a steel OO-Star floating offshore wind turbine
Authors: Shu Jiaqing , Gu Xiaoqing
Published: January 2025

Floating offshore wind turbines (FOWTs) often operate under turbulent wind conditions. However, to enhance computational efficiency, steady wind is sometimes used as an alternative to turbulent wind, potentially resulting in conservative estimates. Assessing FOWT motion and fatigue performance under both steady and turbulent wind conditions is therefore crucial. This study focuses on an enhanced steel semi-submersible FOWT, adapted from the LIFES50+ OO-Star concrete design. The FOWT is modeled using OPENFAST software under various load scenarios, including steady and turbulent winds with irregular waves, for time-domain analysis. The results reveal that the FOWT experiences reduce motion, tension response, blade root loads, and tower-top loads under steady winds combined with irregular waves, compared to turbulent winds with irregular waves. The blade root and tower top loads are lower under steady winds with irregular waves, indicating that steady wind analysis may yield unfavorable outcomes for FOWTs. The findings in this study offer valuable theoretical insights and technical support for the design and evaluation of FOWTs.
Inconspicuous taxa in citizen science-based botanical research: actual contribution, limitations, and new opportunities for non-vascular cryptogams
Authors: Cerrejón Carlos , Noualhaguet Marion , Fenton Nicole J. , Indorf Marc-Frédéric , Feldman Mariano J.
Published: January 2025

Citizen science (CS) has gathered an impressive wealth of open biodiversity data over the last decade, with demonstrated significant scientific contributions in biology and conservation science. However, the contribution of CS in botanical research, and more particularly regarding inconspicuous taxonomic groups such as cryptogams remains largely unexplored. Here we assess the current status and contribution of CS in botanical research, with a special focus on non-vascular “cryptogams” (bryophytes, lichens, fungi, and algae). We conducted a literature review for the period 2012 to 2022 to synthesize the use of CS in botanical studies. We found an increasing trend in the use of CS for botanical research (average annual increase of ∼40%), although highly biased towards vascular plants (246 papers). Cryptogams remained strongly underrepresented (58 papers), although receiving slightly growing attention since 2018. The inconspicuousness nature, high diversity, challenges with species identification, and low public perception of cryptogams not only restrict the contribution made by non-experts but raise concerns about the reliability and robustness of generated data. This is fueled by the scarcity of foundational methodological studies in cryptogams, which seems to undermine the scientific confidence in engaging volunteers for their research or using open data from CS platforms and tools. Despite this, our review showed a gradual adoption of CS approaches for cryptogam research, which is particularly led by mycologists. We highlight the versatility and potential of CS approaches for advancing cryptogam knowledge across various research subjects at spatial and temporal scales otherwise unfathomable by researchers, and provide insights on the opportunities of application and possible solutions to the discussed limitations. We hope our work motivates mycologists, phycologists, bryologists, and lichenologists to further embrace CS, and increase public awareness on these highly sensitive and ecologically important taxa.
Zooming into Berlin: tracking street-scale CO2 emissions based on high-resolution traffic modeling using machine learning
Authors: Anjos Max , Meier Fred
Published: January 2025

Artificial Intelligence (AI) tools based on Machine learning (ML) have demonstrated their potential in modeling climate-related phenomena. However, their application to quantifying greenhouse gas emissions in cities remains under-researched. Here, we introduce a ML-based bottom-up framework to predict hourly CO2 emissions from vehicular traffic at fine spatial resolution (30 × 30 m). Using data-driven algorithms, traffic counts, spatio-temporal features, and meteorological data, our model predicted hourly traffic flow, average speed, and CO2 emissions for passenger cars (PC) and heavy-duty trucks (HDT) at the street scale in Berlin. Even with limited traffic information, the model effectively generalized to new road segments. For PC, the Relative Mean Difference (RMD) was +16% on average. For HDT, RMD was 19% for traffic flow and 2.6% for average speed. We modeled seven years of hourly CO2 emissions from 2015 to 2022 and identified major highways as hotspots for PC emissions, with peak values reaching 1.639 kgCO2 m−2 d−1. We also analyzed the impact of COVID-19 lockdown and individual policy stringency on traffic CO2 emissions. During the lockdown period (March 15 to 1 June 2020), weekend emissions dropped substantially by 25% (−18.3 tCO2 day−1), with stay-at-home requirements, workplace closures, and school closures contributing significantly to this reduction. The continuation of these measures resulted in sustained reductions in traffic flow and CO2 emissions throughout 2020 and 2022. These results highlight the effectiveness of ML models in quantifying vehicle traffic CO2 emissions at a high spatial resolution. Our ML-based bottom-up approach offers a useful tool for urban climate research, especially in areas lacking detailed CO2 emissions data.
YOLOGX: an improved forest fire detection algorithm based on YOLOv8
Authors: Li Caixiong , Du Yue , Zhang Xing , Wu Peng
Published: January 2025

