bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of extended-spectrum beta-lactamase and molecular detection of blaTEM, blaSHV, and blaCTX-M genotypes among gram-negative Bacilli isolates from hospital acquired infections in pediatrics, one institutional study
Authors: Elsayed Ahmed Gomaa Ahmed , Badr Dina F. , El Kheir Nermene Youssef Abo , Zaki Maysaa El Sayed , Mossad Abdelrahman Eid Mahmoud , Mahmoud Ehab Mohammed Fahmy 
Published: February 2024

Abstract
Background
Gram-negative bacilli represents an important pathogen in hospital-acquired infections (HAIs) worldwide. The emergence of antibiotic resistance in these pathogens warrants attention for the proper management of infections. Extended-spectrum beta-lactamase (ESBL) resistance represents a major therapeutic problem in infections due to Gram-negative bacilli.
The present study aimed to study the extended-spectrum beta-lactamase genes blaTEM, blaSHV, and blaCTX-M by multiplex polymerase reaction in isolated Gram-negative bacilli from HAIs in pediatric patients.

Methods
The study included one hundred-five isolates of Gram-negative bacilli from pediatric patients with different types of HAIs. The isolates were subjected to full microbiological identification, antibiotics susceptibility by disc diffusion method, the phenotypic study of ESBL, and the genetic study of ESBL genes by multiplex PCR.

Results
Fifty isolates of Gram-Negative bacilli showed ESBL activity by a phenotypic study by double disc diffusion method (50/105). All ESBL producers’ isolates were positive by PCR for ESBL genes. The most frequent gene was blaTEM (64%), followed by blaSHV (30%) and CTX-M (22%). Mixed genes were found in 4 isolates (8%) for blaTEM and blaSHV, blaTEM and CTX-M. There was a significant association between PCR for ESBL genes and phenotypic ESBL detection (P = 0.001). There was significant detection of ESBL genes in E. coli (28%), followed by Enterobacter spp. (26%), Klebsiella spp. (24%), Serratia (14%), Pseudomonas spp. (6%) and Proteus (2%), P = 0.01. There Seventy percent of isolates positive for ESBL production had an insignificant association between MDR and PCR for ESBL genes (P = 0.23).

Conclusion
The present study highlights the prevalence of ESBL activity among clinical isolates of Gram-negative bacilli isolated from hospital-acquired infections in pediatric patients. The most common gene responsible for this activity was blaTEM gee followed by blaSHV and blaCTX-M. There was a high prevalence of multiple antibiotic resistance among isolates with ESBL activity. The finding of the present study denotes the importance of screening extended beta-lactamase among Gram-negative bacilli associated with HAIs in pediatric patients.
Acute fatal ventricular arrhythmia induced by severe hyperkalemia in a toddler with decompensated methylmalonic acidemia
Authors: Hakimzadeh Zahra , Gilani Abolfazl , Yousefichaijan Parsa , Sarmadian Roham 
Published: February 2024

Abstract
Background
Methylmalonic acidemia is a very rare genetic metabolic disease. Patients with isolated methylmalonic acidemia typically present with acute alterations of consciousness, failure to thrive, anorexia, vomiting, respiratory distress, and muscular hypotonia. Despite the evidence-based management, affected individuals experience significant morbidity and mortality. Hyperkalemia is one of the unusual complications of methylmalonic acidemia.

Case presentation
In this paper, we describe a 4-year-old Persian boy with methylmalonic acidemia who developed life-threatening arrhythmia following severe hyperkalemia and metabolic acidosis. Emergent management of the condition was successfully carried out, and the rhythm changed to normal sinus rhythm by effectively reducing the serum potassium level. We discuss the possible etiology of this lethal condition and describe its management on the basis of the available evidence.

