bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro and In Vivo Evaluation of the De Novo Designed Antimicrobial Peptide P6.2 Against a KPC-Producing P. aeruginosa Clinical Isolate
Authors: Martinez Melina M. B. , Corleto Merlina , Weschenfeller Melanie , Urrea Montes Santiago , Salomón Camila N. , Gonzalez Natalia , Garavaglia Matías , Facone Diego , Maffía Paulo C.
Published: February 2025

The antimicrobial peptide P6.2 was previously de novo designed as an alpha helix cationic amphipathic molecule. In previous work, we have shown that this peptide displayed significant antimicrobial activity against both Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa) bacteria. However, while P6.2 lacked biofilm-inhibiting properties against the P. aeruginosa strain PA01, it displayed anti-inflammatory effects in a murine acute lung infection model challenged with this pathogen. In this work, the peptide P6.2 antimicrobial activity and its possible synergy with meropenem were evaluated both in vitro and in vivo using a Galleria mellonella infection model against a carbapenem-resistant KPC-producing clinical isolate of P. aeruginosa. Firstly, the cytotoxic effect of the peptide on A549 and RAW264.7 cell lines was assayed, showing no cytotoxicity at 64 µg/mL and below. Then, the MIC (minimal inhibitory concentration) and bactericidal effect against the carbapenemase-producing strain P. aeruginosa M13513 strain were determined. P6.2 showed a MIC between 32 and 64 µg/mL, and a rapid bactericidal activity against this strain (less than 45 min). The peptide stability at different temperatures and in bovine serum at 37 °C was also analyzed, showing good stability and almost no degradation after 15 min of incubation at 100 °C or 24 h at 37 °C in serum, respectively. The antibiofilm activity was also evaluated, and although the peptide did not show biofilm inhibitory activity, it did demonstrate biofilm disruptive activity, together with bactericidal activity inside the pre-formed biofilm. The possible synergistic effect with the carbapenem meropenem was then analyzed in vitro by killing kinetics, revealing a synergistic interaction between P6.2 and the antibiotic against this strain. Finally, P6.2 was evaluated in vivo in the Galleria mellonella larvae infection model. Interestingly, in G. mellonella, P6.2 alone did not completely clear the infection caused by P. aeruginosa M13513. However, when combined with meropenem, P6.2 demonstrated a synergistic effect, leading to increased survival rates in infected larvae. The results presented here highlight the potential that this peptide displays when used in combination with carbapenems against a clinically relevant KPC-producing P. aeruginosa.
The Complete Mitochondrial Genome of Thymus mongolicus and Its Phylogenetic Relationship with Lamiaceae Species
Authors: Na Na , Wu Zinian , Wang Zhiyong , Yang Yanting , Tian Chunyu , Zhu Lin , Ou Taiyou , Chen Xiaofei , Xia Hongyan , Li Zhiyong
Published: February 2025

Thymus mongolicus (Lamiaceae) is a plant commonly found throughout China, in which it is widely used in chemical products for daily use, traditional medicinal preparations, ecological management, and cooking. In this study, we have assembled and annotated for the first time the entire mitochondrial genome (mitogenome) of T. mongolicus. The mitochondrial genome of T. mongolicus is composed in a monocyclic structure, with an overall size of 450,543 base pairs (bp) and a GC composition of 45.63%. It contains 32 unique protein-encoding genes. The repetitive sequences of the T. mongolicus mitogenome include 165 forward repetitive sequences and 200 palindromic repetitive sequences, in addition to 88 simple sequence repeats, of which tetramers accounted for the highest proportion (40.91%). An analysis of the mitogenome codons revealed that synonymous codons generally end with A/U. With the exception of nad4L, which uses ACG/ATG as an initiation codon, all other genes begin with the ATG start codon. Codon analysis of the mitogenome also showed that leucine (909) are the most abundant amino acid, while tryptophan (134) are the least prevalent. In total, 374 RNA editing sites were detected. Moreover, 180 homologous segments totaling 105,901 bp were found when the mitochondrial and chloroplast genomes of T. mongolicus were compared. Phylogenetic analysis further indicated that T. mongolicus is most closely related to Prunella vulgaris in the Lamiaceae family. Our findings offer important genetic insights for further research on this Lamiaceae species. To the best of our knowledge, this study is the first description of the entire mitogenome of T. mongolicus.
An Empirical Evaluation of Large Language Models on Consumer Health Questions
Authors: Abrar Moaiz , Sermet Yusuf , Demir Ibrahim
Published: February 2025

Background: Large Language Models (LLMs) have demonstrated strong performances in clinical question-answering (QA) benchmarks, yet their effectiveness in addressing real-world consumer medical queries remains underexplored. This study evaluates the capabilities and limitations of LLMs in answering consumer health questions using the MedRedQA dataset, which consists of medical questions and answers by verified experts from the AskDocs subreddit. Methods: Five LLMs-GPT-4o mini, Llama 3.1-70B, Mistral-123B, Mistral-7B, and Gemini-Flash were assessed using a cross-evaluation framework. Each model generated responses to consumer queries and their outputs were evaluated by every model by comparing them with expert responses. Human evaluation was used to assess the reliability of models as evaluators. Results: GPT-4o mini achieved the highest alignment with expert responses according to four out of the five models’ judges, while Mistral-7B scored the lowest according to three out of five models’ judges. Overall, model responses show low alignment with expert responses. Conclusions: Current small or medium sized LLMs struggle to provide accurate answers to consumer health questions and must be significantly improved.
Advancements in the Esterification of Phytosterols Catalyzed by Immobilized Lipase
Authors: Zhang Yuyang , Yan Yan , Lin Zhiyuan , Kong Fanzhuo , Ni Xing , Zhang Xue , Zhao Yani , Lu Qiongya , Zou Bin
Published: February 2025