To tackle issues, including environmental sensitivity, inadequate fire source recognition, and inefficient feature extraction in existing forest fire detection algorithms, we developed a high-precision algorithm, YOLOGX. YOLOGX integrates three pivotal technologies: First, the GD mechanism fuses and extracts features from multi-scale information, significantly enhancing the detection capability for fire targets of varying sizes. Second, the SE-ResNeXt module is integrated into the detection head, optimizing feature extraction capability, reducing the number of parameters, and improving detection accuracy and efficiency. Finally, the proposed Focal-SIoU loss function replaces the original loss function, effectively reducing directional errors by combining angle, distance, shape, and IoU losses, thus optimizing the model training process. YOLOGX was evaluated on the D-Fire dataset, achieving a mAP@0.5 of 80.92% and a detection speed of 115 FPS, surpassing most existing classical detection algorithms and specialized fire detection models. These enhancements establish YOLOGX as a robust and efficient solution for forest fire detection, providing significant improvements in accuracy and reliability.
Modeling soil respiration in summer maize cropland based on hyperspectral imagery and machine learning
Authors: Zeng Fanchao , Sun Jinwei , Zhang Huihui , Yang Lizhen , Zhao Xiaoxue , Zhao Jing , Bo Xiaodong , Cao Yuxin , Yao Fuqi , Yuan Fenghui
Published: January 2025

Introduction

Soil respiration (SR), the release of carbon dioxide (CO2) from soil due to the decomposition of organic matter and root respiration, is an important indicator for understanding agricultural carbon cycling and assessing anthropogenic impacts on the environment. Hyperspectral remote sensing offers a potential rapid, non-destructive approach for monitoring in agriculture. However, it remains uncertain whether hyperspectral remote sensing can provide an accurate and efficient method for estimating SR rate in croplands, particularly across different maize growth stages of under varying drought conditions.

Methods

In the study, we investigated the potential of combining hyperspectral remote sensing data with machine learning model (ML) to quantify SR rate in croplands. A drought field experiment was conducted, and SR and hyperspectral imagery were collected during four maize growth stages: Jointing Stage (JS), Tasseling Stage (TS), Flowering Stage (FS), and Grain Filling Stage (GFS). We compared the performance of traditional multiple linear regression (MLR) with that of an ML model (extreme gradient boosting, XGBoost), in simulating SR rate across these four growth stages.

Results

Our findings demonstrated that the simulation of the XGBoost model, utilizing soil temperature (Ts) and hyperspectral data, outperformed the MLR model. Across different growth stages, the SR simulated by the XGBoost model (R2 = 0.8103) was more reliable than that of the MLR model (R2 = 0.7451). The XGBoost model can also effectively capture the impact of drought treatments on SR.

