bluuebunny/crossref_metadata_2025 huggingface dataset:
Loss of symbiotic and increase of virulent bacteria through microbial networks in Lynch syndrome colon carcinogenesis
Authors: Sadeghi Mohammad , Mestivier Denis , Carbonnelle Etienne , Benamouzig Robert , Khazaie Khashayarsha , Sobhani Iradj
Published: February 2024

Purpose

Through a pilot study, we performed whole gut metagenomic analysis in 17 Lynch syndrome (LS) families, including colorectal cancer (CRC) patients and their healthy first-degree relatives. In a second asymptomatic LS cohort (n=150) undergoing colonoscopy-screening program, individuals with early precancerous lesions were compared to those with a normal colonoscopy. Since bacteria are organized into different networks within the microbiota, we compared related network structures in patients and controls.

Experimental design

Fecal prokaryote DNA was extracted prior to colonoscopy for whole metagenome (n=34, pilot study) or 16s rRNA sequencing (validation study). We characterized bacteria taxonomy using Diamond/MEGAN6 and DADA2 pipelines and performed differential abundances using Shaman website. We constructed networks using SparCC inference tools and validated the construction’s accuracy by performing qPCR on selected bacteria.

Results

Significant differences in bacterial communities in LS-CRC patients were identified, with an enrichment of virulent bacteria and a depletion of symbionts compared to their first-degree relatives. Bacteria taxa in LS asymptomatic individuals with colonic precancerous lesions (n=79) were significantly different compared to healthy individuals (n=71). The main bacterial network structures, constructed based on bacteria-bacteria correlations in CRC (pilot study) and in asymptomatic precancerous patients (validation-study), showed a different pattern than in controls. It was characterized by virulent/symbiotic co-exclusion in both studies and illustrated (validation study) by a higher Escherichia/Bifidobacterium ratio, as assessed by qPCR.

Conclusion

Enhanced fecal virulent/symbiotic bacteria ratios influence bacterial network structures. As an early event in colon carcinogenesis, these ratios can be used to identify asymptomatic LS individual with a higher risk of CRC.
TGFβ level in healthy and children with Marfan syndrome—effective reduction under sartan therapy
Authors: Stark Veronika C. , Olfe Jakob , Diaz-Gil Daniel , von Kodolitsch Yskert , Kozlik-Feldmann Rainer , Reincke Johannes , Stark Maria , Wiegand Peter , Zeller Tanja , Mir Thomas S.
Published: February 2024

Introduction

Transforming growth factor β (TGFβ) metabolism plays an important role in the pathogenesis of Marfan syndrome (MFS). Accordingly, drug therapy uses TGFβ receptor blockade to slow down the cardiovascular manifestations, above all aortic root dilatation. Angiotensin II type 1 receptor blockers (ARBs) have been shown to reduce TGFβ levels in adults. Data on childhood are lacking and are now being investigated in the TiGer For Kids study presented here.

Methods

We examined 125 children without chronic disease and 31 pediatric Marfan patients with a proven FBN1 variant with regard to TGFβ levels. In addition, we measured TGFβ levels during the initiation of ARB therapy in pediatric Marfan patients.

Results

In children without chronic disease, TGFβ levels were found to decrease from childhood to adolescence (p < 0.0125). We could not measure a relevantly increased TGFβ level in pediatric Marfan patients. However, we showed a significant suppression of the TGFβ level after treatment with ARBs (p < 0.0125) and a renewed increase shortly before the next dose.

Discussion

The TGFβ level in childhood changes in an age-dependent manner and decreases with age. The TGFβ level drops significantly after taking ARBs. Based on our experience and data, a TGFβ receptor blockade in childhood seems reasonable. So far, TGFβ level cannot be used as an MFS screening biomarker.
Data reduction and processing for photon science detectors
Authors: Pennicard David , Rahmani Vahid , Graafsma Heinz
Published: February 2024

New detectors in photon science experiments produce rapidly-growing volumes of data. For detector developers, this poses two challenges; firstly, raw data streams from detectors must be converted to meaningful images at ever-higher rates, and secondly, there is an increasing need for data reduction relatively early in the data processing chain. An overview of data correction and reduction is presented, with an emphasis on how different data reduction methods apply to different experiments in photon science. These methods can be implemented in different hardware (e.g., CPU, GPU or FPGA) and in different stages of a detector’s data acquisition chain; the strengths and weaknesses of these different approaches are discussed.
A non-canonical Aux/IAA gene MsIAA32 regulates peltate glandular trichome development in spearmint
Authors: Reddy Vaishnavi Amarr , Saju Jolly Madathiparambil , Nadimuthu Kumar , Sarojam Rajani
Published: February 2024

