bluuebunny/crossref_metadata_2025 huggingface dataset:
Advances in the Development of Positron Emission Tomography Tracers for Improved Detection of Differentiated Thyroid Cancer
Authors: Coerts Hannelore Iris , de Keizer Bart , Verburg Frederik Anton
Published: April 2024

Thyroid cancer poses a significant challenge in clinical management, necessitating precise diagnostic tools and treatment strategies for optimal patient outcomes. This review explores the evolving field of radiotracers in the diagnosis and management of thyroid cancer, focusing on prostate-specific membrane antigen (PSMA)-based radiotracers, fibroblast activation protein inhibitor (FAPI)-based radiotracers, Arg-Gly-Asp (RGD)-based radiotracers, and 18F-tetrafluoroborate (18F-TFB). PSMA-based radiotracers, initially developed for prostate cancer imaging, have shown promise in detecting thyroid cancer lesions; however, their detection rate is lower than 18F-FDG PET/CT. FAPI-based radiotracers, targeting fibroblast activation protein highly expressed in tumors, offer potential in the detection of lymph nodes and radioiodine-resistant metastases. RGD-based radiotracers, binding to integrin αvβ3 found on tumor cells and angiogenic blood vessels, demonstrate diagnostic accuracy in detecting radioiodine-resistant thyroid cancer metastases. 18F-TFB emerges as a promising PET tracer for imaging of lymph node metastases and recurrent DTC, offering advantages over traditional methods. Overall, these radiotracers show promise in enhancing diagnostic accuracy, patient stratification, and treatment selection in differentiated thyroid cancer, warranting further research and clinical validation. Given the promising staging capabilities of 18F-TFB and the efficacy of FAP-targeting tracers in advanced, potentially dedifferentiated cases, continued investigation in these domains is justified.
Visualization of the Association of Dimeric Protein Complexes on Specific Enhancers in the Salivary Gland Nuclei of Drosophila Larva
Authors: Vanderperre Solène , Merabet Samir
Published: April 2024

Transcription factors (TFs) regulate gene expression by recognizing specific target enhancers in the genome. The DNA-binding and regulatory activity of TFs depend on the presence of additional protein partners, leading to the formation of versatile and dynamic multimeric protein complexes. Visualizing these protein–protein interactions (PPIs) in the nucleus is key for decrypting the molecular cues underlying TF specificity in vivo. Over the last few years, Bimolecular Fluorescence Complementation (BiFC) has been developed in several model systems and applied in the analysis of different types of PPIs. In particular, BiFC has been applied when analyzing PPIs with hundreds of TFs in the nucleus of live Drosophila embryos. However, the visualization of PPIs at the level of specific target enhancers or genomic regions of interest awaits the advent of DNA-labelling methods that can be coupled with BiFC. Here, we present a novel experimental strategy that we have called BiFOR and that is based on the coupling of BiFC with the bacterial ANCHOR DNA-labelling system. We demonstrate that BiFOR enables the precise quantification of the enrichment of specific dimeric protein complexes on target enhancers in Drosophila salivary gland nuclei. Given its versatility and sensitivity, BiFOR could be applied more widely to other tissues during Drosophila development. Our work sets up the experimental basis for future applications of this strategy.
New Approach for Sulfidation Process in Packed Bed with Hi-Fuel A310 Sorbent—Thermodynamical Studies
Authors: Lorreyte Clarisse , Malinowska Barbara , Butin Vincent , Ruscassier Nathalie , Casalinho Joel , Perré Patrick
Published: April 2024

This paper presents tests related to the reactivity of commercial Hi-Fuel sorbent toward H2S (H2S/N2 mixture) in a packed bed at 300 °C. The sorbent used for breakthrough test was characterized before and after test by ESEM-EDX, FTIR-ATR, Raman, and elemental analyses. Testing reveals that the commercial sorbent contains two compounds reacting with H2S: ZnO and ZnCO3. According to thermodynamical studies, the reactivity of ZnCO3 at 300 °C is privileged (KR = 9.5 × 108) than ZnO (KR = 6.6× 106). In addition, the reaction of H2S with ZnCO3 induces a volume decrease, which promotes the movement of gas through the newly formed layer. The properties of this sorbent thus hold a good potential for the desulfurization process of gases polluted with H2S. We observed that the maximum sulfidation rate was reached on the surface of the sorbent and showed a maximum conversion of 27%.
Callous–Unemotional Traits and Emotion Perception Accuracy and Bias in Youths
Authors: Ciucci Enrica , Baroncelli Andrea , Facci Carolina , Righi Stefania , Frick Paul J.
Published: April 2024