Phytosterol exhibits cholesterol-lowering, cardiovascular-protecting, anti-inflammatory, and anticancer efficacies but has low bioavailability due to its high melting point and poor solubility. Esterification with fatty acids enhances liposolubility, improving absorption and utilization fivefold. Industrial production of phytosterol esters mainly relies on chemical synthesis, which faces challenges in separation, purification, and quality assurance due to side reactions. Enzymatic synthesis, featuring mild conditions, environmental friendliness, and high selectivity, has gained attention from academia and industry. Candida rugosa lipase (CRL) is widely utilized due to its high efficiency in catalyzing the esterification of phytosterol. Natural lipases are highly sensitive to changes in temperature and pH and are difficult to reuse in continuous cycles; however, certain immobilization techniques can improve their catalytic activity and stability. Furthermore, the application of immobilized lipases in the synthesis of phytosterol esters can be combined with ultrasonic treatment to enhance the efficiency of enzymatic catalysis. This paper reviews the research progress on the catalytic esterification of phytosterol by immobilized lipases, highlighting the current challenges and future research directions, thereby fostering further advancements in the field of preparing phytosterol esters through immobilized lipase catalysis.
Pro-Fibrotic Macrophage Subtypes: SPP1+ Macrophages as a Key Player and Therapeutic Target in Cardiac Fibrosis?
Authors: Uhlig Moritz , Billig Sebastian , Wienhold Jan , Schumacher David
Published: February 2025

Cardiac fibrosis is a major driver of heart failure, a leading cause of morbidity and mortality worldwide. Advances in single-cell transcriptomics have revealed the pivotal role of SPP1+ macrophages in the pathogenesis of cardiac fibrosis, positioning them as critical mediators and promising therapeutic targets. SPP1+ macrophages, characterized by elevated expression of secreted phosphoprotein 1 (SPP1) and often co-expressing Triggering Receptor Expressed on Myeloid Cells 2 (TREM2), localize to fibrotic niches in the heart and other organs. These cells interact with activated fibroblasts and myofibroblasts, driving extracellular matrix remodeling and fibrosis progression. Their differentiation is orchestrated by signals such as CXCL4, GM-CSF, and IL-17A, further emphasizing their regulatory complexity. Therapeutic strategies targeting SPP1+ macrophages have shown encouraging preclinical results. Approaches include silencing Spp1 using antibody–siRNA conjugates and modulating key pathways involved in macrophage differentiation. These interventions have effectively reduced fibrosis and improved cardiac function in animal models. The mechanisms underlying SPP1+ macrophage function in cardiac fibrosis provide a foundation for innovative therapies aimed at mitigating pathological remodeling and improving outcomes in patients with heart failure. This emerging field has significant potential to transform the treatment of fibrotic heart disease.
Discriminatory Value and Validation of a Risk Prediction Model Based on Serum Cytokines in Pediatric Acute Appendicitis: A Single-Center Experience of 483 Cases
Authors: Zhou Jiajia , Liu Guobin , Song Xiaofeng , Kang Quan
Published: February 2025

Objectives: Pediatric acute appendicitis (AA) is one of the most prevalent acute abdominal conditions in pediatric surgery. Children with complicated acute appendicitis (CA) may need timely surgical decisions and have a worse prognosis. In this study, we explored the risk factors and developed a predictive model for complicated AA in children. Methods: A retrospective analysis was conducted on patients data from those hospitalized for acute appendicitis, confirmed by post-surgery pathological results, at Children’s Hospital of Chongqing Medical University between September 2022 and October 2023. Lasso regression was performed to identify risk factors, and multivariate logistic regression analysis was used for model establishment. Results: Serum levels of IFN-γ, IL-5, IL-6, IL-8, and IL-10 before surgery were useful in classifying acute appendicitis in children. IL-6, IL-8, and IL-10, on their own, had high predictive values for CA in children. Independent risk factors for CA were age, IL-10, and IFN-γ. A multifactorial logistic regression prediction model was established, demonstrating good predictive efficacy. Its predictive sensitivity was 70.0%, specificity 73.9%, with an AUC of 0.7949. Furthermore, the results of the external validation indicated that the model’s accuracy was good, with an AUC of 0.8567. Conclusions: Early identification of CA is imperative for timely clinical decision-making. Prediction models based on age, IL-10, and IFN-γ may be reliable and accurate in predicting the incidence of CA, which may lead to better clinical outcomes for children with AA.
Adaptation and Implementation of the Global Scales for Early Development (GSED) Tool in Ethiopia
Authors: Yibeltal Kalkidan , Teklehaimanot Atsede , Workneh Firehiwot , Fasil Nebiyou , Jensen Sarah K. G. , Chin Theresa I. , North Krysten , Haymanot Betelhem , Worku Alemayehu , Lee Anne CC , Berhane Yemane
Published: February 2025