Phytohormone auxin controls various aspects of plant growth and development. The typical auxin signalling involves the degradation of canonical Aux/IAA proteins upon auxin perception releasing the auxin response factors (ARF) to activate auxin-regulated gene expression. Extensive research has been pursued in deciphering the role of canonical Aux/IAAs, however, the function of non-canonical Aux/IAA genes remains elusive. Here we identified a non-canonical Aux/IAA gene, MsIAA32 from spearmint (Mentha spicata), which lacks the TIR1-binding domain and shows its involvement in the development of peltate glandular trichomes (PGT), which are the sites for production and storage of commercially important essential oils. Using yeast two-hybrid studies, two canonical Aux/IAAs, MsIAA3, MsIAA4 and an ARF, MsARF3 were identified as the preferred binding partners of MsIAA32. Expression of a R2R3-MYB gene MsMYB36 and a cyclin gene MsCycB2-4 was altered in MsIAA32 suppressed plants indicating that these genes are possible downstream targets of MsIAA32 mediated signalling. Ectopic expression of MsIAA32 in Arabidopsis affected non-glandular trichome formation along with other auxin related developmental traits. Our findings establish the role of non-canonical Aux/IAA mediated auxin signalling in PGT development and reveal species-specific functionalization of Aux/IAAs.
Core and bridge symptoms of demoralization in Chinese female cancer patients: a network analysis
Authors: Gong Yijing , Shang Bin , Tan Jianing , Luo Caifeng , Bian Zekun , Wu Xiaoxiang , Fan Tingting , Zhao Qian , Liu Lili , Sun Weiyi
Published: February 2024

Objective

In this study, we explore the core and bridge symptoms of demoralization in female cancer patients in China, and provide a basis for precise psychological intervention among female cancer patients.

Methods

This study used a cross-sectional survey. Participants were recruited from three third-class hospitals in Jiangsu Province from June 2022 to June 2023 using the convenience sampling method. The severity of each symptom of demoralization was investigated in female cancer patients using the Demoralization Scale (DS). Network analysis was performed using the R language to identify core and bridge symptoms in the network and further explore some characteristic edge connections in the network.

Results

The network structure model of demoralization had strong accuracy and stability. In the network, the symptoms with the highest strength centrality were “Discouragement” (C3, strength=2.19), “No self-worth” (A3, strength=1.21), “Don’t want to live” (A5, strength=1.20), “Hopeless” (D4, strength=0.81), and “Vulnerability” (B3, strength=0.74), respectively. The bridge strength analysis identified “Hopeless” (D4, bridge strength=0.92), “Discouragement” (C3, bridge strength=0.85), “No self-worth” (A3, bridge strength=0.75), “Poor spirits” (E2, bridge strength=0.71), and “Vulnerability” (B3, bridge strength=0.69) as the bridge symptoms. The strongest edge connections of all dimensions were “No self-worth” and “Worthless” (A3—E6, edge weighting=0.27), “Poor spirits” and “Loss of emotional control” (E2—D1, edge weighting=0.22), “Discouragement” and “Vulnerability” (C3—B3, edge weighting=0.14), and “Hopeless” and “No meaning of survival” (D4—A4, edge weighting=0.12).

Conclusion

“Discouragement (C3)”, “No self-worth (A3)”, “Hopeless (D4)”, and “Vulnerability (B3)” are both core symptoms and bridge symptoms. These symptoms can not only trigger a patient’s demoralization but also stimulate more severe symptom clusters through interactions. The early recognition of and intervention regarding these symptoms could be important for the prevention and treatment of demoralization among female cancer patients.
The context of COVID-19 affected the long-term sleep quality of older adults more than SARS-CoV-2 infection
Authors: Peixoto Vanessa Giffoni M. N. P. , Facci Lucas Alves , Barbalho Thiago C. S. , Souza Raíssa Nascimento , Duarte Alice Mendes , Almondes Katie Moraes
Published: February 2024

Introduction

Sleep problems are one of the most persistent symptoms of post-COVID syndrome in adults. However, most recent research on sleep quality has relied on the impact of the pandemic, with scarcely any data for older adults on the long-term consequences of COVID infection. This study aims to understand whether older individuals present persistently impaired sleep quality after COVID-19 infection and possible moderators for this outcome.

Methods

This is a cross-sectional analysis of a longitudinal cohort study with 70 elders with 6-month-previous SARS-CoV-2 infection and 153 controls. The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality; Geriatric Depression Scale and Geriatric Anxiety Inventory for screening depression and anxiety. Demographics and comorbid conditions were collected.

Results

The mean age of participants was 66,97 ± 4,64 years. There were no statistical differences in depression and anxiety between groups. Poor sleep quality was found in 52,9% and 43,8% of the COVID and control groups (p=.208). After controlling for multiple variables, all the following factors resulted in greater chances of poor sleep quality: female gender (OR, 2.12; p=.027), memory complaints (OR, 2.49; p=.074), insomnia (OR, 3.66; p=.032), anxiety (OR, 5.46; p<.001), depression (OR, 7.26; p=.001), joint disease (OR, 1.80; p=.050), glucose intolerance (OR, 2.20; p=.045), psychoactive drugs (OR, 8.36; p<.001), diuretics (OR, 2.46; p=.034), and polypharmacy (OR, 2.84; p=.016).