Conclusion
During metabolic decompensation in methylmalonic acidemia, frequent blood gas and electrolyte testing to prescribe and adjust therapy and annual echocardiogram and electrocardiogram screening are essential.
Primary thyroid lymphoma: a case series
Authors: Sakhri Saida , Zemni Ines , Ayadi Mohamed Ali , Kamoun Salma , Chargui Riadh , Ben Dhiab Tarek 
Published: February 2024

Abstract
Introduction
Primary Thyroid Lymphoma (PTL) is defined as lymphoma involving the thyroid gland alone or the thyroid gland and adjacent neck lymph nodes without contiguous spread or distant metastases at the time of diagnosis. Most thyroid lymphomas are B cell lymphomas, and 98% of all PTL cases are non-Hodgkin’s lymphoma. It is a rare disease accounting for around 5% of the thyroid neoplasms and 2% of extranodal lymphomas. If properly diagnosed and treated, the prognosis is favorable.

Case presentation
Five cases (three men and two women) of PTL were diagnosed and treated in our institute between January 2005 and September 2019. These are 5 cases of Caucasian origin. The mean age was 76.2 (range: 63–95 years); one patient had associated hypothyroid. One patient had a medical history of breast cancer; one was hypothyroid, and four were euthyroid at the diagnosis. In 4 of these patients, PTL started with compressive symptoms. No patients underwent fine needle aspiration cytology (FNAC) or biopsy for the diagnostic only. In sonography, two cases showed bilateral nodules with goiter; in the three cases it showed nodules in the lobe and isthmus. Technetium-99m scintigraphy was performed on only two patients. Bone Marrow Biopsy (BMB) showed normal cellularity in 4 cases and only one case showed tumor cells. LDH levels were increased in all cases. The extension was evaluated in all patients with cervical and thoracic CT scans, Bone Marrow Biopsy (BMB), beta-2 microglobulin, and serum lactate dehydrogenase (LDH) levels. Three cases were staged as IE and two cases as IIE. Three patients underwent total thyroidectomy; two of them underwent cervical lymph node dissection. Two patients underwent lobectomy. All were diagnosed with lymphoma postoperatively and all were diffuse large B cell lymphoma (DLBCL). One patient completed treatment with R-CHOP (Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone), and two cases received adjuvant chemo-radiotherapy (30 Gy). Two patients died immediately after surgery.

Conclusion
PTL is a rare disease whose diagnosis should be considered in cases of rapidly growing goitres. Timely needle biopsy in suspected cases can avoid unnecessary surgery. Systemic treatment is required, depending on the stage of the tumour.
Efficient crop straws biotreatment using the fungus Cerrena Unicolor GC.u01
Authors: Ying Wang , Chunjing Cai , Junhua Lu , Xuan Li , Zhaojiang Wang , Jie Chu 
Published: February 2024

AbstractLignin is main composition of agricultural biomass which can be decomposed through enzymatic hydrolysis by fungi. However, there are still needs to identify more efficient and effective fungal stain for biomass valorization. In this study, lignin degrading fungi from birch forest were screened for sustainable degradation of waste agricultural straws. The most effective strain was identified as Cerrena unicolor GC.u01 using 18 S rDNA gene-sequencing technology. Three different crop straws (corn stalk, rice and wheat straws) were used for the biotreatment studies. The activities of lignin degrading enzymes, laccase (Lac), cellulase and xylanase, secreted by C. unicolor were also determined. Scanning electron microscopy (SEM), fourier transform infrared spectroscopy (FTIR) and thermal gravimetric analyzer (TGA) were further used to monitor the effects of the biotreatment process. The results showed that C. unicolor degraded 34.3% rice straw lignin, a percentage which was higher than other isolated strains after 15 d straw liquid fermentation. The highest Lac activity (8.396 U•mL− 1) was observed with corn stalk on the 7 d. Cellulase and xylanase activities, in the same biomass, were higher than those of wheat and rice straws after 15 d. Furthermore, SEM, FTIR and TGA analyses showed that C. unicolor pretreatment process had significant effects on corn stalk, rice and wheat straws’ structures. The newly isolated stain of C. unicolor demonstrated high lignin degradation potential that can provide effective, ecofriendly means of valorizing biomass to industrial useable raw-material.
Distributed transmission and optimization of relay-assisted space-air-ground IoT systems
Authors: Sun Ying 
Published: February 2024