This study investigated the associations among conduct problems, callous–unemotional (CU) traits, and indices of emotion recognition accuracy and emotion recognition bias obtained from human faces. Impairments in emotion recognition were considered within broader, impaired emotional and social functioning. The sample consisted of 293 middle-school students (51.19% girls; M age = 12.97 years, SD = 0.88 years). In general, CU traits were associated with less accuracy in recognizing emotions, especially fearful and angry faces, and such deficits in emotional recognition were not associated with conduct problems independent of CU traits. These results support the importance of studying potential deficits in the recognition of emotions other than fear. Furthermore, our results support the importance of considering the role of CU traits when studying emotional correlates of conduct problems. For children scoring high on CU traits, the emotion recognition accuracy of anger was low irrespective of the level of conduct problems, whereas in children scoring low on CU traits, less accuracy in recognizing emotions was related to increases in conduct problems. Finally, our results support the need for research to not only focus on accuracy of emotional recognition but also test whether there are specific biases leading to these inaccuracies. Specifically, CU traits were associated not only with lower accuracy in recognizing fearful faces but also with a tendency to interpret fearful faces as angry. This suggests that the emotional deficit associated with CU traits is not just a deficit in empathic concern toward others distress but also includes a tendency to overinterpret emotions as potential threats to oneself.
Oral Microbiota of Infants in Maternal Gestational Diabetes: A Systematic Review
Authors: Camoni Nicole , Conti Giulio , Majorana Alessandra , Bardellini Elena , Salerno Claudia , Wolf Thomas Gerard , Campus Guglielmo , Cagetti Maria Grazia
Published: April 2024

Gestational diabetes mellitus (GDM) affects approximately 5–20% of pregnant women and is associated with adverse pregnancy outcomes. This review aimed to assess whether the oral microbiota of infants and their mothers with GDM had a different composition from that found in unaffected women and offspring. PubMed, Embase, Scopus, and Google Scholar were searched in December 2023 after protocol registration in the International Prospective Register of Systematic Reviews (CRD42023406505). Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal tools. Overall, 1113 articles were identified; after evaluating the full texts, 12 papers were included in the qualitative analysis. In six studies of the eight included, significant differences in microbiota between M-GDM and M-nGDM were found. In four studies, a depletion of Firmicutes and an enrichment of Proteobacteria was found in the microbiota of infants. Since all included studies were judged to have high risk of bias, a quantitative synthesis of the results was not carried out. In conclusion, although the oral microbiota of infants from mothers with GDM could be different from that of infants from mothers without GDM, there is insufficient evidence to clarify this aspect so far.
Exploring Progesterone Deficiency in First-Trimester Miscarriage and the Impact of Hormone Therapy on Foetal Development: A Scoping Review
Authors: Bataa Munkhtuya , Abdelmessih Erini , Hanna Fahad
Published: April 2024

Background and Objectives: Progesterone deficiency during pregnancy may lead to various complications, including first-trimester miscarriage, which is the most common pregnancy complication. However, progesterone therapy may play a role in pregnancy maintenance and foetal development. The aim of this scoping review is to present evidence on the link between progesterone deficiency and first-trimester miscarriage among pregnant women and assess the impact of progesterone therapy on foetal development. Methods: A comprehensive global systematic search of mainly primary research studies was conducted using several databases. Peer-reviewed studies published between 2010 and 2023 were included. The scoping review was conducted using the framework outlined by the Joanna Briggs Institute (JBI) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses—Extension for Scoping Reviews (PRISMA-ScR) statement. Results: Twenty-three articles (which included 35,862 participants) were included in the analysis. Most studies were conducted in mid- to high-income countries. All 23 articles reported a significant positive relationship between progesterone deficiency and first-trimester miscarriage. Furthermore, the majority of studies reported a higher risk of miscarriage when lower levels of progesterone are combined with other declined hormones. While most studies reported that progesterone therapy may reduce the rate of first-trimester miscarriage among pregnant women, no evidence of health-related harm to offspring development was reported. Conclusions: The findings from this systematic–scoping review indicate possible benefits of progesterone replacement therapy in maintaining a healthy pregnancy and foetal development. Rigorous studies that include large sample sizes and systematic reviews are required to confirm these findings further.
Overview of the Application of Physically Informed Neural Networks to the Problems of Nonlinear Fluid Flow in Porous Media
Authors: Dieva Nina , Aminev Damir , Kravchenko Marina , Smirnov Nikolay
Published: April 2024

To describe unsteady multiphase flows in porous media, it is important to consider the non-Newtonian properties of fluids by including rheological laws in the hydrodynamic model. This leads to the formation of a nonlinear system of partial differential equations. To solve this direct problem, it is necessary to linearize the equation system. Algorithm construction for inverse problem solution is problematic since the numerical solution is unstable. The application of implicit methods is reduced to matrix equations with a high rank of the coefficient matrix, which requires significant computational resources. The authors of this paper investigated the possibility of parameterized function (physics-informed neural networks) application to solve direct and inverse problems of non-Newtonian fluid flows in porous media. The results of laboratory experiments to process core samples and field data from a real oil field were selected as examples of application of this method. Due to the lack of analytical solutions, the results obtained via the finite difference method and via real experiments were proposed for validation.
The Impact of Sarcopenia in the Long-Term Survival of Patients following Complex Endovascular Aortic Surgery for Thoracoabdominal Aortic Aneurysms
Authors: Sachsamanis Georgios , Stahl Judith , Pfister Karin , Schierling Wilma , Betz Thomas , Jage Simon
Published: April 2024

