bluuebunny/crossref_metadata_2025_split huggingface dataset:
Current Scenario of Foot and Mouth Disease (FMD) at Dhanbari Upazila, Tangail, Bangladesh
Authors: Rupa Akter  , Mayisha Maliha Kona  , Subrato Biswas  , Md Rakibul Islam  , Md Abu Zar Gefari  , Md Abdul Masum  
Published: January 2025

Foot-and-mouth disease (FMD) is considered an economically devastating and highly contagious disease affecting both domestic and wild cloven-hoofed animals. It also poses a significant threat to the livestock industry in Bangladesh, impacting production and hindering trade. To address this concern, a study was conducted at Dhanbari Upazila, Tangail, Bangladesh, from October 5, 2022, to November 4, 2023. A total of 1071 cattle were examined, comprising 358 males and 713 females. The overall prevalence of FMD in Dhanbari Upazila was found to be 30.25%. The study investigated the influence of several factors, such as age, sex, breed, season, farming system, and vaccination, on the prevalence of FMD. Results indicated a significantly higher prevalence during winter (41.56%), with older cattle exhibiting a higher susceptibility (30.07%). Moreover, females were more susceptible (39.69%) than males (11.45%). The indigenous breeds were more prevalent (47.64%) than crossbreeds (19.76%). Additionally, a higher prevalence was found in non-vaccinated cattle (38.53%) than in vaccinated cattle (4.9%). Cattle from rural household farms have a higher prevalence (31.26%) compared to cattle from intensive farms (29.06%). Age, sex, breed, season, vaccination, and nutrition were significantly (p<0.05) associated with the prevalence of FMD. These findings highlight the genetic factors, managemental factors, and seasonal variations that contribute to the prevalence of FMD in this area. Moreover, it would help the farmers to establish an effective prevention and control program for FMD.
Res. Agric. Livest. Fish. Vol. 11, No. 3, December 2024: 295-303
Diagnosa Keperawatan : Gangguan Integritas Kulit Pada Pasien Penyakit Ginjal Kronis Menjalani Terapi Hemodialisa
Authors: Cita Errick Endra , Ka’arayeno Arie Jefry , Tumiani Tumiani 
Published: January 2025

Gangguan integritas kulit dialami pasien gagal ginjal kronik berdampak pada kualitas hidup dalam kehidupan sehari-hari. Penelitian ini mengidentifikasi tanda gejala dan faktor berhubungan gangguan integritas kulit pada pasien gagal ginjal kronik yang menjalani terapi hemodialisa. Jenis penelitian ini adalah kuantitatif, deskriptif, dan eksploratif. Populasi dan sampel penelitian adalah pasien gagal ginjal kronik menjalani hemodialisis berjumlah 52 sampel yang diambil dengan teknik consecutive sampling. Instrumen penelitian berupa lembar observasi pemeriksaan fisik pada kulit dan skin detector untuk mengukur kelembaban kulit. Data dianalisis berdasarkan nomenklatur Standar Diagnosis Keperawatan Indonesia(SDKI). Penelitian ini disetujui oleh Komite Etik Penelitian Kesehatan STIKES Guna Bangsa Yogyakarta. Hasil menunjukkan gangguan integritas kulit pada pasien gagal ginjal kronik didukung oleh adanya data kerusakan lapisan kulit seperti kulit kering, kulit kasar, ekskoriasi, kulit bersisik berpola, purpura, hiperpigmentasi, gatal, berhubungan dengan perubahan sirkulasi, kelebihan volume cairan dan perubahan status nutrisi. Penentuan diagnosis keperawatan gangguan integritas kulit ditentukan tanda mayor yang lebih spesifik untuk menggambarkan kerusakan lapisan kulit pada tanda mayor terdapat pada SDKI
Pengetahuan dan Perilaku Ibu dalam Pencegahan Stunting pada Balita
Authors: Ade Devriany  , Irma Azzah Rika Niara  , Ori Pertami Enardi  
Published: January 2025

Stunting merupakan masalah kekurangan gizi yang masih dialami oleh balita di Indonesia. Menurut Studi Status Gizi Indonesia (SSGI) 2022 prevalensi stunting di Provinsi Bangka Belitung tertinggi berada di Kabupaten Bangka Selatan yaitu 23%. Salah satu penyebabnya adalah kurang pengetahuan dan perilaku ibu dalam pencegahan stunting. Tujuan penelitian menggambarkan pengetahuan dan perilaku ibu dalam pencegahan stunting pada balita di Desa Serdang Kabupaten Bangka Selatan. Metode penelitian ini menggunakan metode kuantitatif dengan desain penelitian deskriptif yang dilaksanakan pada bulan April 2024 di Wilayah Desa Serdang. Penelitian ini melibatkan 35 ibu yang mempunyai balita usia 3 – 5 tahun yang dipilih menggunakan simple random sampling. Hasil penelitian rata – rata umur balita 4 tahun sebanyak 66,9% dengan jenis kelamin paling banyak adalah perempuan. Ibu balita berusia 21 - 64 tahun sebanyak 97,1% dengan kategori pengetahuan yang baik sebanyak 97,1%. Seluruh ibu telah memiliki pengetahuan yang baik terkait ciri – ciri stunting pada anak dengan persentase 100% namun 40% ibu belum mengetahui kategori anak sehat dinilai dari tinggi badan dengan usianya. Sebanyak 88,6% ibu yang memiliki perilaku baik dalam pencegahan stunting dengan membiasakan cuci tangan sebelum memberikan makan anak. Namun, sebesar 31,4% ibu tidak pernah mencari tahu informasi tentang stunting. Kesimpulan penelitian terdapat pengetahuan dan perilaku ibu dalam pencegahan stunting dalam kategori baik.
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

PurposeTo examine the effects of different warm-up methods on 50 m breaststroke performance in both breaststroke specialists and individual medley swimmers.Methods18 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.ResultsThe 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.ConclusionBreaststroke 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.
Antibodies directed against bacterial antigens in sera of Polish patients with primary biliary cholangitis
Authors: Bauer Alicja , Habior Andrzej 
Published: January 2025

BackgroundPrimary 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.MethodWe 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.ResultsAnti-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 &lt; 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.ConclusionMicrobial 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

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

IntroductionResilience 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.MethodsThis 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.ResultsBased on findings, teachers’ attitudes towards change were moderate in the affective and behavioral aspects but strongly positive in the cognitive aspect (p &lt; 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 &lt; 0.001) not only perceived fewer barriers but also exhibited more positive attitudes toward change (p = 0.002).ConclusionAttitudinal 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.
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

BackgroundIn 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.MethodsIn 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.ResultsThis 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 &lt; 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 &lt; 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.ConclusionThe 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.
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.
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

IntroductionSoil 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.MethodsIn 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.ResultsOur 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.DiscussionThe 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.
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

IntroductionMegaleporinus 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.MethodsThis 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.ResultsOur 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.DiscussionThese 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.