bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing HCH isomer uptake in Alnus glutinosa: implications for phytoremediation and microbial response
Authors: Amirbekov Aday , Vrchovecka Stanislava , Riha Jakub , Petrik Ivan , Friedecky David , Novak Ondrej , Cernik Miroslav , Hrabak Pavel , Sevcu Alena 
Published: February 2024

AbstractAlthough the pesticide hexachlorocyclohexane (HCH) and its isomers have long been banned, their presence in the environment is still reported worldwide. In this study, we investigated the bioaccumulation potential of α, β, and δ hexachlorocyclohexane (HCH) isomers in black alder saplings (Alnus glutinosa) to assess their environmental impact. Each isomer, at a concentration of 50 mg/kg, was individually mixed with soil, and triplicate setups, including a control without HCH, were monitored for three months with access to water. Gas chromatography–mass spectrometry revealed the highest concentrations of HCH isomers in roots, decreasing towards branches and leaves, with δ-HCH exhibiting the highest uptake (roots—14.7 µg/g, trunk—7.2 µg/g, branches—1.53 µg/g, leaves—1.88 µg/g). Interestingly, α-HCH was detected in high concentrations in β-HCH polluted soil. Phytohormone analysis indicated altered cytokinin, jasmonate, abscisate, and gibberellin levels in A. glutinosa in response to HCH contamination. In addition, amplicon 16S rRNA sequencing was used to study the rhizosphere and soil microbial community. While rhizosphere microbial populations were generally similar in all HCH isomer samples, Pseudomonas spp. decreased across all HCH-amended samples, and Tomentella dominated in β-HCH and control rhizosphere samples but was lowest in δ-HCH samples.
ERCP-Net: a channel extension residual structure and adaptive channel attention mechanism for plant leaf disease classification network
Authors: Ma Xiu , Chen Wei , Xu Yannan 
Published: February 2024

AbstractPlant leaf diseases are a major cause of plant mortality, especially in crops. Timely and accurately identifying disease types and implementing proper treatment measures in the early stages of leaf diseases are crucial for healthy plant growth. Traditional plant disease identification methods rely heavily on visual inspection by experts in plant pathology, which is time-consuming and requires a high level of expertise. So, this approach fails to gain widespread adoption. To overcome these challenges, we propose a channel extension residual structure and adaptive channel attention mechanism for plant leaf disease classification network (ERCP-Net). It consists of channel extension residual block (CER-Block), adaptive channel attention block (ACA-Block), and bidirectional information fusion block (BIF-Block). Meanwhile, an application for the real-time detection of plant leaf diseases is being created to assist precision agriculture in practical situations. Finally, experiments were conducted to compare our model with other state-of-the-art deep learning methods on the PlantVillage and AI Challenger 2018 datasets. Experimental results show that our model achieved an accuracy of 99.82% and 86.21%, respectively. Also, it demonstrates excellent robustness and scalability, highlighting its potential for practical implementation.
Comparison of metabolic and neurological comorbidities in Asian patients with psoriasis and atopic dermatitis
Authors: Yang Hee Joo , Lee Mi Young , Lee Jeong Hyeon , Jung Chang Jin , Lee Woo Jin , Won Chong Hyun , Lee Mi Woo , Jung Joon Min , Chang Sung Eun 
Published: February 2024

AbstractAlthough various comorbidities have been noted to be associated with atopic dermatitis (AD) and psoriasis, few studies have compared comorbidities between the two diseases, and little is known about whether these comorbidities vary by the subtypes of psoriasis. In this study of 1:1 age- and sex-matched pair analysis between patients diagnosed with either psoriasis or AD at Asan Medical Center between 1991 and 2020, comorbidities, as determined by the International Classification of Diseases-10 codes, and likelihood ratios of metabolic and neurologic comorbidities in psoriasis compared with AD were studied using a logistic regression model. Among a total of 14,128 patients, the psoriasis group had higher odds of obesity (odds ratio [95% confidence interval]: 1.49 [1.34–1.66]), hypertension (1.14 [1.03–1.26]), diabetes mellitus (1.46 [1.29–1.66]), chronic kidney disease (1.59 [1.22–2.08]), and Parkinson's disease (2.1 [1.15–3.83]) than the AD group. Subgroup analysis revealed that patients with plaque psoriasis had higher odds of obesity (1.18 [1.05–1.33]), hypertension (1.18 [1.06–1.32]), diabetes mellitus (1.53 [1.34–1.75]), chronic kidney disease (1.66 [1.26–2.17]), and Parkinson’s disease (2.12 [1.16–3.88]) compared with AD. Meanwhile, guttate psoriasis was associated with higher odds of dementia (3.63 [1.06–12.40]) and patients with generalized pustular psoriasis showed higher odds of diabetes mellitus (5.42 [1.56–18.83]) compared with AD. In conclusion, Asian patients with all types of psoriasis should be closely monitored for the development of metabolic and neurologic diseases, especially men and those aged ≥ 40 years.
Exploring new horizons in neuroscience disease detection through innovative visual signal analysis
Authors: Amer Nisreen Said , Belhaouari Samir Brahim 
Published: February 2024

