bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of baicalin on eradicating biofilms of bovine milk derived Acinetobacter lwoffii
Authors: Ma Chengjun , Mei Cui , Liu JingJing , Li Hui , Jiao Min , Hu Huiming , Zhang Yang , Xiong Jing , He Yuzhang , Wei Wei , Yang Hongzao , Chen Hongwei 
Published: May 2024

Abstract
Background
Acinetobacter lwoffii (A.lwoffii) is a serious zoonotic pathogen that has been identified as a cause of infections such as meningitis, bacteremia and pneumonia. In recent years, the infection rate and detection rate of A.lwoffii is increasing, especially in the breeding industry. Due to the presence of biofilms, it is difficult to eradicate and has become a potential super drug-resistant bacteria. Therefore, eradication of preformed biofilm is an alternative therapeutic action to control A.lwoffii infection. The present study aimed to clarify that baicalin could eradicate A.lwoffii biofilm in dairy cows, and to explore the mechanism of baicalin eradicating A.lwoffii.

Results
The results showed that compared to the control group, the 4 MIC of baicalin significantly eradicated the preformed biofilm, and the effect was stable at this concentration, the number of viable bacteria in the biofilm was decreased by 0.67 Log10CFU/mL. The total fluorescence intensity of biofilm bacteria decreased significantly, with a reduction rate of 67.0%. There were 833 differentially expressed genes (367 up-regulated and 466 down-regulated), whose functions mainly focused on oxidative phosphorylation, biofilm regulation system and trehalose synthesis. Molecular docking analysis predicted 11 groups of target proteins that were well combined with baicalin, and the content of trehalose decreased significantly after the biofilm of A.lwoffii was treated with baicalin.

Conclusions
The present study evaluated the antibiofilm potential of baicalin against A.lwoffii. Baicalin revealed strong antibiofilm potential against A.lwoffii. Baicalin induced biofilm eradication may be related to oxidative phosphorylation and TCSs. Moreover, the decrease of trehalose content may be related to biofilm eradication.
Characterization of the genetic variation and evolutionary divergence of the CLEC18 family
Authors: Chang Che-Mai , Chang Wei-Chiao , Hsieh Shie‐Liang 
Published: May 2024

Abstract
Background
The C-type lectin family 18 (CLEC18) with lipid and glycan binding capabilities is important to metabolic regulation and innate immune responses against viral infection. However, human CLEC18 comprises three paralogous genes with highly similar sequences, making it challenging to distinguish genetic variations, expression patterns, and biological functions of individual CLEC18 paralogs. Additionally, the evolutionary relationship between human CLEC18 and its counterparts in other species remains unclear.

Methods
To identify the sequence variation and evolutionary divergence of human CLEC18 paralogs, we conducted a comprehensive analysis using various resources, including human and non-human primate reference genome assemblies, human pangenome assemblies, and long-read-based whole-genome and -transcriptome sequencing datasets.

Results
We uncovered paralogous sequence variants (PSVs) and polymorphic variants (PVs) of human CLEC18 proteins, and identified distinct signatures specific to each CLEC18 paralog. Furthermore, we unveiled a novel segmental duplication for human CLEC18A gene. By comparing CLEC18 across human and non-human primates, our research showed that the CLEC18 paralogy probably occurred in the common ancestor of human and closely related non-human primates, and the lipid-binding CAP/SCP/TAPS domain of CLEC18 is more diverse than its glycan-binding CTLD. Moreover, we found that certain amino acids alterations at variant positions are exclusive to human CLEC18 paralogs.

Conclusions
Our findings offer a comprehensive profiling of the intricate variations and evolutionary characteristics of human CLEC18.
Chondroitin sulfate-modified tragacanth gum–gelatin composite nanocapsules loaded with curcumin nanocrystals for the treatment of arthritis
Authors: Sun Junpeng , Du Jiaqun , Liu Xiaobang , An Jinyu , Hu Yu , Wang Jing , Zhu Fu , Feng Huicong , Cheng Shuai , Tian He , Mei Xifan , Wu Chao 
Published: May 2024