Conclusion

Psychosocial burden in the context of the COVID-19 pandemic and pre-existing conditions seems to influence the sleep quality of older adults more than SARS-CoV-2 infection.
Analyzing global utilization and missed opportunities in debt-for-nature swaps with generative AI
Authors: Tkachenko Nataliya , Frieder Simon , Griffiths Ryan-Rhys , Nedopil Christoph
Published: February 2024

We deploy a prompt-augmented GPT-4 model to distill comprehensive datasets on the global application of debt-for-nature swaps (DNS), a pivotal financial tool for environmental conservation. Our analysis includes 195 nations and identifies 21 countries that have not yet used DNS before as prime candidates for DNS. A significant proportion demonstrates consistent commitments to conservation finance (0.86 accuracy as compared to historical swaps records). Conversely, 35 countries previously active in DNS before 2010 have since been identified as unsuitable. Notably, Argentina, grappling with soaring inflation and a substantial sovereign debt crisis, and Poland, which has achieved economic stability and gained access to alternative EU conservation funds, exemplify the shifting suitability landscape. The study's outcomes illuminate the fragility of DNS as a conservation strategy amid economic and political volatility.
Unlocking the paracetamol adsorption mechanism in graphene tridimensional-based materials: an experimental-theoretical approach
Authors: de Matos Carolina F. , Leão Mayara B. , Vendrame Laura F. O. , Jauris Iuri M. , Zanella Ivana , Fagan Solange B.
Published: February 2024

The omnipresence of emerging contaminants in the aquatic environment is indisputable. These contaminants include chemical substances not removed in traditional water and sewage treatment processes. To ensure the quality of water and healthy aquatic ecosystems, new treatment technologies and materials are essential to effectively control the presence of these contaminants in the aquatic environment. More than that, it is important to know how molecules interact with these new materials. A low-cost alternative currently available is adsorption. Despite this method being widely studied, describing the interaction mechanisms between the materials and the analytes is not usual, limiting the obtainment of more efficient materials. Thus, the objective of this work was to understand, in a theoretical-experimental way, the forms of interaction in the adsorption of the drug paracetamol, widely used worldwide, in materials based on graphene with different chemical and structural properties. For this, kinetic and isothermal experimental studies were carried out using four materials that contemplated different dimensions, pore sizes, and oxidation degrees. In theoretical studies, density functional theory (DFT) simulations were performed to cover quantum details, revealing how paracetamol interacts with different graphene structures. According to theoretical studies, binding energies, binding distances, and charge transfer between oxidized graphene and paracetamol drug are compatible with physical adsorption, strongly dependent on the type and number of functional groups on the graphene surface. These results agree with the experimental data where the highest adsorptions were observed precisely for materials containing a higher proportion of functional groups and where these groups are more available (more porous), with adsorptive capacities reaching 235.7 mg/g. Our findings contribute to scientific knowledge about using graphene structures as an adsorbent material, providing a solid basis for future studies and developing more efficient and advanced water treatment technologies.
Interactions with virtual therapists during motor rehabilitation in immersive virtual environments: a systematic review
Authors: Crowe Stephanie Elena , Yousefi Mamehgol , Shahri Bahareh , Piumsomboon Thammathip , Hoermann Simon
Published: February 2024

Introduction: Virtual Reality applications for rehabilitation are increasing in popularity. In traditional as well as virtual rehabilitation, the guidance of an occupational therapist through physical and verbal interaction is often required. Several studies have attempted to implement a virtual therapist or assistant in immersive virtual environments for rehabilitation.

Objective: This research aims to systematically review these studies, understanding the therapist’s role and how they are represented in the virtual environment, how the virtual therapist and patient interact and the experience of users. Our goal is to provide guidance for virtual therapist implementations into fully immersive virtual reality environments.

Method: The researchers systematically reviewed the literature on virtual therapists in immersive virtual environments for motor rehabilitation (protocol prospectively registered with PROSPERO ID: CRD42022357369).

Results and Conclusion: Seven studies were identified, with findings showing that virtual therapists are often human-like avatars that guide patients, requiring them to mimic the therapist’s movements. Visual, haptic, or one-direction audio feedback from the therapist to the patient was provided in five studies. The selected studies were all newly developed custom-made systems, with five systems developed using the same game engine. Studies carrying out user testing utilised several methods to understand user experience, evidencing a positive attitude from therapists and motivated and satisfied patients.

Future Research: The roles of virtual therapists for motor rehabilitation needs to be explored further in rigorous empirical studies to gather data on patient and therapist user experience. Considerable potential was identified in the development of virtual therapists and therapeutic alliance in the virtual environment. Future systems should reduce manual input from therapists and include personalisation and individualised patient feedback.

Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=357369], PROSPERO ID [CRD42022357369].
The application of extended reality technology-assisted intraoperative navigation in orthopedic surgery
Authors: Bian Dongxiao , Lin Zhipeng , Lu Hao , Zhong Qunjie , Wang Kaifeng , Tang Xiaodong , Zang Jie
Published: February 2024

Extended reality (XR) technology refers to any situation where real-world objects are enhanced with computer technology, including virtual reality, augmented reality, and mixed reality. Augmented reality and mixed reality technologies have been widely applied in orthopedic clinical practice, including in teaching, preoperative planning, intraoperative navigation, and surgical outcome evaluation. The primary goal of this narrative review is to summarize the effectiveness and superiority of XR-technology-assisted intraoperative navigation in the fields of trauma, joint, spine, and bone tumor surgery, as well as to discuss the current shortcomings in intraoperative navigation applications. We reviewed titles of more than 200 studies obtained from PubMed with the following search terms: extended reality, mixed reality, augmented reality, virtual reality, intraoperative navigation, and orthopedic surgery; of those 200 studies, 69 related papers were selected for abstract review. Finally, the full text of 55 studies was analyzed and reviewed. They were classified into four groups—trauma, joint, spine, and bone tumor surgery—according to their content. Most of studies that we reviewed showed that XR-technology-assisted intraoperative navigation can effectively improve the accuracy of implant placement, such as that of screws and prostheses, reduce postoperative complications caused by inaccurate implantation, facilitate the achievement of tumor-free surgical margins, shorten the surgical duration, reduce radiation exposure for patients and surgeons, minimize further damage caused by the need for visual exposure during surgery, and provide richer and more efficient intraoperative communication, thereby facilitating academic exchange, medical assistance, and the implementation of remote healthcare.
Hands-Only Cardiopulmonary Resuscitation Education for Elementary School Students in Korea: Tracking by School Grade, Physical Characteristics, and Physical Strength
Authors: Ko Jang Sik , Kim Seon Rye , Cho Byung Jun
Published: February 2024

Objectives: This study aimed to assess variations in chest compression depth among Korean elementary school students based on grade, physical characteristics, and strength.

Methods: The study involved 140 children in the third to sixth grades from elementary schools. Before providing cardiopulmonary resuscitation (CPR) education, we assessed height, weight, BMI, grip strength, and back strength. Subsequently, CPR education was administered, followed by individual measurements of compression depth. The factors related to compression depths was analyzed using t-test, ANOVA and multivariable regression.

Results: The mean compression depth was consistently lower than the guideline standard across all grades, indicating grade-dependent differences (p = 0.000). Moreover, height, weight, BMI, grip strength and back strength increased, exhibited significant increases with grade (p = 0.000). In multivariable regression analysis, it was observed that as grade increased, chest compression depth increased by 0.701 cm (p = 0.000).

Conclusion: School grade significantly influenced achieving the proper chest compressions depth, no notable correlation found for physical factors. Thus, a strategy emphasizing the importance of sufficient chest compressions during CPR education, particularly targeting elementary school students, seems necessary to encourage greater effort.
Multiphysics Modeling of a Synthetic Jet Actuator in Operation
Authors: Butler Matthew G. M. , Ekmekci Alis , Sullivan Pierre E.
Published: February 2024

Active flow control is a promising technology for reducing noise, emissions, and power consumption in various applications. To better understand the performance of synthetic jet actuators, a computational model that couples structural mechanics with electrostatics, pressure acoustics, and fluid dynamics is needed. The model presented here was validated against experimental data and then used to investigate the fluid behavior inside and outside the synthetic jet actuator cavity, the impacts of thermoviscous losses on capturing the acoustic response of the actuator, and the viability of different modeling methods of diaphragms in computational simulations. The results capture the feedback from the fluid onto the diaphragm and highlight the need for careful acoustic modeling.
Mission-Driven Inverse Design of Blended Wing Body Aircraft with Machine Learning
Authors: Sharma Rohan S. , Hosder Serhat
Published: February 2024

The intent of this work was to investigate the feasibility of developing machine learning models for calculating values of airplane configuration design variables when provided time-series, mission-informed performance data. Shallow artificial neural networks were developed, trained, and tested using data pertaining to the blended wing body (BWB) class of aerospace vehicles. Configuration design parameters were varied using a Latin-hypercube sampling scheme. These data were used by a parametric-based BWB configuration generator to create unique BWBs. Performance for each configuration was obtained via a performance estimation tool. Training and testing of neural networks was conducted using a K-fold cross-validation scheme. A random forest approach was used to determine the values of predicted configuration design variables when evaluating neural network accuracy across a blended wing body vehicle survey. The results demonstrated the viability of leveraging neural networks in mission-dependent, inverse design of blended wing bodies. In particular, feed-forward, shallow neural network architectures yielded significantly better predictive accuracy than cascade-forward architectures. Furthermore, for both architectures, increasing the number of neurons in the hidden layer increased the prediction accuracy of configuration design variables by at least 80%.
ViT-SmartAgri: Vision Transformer and Smartphone-Based Plant Disease Detection for Smart Agriculture
Authors: Barman Utpal , Sarma Parismita , Rahman Mirzanur , Deka Vaskar , Lahkar Swati , Sharma Vaishali , Saikia Manob Jyoti
Published: February 2024