AbstractBrain disorders pose a substantial global health challenge, persisting as a leading cause of mortality worldwide. Electroencephalogram (EEG) analysis is crucial for diagnosing brain disorders, but it can be challenging for medical practitioners to interpret complex EEG signals and make accurate diagnoses. To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. We introduce the concept of eye-naked classification, which integrates domain-specific knowledge and clinical expertise into the classification process. Our study demonstrates the effectiveness of the FBFT method, achieving impressive accuracies across multiple brain disorders using CNN-based classification. Specifically, we achieve accuracies of 99.82% for epilepsy, 95.91% for Alzheimer’s disease (AD), 85.1% for murmur, and 100% for mental stress using CNN-based classification. Furthermore, in the context of naked-eye classification, we achieve accuracies of 78.6%, 71.9%, 82.7%, and 91.0% for epilepsy, AD, murmur, and mental stress, respectively. Additionally, we incorporate a mean correlation coefficient (mCC) based channel selection method to enhance the accuracy of our classification further. By combining these innovative approaches, our study enhances the visualization of EEG signals, providing medical professionals with a deeper understanding of TF medical images. This research has the potential to bridge the gap between image classification and visual medical interpretation, leading to better disease detection and improved patient care in the field of neuroscience.
Deep clustering using 3D attention convolutional autoencoder for hyperspectral image analysis
Authors: Zheng Ziyou , Zhang Shuzhen , Song Hailong , Yan Qi 
Published: February 2024

AbstractDeep clustering has been widely applicated in various fields, including natural image and language processing. However, when it is applied to hyperspectral image (HSI) processing, it encounters challenges due to high dimensionality of HSI and complex spatial-spectral characteristics. This study introduces a kind of deep clustering model specifically tailed for HSI analysis. To address the high dimensionality issue, redundant dimension of HSI is firstly eliminated by combining principal component analysis (PCA) with t-distributed stochastic neighbor embedding (t-SNE). The reduced dataset is then input into a three-dimensional attention convolutional autoencoder (3D-ACAE) to extract essential spatial-spectral features. The 3D-ACAE uses spatial-spectral attention mechanism to enhance captured features. Finally, these enhanced features pass through an embedding layer to create a compact data-representation, and the compact data-representation is divided into distinct clusters by clustering layer. Experimental results on three publicly available datasets validate the superiority of the proposed model for HSI analysis.
Inflammation drives pathogenesis of early intestinal failure-associated liver disease
Authors: Fligor Scott C. , Tsikis Savas T. , Hirsch Thomas I. , Jain Ashish , Sun Liang , Rockowitz Shira , Gura Kathleen M. , Puder Mark 
Published: February 2024