AbstractRheumatoid arthritis (RA) is a chronic autoimmune disease of yet undetermined etiology that is accompanied by significant oxidative stress, inflammatory responses, and damage to joint tissues. In this study, we designed chondroitin sulfate (CS)-modified tragacanth gum–gelatin composite nanocapsules (CS-Cur-TGNCs) loaded with curcumin nanocrystals (Cur-NCs), which rely on the ability of CS to target CD44 to accumulate drugs in inflamed joints. Cur was encapsulated in the form of nanocrystals into tragacanth gum–gelatin composite nanocapsules (TGNCs) by using an inborn microcrystallization method, which produced CS-Cur-TGNCs with a particle size of approximately 80 ± 11.54 nm and a drug loading capacity of 54.18 ± 5.17%. In an in vitro drug release assay, CS-Cur-TGNCs showed MMP-2-responsive properties. During the treatment of RA, CS-Cur-TGNCs significantly inhibited oxidative stress, promoted the polarization of M2-type macrophages to M1-type macrophages, and decreased the expression of inflammatory factors (TNF-α, IL-1β, and IL-6). In addition, it also exerted excellent anti-inflammatory effects, and significantly alleviated the swelling of joints during the treatment of gouty arthritis (GA). Therefore, CS-Cur-TGNCs, as a novel drug delivery system, could lead to new ideas for clinical therapeutic regimens for RA and GA.
Graphical Abstract
The Patient Activation Measure-13 (PAM-13) in an oncology patient population: psychometric properties and dimensionality evaluation
Authors: Roesel Inka , Froehlich Daniela , Joos Stefanie , Valentini Jan , Mauch Holger , Martus Peter 
Published: May 2024

AbstractBackgroundAccurate assessment and enhancement of health-related skills among oncology patients are pivotal for optimizing cancer care. The Patient Activation Measure (PAM-13), a questionnaire designed to reflect an individual’s knowledge, skills, and confidence in self-healthcare management, has been validated across diverse countries and settings. Concerns have been raised regarding the cross-situational applicability, as patients with specific diseases and cultural backgrounds interpret questionnaire items differently. This study aimed to examine the structural validity and psychometric properties of the PAM-13 in an oncological patient cohort.MethodsBaseline data from a longitudinal non-randomized controlled study involving cancer out-patients (n = 1,125) from Comprehensive Cancer Centres in Southern Germany were analysed. The German version of the PAM-13 was employed. With classical test and item response theory methods data quality, reliability, convergent and structural validity, as well as psychometric properties were assessed. Exploratory (EFA) and confirmatory factor analyses (CFA) were employed to investigate the postulated unidimensionality of the underlying construct. With a partial credit model (PCM) we examined item fit, targeting, local independence and differential item functioning.ResultsParticipants were predominantly female (73.0%) with a breast cancer diagnosis (41.3%). While items were generally well-accepted, ceiling effects were observed and a high mean PAM-13 score (69.7, SD = 14.2) was noted, potentially compromising responsiveness to interventions. Reliability was adequate (Cronbach’s α = 0.81), person and item separation reliability were good to excellent (0.81 and 0.99, respectively). Explorations of the unidimensionality of the construct (EFA, CFA, PCM) yielded inconclusive results, hinting towards a two-factor solution. Item difficulty rankings deviated from the original. No differential item functioning was identified, and local independence was confirmed.ConclusionsWhile the PAM-13 serves as a valuable instrument for comprehending and promoting health-related skills in cancer patients, the identification of ceiling effects, disordered item-difficulty rankings, and inconclusive findings regarding unidimensionality contribute to the expanding body of evidence, emphasizing the dependency of PAM-13’s validity and reliability on distinctive characteristics within the population under investigation. Future research should prioritize refining or adding PAM-13 items to better capture the specific health-related challenges within diverse populations, paving the way for more effective patient engagement strategies in oncology.Trial registration numberDRKS00021779
Analysis of copy number variants detected by sequencing in spontaneous abortion
Authors: Liu Anhui , Zhou Liyuan , Huang Yazhou , Peng Dan 
Published: May 2024

Abstract
Background
The incidence of spontaneous abortion (SA), which affects approximately 15–20% of pregnancies, is the most common complication of early pregnancy. Pathogenic copy number variations (CNVs) are recognized as potential genetic causes of SA. However, CNVs of variants of uncertain significance (VOUS) have been identified in products of conceptions (POCs), and their correlation with SA remains uncertain.