Invading pests and diseases always degrade the quality and quantity of plants. Early and accurate identification of plant diseases is critical for plant health and growth. This work proposes a smartphone-based solution using a Vision Transformer (ViT) model for identifying healthy plants and unhealthy plants with diseases. The collected dataset of tomato leaves was used to collectively train Vision Transformer and Inception V3-based deep learning (DL) models to differentiate healthy and diseased plants. These models detected 10 different tomato disease classes from the dataset containing 10,010 images. The performance of the two DL models was compared. This work also presents a smartphone-based application (Android App) using a ViT-based model, which works on the basis of the self-attention mechanism and yielded a better performance (90.99% testing) than Inception V3 in our experimentation. The proposed ViT-SmartAgri is promising and can be implemented on a colossal scale for smart agriculture, thus inspiring future work in this area.
DiffusionFR: Species Recognition of Fish in Blurry Scenarios via Diffusion and Attention
Authors: Wang Guoying , Shi Bing , Yi Xiaomei , Wu Peng , Kong Linjun , Mo Lufeng
Published: February 2024

Blurry scenarios, such as light reflections and water ripples, often affect the clarity and signal-to-noise ratio of fish images, posing significant challenges for traditional deep learning models in accurately recognizing fish species. Firstly, deep learning models rely on a large amount of labeled data. However, it is often difficult to label data in blurry scenarios. Secondly, existing deep learning models need to be more effective for the processing of bad, blurry, and otherwise inadequate images, which is an essential reason for their low recognition rate. A method based on the diffusion model and attention mechanism for fish image recognition in blurry scenarios, DiffusionFR, is proposed to solve these problems and improve the performance of species recognition of fish images in blurry scenarios. This paper presents the selection and application of this correcting technique. In the method, DiffusionFR, a two-stage diffusion network model, TSD, is designed to deblur bad, blurry, and otherwise inadequate fish scene pictures to restore clarity, and a learnable attention module, LAM, is intended to improve the accuracy of fish recognition. In addition, a new dataset of fish images in blurry scenarios, BlurryFish, was constructed and used to validate the effectiveness of DiffusionFR, combining bad, blurry, and otherwise inadequate images from the publicly available dataset Fish4Knowledge. The experimental results demonstrate that DiffusionFR achieves outstanding performance on various datasets. On the original dataset, DiffusionFR achieved the highest training accuracy of 97.55%, as well as a Top-1 accuracy test score of 92.02% and a Top-5 accuracy test score of 95.17%. Furthermore, on nine datasets with light reflection noise, the mean values of training accuracy reached a peak at 96.50%, while the mean values of the Top-1 accuracy test and Top-5 accuracy test were at their highest at 90.96% and 94.12%, respectively. Similarly, on three datasets with water ripple noise, the mean values of training accuracy reached a peak at 95.00%, while the mean values of the Top-1 accuracy test and Top-5 accuracy test were at their highest at 89.54% and 92.73%, respectively. These results demonstrate that the method showcases superior accuracy and enhanced robustness in handling original datasets and datasets with light reflection and water ripple noise.
Modeling Environmental Conditions in Poultry Production: Computational Fluid Dynamics Approach
Authors: Küçüktopçu Erdem , Cemek Bilal , Simsek Halis
Published: February 2024

In recent years, computational fluid dynamics (CFD) has become increasingly important and has proven to be an effective method for assessing environmental conditions in poultry houses. CFD offers simplicity, efficiency, and rapidity in assessing and optimizing poultry house environments, thereby fueling greater interest in its application. This article aims to facilitate researchers in their search for relevant CFD studies in poultry housing environmental conditions by providing an in-depth review of the latest advancements in this field. It has been found that CFD has been widely employed to study and analyze various aspects of poultry house ventilation and air quality under the following five main headings: inlet and fan configuration, ventilation system design, air temperature–humidity distribution, airflow distribution, and particle matter and gas emission. The most commonly used turbulence models in poultry buildings are the standard k-ε, renormalization group (RNG) k-ε, and realizable k-ε models. Additionally, this article presents key solutions with a summary and visualization of fundamental approaches employed in addressing path planning problems within the CFD process. Furthermore, potential challenges, such as data acquisition, validation, computational resource requirements, meshing, and the selection of a proper turbulence model, are discussed, and avenues for future research (the integration of machine learning, building information modeling, and feedback control systems with CFD) are explored.
Slaying the Swiss Unicorn of Animal Dignity
Authors: Shaw David , Rodriguez Perez Christian , Persson Kirsten
Published: February 2024

In this article, we describe and analyse the Swiss legislation relating to animal dignity. We conclude that previous criticisms of the law do not go far enough: far from protecting animal dignity, the Swiss law not only undermines such dignity but itself serves as a means to ensure that animals can be used merely as a means, and not treated with respect. As such, the Swiss Animal Welfare Act is deeply unethical and undermines the constitutional requirement to treat animals with dignity.
Effects of Dietary Supplementation with Caesalpinia sappan Linn. Extract for Promoting Flock Health and Performance in Late-Phase Laying Hens
Authors: Longchuphon Methisa , Chongrattanameteekul Peerawit , Mektrirat Raktham , Sringarm Korawan , Tapingkae Wanaporn , Srinual Orranee , Huanhong Kiattisak , Chaiphun Wipasiri , Arjin Chaiwat , Jaturasitha Sanchai , Lumsangkul Chompunut
Published: February 2024