Background: The World Health Organization (WHO) recently developed the Global Scales for Early Development (GSED) tool to address the lack of a population-level metric for early childhood development globally. This paper describes learning from the first experience with the translation, adaptation, and implementation of the GSED tool in Ethiopia. Methods: WHO guidelines were followed to translate and adapt the GSED tool to Amharic. Two Ethiopian child health experts were trained as GSED Master Trainers. The tool was forward translated by two independent translators with previous experience in child development assessment, consensus was obtained, and the back translation was reviewed/approved by the WHO. The GSED app was programmed in Amharic and piloted for 40 children aged 6–36 months, followed by its implementation by trained study nurses in a child development study in Bahir Dar. Results: Minor adaptations were made to terminologies and certain items were rephrased in the short and long forms. Modifications were made to physical objects used in the long form to make the items culturally appropriate and familiar. Local examples were used where necessary. The tool was administered to 364 children aged 6–36 months with an average administration time of 50–60 min. Quality control assessments by master trainers showed high agreement with assessments by trained study nurses throughout the study (average agreement: 91%). This study demonstrated the high acceptability and feasibility of the GSED tools. Conclusions: Local adaptations were required to contextualize the GSED tool for the Ethiopian setting. The preliminary experience with the GSED tool in Ethiopia is positive, with high-competency trained staff and ease of administration.
SJB2-043, a USP1 Inhibitor, Suppresses A549 Cell Proliferation, Migration, and EMT via Modulation of PI3K/AKT/mTOR, MAPK, and Wnt Signaling Pathways
Authors: Wu Lipeng , Yu Meng , Liang Huosheng , Lin Long , Li Huajian , Chen Guangyang , Muhetaer Halimulati , Li Jingjing , Wu Bo , Jia Xuejing , Dang Yuanye , Zheng Guodong , Li Chuwen
Published: February 2025

Objective: Non-small cell lung cancer (NSCLC) remains one of the most significant contributors to cancer-related mortality. This investigation explores the influence and underlying mechanisms of the USP1 inhibitor SJB2-043 on A549 cells, with the aim of advancing the development of anti-NSCLC therapeutics. Methods: Publicly available databases were utilized to assess USP1 expression and its association with the progression of NSCLC. Gene expression variations were ascertained through RNA sequencing, followed by the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology pathway enrichment evaluations. Various doses of SJB2-043 were administered to A549 cells to evaluate its impact on cell multiplication, motility, apoptosis, and the cell cycle using CCK-8 assays, colony formation, wound healing, flow cytometry, and Western blotting (WB). Results: USP1 was found to be overexpressed in NSCLC specimens and linked to adverse prognosis. Treatment with SJB2-043 markedly inhibited A549 cell proliferation and migration, diminished clonogenic potential, and triggered apoptosis in a dose-dependent manner. Modifications in the cell cycle were observed, showing an elevated percentage of cells in the G2 phase while exhibiting a parallel decline in the G1 phase. WB examination demonstrated diminished protein levels of N-cadherin, CyclinB1, CDK1, C-myc, Bcl-2, p-ERK/ERK, p-p38/p38, p-JNK/JNK, p-AKT/AKT, and p-mTOR/mTOR, alongside an upregulation of E-cadherin, ZO-1, occludin, p53, Bax, p-β-catenin/β-catenin, and GSK3β. Conclusions: SJB2-043 exerts a suppressive effect on A549 cell proliferation, migration, and epithelial–mesenchymal transition while enhancing apoptosis. These cellular effects appear to be mediated through the inhibition of the MAPK, Wnt/β-catenin, and PI3K/AKT/mTOR signaling cascades, in addition to modulation of the cell cycle.
Preparation and Hydrogen Resistance Property of CrCN Coating by Magnetron Sputtering Method Under Different C-Target Powers
Authors: Cai Ke , Jiang Bailing , Su Xiaolei
Published: February 2025

CrCN coatings on an X80 substrate were prepared by the magnetron sputtering method under different C-target powers. The prepared coatings were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and XPS (X-ray Photoelectron Spectroscopy), respectively. The electrochemical corrosion behavior and contact angle of the prepared coatings were tested by an electrochemical workstation and a wetness angle measuring instrument, respectively. Results showed that when the C-target power was 0 W, the prepared coating was a pure CrN phase, and when the C-target power was above 0 W, the prepared coating was an amorphous phase. The corrosion potential of the prepared coating increased with increasing C-target power. The contact angle increased with increasing C-target power. XPS results showed that there were Cr-N, C-N, C-Cr, sp2 C-C/C-N, and sp3 C-C/C-N bonds in the CrCN crystal. The C-doped CrCN coating indicated better hydrogen resistance than the pure CrN coating. When the C-target power was 140 W, the hydrogen barrier performance of the CrCN coating was about twice that of pure CrN.
Exploring New Nitrogen-Rich Compounds: Hybrid First-Principle Calculations and Machine-Learning Algorithms
Authors: Zhou Hang , Wu Jie , Yang Jiangtao , Fan Qingyang
Published: February 2025