Objectives: Image-based sarcopenia has been the subject of recent studies, hypothesized as a prognostic factor for patients with thoracoabdominal aortic aneurysms. Methods and Materials: We conducted a single-center retrospective analysis of patients who underwent complex endovascular repair for thoracoabdominal aortic aneurysms between 2008 and 2016. CT image assessment was performed and patients were classified as sarcopenic and non-sarcopenic using two stratification methods: skeletal mass index (SMI) and total psoas muscle index (TPMI). According to sex, each patient was defined as sarcopenic if their SMI or TPMI was in the lowest third of the study group. The primary endpoint was impact of sarcopenia on perioperative mortality and long-term survival. Secondary endpoints were perioperative complications. Results: From a total of 155 patients, 135 were eligible for study. Overall, in-hospital mortality was 5.9% (8/135). The 30-day, 1-year, 3-year and 5-year mortality was 10.4% (14/135), 20% (27/135), 28.1% (38/135) and 31.1% (42/135), respectively. There was no difference in the long-term mortality rates between sarcopenic and non-sarcopenic patients regardless of the stratification method used (p = 0.4 for SMI and p = 0.2 for TPMI). According to SMI, 30-day mortality of sarcopenic patients was significantly lower in comparison to non-sarcopenic patients (1/45, 2.2% vs. 13/90, 14.4%, p = 0.028). Based on the total psoas muscle index, sarcopenic patients were at higher risk for development of pulmonary complications in comparison to non-sarcopenic patients postoperatively (p = 0.03). Conclusion: Using SMI and TPMI, sarcopenia was not associated with reduced long-term survival in patients undergoing complex endovascular repair for thoracoabdominal aortic aneurysms.
Advancing Dermatological Diagnostics: Interpretable AI for Enhanced Skin Lesion Classification
Authors: Metta Carlo , Beretta Andrea , Guidotti Riccardo , Yin Yuan , Gallinari Patrick , Rinzivillo Salvatore , Giannotti Fosca
Published: April 2024

A crucial challenge in critical settings like medical diagnosis is making deep learning models used in decision-making systems interpretable. Efforts in Explainable Artificial Intelligence (XAI) are underway to address this challenge. Yet, many XAI methods are evaluated on broad classifiers and fail to address complex, real-world issues, such as medical diagnosis. In our study, we focus on enhancing user trust and confidence in automated AI decision-making systems, particularly for diagnosing skin lesions, by tailoring an XAI method to explain an AI model’s ability to identify various skin lesion types. We generate explanations using synthetic images of skin lesions as examples and counterexamples, offering a method for practitioners to pinpoint the critical features influencing the classification outcome. A validation survey involving domain experts, novices, and laypersons has demonstrated that explanations increase trust and confidence in the automated decision system. Furthermore, our exploration of the model’s latent space reveals clear separations among the most common skin lesion classes, a distinction that likely arises from the unique characteristics of each class and could assist in correcting frequent misdiagnoses by human professionals.
Adaptive Terminal Time and Impact Angle Constraint Cooperative Guidance Strategy for Multiple Vehicles
Authors: Li Ao , Hu Xiaoxiang , Yang Shaohua , Dong Kejun
Published: April 2024

This paper addresses the guidance of various flight vehicles under multiple constraints in three-dimensional space. A cooperative guidance strategy that satisfies both time and angle constraints is designed to reach a moving target. The strategy is organized into two parts: modeling and programming calculations. First, a nonlinear motion model for guidance is established and normalized, including both the vehicle and the target. Later, the arrival method is automatically determined according to the strategy and depending on the type of target. The cooperative terminal time is determined based on an augmented proportional navigation method. An improved model predictive static programming (MPSP) algorithm was designed as a means of adjusting the adaptive terminal time. Then, the algorithm was used to update the control quantity iteratively until the off-target quantity and the angle of constraints were satisfied. The simulation results showed that the strategy could enable multiple flight vehicles at different initial positions to reach the target accurately at the same time and with the ideal impact angle. The strategy boasts a high computational efficiency and is capable of being implemented in real time.
iBVP Dataset: RGB-Thermal rPPG Dataset with High Resolution Signal Quality Labels
Authors: Joshi Jitesh , Cho Youngjun
Published: April 2024

Remote photo-plethysmography (rPPG) has emerged as a non-intrusive and promising physiological sensing capability in human–computer interface (HCI) research, gradually extending its applications in health-monitoring and clinical care contexts. With advanced machine learning models, recent datasets collected in real-world conditions have gradually enhanced the performance of rPPG methods in recovering heart-rate and heart-rate-variability metrics. However, the signal quality of reference ground-truth PPG data in existing datasets is by and large neglected, while poor-quality references negatively influence models. Here, this work introduces a new imaging blood volume pulse (iBVP) dataset of synchronized RGB and thermal infrared videos with ground-truth PPG signals from ear with their high-resolution-signal-quality labels, for the first time. Participants perform rhythmic breathing, head-movement, and stress-inducing tasks, which help reflect real-world variations in psycho-physiological states. This work conducts dense (per sample) signal-quality assessment to discard noisy segments of ground-truth and corresponding video frames. We further present a novel end-to-end machine learning framework, iBVPNet, that features an efficient and effective spatio-temporal feature aggregation for the reliable estimation of BVP signals. Finally, this work examines the feasibility of extracting BVP signals from thermal video frames, which is under-explored. The iBVP dataset and source codes are publicly available for research use.
A Method for Evaluating Coalbed Methane Reservoir Productivity Considering Drilling Fluid Damage
Authors: Li Chen , Sun Lichun , Zhao Zhigang , Zhang Jian , Li Yong , Meng Yanjun , Wang Lei
Published: April 2024