AbstractThis paper investigates the integration of relay-assisted Internet of Things (IoT) systems, focusing on the use of multiple relays to enhance the system performance. The central metric of interest in this study is system outage probability, evaluated in terms of latency. Our research provides a comprehensive analysis of system outage probability, considering different relay selection criteria to optimize the system’s transmission performance. Three relay selection strategies are employed to enhance the system transmission performance. Specifically, the first strategy, optimal relay selection, aims to identify the relay that minimizes the latency and maximizes the data transmission reliability. The second approach, partial relay selection, focuses on selecting a subset of relays strategically to balance the system resources and achieve the latency reduction. The third strategy, random relay selection, explores the potential of opportunistic relay selection without prior knowledge. Through a rigorous investigation, our paper evaluates the impact of these relay selection criteria on the performance of relay-assisted edge computing systems. By assessing the system outage probability in relation to latency, we provide valuable insights into the trade-offs and advantages associated with each selection strategy. Our findings contribute to the design and optimization of reliable and efficient edge computing systems, with implications for various applications, including the IoT and intelligent data processing.
RETRACTED ARTICLE: RFID tag recognition model for Internet of Things for training room management
Authors: Wu Shengqi 
Published: February 2024

AbstractWith the rapid development of the Internet of Things and intelligent technology, the application of Radio Frequency Identification (RFID) technology in training room management is becoming increasingly widespread. An efficient and accurate RFID system can significantly improve the management efficiency and resource utilization of the training room, thereby improving teaching quality and reducing management costs. Although RFID technology has many advantages, there are still some problems in practical applications, such as label collision and recognition of unknown labels. These issues not only affect the performance of the system but may also cause interference with actual teaching and management. This study proposes a grouping-based bit arbitration query tree algorithm and anti-collision technology to solve label collisions and reduce label recognition time in the technology. A new unknown label recognition algorithm is also proposed to improve the recognition efficiency and accuracy of identifying new unknown labels. Related experiments have shown that the recognition accuracy of the algorithm designed this time is 95.86%. Compared with other algorithms, the number of idle time slots is the smallest. When the number of queries is 1000, the algorithm has 1842 queries, and the communication complexity is the best. When the number of unknown tags is 10,000, the actual accuracy rate is 95.642%. Compared with traditional recognition algorithms, the new unknown label recognition algorithm has a smaller frame length in the same label proportion and good recognition performance. On a theoretical level, the research content on RFID technology helps to improve and develop the basic theories of the Internet of Things and intelligent recognition technology and provides solutions and application technologies for equipment management and IoT applications in training rooms. On a practical level, the research results can provide specific guidance for the management of training rooms, help solve equipment management and safety maintenance problems in practical applications, and improve the management efficiency of training rooms.
Soybean flower-specific R2R3-MYB transcription factor gene GmMYB108 induces anthocyanin production in Arabidopsis thaliana
Authors: Moon Ju Yeon , Lee Saet Buyl , Jeong Yu Jeong , Lim Gah-Hyun , Shin Gilok , Choi Man-Soo , Kim Jeong Ho , Park Ki Hun , Lee Jiyoung , Jeong Jae Cheol , Kim Cha Young 
Published: February 2024

AbstractR2R3-MYB transcription factors (TFs) are known to play a key role in regulating the expression of structural genes involved in plant flavonoid biosynthesis. However, the regulatory networks and related genes controlling isoflavonoid biosynthesis in soybean are poorly understood. We previously reported that ethephon application increases the production of isoflavonoids in soybean leaves. In this study, we attempted to identify a potential regulatory gene that positively controls isoflavonoid production in response to ethephon treatment in soybean (Glycine max L.). RNA sequencing (RNA-seq) revealed that ethephon application led to the upregulation of 22 genes, including the genes for R2R3-MYB TFs, related to isoflavonoid biosynthesis in soybean plants. Ethephon treatment highly induced the expression of GmMYB108, and its expression was exclusively enriched in flowers as determined using in silico and real-time quantitative PCR analyses. Furthermore, GmMYB108 overexpression resulted in an intense accumulation of anthocyanins as well as total flavonoid production in the leaf tissues of transgenic Arabidopsis plants. In addition, GmMYB108 overexpression increased the transcript levels of several genes involved in the biosynthesis of anthocyanins and their regulatory pathways in Arabidopsis. These results suggest that GmMYB108 is a potential positive regulator of the biosynthesis of flavonoids and anthocyanins in soybean flowers.
Challenges and strategies associated with CAR-T cell therapy in blood malignancies
Authors: Liu Zhaoyun , Lei Wenhui , Wang Hao , Liu Xiaohan , Fu Rong 
Published: February 2024