The present study investigated the effects of dietary supplementation of Caesalpinia sappan Linn Extract (CSE) on the health and productive performance of late-phase laying hens on farms. Proximate composition and antioxidant markers of CSE powder revealed favorable characteristics with high total dry matter; phenolic content, and antioxidant potency. Three hundred and sixty (64-week-old) Hy-line Brown hens were divided into five groups with 0 (control diet), 250, 500, 1000, and 2000 mg/kg CSE, respectively. The laying performance and egg quality of the CSE supplementation groups demonstrated significant improvements in egg weight and albumin weight (p < 0.05), and a tendency for enhanced egg mass and feed conversion ratio. Additionally, the intestinal morphostructural indices in the 2000 mg CSE/kg diet group showed the greatest statistical significance (p < 0.05), with a detectable trend suggesting an increase in the villus height to crypt depth ratio. In addition, significant downregulation of proinflammatory genes occurred in their liver tissues, coupled with a greater expression of genes linked to antioxidants and anti-inflammatory processes. Furthermore, the blood biochemical parameters and the organ weights may suggest a favorable safety profile of CSE supplementation. These findings highlight the potential of CSE as a dietary supplement to enhance the productive performance and flock health of late-phase laying hens. Further research is warranted to explore the long-term effects and optimal dosage of CSE supplementation for laying hens in farming practices
Assessment of Tumor-Associated Tissue Eosinophilia (TATE) and Tumor-Associated Macrophages (TAMs) in Canine Transitional Cell Carcinoma of the Urinary Bladder
Authors: Files Rita , Okwu Victor , Topa Nuno , Sousa Marisa , Silva Filipe , Rodrigues Paula , Delgado Leonor , Prada Justina , Pires Isabel
Published: February 2024

Transitional cell carcinoma of the urinary bladder is a significant neoplasm in dogs, characterized by a poor prognosis and a high metastatic potential. These canine spontaneous tumors share many characteristics with human transitional cell carcinoma, making them an excellent comparative model. The role of inflammatory infiltration in tumor development and progression is frequently contradictory, especially concerning tumor-associated tissue eosinophils (TATE) and tumor-associated macrophages (TAMs). This study aims to analyze TATE and TAMs in canine transitional cell carcinoma of the urinary bladder. Congo Red staining was used to identify TATE, and immunohistochemistry was performed to detect TAMs in 34 cases of canine transitional cell carcinoma of the bladder carcinomas, categorized into low and high grades. Statistically significant differences were observed between the number of eosinophils and macrophages in the two groups of tumors. The number of TATE was higher in low-grade malignant tumors, but the number of TAMs was higher in high-grade tumors. Our findings suggest the importance of TATEs and TAMs in the aggressiveness of canine transitional cell carcinoma and propose their potential use as therapeutic targets.
Comparative Analysis of Polyphenol Content and Antioxidant Activity of Different Parts of Five Onion Cultivars Harvested in Korea
Authors: Kim Yena , Kim Young-Jun , Shin Youngjae
Published: February 2024

Onions are typically consumed as the bulb, but the peel and root are discarded as by-products during processing. This study investigated the potential functional use of these by-products by analyzing the polyphenols, antioxidant compounds, and antioxidant activity contained in onions. In this study, the bulb, peel, and root of five onion cultivars (‘Tank’, ‘Bomul’, ‘Gujji’ ‘Cobra’, and ‘Hongbanjang’) harvested in Korea were investigated. Caffeic acid and quercetin were most abundant in the peel, whereas methyl gallate was the predominant polyphenol in the bulb. Both DPPH and ABTS radical scavenging activity were higher in onion peel and root than in the bulb. These findings suggest that onion peel and roots, which are often discarded, have abundant antioxidant substances and excellent antioxidant activity. This study provides basic data for the future use of onion peel and roots as functional ingredients with high added value.
Piceid Octanoate Protects Retinal Cells against Oxidative Damage by Regulating the Sirtuin 1/Poly-ADP-Ribose Polymerase 1 Axis In Vitro and in rd10 Mice
Authors: Moshtaghion Seyed Mohamadmehdi , Caballano-Infantes Estefanía , Plaza Reyes Álvaro , Valdés-Sánchez Lourdes , Fernández Patricia Gallego , de la Cerda Berta , Riga Maurizio S. , Álvarez-Dolado Manuel , Peñalver Pablo , Morales Juan C. , Díaz-Corrales Francisco J.
Published: February 2024

Retinitis pigmentosa is a common cause of inherited blindness in adults, which in many cases is associated with an increase in the formation of reactive oxygen species (ROS) that induces DNA damage, triggering Poly-ADP-Ribose Polymerase 1 (PARP1) activation and leading to parthanatos-mediated cell death. Previous studies have shown that resveratrol (RSV) is a promising molecule that can mitigate PARP1 overactivity, but its low bioavailability is a limitation for medical use. This study examined the impact of a synthesized new acylated RSV prodrug, piceid octanoate (PIC-OCT), in the 661W cell line against H2O2 oxidative stress and in rd10 mice. PIC-OCT possesses a better ADME profile than RSV. In response to H2O2, 661W cells pretreated with PIC-OCT preserved cell viability in more than 38% of cells by significantly promoting SIRT1 nuclear translocation, preserving NAD+/NADH ratio, and suppressing intracellular ROS formation. These effects result from expressing antioxidant genes, maintaining mitochondrial function, reducing PARP1 nuclear expression, and preventing AIF nuclear translocation. In rd10 mice, PIC-OCT inhibited PAR-polymer formation, increased SIRT1 expression, significantly reduced TUNEL-positive cells in the retinal outer nuclear layer, preserved ERGs, and enhanced light chamber activity (all p values < 0.05). Our findings corroborate that PIC-OCT protects photoreceptors by modulating the SIRT1/PARP1 axis in models of retinal degeneration.
New Insights into Antioxidant Peptides: An Overview of Efficient Screening, Evaluation Models, Molecular Mechanisms, and Applications
Authors: Zhang Yuhao , Li Yun , Quan Zhengze , Xiao Ping , Duan Jin-Ao
Published: February 2024