In the process of coalbed methane development, drilling fluid and fracturing fluid cannot achieve absolute compatibility with formation. The incompatibility between the working fluid and reservoir will lead to the intrusion of working fluid into the reservoir and cause reservoir pollution. This is a very common phenomenon. There is a large amount of pulverized coal in the coal seam, and the intrusion of working liquid will be combined with the pulverized coal to form cement to block the seepage space in the reservoir. Since pressure relief and fracturing fluid backflow will be performed at the first time after fracturing, the intrusion range of the working fluid is small, generally reaching 10 m to 50 m. Compared with a conventional gas reservoir or shale gas reservoir, the working fluid loss during CBM development will seriously affect the subsequent production project and even make the gas well lose production capacity. On the other hand, in order to avoid this phenomenon, measures such as acidification or volumetric fracturing are sometimes used to improve the seepage environment near the well and near the fracture. The purpose of this study is to quantitatively evaluate the impacts of working fluid filtration and reservoir reconstruction on production. In this study, a single well productivity evaluation model and sensitivity analysis method considering drilling fluid filtration loss, fracturing fluid filtration loss, reservoir reconstruction and other processes is proposed. The formation mechanism of fluid loss during drilling and fracturing is described, and the productivity evaluation model considering fluid loss is combined with the Langmuir isothermal adsorption equation, steady-state diffusion law, Darcy’s seepage law and Duhamel convolution formation. Combined with the distribution of actual gas reservoir flow characteristics, the sensitivity of single well productivity to gas reservoir porosity, gas reservoir permeability, coal seam adsorption coefficient, working fluid filtration loss and reservoir reconstruction measures are analyzed. Through the analysis and fitting of the actual production data on site, the relationship curve can better fit the field production data, and the evaluation results are in line with the drilling and fracturing conditions at that time and the subsequent production conditions, with small errors. The obtained method is suitable for predicting the productivity of fractured vertical wells in different working conditions and provides a basis for the development and productivity prediction of CBM reservoirs in China and in international cooperation.
Unveiling Gene Interactions in Alzheimer’s Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach
Authors: Sanders Keith L. , Manuel Astrid M. , Liu Andi , Leng Boyan , Chen Xiangning , Zhao Zhongming
Published: April 2024

Alzheimer’s Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD’s pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted Web-based Cell-type-Specific Enrichment Analysis (WebCSEA) on genes within the top 10% of dmGWAS modules, highlighting monocyte as the most significant cell type (p < 5 × 10−12). Functional enrichment analysis revealed Gene Ontology Biological Process terms relevant to AD pathology (adjusted p < 0.05). Additionally, drug target enrichment identified five FDA-approved targets (p-value = 0.03) for further research. In summary, dmGWAS integration of genetic and epigenetic signals unveiled new gene interactions related to AD, offering promising avenues for future studies.
A Fast Detection Algorithm for Change Detection in National Forestland “One Map” Based on NLNE Quad-Tree
Authors: Gao Fei , Su Xiaohui , Chen Yuling , Wu Baoguo , Tian Yingze , Zhang Wenjie , Li Tao
Published: April 2024

The National Forestland “One Map” applies the boundaries and attributes of sub-elements to mountain plots by means of spatial data to achieve digital management of forest resources. The change detection and analysis of forest space and property is the key to determining the change characteristics, evolution trend and management effectiveness of forest land. The existing spatial overlay method, rasterization method, object matching method, etc., cannot meet the requirements of high efficiency and high precision at the same time. In this paper, we investigate a fast algorithm for the detection of changes in “One Map”, taking Sichuan Province as an example. The key spatial characteristic extraction method is used to uniquely determine the sub-compartments. We construct an unbalanced quadtree based on the number of maximum leaf node elements (NLNE Quad-Tree) to narrow down the query range of the target sub-compartments and quickly locate the sub-compartments. Based on NLNE Quad-Tree, we establish a change detection model for “One Map” (NQT-FCDM). The results show that the spatial feature combination of barycentric coordinates and area can ensure the spatial uniqueness of 44.45 million sub-compartments in Sichuan Province with 1 m~0.000001 m precision. The NQT-FCDM constructed with 1000–6000 as the maximum number of leaf nodes has the best retrieval efficiency in the range of 100,000–500,000 sub-compartments. The NQT-FCDM shortens the time by about 75% compared with the traditional spatial union analysis method, shortens the time by about 50% compared with the normal quadtree and effectively solves the problem of generating a large amount of intermediate data in the spatial union analysis method. The NQT-FCDM proposed in this paper improves the efficiency of change detection in “One Map” and can be generalized to other industries applying geographic information systems to carry out change detection, providing a basis for the detection of changes in vector spatial data.
Eriobotrya japonica Fermentation with Plant-Derived Lactiplantibacillus plantarum MSC-5T Ameliorates Antioxidant Activity in HEK293 Cells
Authors: Danshiitsoodol Narandalai , Inoue Yusuke , Sugimoto Sachiko , Shakya Shrijana , Noda Masafumi , Sugiyama Masanori
Published: April 2024