Discussion

The XGBoost model’s tree-based structure allows it to effectively capture complex interactions and nonlinear patterns within variables, while its high sensitivity to changes in SR rates under drought conditions makes it more reliable for modeling SR across different growth stages compared to the linear-based MLR model. This study highlights the great promise of ML combined with hyperspectral imaging in predicting SR rate in croplands, which will help guide future agricultural management and environmental informatics.
Chronobiology as compensation: can biological rhythms compensate for sexual signals?
Authors: Westwood Mary L. , Broder E. Dale , Welsh Gabrielle T. , Tinghitella Robin M.
Published: January 2025

Conspicuous sexual signals come with costs and benefits. Such signals increase reproductive success but may also reduce survival or viability. It has recently been suggested that non-signal traits may alleviate some of those costs (termed “compensatory traits”). In this perspective piece, we argue that biological rhythms should be considered in the milieu of compensatory traits, as they can reduce the natural selection burden of signaling. This may be particularly true for the many sexual signals that are ephemeral (i.e., only periodically present like a courtship dance). Biological rhythms (e.g., circadian and circannual rhythms) are ubiquitous in nature and help organisms perform the right activity at the right time—this includes the timing of many sexual signals and reproductive traits. Timing itself may, in fact, reduce the costs of such sexual signals. Here, we review sexual signals that are governed by biological rhythms and discuss how signal modality and type (ornament, weapon, dominance trait) account for differences in how chronobiology may act as a compensatory trait. We then consider how biologists might examine the untested role of chronobiology as a compensatory trait and set forth compelling questions for future work.
DNA barcoding reveals an unexpected distribution of two Megaleporinus species in the La Plata Basin system
Authors: Coronel Florencia Paola , Loretán Gisela , Sanchez Sebastián , Silva Natalia , Pacheco-Sierra Gualberto , Brancolini Florencia , Aichino Danilo , Vargas Facundo , Scarabotti Pablo , Espínola Luis , Pavanelli Carla Simone , Rueda Eva Carolina
Published: January 2025

Introduction

Megaleporinus obtusidens, also known as "boga," is a freshwater teleost fish species widely distributed across South America with significant commercial value in Argentina and Brazil. Fishers, particularly those in the lower Paraná River, frequently classify the fish they catch as M. obtusidens. Despite various approaches, including cytogenetics, molecular data, and morphological analysis, the taxonomic classification of the boga fish remains debated among researchers, resulting in discrepancies in the literature.

Methods

This study aimed to assess the diversity of specimens captured in the La Plata River Basin, initially classified as Megaleporinus obtusidens by fishers, using DNA barcoding. The mitochondrial COI marker was employed to explore species assignment and genetic diversity in Megaleporinus, a genus with high commercial exploitation in the southern area of the La Plata Basin.

Results

Our findings indicate that some boga samples, previously identified as M. obtusidens, are actually M. piavussu. We also observed significant differences in the geographic distribution, diversity, and genetic structure between the two species.

Discussion

These results highlight the importance of studying the ecology of each species separately. Proper resource management, based on accurate species identification, is critical for the conservation of ichthyofauna in the region.
Analysis of fatty acid-derived lipids in critically ill patients after cardiac surgery yields novel pathophysiologically relevant mediators with possible relevance for systemic inflammatory reactions
Authors: Neb Holger , Roth Verena , Roos Jessica , Bauer Tom , Urbschat Anja , Heinicke Ulrike , Angioni Carlo , Steinhilber Dieter , Piesche Matthias , Ferreirós Nerea , Gurke Robert , Geisslinger Gerd , Utech Edith , Zacharowski Kai , Meybohm Patrick , Paulus Patrick , Schmitt Elke , Maier Thorsten Jürgen
Published: January 2025

Introduction

Critically ill patients suffer from a wide variety of clinical events, most of them leading to pro-inflammatory states such as sepsis or simply as consequence of major surgery. Many of these patients develop forms of acute kidney injury, heart or acute liver failure during intensive care. Lipid signaling is critically involved in triggering systemic inflammation processes, pain and vascular tone. We therefore hypothesized that fatty-acid-derived lipid mediators might be regulated during inflammatory stages and other clinical events in critically ill patients and might serve as potential biomarker candidates.

Methods and study design

Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we determined the levels of 53 lipid mediators in plasma from nine patients. These patients were hospitalized at Frankfurt University Hospital’s intensive care unit (ICU) after cardiac surgery. Inflammatory stages were illustrated over time using clinically established biomarkers such as interleukin-6 (IL-6) and leukocyte count. Normal range values of the lipids were obtained from healthy volunteers.