The third-generation semiconductors have the characteristics of a large bandgap, a high breakdown electric field, a fast electron saturation rate, high-temperature resistance, corrosion resistance, and radiation resistance, making them the preferred core materials and devices for cutting-edge high-tech fields, such as mobile communication, new energy vehicles, and smart grids in the future. The III–V compound semiconductors are a typical representative of them. In order to discover and explore new III–V semiconductor materials more efficiently and accurately, this paper adopts a machine-learning method optimized by the beetle algorithm and combined with first-principle calculation verification to efficiently and accurately predict the performance of III–V nitride materials and study their physicochemical properties. This study improved the prediction efficiency of nitrogen-rich III–V semiconductor materials through the combination of machine learning and first principles, providing a new approach for the efficient and accurate prediction of semiconductor materials.
Enhancing Care Through a Virtual Canadian Community of Practice for Managing Immune-Related Adverse Events
Authors: Esfahani Khashayar , Walker John , Bambury Kevin , O’Carroll Eoin , Snow Stephanie
Published: February 2025

The advent of immune checkpoint inhibitors (ICIs) has significantly transformed cancer treatment outcomes. However, these therapies can induce immune-related adverse events (irAEs) that may affect any organ system, sometimes requiring specialized expertise. As ICIs are increasingly used across various tumor types and in earlier treatment settings, not all practitioners have the necessary support network to handle complex irAEs. To address this gap, we collaborated with ONCOassist, a leading app for oncology professionals, to establish the first virtual Canadian Community of Practice (CoP) focused on irAEs. The CoP facilitates continuous learning and improves patient care among Canadian clinicians treating patients with immunotherapy by providing a platform for knowledge exchange and peer-to-peer support. This article outlines the development and growth of the CoP on irAEs, highlighting both successes and challenges. As of May 2024, over a year since its inception, the CoP on irAEs has attracted almost 130 Canadian oncology healthcare professionals, and peer-to-peer interactions and engagement continue to increase. To ensure its long-term sustainability, we plan to evolve and adapt the CoP to meet the needs of the oncology community and address clinical challenges associated with new therapies.
Substrate Preference and Seasonal Distribution of Bdelloid Rotifers in Mosses in a Primary Forest in Thailand
Authors: Pokpongmongkol Poomipat , Jaturapruek Rapeepan , Sa-ardrit Phannee , Maiphae Supiyanit
Published: February 2025

Previous studies have shown that the bdelloid rotifer diversity and composition vary across substrates, yet microscale investigations remain unexplored. To address this gap in knowledge, we examined the diversity, density, and composition of bdelloid rotifers across moss substrates and seasons. They were analyzed from 491 moss samples collected monthly from seven substrate types in a primary forest in Thailand between September 2021 and December 2022. Our study reveals high bdelloid rotifer diversity. The morphological and molecular analyses identified 17 species, including 4 new records for Thailand, increasing the total to 34. In addition, while moss on tree trunks and the wet season showed a high species richness and total density, the results revealed no significant variation across the substrates or seasons. However, the similarity of the species composition varied significantly between the substrates (<25%) and between seasons (36.99%). Moreover, rainfall and humidity appear to be key factors shaping the bdelloid rotifer community in this limnoterrestrial habitat.
Automatic Detection of Radiographic Alveolar Bone Loss in Bitewing and Periapical Intraoral Radiographs Using Deep Learning Technology: A Preliminary Evaluation
Authors: AlGhaihab Amjad , Moretti Antonio J. , Reside Jonathan , Tuzova Lyudmila , Huang Yiing-Shiuan , Tyndall Donald A.
Published: February 2025

Background/Objective: Periodontal disease is a prevalent inflammatory condition affecting the supporting structures of teeth, with radiographic bone loss (RBL) being a critical diagnostic marker. The accurate and consistent evaluation of RBL is essential for the staging and grading of periodontitis, as outlined by the 2017 AAP/EFP Classification. Advanced tools such as deep learning (DL) technology, including Denti.AI, an FDA-cleared software utilizing convolutional neural networks (CNNs), offer the potential for enhancing diagnostic accuracy. This study evaluated the diagnostic accuracy of Denti.AI for detecting RBL in intraoral radiographs. Methods: A dataset of 39 intraoral radiographs (22 periapical and 17 bitewing), covering 316 tooth surfaces (123 periapical and 193 bitewing), was selected from a de-identified pool of 500 radiographs provided by Denti.AI. RBL was assessed using the 2017 AAP/EFP Classification. A consensus panel of three board-certified dental specialists served as the reference standard. Performance metrics, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and mean absolute error (MAE), were calculated. Results: For periapical radiographs, Denti.AI achieved a sensitivity of 76%, specificity of 86%, PPV of 83%, NPV of 80%, and accuracy of 81%, with an MAE of 0.046%. For bitewing radiographs, sensitivity was 65%, specificity was 90%, PPV was 88%, NPV was 70%, and accuracy was 76%, with an MAE of 0.499 mm. Conclusions: Denti.AI demonstrated clinically acceptable performance in detecting RBL and shows potential as an adjunctive diagnostic tool, supporting clinical decision-making. While performance was robust for periapical radiographs, further optimization may enhance its accuracy for bitewing radiographs.
Bone Health in Paediatric Inflammatory Bowel Disease
Authors: Sen Proteek , Uday Suma
Published: February 2025