Oxidative stress from an excess of radical compounds generally impacts apoptosis and inflammation. The use of probiotics, therefore, has emerged as a favorable tool to suppress the formation of reactive oxygen species. In the present study, we investigated the antioxidant activity of plant-derived Lactiplantibacillus (L.) plantarum MSC-5T fermented in Eriobotrya japonica (EJ) aqueous extract. In the in vitro study, the extract fermented with the MSC-5T strain markedly decreased the cell death of H2O2-induced HEK293 cells. In addition, the fermented extract showed a protective effect against fungal toxin ochratoxin A (OTA) and citrinin (CTN). Regarding the evaluation of glutathione homeostasis, it can be clearly seen that pretreatment of HEK293 cells with fermented EJ extract greatly increased glutathione (GSH) levels, while unfermented extract did not affect the cellular GSH content. Furthermore, we identified a bioactive compound as pyrocatechol, which displayed significant antioxidation activity. The extract fermented for 48 h with the MSC-5T strain in EJ extract produces 167.4 μg/mL pyrocatechol.
SDN-Based Secure Common Emergency Service for Railway and Road Co-Existence Scenarios
Authors: Singh Radheshyam , Mendiboure Leo , Soler José , Berger Michael Stübert , Sylla Tidiane , Berbineau Marion , Dittmann Lars
Published: April 2024

In the near future, there will be a greater emphasis on sharing network resources between roads and railways to improve transportation efficiency and reduce infrastructure costs. This could enable the development of global Cooperative Intelligent Transport Systems (C-ITSs). In this paper, a software-defined networking (SDN)-based common emergency service is developed and validated for a railway and road telecommunication shared infrastructure. Along with this, the developed application is capable of reducing the chances of distributed denial-of-service (DDoS) situations. A level-crossing scenario is considered to demonstrate the developed solution where railway tracks are perpendicular to the roads. Two cases are considered to validate and analyze the developed SDN application for common emergency scenarios. In case 1, no cross-communication is available between the road and railway domains. In this case, emergency message distribution is carried out by the assigned emergency servers with the help of the SDN controller. In case 2, nodes (cars and trains) are defined with two wireless interfaces, and one interface is reserved for emergency data communication. To add the DDoS resiliency to the developed system the messaging behavior of each node is observed and if an abnormality is detected, packets are dropped to avoid malicious activity.
Polysaccharides from Eucommia ulmoides Oliv. Leaves Alleviate Acute Alcoholic Liver Injury by Modulating the Microbiota–Gut–Liver Axis in Mice
Authors: Li Yingzhi , Wang Huimei , Leng Xueping , Gao Jiaming , Li Chang , Huang Danfei
Published: April 2024

The interplay among gut microbiota, intestines, and liver is crucial in preventing acute alcoholic liver injury. In this study, the hepatoprotective potential of polysaccharides from Eucommia ulmoides Oliv. leaves (EULP) on acute alcoholic liver injury in Kunming male mice was investigated. The structural features suggested that the EULP appeared as a heterogeneous mixture of polysaccharides with a molecular weight of 186132 Da. A 14-day pretreatment of EULP ameliorated acute alcoholic-induced hepatic inflam mation (TNF-α, IL-6, and IL-10), oxidative stress (GSH, SOD, and T-AOC), and liver damage (ALT and AST) via enhancing intestinal barrier (Occludin, Claudin 1, and ZO-1) and modulating microbiome, which subsequently inhibiting endotoxemia and balancing the homeostasis of the gut–liver axis. EULP restored the composition of intestinal flora with an increase in the relative abundance of Lactobacillaceae and a decrease in Lachnospiraceae and Verrucomicrobiaceae. Notably, prolonged EULP pretreatment (14 days) but no single gavage of EULP achieved excellent hepatoprotection. These findings endorsed the potential of EULP as a functional food for mitigating acute alcoholic-induce d liver damage, attributed to its anti-inflammatory, antioxidant, and prebiotic properties facilitated by the microbiota–gut–liver axis.
The Effect of Genome Parametrization and SNP Marker Subsetting on Genomic Selection in Autotetraploid Alfalfa
Authors: Nazzicari Nelson , Franguelli Nicolò , Ferrari Barbara , Pecetti Luciano , Annicchiarico Paolo
Published: April 2024

Background: Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and the extent of the non-additive genetic variance associated with its autotetraploid genome. Methods: To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as tetraploid and diploid dosages, plus allele ratios) and SNP marker subsetting (all available SNPs, only genic regions, and only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used genotyping by sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and the onset of flowering, which were assessed in 143 genotyped plants from a genetically broad European reference population and their phenotyped half-sib progenies. Results: On average, the allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), while using all the SNPs offered an advantage compared with any specific SNP subsetting (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting achieved better performances. We also released Legpipe2, an SNP calling pipeline tailored for reduced representation (GBS, RAD) in medium-sized genotyping experiments.
Transcription Factors in Prostate Cancer: Insights for Disease Development and Diagnostic and Therapeutic Approaches
Authors: Silva Karla C. S. , Tambwe Nadine , Mahfouz Dalia H. , Wium Martha , Cacciatore Stefano , Paccez Juliano D. , Zerbini Luiz F.
Published: April 2024

