bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of patient-derived intestinal organoids for modelling fibrosis in Inflammatory Bowel Disease
Authors: Laudadio Ilaria , Carissimi Claudia , Scafa Noemi , Bastianelli Alex , Fulci Valerio , Renzini Alessandra , Russo Giusy , Oliva Salvatore , Vitali Roberta , Palone Francesca , Cucchiara Salvatore , Stronati Laura 
Published: June 2024

Abstract
Background and aims
Intestinal fibrosis is a common complication of Inflammatory Bowel Disease (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC), but the precise mechanism by which it occurs is incompletely understood hampering the development of effective therapeutic strategies. Here, we aimed at inducing and characterizing an inflammation-mediated fibrosis in patient-derived organoids (PDOs) issued from crypts isolated from colonic mucosal biopsies of IBD pediatric patients and age matched-control subjects (CTRLs).

Methods
Inflammatory-driven fibrosis was induced by exposing CTRL-, CD- and UC-PDOs to the pro-inflammatory cytokine TNF-α for one day, followed by a co-treatment with TNF-α and TGF-β1 for three days. Fibrotic response was proven by analyzing inflammatory and fibrotic markers by RT-qPCR and immunofluorescence. Transcriptomic changes were assessed by RNA-sequencing.

Results
Co-treatment with TNF-α and TGF-β1 caused in CTRL- and IBD-PDOs morphological changes towards a mesenchymal-like phenotype and up-regulation of inflammatory, mesenchymal, and fibrotic markers. Transcriptomic profiling highlighted that in all intestinal PDOs, regardless of the disease, the co-exposure to TNF-α and TGF-β1 regulated EMT genes and specifically increased genes involved in positive regulation of cell migration. Finally, we demonstrated that CD-PDOs display a specific response to fibrosis compared to both CTRL- and UC-PDOs, mainly characterized by upregulation of nuclear factors controlling transcription.

Conclusions
This study demonstrates that intestinal PDOs may develop an inflammatory-derived fibrosis thus representing a promising tool to study fibrogenesis in IBD. Fibrotic PDOs show increased expression of EMT genes. In particular, fibrotic CD-PDOs display a specific gene expression signature compared to UC and CTRL-PDOs.
The intestine microbiota of shrimp and its impact on cultivation
Authors: Zeng Shenzheng , He Jianguo , Huang Zhijian 
Published: June 2024

Abstract
Intestinal microbiome contains several times of functional genes compared to the host and mediates the generation of multiple metabolic products, and therefore it is called “second genome” for host. Crustaceans rank second among the largest subphylum of aquaculture animals that are considered potentially satisfy global substantial food and nutrition security, among which the Pacific white shrimp (Litopenaeus vannamei) ranks the first in the production. Currently, increasing evidences show that outbreaks of some most devastating diseases in shrimp, including white feces syndrome (WFS) and acute hepatopancreatic necrosis disease (AHPND), are related to intestinal microbiota dysbiosis. Importantly, the intestine microbial composition can be altered by environmental stress, diet, and age. In this review, we overview the progress of intestinal microbiota dysbiosis and WFS or ANPHD in shrimp, and how the microbial composition is altered by external factors. Hence, developing suitable microbial micro-ecological prevention and control strategy to maintain intestinal balance may be a feasible solution to reduce the risk of disease outbreaks. Moreover, we highlight that defining the “healthy intestine microbiota” and evaluating the causality of intestinal microbiota dysbiosis and diseases following the logic of “Microecological Koch’s postulates” should be the key goal in future shrimp intestinal field, which help to guide disease diagnosis and prevent disease outbreaks in shrimp farming.