Paediatric inflammatory bowel disease (IBD) is often complicated by bone loss resulting in an increased risk of fractures and impaired quality of life. Underlying inflammation, nutritional deficiencies and glucocorticoid therapy are some of the factors contributing to secondary osteoporosis in IBD. Optimising nutrition, dietary supplementation and timely screening are essential in preventing bone loss. Bisphosphonate therapy remains the cornerstone of medical management of osteoporosis. This review explores the various mechanisms contributing towards poor bone health in IBD and the recent advances in diagnostic and preventive approaches along with updates in management strategies.
Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey
Authors: Liu Yu , Sun Biao , Wu Yuru , Zhang Yongxin , Yang Jiahui , Wang Wen , Thotakura Naga Lakshmi , Liu Qian , Liu Yilu
Published: February 2025

In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.
How Much Is Needed? Discussion on Benchmarks for Primary Energy Input and Global Warming Potential Caused by Building Construction
Authors: Rabenseifer Roman , Kalivodová Martina , Kononets Yevhen , Mahas Nataliia , Minarovičová Katarína , Provazník Robert , Bordun Maryna , Shekhorkina Svitlana , Savytskyi Mykola , Savytskyi Oleksandr , Semko Volodymyr
Published: February 2025

The operational energy efficiency of new buildings in the EU should be at the level of ultra-low or near-zero energy buildings. It is therefore relatively difficult to achieve further energy savings. However, the pre-operational phase—raw material sourcing, manufacturing, transportation, and construction—offers significant energy savings and greenhouse gas reduction opportunities, referred to as embodied energy and equivalent CO2 emissions. Unlike operational energy, no standard or legislative criteria have yet been established for embodied energy. Setting maximum embodied energy values converted to the unit of heated building area, accounting for building shape factor, and differentiating between high-mass and lightweight constructions are proposed. This study illustrates assessing environmental indicators based on building shape, highlighting the necessity of relative assessments over absolute values to favour energy efficiency. It also emphasizes that precise criteria should derive from authentic data collected during the energy certification and building permitting processes. Integrating assessments of embodied energy and operational energy demand facilitates a comprehensive evaluation of buildings’ environmental performance.
Insight into Bioactive Compounds and Antioxidant Activity of Bakery Products Fortified with Fruit Pomace
Authors: Mandache Maria Bianca , Vijan Loredana Elena , Cosmulescu Sina
Published: February 2025

The aim of this work was to analyse the influence of the application of apple, sour cherry and peach pomace on the content of bioactive compounds and antioxidant activity in bakery products supplemented with different proportions of pomace (5%, 10% and 15%). The type of pomace applied determined some variations, but it was observed that at a maximum substitution percentage (15%), breads with peach pomace recorded the highest levels of polyphenols (855.10 mg GAE/100 g), flavonoids (181.01 mg CE/100 g) and tannins (385.26 mg GAE/100 g), which also generated the highest antiradical activity (42.84%). In general, an evolutionary distribution was observed between the increase in the content of polyphenols, flavonoids, tannins and antioxidant activity, which could indicate a synergistic action between all components. In all the analysed samples, increases in the constituent compounds and antioxidant activity were observed, consistent with the percentage of added pomace, with the analysis of the inclusion of different types of pomace becoming relevant in the context of industrial production.
Impact and Integration of Culturally Centered American Indian/Alaska Native Practices and Training During COVID-19 on Tele-Behavioral Substance Use Treatment: Protocol for a Community-Derived Mixed Methods Study
Authors: D’Silva Neshay S. , Wheeler Melissa , Roddy Juliette , Haberstroh Shane , Baldwin Julie A. , Mellott Ramona N. , Keene Chesleigh
Published: February 2025

(1) Background: American Indian and Alaska Native (AI/AN) communities faced disproportionate COVID-19 infection rates and a higher prevalence of substance use disorders (SUDs). Telehealth emerged as a key strategy to address these health disparities. (2) Objective: In response to a call to action from an urban Indian organization (UIO), our multidisciplinary team conducted a community-based participatory study to (1) examine the integration of Native practices in SUD treatment during COVID-19, and (2) develop provider training modules based on these findings. (3) Methods: Using a mixed methods approach, we conducted semi-structured interviews with six community SUD providers, surveyed 91 clients, and analyzed 278 de-identified health records from the UIO Native-serving facility in the Southwest U.S. from May 2020 to May 2021. (4) Results: As of October 2024, analysis of Aim 1 is ongoing. With UIO engagement, findings from Aim 1 are being translated into training modules for Aim 2. (5) Conclusion: This community-driven study lays the foundation for future research on Indigenous mental well-being, centering strength, resilience, and cultural knowledge in substance use treatment. Findings will be disseminated through presentations and publications with Native and non-Native communities, treatment centers, educators, and leaders. Future studies will assess the effectiveness of the training modules among clinicians.
DRFormer: A Benchmark Model for RNA Sequence Downstream Tasks
Authors: Fu Jianqi , Li Haohao , Kang Yanlei , Zhu Hancan , Huang Tiren , Li Zhong
Published: February 2025