Transcription factors (TFs) are proteins essential for the regulation of gene expression, and they regulate the genes involved in different cellular processes, such as proliferation, differentiation, survival, and apoptosis. Although their expression is essential in normal physiological conditions, abnormal regulation of TFs plays critical role in several diseases, including cancer. In prostate cancer, the most common malignancy in men, TFs are known to play crucial roles in the initiation, progression, and resistance to therapy of the disease. Understanding the interplay between these TFs and their downstream targets provides insights into the molecular basis of prostate cancer pathogenesis. In this review, we discuss the involvement of key TFs, including the E26 Transformation-Specific (ETS) Family (ERG and SPDEF), NF-κB, Activating Protein-1 (AP-1), MYC, and androgen receptor (AR), in prostate cancer while focusing on the molecular mechanisms involved in prostate cancer development. We also discuss emerging diagnostic strategies, early detection, and risk stratification using TFs. Furthermore, we explore the development of therapeutic interventions targeting TF pathways, including the use of small molecule inhibitors, gene therapies, and immunotherapies, aimed at disrupting oncogenic TF signaling and improving patient outcomes. Understanding the complex regulation of TFs in prostate cancer provides valuable insights into disease biology, which ultimately may lead to advancing precision approaches for patients.
Defense and Protection of the Marine Coastal Areas and Human Health: A Case Study of Asbestos Cement Contamination (Italy)
Authors: Somma Roberta , Giacobbe Salvatore , La Monica Francesco Paolo , Molino Maria Letizia , Morabito Marina , Spoto Sebastiano Ettore , Zaccaro Salvatore , Zaffino Giuseppe
Published: April 2024

Pivotal environmental geology research was carried out in the protected area of Cape Peloro (Messina, NE Sicily, Italy). The main aims were the ascertainment of the presence of Asbestos Cement Materials (ACMs), their mapping, and, consequently, an estimation of the potential risk for human health and marine coastal environments. The beaches surveyed covered 4500 m of coastline. Through high-resolution photographic surveys, over 520 fiber cement fragments were documented on the beaches as well as in beach deposits. The materials, after microscope, SEM-EDS, and FTIR analyses, were found to be composed of Portland cement with chrysotile and crocidolite fibers. Fragments of ACMs showed typical corrugated forms with centimeter-to-decimeter sizes and prevailing well-rounded, platy, and sub-elongate shapes. In a few localities, some fragments were found to be angular or friable. Furthermore, some fragments found on the beach were covered by conspicuous encrustations of marine organisms, testifying to their long staying in shallow-water marine environments. Illicit landfills and abandoned materials were identified in natural sections on the coastal plain. Most of the rounded ACMs were characterized by their surface texture, with mm-size asbestos fibers exposed on the surface due to significant weathering and abrasion. Notably, new fragments appeared after storms. Significant criticisms have been made related to the ACMs, analogously to what was reported for other Italian marine beaches. Possible intervention and reclamation activities cannot limit themselves to removing the fragments on the beach, as fragments are immersed in the coastal sediments at different depths and are also found in the marine deposits. Here, it is underlined that any asbestos removal and reclamation activities, if not designed and based on a multidisciplinary approach and knowledge of local coastal dynamics and the meteo-marine climate, will be very expensive and ineffective.
Aphasia Depression and Psychological Therapy (ADaPT): Perspectives of People with Post-Stroke Aphasia on Participating in a Modified Cognitive Behavioral Therapy
Authors: Baker Caroline , Thomas Sonia , Tjokrowijoto Priscilla , Ryan Brooke , Kneebone Ian , Stolwyk Renerus
Published: April 2024

Aphasia, a communication disability commonly caused by stroke, can profoundly affect a person’s mood and identity. We explored the experiences of stroke survivors with aphasia and depression who received a modified cognitive behavioral therapy (CBT)-based psychological intervention. The therapy is manualized with a flexible treatment protocol, including 10 individually based therapy sessions (+2 booster sessions) either via telehealth or in person. Six participants with chronic aphasia (60% of the total sample) participated in in-depth interviews that were analyzed using reflexive thematic analysis. Two core themes were derived from the data: the first theme, helpful elements of therapy—doing enjoyable activities, new ways of thinking, problem solving, working with the experienced therapist, and using telehealth; and the second theme, making progress—mood, communication, acceptance of the ‘new me’, and improving relationships. All participants found the therapy to be helpful in managing mood problems with various elements being beneficial depending on the individual, highlighting the importance of tailoring the intervention. Therefore, delivering modified CBT to individuals with aphasia is likely to be acceptable both in person and through telehealth. Further evaluation of the intervention and its impact on mood would be beneficial.
Physiological and Growth Responses of W. Murcott Tangor Grafted on Four Rootstocks under Water Restriction
Authors: Tobar Sophia , Gil Pilar M. , Schaffer Bruce , Schwember Andrés R. , Cautín Ricardo , Mártiz Johanna
Published: April 2024