AbstractPatients with intestinal failure who receive long-term parenteral nutrition (PN) often develop intestinal failure-associated liver disease (IFALD). Although there are identified risk factors, the early pathogenesis is poorly understood and treatment options are limited. Here, we perform a transcriptomic analysis of liver tissue in a large animal IFALD model to generate mechanistic insights and identify therapeutic targets. Preterm Yorkshire piglets were provided PN or bottle-fed with sow-milk replacer for 14 days. Compared to bottle-fed controls, piglets receiving PN developed biochemical cholestasis by day of life 15 (total bilirubin 0.2 vs. 2.9 mg/dL, P = 0.01). RNA-Seq of liver tissue was performed. Ingenuity Pathway Analysis identified 747 differentially expressed genes (343 upregulated and 404 downregulated) with an adjusted P < 0.05 and a fold-change of > |1|. Enriched canonical pathways were identified, demonstrating broad activation of inflammatory pathways and inhibition of cell cycle progression. Potential therapeutics including infliximab, glucocorticoids, statins, and obeticholic acid were identified as predicted upstream master regulators that may reverse the PN-induced gene dysregulation. The early driver of IFALD in neonates may be inflammation with an immature liver; identified therapeutics that target the inflammatory response in the liver should be investigated as potential treatments.
Assessing the efficacy of simulation-based education for paramedics in extended focused assessment with sonography for trauma under physician guidance
Authors: Ohira Akiko , Maki Jota , Ageta Kohei , Nakato Hikari , Oba Hikaru , Mitoma Tomohiro , Mishima Sakurako , Tani Kazumasa , Kirino Satoe , Eto Eriko , Nakao Atsunori , Masuyama Hisashi 
Published: February 2024

AbstractWe investigated the effectiveness of simulation-based education in Focused Assessment with Sonography for Trauma (FAST) to increase the number of Emergency Medical Technicians (EMTs) capable of performing ultrasound examinations in vehicles under the guidance of a physician. Twenty-eight paramedics watched a 14-min video on the features of the ultrasound system, its use, and the scanning method for each part of the body. Each participant performed four FAST examinations using a portable ultrasound device, and the task performance was rated using the Task Specific Checklist (TSC) and Global Rating Scale (GRS). The time required for visualizing each examination site and each FAST was assessed. The mean time required for the first and fourth FAST was 144.6 ± 52.4 s and 90.5 ± 31.0 s, respectively. The time required for each test significantly decreased with repeated testing (p < 0.001). The time to complete FAST was significantly shortened for the pericardial cavity (33.4 ± 23.1/15.3 ± 10.6 s, p < 0.01), right thoracic cavity (25.2 ± 11.8/12.1 ± 8.3 s, p < 0.01), Morrison fossa (19.1 ± 10.8/10.8 ± 6.3 s, p < 0.05), and left thoracic cavity (19.0 ± 8.3/15.6 ± 8.3 s, p < 0.05). TSC and GRS scores were elevated, and all EMTs could obtain valid images. The combination of a brief video lecture and hands-on training significantly reduced the time required for FAST performance. Moreover, repeated practice enabled the EMTs to efficiently obtain accurate and clinically useful images.
Comparison of tendon and muscle belly vibratory stimulation in the treatment of post-stroke upper extremity spasticity: a retrospective observational pilot study
Authors: Takeuchi Kenta , Takebayashi Takashi , Hanioka Daiki , Okita Yuho , Shimada Shinichi 
Published: February 2024

AbstractPrevious studies have reported the effects of vibratory stimulation (VS) therapy in reducing upper extremity spasticity after stroke. However, the effective location of the VS in patients with stroke remains unclear. This study aimed to determine the VS location that is most effective in reducing post-stroke finger and wrist flexor spasticity. We enrolled 27 consecutive patients with stroke and upper extremity spasticity in this retrospective observational study. The participants received stretching, tendon vibration, and muscle belly vibration for 5 min over a period of 3 days. To evaluate spasticity, we assessed the Modified Ashworth Scale score before and immediately after each treatment and immediately after voluntary finger flexion. Participants who received tendon vibration showed greater improvement in flexor tone in the fingers than participants who received stretching and muscle belly vibration (P < 0.05 and < 0.001, respectively). Participants who underwent VS showed no significant improvement in the wrist flexor tone compared to those who underwent stretching. Our results suggest that the tendon may be the most effective location for treating spasticity of the finger flexor muscles and that VS may not significantly improve spasticity of the wrist flexors more than stretching.
Consistent detection of Trypanosoma brucei but not T. congolense DNA in faeces of experimentally infected cattle
Authors: Saldanha Isabel , Betson Martha , Vrettou Christina , Paxton Edith , Nixon James , Tennant Peter , Ritchie Adrian , Matthews Keith R. , Morrison Liam J. , Torr Stephen J. , Cunningham Lucas J. 
Published: February 2024