Background/Objectives: RNA research is critical for understanding gene regulation, disease mechanisms, and therapeutic development. Constructing effective RNA benchmark models for accurate downstream analysis has become a significant research challenge. The objective of this study is to propose a robust benchmark model, DRFormer, for RNA sequence downstream tasks. Methods: The DRFormer model utilizes RNA sequences to construct novel vision features based on secondary structure and sequence distance. These features are pre-trained using the SWIN model to develop a SWIN-RNA submodel. This submodel is then integrated with an RNA sequence model to construct a multimodal model for downstream analysis. Results: We conducted experiments on various RNA downstream tasks. In the sequence classification task, the MCC reached 94.4%, surpassing the state-of-the-art RNAErnie model by 1.2%. In the protein–RNA interaction prediction, DRFormer achieved an MCC of 0.492, outperforming advanced models like BERT-RBP and PrismNet. In RNA secondary structure prediction, the F1 score was 0.690, exceeding the widely used SPOT-RNA model by 1%. Additionally, generalization experiments on DNA tasks yielded satisfactory results. Conclusions: DRFormer is the first RNA sequence downstream analysis model that leverages structural features to construct a vision model and integrates sequence and vision models in a multimodal manner. This approach yields excellent prediction and analysis results, making it a valuable contribution to RNA research.
Genetic Variants Associated with Suspected Neonatal Hypoxic Ischaemic Encephalopathy: A Study in a South African Context
Authors: Foden Caroline J. , Durant Kevin , Mellet Juanita , Joubert Fourie , van Rensburg Jeanne , Masemola Khomotso , Velaphi Sithembiso C. , Nakwa Firdose L. , Horn Alan R. , Pillay Shakti , Kali Gugu , Coetzee Melantha , Ballot Daynia E. , Kalua Thumbiko , Babbo Carina , Pepper Michael S.
Published: February 2025

Neonatal encephalopathy suspected to be due to hypoxic ischaemic encephalopathy (NESHIE) carries the risk of death or severe disability (cognitive defects and cerebral palsy). Previous genetic studies on NESHIE have predominantly focused on exomes or targeted genes. The objective of this study was to identify genetic variants associated with moderate–severe NESHIE through whole-genome, unbiased analysis. Variant filtering and prioritization were performed, followed by association testing both on a case–control basis and to compare the grades of severity and/or progression. Association testing on neonates with NESHIE (N = 172) and ancestry-matched controls (N = 288) produced 71 significant genetic variants (false discovery rate corrected p-value < 6.2 × 10−4), all located in non-coding regions and not previously implicated in NESHIE. Disease-associated variants in non-coding regions are considered to affect regulatory functions, possibly by modifying gene expression, promoters, enhancers, or DNA structure. The most significant variant was at position 6:162010973 in the Parkin RBR E3 ubiquitin protein ligase (PRKN) intron. Intronic variants were also identified in genes involved in inflammatory processes (SLCO3A1), DNA repair (ZGRF1), synaptogenesis (CNTN5), haematopoiesis (ASXL2), and the transcriptional response to hypoxia (PADI4). Ten variants were associated with a higher severity or lack of improvement in NESHIE, including one in ADAMTS3, which encodes a procollagen amino protease with a role in angiogenesis and lymphangiogenesis. This analysis represents one of the first efforts to analyze whole-genome data to investigate the genetic complexity of NESHIE in diverse ethnolinguistic groups of African origin and provides direction for further study.
Cellular Phenotypic Transformation During Atherosclerosis: The Potential Role of miRNAs as Biomarkers
Authors: Wassaifi Souhir , Kaeffer Bertrand , Zarrouk Sinda
Published: February 2025

Cellular phenotypic transformation is a key process that occurs during the development and progression of atherosclerosis. Within the arterial wall, endothelial cells, vascular smooth muscle cells, and macrophages undergo phenotypic changes that contribute to the pathogenesis of atherosclerosis. miRNAs have emerged as potential biomarkers for cellular phenotypic changes during atherosclerosis. Monitoring miR-155-5p, miR-210-3p, and miR-126-3p or 5p levels could provide valuable insights into disease progression, risk of complications, and response to therapeutic interventions. Moreover, miR-92a-3p’s elevated levels in atherosclerotic plaques present opportunities for predicting disease progression and related complications. Baseline levels of miR-33a/b hold the potential for predicting responses to cholesterol-lowering therapies, such as statins, and the likelihood of dyslipidemia-related complications. Additionally, the assessment of miR-122-5p levels may offer insights into the efficacy of low-density-lipoprotein-lowering therapies. Understanding the specific miRNA-mediated regulatory mechanisms involved in cellular phenotypic transformations can provide valuable insights into the pathogenesis of atherosclerosis and potentially identify novel therapeutic targets.
Overexpression of NKG2D and IL24 in NK Cell-Derived Exosomes for Cancer Therapy
Authors: Huang Chujun , Hu Qian , Wang Peiyun , Xie Mi , Zhang Ying , Li Zhixing , Tang Shuqing , Zhang Yuxuan , Tian Zhixin , Liu Xionghao , Hu Zhiqing , Liang Desheng
Published: February 2025