Citrus orchards in semi-arid regions are increasingly exposed to drought conditions due to climate change. This study compared the physiological and growth responses of ‘W. Murcott’ tangor (WM) grafted onto Citrus macrophylla (M), Swingle citrumelo (SC), C-35 citrange (C35), or bitter citrandarin (C22) rootstock subjected to two irrigation treatments: daily irrigation to replace 100% of the water lost daily by evapotranspiration (ET; control treatment) or daily irrigation to replace 75% of the water lost daily by ET (water deficit treatment). For trees in each treatment, leaf gas exchange, relative chlorophyll content, chlorophyll fluorescence, midday stem water potential, trunk cross-sectional area, and shoot length were measured 46 days after treatments were initiated. The results showed that WM on SC or C22 rootstock exhibited isohydric behavior, where decreased stomatal conductance limited transpiration in the water deficit treatment. WM on M rootstock exhibited an anisohydric response in the water deficit treatment, where there was no stomatal control of water loss by transpiration. Among the rootstocks tested for WM, the most tolerant to soil water deficit was SC, whereas trees on M rootstock were the most negatively affected by soil water deficit.
Epstein–Barr Virus Latent Membrane Protein 2A (LMP2A) Enhances ATP Production in B Cell Tumors through mTOR and HIF-1α
Authors: Incrocci Ryan , Monroy Del Toro Rosalinda , Devitt Grace , Salimian Melody , Braich Kamaljit , Swanson-Mungerson Michelle
Published: April 2024

Epstein–Barr Virus (EBV) exists in a latent state in 90% of the world’s population and is linked to numerous cancers, such as Burkitt’s Lymphoma, Hodgkin’s, and non-Hodgkin’s Lymphoma. One EBV latency protein, latency membrane protein 2A (LMP2A), is expressed in multiple latency phenotypes. LMP2A signaling has been extensively studied and one target of LMP2A is the mammalian target of rapamycin (mTOR). Since mTOR has been linked to reprogramming tumor metabolism and increasing levels of hypoxia-inducible factor 1 α (HIF-1α), we hypothesized that LMP2A would increase HIF-1α levels to enhance ATP generation in B lymphoma cell lines. Our data indicate that LMP2A increases ATP generation in multiple Burkitt lymphoma cell lines that were dependent on HIF-1α. Subsequent studies indicate that the addition of the mTOR inhibitor, rapamycin, blocked the LMP2A-dependent increase in HIF-1α. Further studies demonstrate that LMP2A does not increase HIF-1α levels by increasing HIF-1α RNA or STAT3 activation. In contrast, LMP2A and mTOR-dependent increase in HIF-1α required mTOR-dependent phosphorylation of p70 S6 Kinase and 4E-BP1. These findings implicate the importance of LMP2A in promoting B cell lymphoma survival by increasing ATP generation and identifying potential pharmaceutical targets to treat EBV-associated tumors.
Dichotomous Effects of Glypican-4 on Cancer Progression and Its Crosstalk with Oncogenes
Authors: Chérouvrier Hansson Victor , Cheng Fang , Georgolopoulos Grigorios , Mani Katrin
Published: April 2024

Glypicans are linked to various aspects of neoplastic behavior, and their therapeutic value has been proposed in different cancers. Here, we have systematically assessed the impact of GPC4 on cancer progression through functional genomics and transcriptomic analyses across a broad range of cancers. Survival analysis using TCGA cancer patient data reveals divergent effects of GPC4 expression across various cancer types, revealing elevated GPC4 expression levels to be associated with both poor and favorable prognoses in a cancer-dependent manner. Detailed investigation of the role of GPC4 in glioblastoma and non-small cell lung adenocarcinoma by genetic perturbation studies displays opposing effects on these cancers, where the knockout of GPC4 with CRISPR/Cas9 attenuated proliferation of glioblastoma and augmented proliferation of lung adenocarcinoma cells and the overexpression of GPC4 exhibited a significant and opposite effect. Further, the overexpression of GPC4 in GPC4-knocked-down glioblastoma cells restored the proliferation, indicating its mitogenic effect in this cancer type. Additionally, a survival analysis of TCGA patient data substantiated these findings, revealing an association between elevated levels of GPC4 and a poor prognosis in glioblastoma, while indicating a favorable outcome in lung carcinoma patients. Finally, through transcriptomic analysis, we attempted to assign mechanisms of action to GPC4, as we find it implicated in cell cycle control and survival core pathways. The analysis revealed upregulation of oncogenes, including FGF5, TGF-β superfamily members, and ITGA-5 in glioblastoma, which were downregulated in lung adenocarcinoma patients. Our findings illuminate the pleiotropic effect of GPC4 in cancer, underscoring its potential as a putative prognostic biomarker and indicating its therapeutic implications in a cancer type dependent manner.
The MDM2–p53 Axis Represents a Therapeutic Vulnerability Unique to Glioma Stem Cells
Authors: Nakagawa-Saito Yurika , Mitobe Yuta , Togashi Keita , Suzuki Shuhei , Sugai Asuka , Takenouchi Senri , Nakamura Kazuki , Sonoda Yukihiko , Kitanaka Chifumi , Okada Masashi
Published: April 2024