Key points
• Intestinal microbiota dysbiosis is relevant to multiple shrimp diseases.
• Microecological Koch’s postulates help to evaluate the causality of shrimp diseases.
Irreversible Electroporation as a Valid Treatment Option for Hepatic Epithelioid Hemangioendothelioma: An International Multicenter Experience
Authors: Narayanan Govindarajan , Spano Anthony , Gentile Nicole T. , Shnayder-Adams Michelle M. , Gurusamy Varshana , Levi David M. , Wilky Breelyn A. , Mora Ronald A. , Noman Raihan , Peddu Praveen , Dijkstra Madelon 
Published: June 2024

Abstract
Purpose
Hepatic epithelioid hemangioendothelioma (HEHE) is a rare tumor with currently no established standard of care. This international multicenter retrospective study assesses the use of percutaneous irreversible electroporation (IRE) as an ablative tool to treat HEHE and provides a clinical overview of the current management and role of IRE in HEHE treatment.

Material and Methods
Between 2017 and 2023, 14 patients with 47 HEHE tumors were treated with percutaneous IRE using CT-scan guidance in 23 procedures. Baseline patient and tumor characteristics were evaluated. Primary outcome measures included safety and effectiveness, analyzed using Common Terminology Criteria for Adverse Events (CTCAE) and treatment response by mRECIST criteria. Secondary outcome measures included technical success, post-treatment tumor sizes and length of hospital stay. Technical success was defined as complete ablation with an adequate ablative margin (intentional tumor free ablation margin > 5 mm).

Results
IRE treatment resulted in technical success in all tumors. Following a median follow-up of 15 months, 30 tumors demonstrated a complete response according to mRECIST criteria. The average tumor size pre-treatment was 25.8 mm, accompanied by an average reduction in tumor size by 7.5 mm. In 38 out of 47 tumors, there was no evidence of local recurrence. In nine tumors, residual tumor was present. There were no cases of progressive disease. Median length of hospital stay was one day. Only one grade 3 CTCAE event occurred, a pneumothorax requiring chest tube placement.

Conclusion
The current study provides evidence that IRE is a safe and efficacious minimally invasive treatment option for HEHE.

Graphical Abstract
Comparing field-scale eddy covariance measurements and crop coefficient estimates of alfalfa evapotranspiration to OpenET model estimates and exploring water budget implications in a dryland environment
Authors: Sabiston Liam , Sabie Robert , Buenemann Michaela , Stringam Blair , Fernald Alexander 
Published: June 2024

AbstractRemote sensing evapotranspiration (ET) models have the potential to be powerful tools for water planning and management, particularly for agriculture. OpenET is an emerging web-based tool that uses satellite imagery and climate data for calculating six distinct ET models, and an ensemble model of the six models, to provide estimates of actual ET (ETa) which is useful for field-scale irrigation management decisions. Previous studies examining the performance of individual models included in the OpenET platform showed some models used in OpenET consistently predicted lower values of ETa in dryland regions relative to in-situ measurements. The OpenET research team has made modifications to address these isues. There are few studies examining if the modified models included in OpenET sill produce lower values of ETa compared to field values in dryland environments. This study compared satellite-based OpenET estimates of ETa from three alfalfa fields in the Mesilla Valley, New Mexico, USA–one field with measurements of ETa from an eddy covariance tower and two fields with estimated crop evapotranspiration (ETc)–during the 2017 growing season to investigate if OpenET ETa estimates demonstrate an underestimation bias. OpenET ETa estimates were tested against in-situ ETa measurements and ETc estimates using two sample t-tests and Mann-Whitey U tests to determine if there were any significant differences in means between the two groups. Model seasonal percent mean bias error ranged from −33.99 to +11.37%. eeMETRIC and SIMS seasonal estimates were within ±15% of in-situ measurements at any of the three sites and within ±10% of in-situ measurements on average. SSEBop and DisALEXI produced significantly different monthly ETa estimates (p-values < 0.05) when data were extracted using the OpenET field polygons. The results of the small sample of fields suggest the OpenET models may estimate lower values of ETa relative to the field data. Future research should improve the methodology for assessing accuracy of OpenET in small agricultural fields in the western United States.
Post Covid telogen effluvium: the diagnostic value of serum ferritin biomarker and the preventive value of dietary supplements. a case control study
Authors: Bedair Nermeen Ibrahim , Abdelaziz Alaa Safwat , Abdelrazik Fatemaalzahraa Saad , El-kassas Mohamed , AbouHadeed Mohamed Hussein 
Published: June 2024