Natural killer (NK) cell-derived exosomes (NK-Exos) are emerging as a promising avenue in cancer immunotherapy due to their inherent tumor-targeting properties and their capacity to deliver therapeutic agents directly to malignant cells. This research delves into the boosted anti-tumor potency of NK-Exos that has been genetically enhanced to overexpress NKG2D, a vital activating receptor, along with interleukin-24 (IL24), a cytokine renowned for its selective suppressive impact on tumor cells. NKG2D facilitates the recognition of tumor cells by binding to stress-induced ligands, while IL24 induces apoptosis and modulates immune responses to enhance tumor destruction. The NK-Exos engineered to express both NKG2D and IL24 significantly enhanced tumor targeting and increased the apoptosis rate of tumor cells by 30% in A549 and by 20% in HELA at 48 h compared with non-modified NK-Exos, respectively. Furthermore, this enhancement also impacted cell proliferation, with inhibition rates increasing by 30%, 15%, and 15% in A549, HELA, and MCF-7 cells, respectively, and it reduced A549 cell migration by 10%. The integration of NKG2D and IL24 within NK-Exos confers a dual therapeutic mechanism, synergistically amplifying their efficacy in cancer treatment. The utility of NK-Exos co-expressing NKG2D and IL24 offers a novel approach to overcome the limitations of current therapies, providing prolonged tumor suppression and precise targeting of malignant cells and holding great promise for clinical application.
Metabolomic Panel for the Diagnosis of Heart Failure with Preserved Ejection Fraction
Authors: Kozhevnikova Maria V. , Kakotkina Anastasiia V. , Korobkova Ekaterina O. , Kuznetsov Ivan V. , Shestakova Ksenia M. , Moskaleva Natalia E. , Appolonova Svetlana A. , Belenkov Yuri N.
Published: February 2025

The diagnosis of heart failure with preserved ejection fraction (HFpEF) remains challenging. The use of metabolomics approaches seems promising in speeding up and simplifying the diagnostic process in HFpEF patients, which can lead to earlier treatment initiation and better improvement of patient condition. The aim of this study was to develop a diagnostic panel of metabolites (metabolomic biomarkers) for the detection and diagnosis of HF with preserved ejection fraction. The study included 76 participants with hypertension, 36 of whom were diagnosed with HFpEF. The blood plasma metabolomic profile, including 72 metabolites, was detected using high-performance liquid chromatography combined with mass spectrometry. There were 18 statistically significant differences in concentrations of metabolites and 3 differences in their ratios between HFpEF and hypertension groups. The prognostic model for detecting the possibility of HFpEF included seven metabolites and two ratios: hexadecenoylcarnitine, arginine, trimethylamine-N-oxide, asymmetric dimethylarginine (ADMA), arginine/ADMA ratio, kynurenine, kynurenine/tryptophan, neopterin, and anthranilic acid. The area under the ROC curve was 0.981 ± 0.017. The resulting model was statistically significant (p < 0.001). The metabolomic panel could be considered as an addition to the present HFpEF laboratory diagnostic criteria for blood plasma analysis in clinical practice.
Impact of Estrogen on Purinergic Signaling in Microvascular Disease
Authors: Cassavaugh Jessica , Longhi Maria Serena , Robson Simon C.
Published: February 2025

Microvascular ischemia, especially in the heart and kidneys, is associated with inflammation and metabolic perturbation, resulting in cellular dysfunction and end-organ failure. Heightened production of adenosine from extracellular nucleotides released in response to inflammation results in protective effects, inclusive of adaptations to hypoxia, endothelial cell nitric oxide release with the regulation of vascular tone, and inhibition of platelet aggregation. Purinergic signaling is modulated by ectonucleoside triphosphate diphosphohydrolase-1 (NTPDase1)/CD39, which is the dominant factor dictating vascular metabolism of extracellular ATP to adenosine throughout the cardiovascular tissues. Excess levels of extracellular purine metabolites, however, have been associated with metabolic and cardiovascular diseases. Physiological estrogen signaling is anti-inflammatory with vascular protective effects, but pharmacological replacement use in transgender and postmenopausal individuals is associated with thrombosis and other side effects. Crucially, the loss of this important sex hormone following menopause or with gender reassignment is associated with worsened pro-inflammatory states linked to increased oxidative stress, myocardial fibrosis, and, ultimately, diastolic dysfunction, also known as Yentl syndrome. While there is a growing body of knowledge on distinctive purinergic or estrogen signaling and endothelial health, much less is known about the relationships between the two signaling pathways. Continued studies of the interactions between these pathways will allow further insight into future therapeutic targets to improve the cardiovascular health of aging women without imparting deleterious side effects.
Overexpression of a Fragaria × ananassa AP2/ERF Transcription Factor Gene (FaTINY2) Increases Cold and Salt Tolerance in Arabidopsis thaliana
Authors: Li Wenhui , Zhang Wenhao , Li Huiwen , Yao Anqi , Ma Zhongyong , Kang Rui , Guo Yanbo , Li Xingguo , Yu Wenquan , Han Deguo
Published: February 2025