Antioxidant peptides are currently a hotspot in food science, pharmaceuticals, and cosmetics. In different fields, the screening, activity evaluation, mechanisms, and applications of antioxidant peptides are the pivotal areas of research. Among these topics, the efficient screening of antioxidant peptides stands at the forefront of cutting-edge research. To this end, efficient screening with novel technologies has significantly accelerated the research process, gradually replacing the traditional approach. After the novel antioxidant peptides are screened and identified, a time-consuming activity evaluation is another indispensable procedure, especially in in vivo models. Cellular and rodent models have been widely used for activity evaluation, whilst non-rodent models provide an efficient solution, even with the potential for high-throughput screening. Meanwhile, further research of molecular mechanisms can elucidate the essence underlying the activity, which is related to several signaling pathways, including Keap1-Nrf2/ARE, mitochondria-dependent apoptosis, TGF-β/SMAD, AMPK/SIRT1/PGC-1α, PI3K/Akt/mTOR, and NF-κB. Last but not least, antioxidant peptides have broad applications in food manufacture, therapy, and the cosmetics industry, which requires a systematic review. This review introduces novel technologies for the efficient screening of antioxidant peptides, categorized with a new vision. A wide range of activity evaluation assays, encompassing cellular models, as well as rodent and non-rodent models, are provided in a comprehensive manner. In addition, recent advances in molecular mechanisms are analyzed with specific cases. Finally, the applications of antioxidant peptides in food production, therapy, and cosmetics are systematically reviewed.
Recovering Sustainable Mobility after COVID-19: The Case of Almeria (Spain)
Authors: Garrido-Jiménez Francisco Javier , Rodríguez-Rojas María I. , Vallecillos-Siles Manuel Ricardo
Published: February 2024

The COVID-19 pandemic brought about a significant change in mobility habits within cities, leading to a significant decrease in the use of collective urban transport in many countries that has been only partially and unevenly reversed. In this context, many cities are analyzing what factors are hindering this recovery process to design actions to promote sustainable mobility. Thus, this study, carried out in the city of Almeria (Spain), tried to analyze whether the main operating variables of the municipal bus network (frequency, average vehicle occupancy, the length of the lines, urban or suburban character, circularity, nodality, and intermodality) have an impact on the annual number of users recovered in 2022 compared to 2019. Although a strong statistical correlation between variables was not observed, the overall results show that the lines that have recovered the most users on average are suburban lines, as well as the nodal lines that serve key centroids such as the university, highlighting that the dependence of users on public transport might be the most important determinant in the recovery process, more than other variables representative of the service’s intrinsic quality such as frequency or average vehicle occupancy. This result shows the importance of facilitating public transport to those who lack alternatives, as well as the convenience of restrictions on less sustainable transportation alternatives for the prompt recovery of the space lost by urban public transportation.
Geochemical Evolution of Mg-Bentonite Affected by the Contact of Carbon Steel and a Hydrothermal Gradient
Authors: Mota-Heredia Carlos , Cuevas Jaime , Fernández Raúl
Published: February 2024

Carbon steel and bentonite are materials selected as engineered barriers for high-level radioactive waste confinement. Their long-term interaction must be evaluated to confirm the barrier’s stability. Three laboratory experiments of the carbon steel—Mg-bentonite interaction were conducted for 1, 6, and 22 months under a hydrothermal gradient. Changes in bentonite’s water content, specific surface area, and cation exchange capacity were measured. Mineralogy was studied by X-ray diffraction and scanning electron microscopy. The redistribution of aqueous species and the redox state of iron were determined across the bentonite columns. Results indicated water saturation after 22 months. The specific surface area of bentonite was reduced near contact with the steel, while the cation exchange capacity mostly decreased at 3–6 mm from the steel interface. The corrosion rate decreased with time and bentonite enriched in Fe in the first 1.5 mm from the steel contact. The formation of new Fe-bearing minerals, such as di-tri ferri-sudoite, magnetite, hematite, maghemite, lepidocrocite, siderite and ankerite was observed. Aqueous species redistributed in the porewater of bentonite with decreasing concentrations of Fe and Cl as a function of time and increasing concentrations of Na, Ca and SO4 after 22 months. This occurs under conditions where the bentonite is saturated with Mg, which conditioned the formation and nature of iron clay minerals with time.
Experimental Study on Seismic Behavior of Newly Assembled Concrete Beam–Column Joints with L-Shaped Steel Bars
Authors: Lv Mengjiao , Yang Taochun , Lin Mingqiang
Published: February 2024