AbstractTelogen effluvium is characterized by excessive hair shedding usually following a stressful event. Ferritin has been used in clinical practice as a biomarker of nonanemic iron deficiency in cases of telogen effluvium. During the years of the COVID19 pandemic, telogen effluvium was reported as a part of post covid manifestations. As ferritin was also a biomarker for inflammation in cases with covid infection, this study was designed to evaluate the value of ferritin in cases with postcovid telogen effluvium one hundred patients recovering from covid 19 for 4–12 weeks were included in the study, detailed drug and laboratory history was obtained and serum ferritin level was measured. the mean serum level of ferritin among telogen effluvium patients was significantly lower than controls (68.52 ± 126 and 137 ± 137.597 ug/L respectively). Patients with telogen effluvium used significantly more azithromycin and ivermectin and significantly less vitamin C, D, lactoferrin and zinc than the controls Although serum ferritin is lower among telogen effluvium patients, it was still higher than the cutoff value for diagnosing nonanemic iron deficiency, we suggest that it will not be a good biomarkers in these cases. Our secondary outcomes showed that dietary supplements used during active infection such as vitamin C, D, lactoferrin and zinc might have a preventive value on postcovid hair loss, while azithromycin and ivermectin could have a negative long term effect on telogen effluvium.
Robotic surgery versus Laparoscopic surgery for anti-reflux and hiatal hernia surgery: a short-term outcomes and cost systematic literature review and meta‐analysis
Authors: Gonçalves-Costa Diogo , Barbosa José Pedro , Quesado Rodrigo , Lopes Vítor , Barbosa José 
Published: June 2024

Abstract
Purpose
The objective of this study is to compare the operative time, intraoperative complications, length of stay, readmission rates, overall complications, mortality, and cost associated with Robotic Surgery (RS) and Laparascopic Surgery (LS) in anti-reflux and hiatal hernia surgery.

Methods
A comprehensive literature search was conducted using MEDLINE (via PubMed), Web of Science and Scopus databases. Studies comparing short-term outcomes and cost between RS and LS in patients with anti-reflux and hiatal hernia were included. Data on operative time, complications, length of stay, readmission rates, overall complications, mortality, and cost were extracted. Quality assessment of the included studies was performed using the MINORS scale.

Results
Fourteen retrospective observational studies involving a total of 555,368 participants were included in the meta-analysis. The results showed no statistically significant difference in operative time, intraoperative complications, length of stay, readmission rates, overall complications, and mortality between RS and LS. However, LS was associated with lower costs compared to RS.

Conclusion
This systematic review and meta-analysis demonstrates that RS has non-inferior short-term outcomes in anti-reflux and hiatal hernia surgery, compared to LS. LS is more cost-effective, but RS offers potential benefits such as improved visualization and enhanced surgical techniques. Further research, including randomized controlled trials and long-term outcome studies, is needed to validate and refine these findings.
Is complementary medicine and diagnosis associated among spinal patients in the secondary sector: a cross-sectional study
Authors: Ziegler Dorthe Schoeler , O’Neill Soeren Francis Dyhrberg , Have Kirstine Vest , Hildebrand Sabine Gantzhorn 
Published: June 2024

Abstract
Purpose
The services defined as complementary and alternative medicine/healthcare (CAM) are used to varying degrees according to the nature of the health problem, and musculoskeletal disorders, in particular, often lead to the use of CAM. Chronic pain is often cited as a reason for using CAM, and it is also the cardinal symptom of patients with back pain referred for specialist care. However, previous studies do not consider the heterogeneity of back pain when examining the use of CAM. Thus, this study aimed to explore the associations between CAM use and clinical findings incl. ICD-10 diagnostic codes in such a context.

Methods
In a cross-sectional study, a logistic regression analysis examined associations between CAM use and clinical findings at a public outpatient spine department. Chi-squared test examined the association between self-reported reasons for CAM use and the diagnostic groups.

Results
Of the 432 patients in the study population, 23.8% reported using CAM within 12 months prior to clinical assessment. CAM use was associated with being female and of younger age. Seeking CAM was not associated with clinical findings nor diagnosis, and no statistically significant association between the reasons for seeking CAM and the diagnostic groups was described.