AbstractCellular immunotherapy, particularly CAR-T cells, has shown potential in the improvement of outcomes in patients with refractory and recurrent malignancies of the blood. However, achieving sustainable long-term complete remission for blood cancer remains a challenge, with resistance and relapse being expected outcomes for many patients. Although many studies have attempted to clarify the mechanisms of CAR-T cell therapy failure, the mechanism remains unclear. In this article, we discuss and describe the current state of knowledge regarding these factors, which include elements that influence the CAR-T cell, cancer cells as a whole, and the microenvironment surrounding the tumor. In addition, we propose prospective approaches to overcome these obstacles in an effort to decrease recurrence rates and extend patient survival subsequent to CAR-T cell therapy.
Multi-omics reveal mechanisms of high enteral starch diet mediated colonic dysbiosis via microbiome-host interactions in young ruminant
Authors: Jin Chunjia , Wu Shengru , Liang Ziqi , Zhang Jun , Lei Xinjian , Bai Hanxun , Liang Gaofeng , Su Xiaodong , Chen Xiaodong , Wang Peiyue , Wang Yue , Guan Leluo , Yao Junhu 
Published: February 2024

AbstractBackgroundAlthough rumen development is crucial, hindgut undertakes a significant role in young ruminants’ physiological development. High-starch diet is usually used to accelerate rumen development for young ruminants, but always leading to the enteral starch overload and hindgut dysbiosis. However, the mechanism behind remains unclear. The combination of colonic transcriptome, colonic luminal metabolome, and metagenome together with histological analysis was conducted using a goat model, with the aim to identify the potential molecular mechanisms behind the disrupted hindgut homeostasis by overload starch in young ruminants.ResultCompared with low enteral starch diet (LES), high enteral starch diet (HES)-fed goats had significantly higher colonic pathology scores, and serum diamine oxidase activity, and meanwhile significantly decreased colonic mucosal Mucin-2 (MUC2) protein expression and fecal scores, evidencing the HES-triggered colonic systemic inflammation. The bacterial taxaPrevotella sp. P4-67,Prevotella sp. PINT, andBacteroides sp. CAG:927, together with fungal taxaFusarium vanettenii,Neocallimastix californiae,Fusarium sp. AF-8,Hypoxylon sp. EC38, andFusarium pseudograminearum, and the involved microbial immune pathways including the “T cell receptor signaling pathway” were higher in the colon of HES goats. The integrated metagenome and host transcriptome analysis revealed that these taxa were associated with enhanced pathogenic ability, antigen processing and presentation, and stimulated T helper 2 cell (TH2)-mediated cytokine secretion functions in the colon of HES goats. Further luminal metabolomics analysis showed increased relative content of chenodeoxycholic acid (CDCA) and deoxycholic acid (DCA), and decreased the relative content of hypoxanthine in colonic digesta of HES goats. These altered metabolites contributed to enhancing the expression of TH2-mediated inflammatory-related cytokine secretion including GATA Binding Protein 3 (GATA3),IL-5, andIL-13. Using the linear mixed effect model, the variation of MUC2 biosynthesis explained by the colonic bacteria, bacterial functions, fungi, fungal functions, and metabolites were 21.92, 20.76, 19.43, 12.08, and 44.22%, respectively. The variation of pathology scores explained by the colonic bacterial functions, fungal functions, and metabolites were 15.35, 17.61, and 57.06%.ConclusionsOur findings revealed that enteral starch overload can trigger interrupted hindgut host-microbiome homeostasis that led to impaired mucosal, destroyed colonic water absorption, and TH2-mediated inflammatory process. Except for the colonic metabolites mostly contribute to the impaired mucosa, the nonnegligible contribution from fungi deserves more future studies focused on the fungal functions in hindgut dysbiosis of young ruminants.
Measuring regularity of human physical activities with entropy models
Authors: Shi Keqin , Chen Zhen , Sun Weiqiang , Hu Weisheng 
Published: February 2024