AbstractAnimal African trypanosomiasis (AAT) is a significant food security and economic burden in sub-Saharan Africa. Current AAT empirical and immunodiagnostic surveillance tools suffer from poor sensitivity and specificity, with blood sampling requiring animal restraint and trained personnel. Faecal sampling could increase sampling accessibility, scale, and species range. Therefore, this study assessed feasibility of detecting Trypanosoma DNA in the faeces of experimentally-infected cattle. Holstein–Friesian calves were inoculated with Trypanosoma brucei brucei AnTat 1.1 (n = 5) or T. congolense Savannah IL3000 (n = 6) in separate studies. Faecal and blood samples were collected concurrently over 10 weeks and screened using species-specific PCR and qPCR assays. T. brucei DNA was detected in 85% of post-inoculation (PI) faecal samples (n = 114/134) by qPCR and 50% by PCR between 4 and 66 days PI. However, T. congolense DNA was detected in just 3.4% (n = 5/145) of PI faecal samples by qPCR, and none by PCR. These results confirm the ability to consistently detect T. brucei DNA, but not T. congolense DNA, in infected cattle faeces. This disparity may derive from the differences in Trypanosoma species tissue distribution and/or extravasation. Therefore, whilst faeces are a promising substrate to screen for T. brucei infection, blood sampling is required to detect T. congolense in cattle.
Genome-wide identification, phylogeny and expressional profile of the Dmrt gene family in Chinese sturgeon (Acipenser sinensis)
Authors: Hu Yacheng , Tan Ruihua , Zhu Xin , Wang Binzhong , Wang Jingshu , Guo Baifu , Li Yuan , Du Hejun , Yang Yuanjin 
Published: February 2024

AbstractChinese sturgeon Dmrt gene family was identified and characterized for the first time. A total of 5 putative Dmrt genes were identified. The gene structure, conserved protein domain and the phylogenetic relationship of Dmrt gene family were systematically analyzed. The expressed profile of Chinese sturgeon Dmrt genes in gonad, pituitary and hypothalamus in the male and female were investigated. The results indicated that the accumulation of Dmrt genes was involved in different tissues, and the expression profile also differed among each Dmrt genes. ASDmrt1A, ASDmrt2, ASDmrt3, and ASDmrtA1 were highly expressed in the testis in comparison with other tissue. This result showed that ASDmrt1A, ASDmrt2, ASDmrt3, and ASDmrtA1 played an important role in the development of testicle, and may be useful tool in distinguishing between male and female of Chinese sturgeon. Our study will provide a basis for additional analyses of Chinese sturgeon Dmrt genes. This systematic analysis provided a foundation for further functional characterization of Dmrt genes with an aim of study of Chinese sturgeon Dmrt gene family.
Numerical investigations of AC arcs’ thermal characteristics in the short gap of copper-cored wires
Authors: Li Yu , Zhang Rencheng , Yang Kai , Qi Yufan , Tu Ran 
Published: February 2024

AbstractExcessive alternating current (AC) arcs generated in electric systems will accumulate heat and easily cause fire. This paper studies the thermal characteristics of different numbers of AC arc plasma generated in a short gap of copper-cored wires in the air. The number of AC arcs is controlled in the AC arc experiment and an infrared thermal imager measures the temperature change at the specified position. Based on magnetohydrodynamics (MHD), a two-dimensional axisymmetric AC arc discharge numerical simulation model is established. The volt-ampere characteristic of the AC arc is used to solve the MHD simulation model to obtain the same 'zero current' characteristics as the real AC arc in the experiment. A large amount of heat accumulates in the electrode gaps when the arc generation, and then the heat dissipates in the 'zero current' stage. The continuously generated arc makes the temperature higher. The volume of the space area with a temperature higher than 10,000 K increases with the arc current, but is unrelated to the number of arcs. The volume of the space area with a temperature higher than 524.15 K and the temperature on the electrode are both positively correlated with the number of AC arcs and arc current. The results of this study can provide a reference for the detection standard of AC arc faults and the prevention of electrical fire.
Novel tumor marker index using carcinoembryonic antigen and carbohydrate antigen 19-9 is a significant prognostic factor for resectable colorectal cancer
Authors: Kamada Teppei , Ohdaira Hironori , Takahashi Junji , Aida Takashi , Nakashima Keigo , Ito Eisaku , Hata Taigo , Yoshida Masashi , Eto Ken , Suzuki Yutaka 
Published: February 2024