Conclusions
Among patients referred to specialist care for back pain, this study provides no evidence that the spinal condition should be expected to lead to the use of CAM. Only the individual demographic findings, specifically age and gender, were associated with CAM use.
Zika virus infection suppresses CYP24A1 and CAMP expression in human monocytes
Authors: Hernández-Sarmiento Lady Johana , Valdés-López Juan Felipe , Urcuqui-Inchima Silvio 
Published: June 2024

AbstractMonocytes are the primary targets of Zika virus (ZIKV) and are associated with ZIKV pathogenesis. Currently, there is no effective treatment for ZIKV infection. It is known that 1,25-dihydroxy vitamin D3 (VitD3) has strong antiviral activity in dengue virus-infected macrophages, but it is unknown whether VitD3 inhibits ZIKV infection in monocytes. We investigated the relationship between ZIKV infection and the expression of genes of the VitD3 pathway, as well as the inflammatory response of infected monocytes in vitro. ZIKV replication was evaluated using a plaque assay, and VitD3 pathway gene expression was analyzed by RT-qPCR. Pro-inflammatory cytokines/chemokines were quantified using ELISA. We found that VitD3 did not suppress ZIKV replication. The results showed a significant decrease in the expression of vitamin D3 receptor (VDR), cytochrome P450 family 24 subfamily A member 1 (CYP24A1), and cathelicidin antimicrobial peptide (CAMP) genes upon ZIKV infection. Treatment with VitD3 was unable to down-modulate production of pro-inflammatory cytokines, except TNF-α, and chemokines. This suggests that ZIKV infection inhibits the expression of VitD3 pathway genes, thereby preventing VitD3-dependent inhibition of viral replication and the inflammatory response. This is the first study to examine the effects of VitD3 in the context of ZIKV infection, and it has important implications for the role of VitD3 in the control of viral replication and inflammatory responses during monocyte infection.
Plasma d-asparagine and the d/l-serine ratio reflect chronic kidney diseases in children regardless of physique
Authors: Morishita Toshimasa , Nishizaki Naoto , Taniguchi Sakiko , Sakai Shinsuke , Kimura Tomonori , Mita Masashi , Nakagawa Mayu , Endo Amane , Ohtomo Yoshiyuki , Yasui Masato , Shimizu Toshiaki , Sasabe Jumpei 
Published: June 2024

AbstractBiomarkers that accurately reflect renal function are essential in management of chronic kidney diseases (CKD). However, in children, age/physique and medication often alter established renal biomarkers. We studied whether amino acid enantiomers in body fluids correlate with renal function and whether they are influenced by physique or steroid medication during development. We conducted a prospective study of children 2 to 18 years old with and without CKD. We analyzed associations of serine/asparagine enantiomers in body fluids with major biochemical parameters as well as physique. To study consequences of kidney dysfunction and steroids on serine/asparagine enantiomers, we generated juvenile mice with uninephrectomy, ischemic reperfusion injury, or dexamethasone treatment. We obtained samples from 27 children, of which 12 had CKD due to congenital (n = 7) and perinatal (n = 5) causes. Plasma d-asparagine and the d/l-serine ratio had robust, positive linear associations with serum creatinine and cystatin C, and detected CKD with high sensitivity and specificity, uninfluenced by body size or biochemical parameters. In the animal study, kidney dysfunction increased plasma d-asparagine and the d/l-serine ratio, but dexamethasone treatment did not. Thus, plasma d-asparagine and the d/l-serine ratio can be useful markers for renal function in children.
Equilibrium optimizer-based harmony search algorithm with nonlinear dynamic domains and its application to real-world optimization problems
Authors: Wang Jinglin , Ouyang Haibin , Li Steven , Ding Weiping , Gao Liqun 
Published: June 2024