A novel concrete beam–column connection utilizing L-shaped steel bars is proposed to address the growing demand for prefabricated buildings and to ensure good seismic performance in such beam–column structures. After positioning two prefabricated beams with L-shaped tendons into the designated connection points at the top and bottom of the columns, concrete is poured into the post-cast section of the joint and the composite beam area, realizing a connection between the beams and columns. Quasi-static tests were performed on four combined backbone curves and one cast-in-place joint to investigate their failure modes and stress mechanisms. Through low-cycle repeated loading tests, it is found that measures such as increasing the area of the post-cast concrete in the joint area, the length of the L-shape, and the concrete strength in the composite beam area can effectively improve the bonding ability between the post-cast area of the joint specimens and the precast members, to improve the ductility performance, energy dissipation capacity, and bearing capacity of the joint specimens. The initial stiffness of the joint can be effectively improved by presetting the steel pipe in the column. Concurrently, the finite element method (FEM) was employed for parameter analysis. By integrating the test and FEM results, an equation for calculating the shear capacity of the connection was derived. The findings demonstrate that the hysteresis curve of the newly assembled joints is full, and its overall performance index is roughly the same as that of the cast-in-place joints. Additionally, enhancing the post-casting area of concrete, the length of the L-shaped bars, the concrete strength in the composite beam region, the axial compression ratio, or the steel tube dimensions can effectively improve the overall performance. The derived equation for the shear-bearing capacity of the connection satisfies design and application requirements.
Emissions of Volatile Organic Compounds (VOCs) as Safety Indicators in the Development of Wood-Based Binderless Boards
Authors: Bertheau Elise , Simon Valérie , Delgado Raynaud Christine
Published: February 2024

Wood-based panels are ubiquitous in our daily lives, both as building materials and as furnishing materials. Numerous studies have revealed that these materials emit volatile organic compounds, such as formaldehyde, into indoor air, which can be harmful to human health. These volatile organic compounds come both from the wood itself, more specifically cellulose, hemicellulose, and lignin, and from the resins used to bind the wood fibers or particles together. Today, new panels bonded with bio-based adhesives and binderless panels are emerging. The aim of this article is to highlight the importance of measuring VOC emissions from binderless wood-based panels, and more specifically, to identify the VOCs, originating from the wood and thermal transformation processes, likely to be emitted during the production of such panels, as well as how to sample them and measure their emissions. This work provides a useful approach to identifying and quantifying VOC emissions from these new materials. These methodologies should be applied more widely to gain knowledge about VOCs, which are relevant indicators for the development of environmentally friendly materials.
Two-Stage Dimensionality Reduction for Social Media Engagement Classification
Authors: Vieira Sobrinho Jose Luis , Teles Vieira Flavio Henrique , Assis Cardoso Alisson
Published: February 2024

The high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will be—a phenomenon commonly referred to as the curse of dimensionality. Laying the paper’s foundation based on this premise, we propose a two-stage dimensionality reduction (TSDR) method for data classification. The first stage extracts high-quality features to a new subset by maximizing the pairwise separation probability, with the aim of avoiding overlap between individuals from different classes that are close to one another, also known as the class masking problem. The second stage takes the previous resulting subset and transforms it into a reduced final space in a way that maximizes the distance between the cluster centers of different classes while also minimizing the dispersion of instances within the same class. Hence, the second stage aims to improve the accuracy of the succeeding classifier by lowering its sensitivity to an imbalanced distribution of instances between different classes. Experiments on benchmark and social media datasets show how promising the proposed method is over some well-established algorithms, especially regarding social media engagement classification.
Machine-Learning-Based Deformation Prediction Method for Deep Foundation-Pit Enclosure Structure
Authors: Xu Yangqing , Zhao Yuxiang , Jiang Qiangqiang , Sun Jie , Tian Chengxin , Jiang Wei
Published: February 2024

During the construction of deep foundation pits in subways, it is crucial to closely monitor the horizontal displacement of the pit enclosure to ensure stability and safety, and to reduce the risk of structural damage caused by pit deformations. With advancements in machine-learning (ML) techniques and correlation analysis in engineering, data-driven methods that combine ML with engineering monitoring data have become increasingly popular. These methods offer benefits such as high prediction accuracy, efficiency, and cost effectiveness. The main goal of this study was to develop a machine-learning method for predicting the enclosure deformation of deep foundation pits. This was achieved by analyzing the factors influencing deep foundation-pit enclosure deformation and incorporating historical cases and monitoring reports. The performance of each machine-learning prediction model was systematically analyzed and evaluated using K-Fold cross validation. The results revealed that the random forest model outperformed the other models. The result of the test data showed that the random forest model achieved an R2 of 0.9905, an MAE of 0.8572 mm, and an RMSE of 1.9119 mm. Feature importance analysis identified the depth of enclosure structure, water level, surface settlement, axial force, and exposure time as the most critical factors for accurate prediction. The depth of the enclosure structure had an especially significant impact on the prediction of enclosure deformation.