AbstractRegularity is an important aspect of physical activity that can provide valuable insights into how individuals engage in physical activity over time. Accurate measurement of regularity not only advances our understanding of physical activity behavior but also facilitates the development of human activity modeling and forecasting. Furthermore, it can inform the design and implementation of tailored interventions to improve population health outcomes. In this paper, we aim to assess the regularity of physical activities through longitudinal sensor data, which reflects individuals’ all physical activities over an extended period. We explore three entropy models, including entropy rate, approximate entropy, and sample entropy, which can potentially offer a more comprehensive evaluation of physical activity regularity compared to metrics based solely on periodicity or stability. We propose a framework to validate the performance of entropy models on both synthesized and real-world physical activity data. The results indicate entropy rate is able to identify not only the magnitude and amount of noise but also macroscopic variations of physical activities, such as differences on duration and occurrence time. Simultaneously, entropy rate is highly correlated with the predictability of real-world samples, further highlighting its applicability in measuring human physical activity regularity. Leveraging entropy rate, we further investigate the regularity for 686 individuals. We find the composition of physical activities can partially explain the difference in regularity among individuals, and the majority of individuals exhibit temporal stability of regularity.
Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning
Authors: Li Jing , Othman Mohd Shahizan , Chen Hewan , Yusuf Lizawati Mi 
Published: February 2024

AbstractInternet of Things (IoT) devices are widely used but also vulnerable to cyberattacks that can cause security issues. To protect against this, machine learning approaches have been developed for network intrusion detection in IoT. These often use feature reduction techniques like feature selection or extraction before feeding data to models. This helps make detection efficient for real-time needs. This paper thoroughly compares feature extraction and selection for IoT network intrusion detection in machine learning-based attack classification framework. It looks at performance metrics like accuracy, f1-score, and runtime, etc. on the heterogenous IoT dataset named Network TON-IoT using binary and multiclass classification. Overall, feature extraction gives better detection performance than feature selection as the number of features is small. Moreover, extraction shows less feature reduction compared with that of selection, and is less sensitive to changes in the number of features. However, feature selection achieves less model training and inference time compared with its counterpart. Also, more space to improve the accuracy for selection than extraction when the number of features changes. This holds for both binary and multiclass classification. The study provides guidelines for selecting appropriate intrusion detection methods for particular scenarios. Before, the TON-IoT heterogeneous IoT dataset comparison and recommendations were overlooked. Overall, the research presents a thorough comparison of feature reduction techniques for machine learning-driven intrusion detection in IoT networks.
Advances in CO2 circulation hydrogen carriers and catalytic processes
Authors: Ono Seo , Santra Dines Chandra , Kanega Ryoichi , Kawanami Hajime 
Published: February 2024

AbstractHydrogen serves as a renewable, clean energy carrier, and the critical development of technologies for safer and simpler storage and transportation is imperative for addressing global warming. There is also a growing demand for efforts to capture and utilize CO2 to tackle similar issues. Consequently, considerable attention has been drawn to carriers that chemically store hydrogen. Hydrogen can be stored and released through hydrogenation and dehydrogenation. Notably, the storage and release of hydrogen via CO2 hydrogenation and subsequent dehydrogenation of its hydrogenation product could potentially bolster the future hydrogen economy, rendering it an appealing option as a CO2 circulation hydrogen carrier (CCHC). To leverage CCHC for various applications, a catalytic process enabling the reversible storage and release of hydrogen is essential. This review focuses on CCHC candidates, such as methanol (MeOH), dimethyl ether (DME), and formic acid (FA), summarizing recent catalytic approaches for hydrogen production through pivotal dehydrogenation processes within the CCHC cycle.