AbstractHarmony Search (HS) algorithm is a swarm intelligence algorithm inspired by musical improvisation. Although HS has been applied to various engineering problems, it faces challenges such as getting trapped in local optima, slow convergence speed, and low optimization accuracy when applied to complex problems. To address these issues, this paper proposes an improved version of HS called Equilibrium Optimization-based Harmony Search Algorithm with Nonlinear Dynamic Domains (EO-HS-NDD). EO-HS-NDD integrates multiple leadership-guided strategies from the Equilibrium Optimizer (EO) algorithm, using harmony memory considering disharmony and historical harmony memory, while leveraging the hidden guidance direction information from the Equilibrium Optimizer. Additionally, the algorithm designs a nonlinear dynamic convergence domain to adaptively adjust the search space size and accelerate convergence speed. Furthermore, to balance exploration and exploitation capabilities, appropriate adaptive adjustments are made to Harmony Memory Considering Rate (HMCR) and Pitch Adjustment Rate (PAR). Experimental validation on the CEC2017 test function set demonstrates that EO-HS-NDD outperforms HS and nine other HS variants in terms of robustness, convergence speed, and optimization accuracy. Comparisons with advanced versions of the Differential Evolution (DE) algorithm also indicate that EO-HS-NDD exhibits superior solving capabilities. Moreover, EO-HS-NDD is applied to solve 15 real-world optimization problems from CEC2020 and compared with advanced algorithms from the CEC2020 competition. The experimental results show that EO-HS-NDD performs well in solving real-world optimization problems.
Plant disease management: a fine-tuned enhanced CNN approach with mobile app integration for early detection and classification
Authors: Iftikhar Mudassir , Kandhro Irfan Ali , Kausar Neha , Kehar Asadullah , Uddin Mueen , Dandoush Abdulhalim 
Published: June 2024

AbstractFarmers face the formidable challenge of meeting the increasing demands of a rapidly growing global population for agricultural products, while plant diseases continue to wreak havoc on food production. Despite substantial investments in disease management, agriculturists are increasingly turning to advanced technology for more efficient disease control. This paper addresses this critical issue through an exploration of a deep learning-based approach to disease detection. Utilizing an optimized Convolutional Neural Network (E-CNN) architecture, the study concentrates on the early detection of prevalent leaf diseases in Apple, Corn, and Potato crops under various conditions. The research conducts a thorough performance analysis, emphasizing the impact of hyperparameters on plant disease detection across these three distinct crops. Multiple machine learning and pre-trained deep learning models are considered, comparing their performance after fine-tuning their parameters. Additionally, the study investigates the influence of data augmentation on detection accuracy. The experimental results underscore the effectiveness of our fine-tuned enhanced CNN model, achieving an impressive 98.17% accuracy in fungal classes. This research aims to pave the way for more efficient plant disease management and, ultimately, to enhance agricultural productivity in the face of mounting global challenges. To improve accessibility for farmers, the developed model seamlessly integrates with a mobile application, offering immediate results upon image upload or capture. In case of a detected disease, the application provides detailed information on the disease, its causes, and available treatment options.
Automated requirement contradiction detection through formal logic and LLMs
Authors: Gärtner Alexander Elenga , Göhlich Dietmar 
Published: June 2024

AbstractThis paper introduces ALICE (Automated Logic for Identifying Contradictions in Engineering), a novel automated contradiction detection system tailored for formal requirements expressed in controlled natural language. By integrating formal logic with advanced large language models (LLMs), ALICE represents a significant leap forward in identifying and classifying contradictions within requirements documents. Our methodology, grounded on an expanded taxonomy of contradictions, employs a decision tree model addressing seven critical questions to ascertain the presence and type of contradictions. A pivotal achievement of our research is demonstrated through a comparative study, where ALICE’s performance markedly surpasses that of an LLM-only approach by detecting 60% of all contradictions. ALICE achieves a higher accuracy and recall rate, showcasing its efficacy in processing real-world, complex requirement datasets. Furthermore, the successful application of ALICE to real-world datasets validates its practical applicability and scalability. This work not only advances the automated detection of contradictions in formal requirements but also sets a precedent for the application of AI in enhancing reasoning systems within product development. We advocate for ALICE’s scalability and adaptability, presenting it as a cornerstone for future endeavors in model customization and dataset labeling, thereby contributing a substantial foundation to requirements engineering.