Results

Plasma levels clearly outside the normal range were observed for 22 of 53 lipid mediators, of which 13 were increased (including ceramides Cer (d18:0/18:0), Cer (d18:1/16:0), Cer (d18:1/18:1), glucosyl-ceramide GluCer (d18:1/24:1), lactosylceramide LacCer (d18:1/18:0), and LacCer (d18:1/24:1), 6-keto-prostaglandin F1alpha (6-keto-PGF1alpha), 11,12- and 14,15-DHET and 1- and 2-arachidonoyl glycerol (1-AG and 2-AG), Sphingosine SPH (d18:1) and 20-HETE. Furthermore, nine lipids were decreased (Cer (d18:1/24:0), LacCer (d18:1/16:0), LacCer (d18:1/24:0), sphingosine-1-phosphate S1P (d18:1), S1P (d18:0), the lysophosphatidic acids LPA (16:0), LPA (18:0), LPA (18:1) and 9-HODE. Among increased lipids, the remarkable changes in 1-AG, 2-AG, and to a lower extent of 6-keto-PGF1-alpha plasma levels showed a certain agreement with inflammatory phases. Furthermore, 6-keto-PGF1alpha had its peak shortly before initiation of continuous veno-venous hemodialysis (at least in 5 of the observed patients), 2-AG was elevated in all our nine patients during (right) heart failure in the context of either re-opening patient’s chest, implementation of veno-arterial ECMO or at least while significantly increasing the amount of catecholamines.

Discussion

In this pilot trial we identified several evaluated lipids in critically ill patients representing either potentially (patho-) physiologically relevant mediators of the pro-inflammatory processes and during heart failure or possible markers preceding veno-venous hemodialysis.
Exploring the shared mechanism of fatigue between systemic lupus erythematosus and myalgic encephalomyelitis/chronic fatigue syndrome: monocytic dysregulation and drug repurposing
Authors: Zheng Daisi , Li Xiaolong , Wang Peicheng , Zhu Qingmiao , Huang Zhiyan , Zhao Ting
Published: January 2025

Background

SLE and ME/CFS both present significant fatigue and share immune dysregulation. The mechanisms underlying fatigue in these disorders remain unclear, and there are no standardized treatments. This study aims to explore shared mechanisms and predict potential therapeutic drugs for fatigue in SLE and ME/CFS.

Methods

Genes associated with SLE and ME/CFS were collected from disease target and clinical sample databases to identify overlapping genes. Bioinformatics analyses, including GO, KEGG, PPI network construction, and key target identification, were performed. ROC curve and correlation analysis of key targets, along with single-cell clustering, were conducted to validate their expression in different cell types. Additionally, an inflammation model was established using THP-1 cells to simulate monocyte activation in both diseases in vitro, and RT-qPCR was used to validate the expression of the key targets. A TF-mRNA-miRNA co-regulatory network was constructed, followed by drug prediction and molecular docking.

Results

Fifty-eight overlapping genes were identified, mainly involved in innate immunity and inflammation. Five key targets were identified (IL1β, CCL2, TLR2, STAT1, IFIH1). Single-cell sequencing revealed that monocytes are enriched with these targets. RT-qPCR confirmed significant upregulation of these targets in the model group. A co-regulatory network was constructed, and ten potential drugs, including suloctidil, N-Acetyl-L-cysteine, simvastatin, ACMC-20mvek, and camptothecin, were predicted. Simvastatin and camptothecin showed high affinity for the key targets.

Conclusion

SLE and ME/CFS share immune and inflammatory pathways. The identified key targets are predominantly enriched in monocytes at the single-cell level, suggesting that classical monocytes may be crucial in linking inflammation and fatigue. RT-qPCR confirmed upregulation in activated monocytes. The TF-mRNA-miRNA network provides a foundation for future research, and drug prediction suggests N-Acetyl-L-cysteine and camptothecin as potential therapies.