The prevention of tumor recurrence by the successful targeting of glioma stem cells endowed with a tumor-initiating capacity is deemed the key to the long-term survival of glioblastoma patients. Glioma stem cells are characterized by their marked therapeutic resistance; however, recent evidence suggests that they have unique vulnerabilities that may be therapeutically targeted. We investigated MDM2 expression levels in glioma stem cells and their non-stem cell counterparts and the effects of the genetic and pharmacological inhibition of MDM2 on the viability of these cells as well as downstream molecular pathways. The results obtained showed that MDM2 expression was substantially higher in glioma stem cells than in their non-stem cell counterparts and also that the inhibition of MDM2, either genetically or pharmacologically, induced a more pronounced activation of the p53 pathway and apoptotic cell death in the former than in the latter. Specifically, the inhibition of MDM2 caused a p53-dependent increase in the expression of BAX and PUMA and a decrease in the expression of survivin, both of which significantly contributed to the apoptotic death of glioma stem cells. The present study identified the MDM2–p53 axis as a novel therapeutic vulnerability, or an Achilles’ heel, which is unique to glioma stem cells. Our results, which suggest that non-stem, bulk tumor cells are less sensitive to MDM2 inhibitors, may help guide the selection of glioblastoma patients suitable for MDM2 inhibitor therapy.
Tumor Cell-Associated IL-1α Affects Breast Cancer Progression and Metastasis in Mice through Manipulation of the Tumor Immune Microenvironment
Authors: Krishnamohan Mathumathi , Kaplanov Irena , Maudi-Boker Sapir , Yousef Muhammad , Machluf-Katz Noy , Cohen Idan , Elkabets Moshe , Titus Jaison , Bersudsky Marina , Apte Ron N. , Voronov Elena , Braiman Alex
Published: April 2024

IL-1α is a dual function cytokine that affects inflammatory and immune responses and plays a pivotal role in cancer. The effects of intracellular IL-1α on the development of triple negative breast cancer (TNBC) in mice were assessed using the CRISPR/Cas9 system to suppress IL-1α expression in 4T1 breast cancer cells. Knockout of IL-1α in 4T1 cells modified expression of multiple genes, including downregulation of cytokines and chemokines involved in the recruitment of tumor-associated pro-inflammatory cells. Orthotopical injection of IL-1α knockout (KO) 4T1 cells into BALB/c mice led to a significant decrease in local tumor growth and lung metastases, compared to injection of wild-type 4T1 (4T1/WT) cells. Neutrophils and myeloid-derived suppressor cells were abundant in tumors developing after injection of 4T1/WT cells, whereas more antigen-presenting cells were observed in the tumor microenvironment after injection of IL-1α KO 4T1 cells. This switch correlated with increased infiltration of CD3+CD8+ and NKp46+cells. Engraftment of IL-1α knockout 4T1 cells into immunodeficient NOD.SCID mice resulted in more rapid tumor growth, with increased lung metastasis in comparison to engraftment of 4T1/WT cells. Our results suggest that tumor-associated IL-1α is involved in TNBC progression in mice by modulating the interplay between immunosuppressive pro-inflammatory cells vs. antigen-presenting and cytotoxic cells.
AI-Driven Precision Clothing Classification: Revolutionizing Online Fashion Retailing with Hybrid Two-Objective Learning
Authors: Abbas Waseem , Zhang Zuping , Asim Muhammad , Chen Junhong , Ahmad Sadique
Published: April 2024

In the ever-expanding online fashion market, businesses in the clothing sales sector are presented with substantial growth opportunities. To utilize this potential, it is crucial to implement effective methods for accurately identifying clothing items. This entails a deep understanding of customer preferences, niche markets, tailored sales strategies, and an improved user experience. Artificial intelligence (AI) systems that can recognize and categorize clothing items play a crucial role in achieving these objectives, empowering businesses to boost sales and gain valuable customer insights. However, the challenge lies in accurately classifying diverse attire items in a rapidly evolving fashion landscape. Variations in styles, colors, and patterns make it difficult to consistently categorize clothing. Additionally, the quality of images provided by users varies widely, and background clutter can further complicate the task of accurate classification. Existing systems may struggle to provide the level of accuracy needed to meet customer expectations. To address these challenges, a meticulous dataset preparation process is essential. This includes careful data organization, the application of background removal techniques such as the GrabCut Algorithm, and resizing images for uniformity. The proposed solution involves a hybrid approach, combining the strengths of the ResNet152 and EfficientNetB7 architectures. This fusion of techniques aims to create a classification system capable of reliably distinguishing between various clothing items. The key innovation in this study is the development of a Two-Objective Learning model that leverages the capabilities of both ResNet152 and EfficientNetB7 architectures. This fusion approach enhances the accuracy of clothing item classification. The meticulously prepared dataset serves as the foundation for this model, ensuring that it can handle diverse clothing items effectively. The proposed methodology promises a novel approach to image identification and feature extraction, leading to impressive classification accuracy of 94%, coupled with stability and robustness.