The AP2/ERF family of transcription factors is one of the most conserved and important transcription factor families, and it is ubiquitous in plants. It plays an essential role in plant morphogenesis, molecular mechanisms of stress responses, hormone signaling pathways, and synthesis of secondary metabolites. FaTINY2 was cloned from the octaploid strawberry Fragaria × ananassa for this investigation. Bioinformatics revealed that the protein possesses a conserved AP2 domain and is localized in the nucleus. When FaTINY2 was expressed in plants, quantitative analysis revealed that the gene was tissue-specific. There are lower contents of reactive oxygen species (ROS) and malondialdehyde (MDA), higher contents of proline, chlorophyll, and higher activities of catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD) in transgenic Arabidopsis thaliana than wild type (WT) and unload line (UL) plants under cold and salt stress. FaTINY2 plays a role in enhancing stress tolerance by regulating a few genes linked to the stress response. The findings of this study were that FaTINY2 transgenic Arabidopsis thaliana plants were more tolerant to salt and cold than WT and UL plants. In addition to offering a theoretical reference for strawberry production under stress, this research established a groundwork for exploration into the molecular mechanisms in which strawberries respond to cold and high salt stress.
Exploring the CDCA-Scd1 Axis: Molecular Mechanisms Linking the Colitis Microbiome to Neurological Deficits
Authors: Du Donglin , Li Qi , Wei Zhengqiang , Wang Ziwei , Xu Lei
Published: February 2025

Inflammatory bowel disease is a risk factor for brain dysfunction; however, the underlying mechanisms remain largely unknown. In this study, we aimed to explore the potential molecular mechanisms through which intestinal inflammation affects brain function and to verify these mechanisms. Mice were treated with multiple cycles of 1% w/v dextran sulfate sodium (DSS) in drinking water to establish a chronic colitis model. Behavioral tests were conducted using the open field test (OFT), tail suspension test (TST), forced swimming test (FST), and Morris water maze test (MWM). Brain metabolomics, transcriptomics, and proteomics analyses were performed, and key target proteins were verified using qPCR and immunofluorescence. Four cycles of DSS administration induced colitis, anxiety, depression, and spatial memory impairment. The integrated multi-omics characterization of colitis revealed decreased brain chenodeoxycholic acid (CDCA) levels as well as reduced stearoyl-CoA desaturase (Scd1) gene and protein expression. Transplantation of the colitis microbiome resulted in anxiety, depression, impaired spatial memory, reduced CDCA content, decreased Scd1 gene and protein expression, and lower concentrations of monounsaturated fatty acids (MUFAs), palmitoleate (C16:1), and oleate (C18:1) in the brain. In addition, CDCA supplementation improved DSS-induced colitis, alleviated depression and spatial memory impairment, and increased Scd1 gene and protein expression as well as MUFA levels in the brain. The gut microbiome induced by colitis contributes to neurological dysfunction, possibly through the CDCA–Scd1 signaling axis. CDCA supplementation alleviates colitis and depressive behavior, likely by increasing Scd1 expression in the brain.
Machine Learning in the Teaching Quality of University Teachers: Systematic Review of the Literature 2014–2024
Authors: Zambrano-Romero Walter , Rodriguez Ciro , Pita-Valencia Josselyn , Zambrano-Romero Walter José , Moran-Tubay José Manuel
Published: February 2025

The growth in the number of students in higher education institutions (HEIs) in Latin America reached 33.5 million in 2021 and more than 220 million worldwide, increasing the number of data volumes in academic management systems. Some of the difficulties that universities face are providing high-quality education to students and developing systems to evaluate the performance of teachers, which encourages offering a better quality of teaching in universities; in this sense, machine learning emerges with great potential in education. This literature review aims to analyze the factors, machine learning algorithms, challenges, and limitations most used to evaluate the quality of teaching based on performance. The methodology used is PRISMA, which considers analyzing literature produced between 2014 and 2024 on factors, prediction algorithms, challenges, and limitations to predict the quality of teaching. Here, 54 articles from journals indexed in the Web of Science and Scopus databases were selected, and 111 factors were identified and categorized into five dimensions: teacher attitude, teaching method, didactic content, teaching effect, and teacher achievements. Regarding the advances in machine learning in predicting teacher teaching quality, 30 ML algorithms were identified, the most used being the Back Propagation (BP) neural network and support vector machines (SVM). The challenges and limitations identified in 14 studies related to HEIs are managing the large volume of data and how to use it to improve the quality of education.
Analyzing Fairness of Computer Vision and Natural Language Processing Models
Authors: Rashed Ahmed , Kallich Abdelkrim , Eltayeb Mohamed
Published: February 2025

Machine learning (ML) algorithms play a critical role in decision-making across various domains, such as healthcare, finance, education, and law enforcement. However, concerns about fairness and bias in these systems have raised significant ethical and social challenges. To address these challenges, this research utilizes two prominent fairness libraries, Fairlearn by Microsoft and AIF360 by IBM. These libraries offer comprehensive frameworks for fairness analysis, providing tools to evaluate fairness metrics, visualize results, and implement bias mitigation algorithms. The study focuses on assessing and mitigating biases for unstructured datasets using Computer Vision (CV) and Natural Language Processing (NLP) models. The primary objective is to present a comparative analysis of the performance of mitigation algorithms from the two fairness libraries. This analysis involves applying the algorithms individually, one at a time, in one of the stages of the ML lifecycle, pre-processing, in-processing, or post-processing, as well as sequentially across more than one stage. The results reveal that some sequential applications improve the performance of mitigation algorithms by effectively reducing bias while maintaining the model’s performance. Publicly available datasets from Kaggle were chosen for this research, providing a practical context for evaluating fairness in real-world machine learning workflows.