AbstractWe evaluated the usefulness of a newly devised tumor marker index (TMI), namely, the geometric mean of normalized carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9), in determining colorectal cancer (CRC) prognosis. This retrospective cohort study included 306 patients with stages I–III CRC who underwent elective laparoscopic resection between April 2010 and March 2020. Survival rates and risk factors of relapse-free survival (RFS) and cancer-specific survival (CSS) were analyzed using Kaplan–Meier curves and Cox proportional hazards model. High-TMI group (122 patients) had significantly lower rates (95% confidence interval [95% CI]) for 5-year RFS (89.7%, 83.9–93.5 vs. 65.8%, 56.3–73.8, p < 0.001) and CSS (94.9%, 89.4–97.6 vs. 77.3%, 67.7–84.4, p < 0.001) than low-TMI group. Multivariate analysis (hazard ratio [95% CI]) indicated ≥ T3 disease (RFS: 2.69, 1.12–6.45, p = 0.026; CSS: 7.64, 1.02–57.3, p = 0.048), stage III CRC (RFS: 3.30, 1.74–6.28, p < 0.001; CSS: 6.23, 2.04–19.0, p = 0.001), and high TMI (RFS: 2.50, 1.43–4.38, p = 0.001; CSS: 3.80, 1.63–8.87, p = 0.002) as significant RFS and CSS predictors. Area under the curve (AUC) of 5-year cancer deaths (0.739, p < 0.001) was significantly higher for TMI than for CEA or CA19-9 alone. Preoperative TMI is a useful prognostic indicator for patients with resectable CRC.
Introducing a new auto edge detection technique capable of revealing cervical root resorption in CBCT scans with pronounced metallic artifacts
Authors: Khosravifard Negar , Vadiati Saberi Bardia , Khosravifard Amir , Hendi Amirreza , Shadi Kimia , Mihandoust Sanaz , Yousefi Zahra , Mortezaei Tahereh , Ghaffari Mohammad Ebrahim 
Published: February 2024

AbstractCervical resorption is a serious threat to the longevity of the teeth. In this study, the Canny edge-detection algorithm was applied on CBCT images to compare the accuracy of original and Canny views for diagnosing cervical resorption in endodontically treated teeth. Intracanal metallic posts were inserted in 60 extracted teeth being randomly divided into three groups: control, 0.5 mm, and 1 mm cervical resorption. CBCT scans of the teeth were presented to three observers in both original and Canny formats with the accuracy being determined by receiver operating characteristic (ROC) analysis. The DeLong test was used for paired comparisons with the significance level set at 0.05. The highest accuracy belonged to Canny images in 1 mm resorption, followed by Canny images in 0.5 mm resorption, original images in 1 mm resorption, and original images in 0.5 mm resorption, respectively. The Canny images were significantly more accurate in the diagnosis of 0.5 mm (p < 0.001) and 1 mm (p = 0.009) resorption. Application of the Canny edge-detection algorithm could be suggested as a new technique for facilitating the diagnosis of cervical resorption in teeth that are negatively affected by metallic artifacts.
Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs
Authors: Wang Li , Chen Xi , Deng XiangWen , Wen Hao , You MingKe , Liu WeiZhi , Li Qi , Li Jian 
Published: February 2024

AbstractThe use of large language models (LLMs) in clinical medicine is currently thriving. Effectively transferring LLMs’ pertinent theoretical knowledge from computer science to their application in clinical medicine is crucial. Prompt engineering has shown potential as an effective method in this regard. To explore the application of prompt engineering in LLMs and to examine the reliability of LLMs, different styles of prompts were designed and used to ask different LLMs about their agreement with the American Academy of Orthopedic Surgeons (AAOS) osteoarthritis (OA) evidence-based guidelines. Each question was asked 5 times. We compared the consistency of the findings with guidelines across different evidence levels for different prompts and assessed the reliability of different prompts by asking the same question 5 times. gpt-4-Web with ROT prompting had the highest overall consistency (62.9%) and a significant performance for strong recommendations, with a total consistency of 77.5%. The reliability of the different LLMs for different prompts was not stable (Fleiss kappa ranged from −0.002 to 0.984). This study revealed that different prompts had variable effects across various models, and the gpt-4-Web with ROT prompt was the most consistent. An appropriate prompt could improve the accuracy of responses to professional medical questions.