Results
Of 189 spontaneous abortion cases, trisomy 16 was the most common numerical chromosome abnormality, followed by monosomy X. CNVs most often occurred on chromosomes 4 and 8. Gene Ontology and signaling pathway analysis revealed significant enrichment of genes related to nervous system development, transmembrane transport, cell adhesion, and structural components of chromatin. Furthermore, genes within the VOUS CNVs were screened by integrating human placental expression profiles, PhyloP scores, and Residual Variance Intolerance Score (RVIS) percentiles to identify potential candidate genes associated with spontaneous abortion. Fourteen potential candidate genes (LZTR1, TSHZ1, AMIGO2, H1-4, H2BC4, H2AC7, H3C8, H4C3, H3C6, PHKG2, PRR14, RNF40, SRCAP, ZNF629) were identified. Variations in LZTR1, TSHZ1, and H4C3 may contribute to embryonic lethality.

Conclusions
CNV sequencing (CNV-seq) analysis is an effective technique for detecting chromosomal abnormalities in POCs and identifying potential candidate genes for SA.
MRI radiomics based on deep learning automated segmentation to predict early recurrence of hepatocellular carcinoma
Authors: Wei Hong , Zheng Tianying , Zhang Xiaolan , Wu Yuanan , Chen Yidi , Zheng Chao , Jiang Difei , Wu Botong , Guo Hua , Jiang Hanyu , Song Bin 
Published: May 2024

Abstract
Objectives
To investigate the utility of deep learning (DL) automated segmentation-based MRI radiomic features and clinical-radiological characteristics in predicting early recurrence after curative resection of single hepatocellular carcinoma (HCC).

Methods
This single-center, retrospective study included consecutive patients with surgically proven HCC who underwent contrast-enhanced MRI before curative hepatectomy from December 2009 to December 2021. Using 3D U-net-based DL algorithms, automated segmentation of the liver and HCC was performed on six MRI sequences. Radiomic features were extracted from the tumor, tumor border extensions (5 mm, 10 mm, and 20 mm), and the liver. A hybrid model incorporating the optimal radiomic signature and preoperative clinical-radiological characteristics was constructed via Cox regression analyses for early recurrence. Model discrimination was characterized with C-index and time-dependent area under the receiver operating curve (tdAUC) and compared with the widely-adopted BCLC and CNLC staging systems.

Results
Four hundred and thirty-four patients (median age, 52.0 years; 376 men) were included. Among all radiomic signatures, HCC with5 mmtumorborderextensionandliver showed the optimal predictive performance (training set C-index, 0.696). By incorporating this radiomic signature, rim arterial phase hyperenhancement (APHE), and incomplete tumor “capsule,” a hybrid model demonstrated a validation set C-index of 0.706 and superior 2-year tdAUC (0.743) than both the BCLC (0.550; p < 0.001) and CNLC (0.635; p = 0.032) systems. This model stratified patients into two prognostically distinct risk strata (both datasets p < 0.001).

Conclusion
A preoperative imaging model incorporating the DL automated segmentation-based radiomic signature with rim APHE and incomplete tumor “capsule” accurately predicted early postsurgical recurrence of a single HCC.

Critical relevance statement
The DL automated segmentation-based MRI radiomic model with rim APHE and incomplete tumor “capsule” hold the potential to facilitate individualized risk estimation of postsurgical early recurrence in a single HCC.

Key Points

A hybrid model integrating MRI radiomic signature was constructed for early recurrence prediction of HCC.

The hybrid model demonstrated superior 2-year AUC than the BCLC and CNLC systems.

The model categorized the low-risk HCC group carried longer RFS.

Graphical Abstract
Splenic artery pseudoaneurysm; a cause or consequence: a case report
Authors: Abbas Aymen , Mahmoud Fatma , Gaba Waqar 
Published: May 2024

Abstract
Background
Splenic artery pseudoaneurysm is a rare complication of recurrent pancreatitis usually presenting as an incidental finding on abdominal computed tomography.

Case presentation
We present the case of a 66-year-old north African male with a known history of previous pancreatitis who presented with upper gastrointestinal bleeding along with recurrent epigastric pain for 3 days. Investigations did not reveal any particular pancreatitis etiology. Computed tomography of the abdomen with contrast showed splenic artery pseudoaneurysm along with findings suggestive of acute pancreatitis. Upper and lower endoscopies failed to identify gastrointestinal the bleed source. The patient underwent intervention radiology embolization of the aneurysm sac with multiple coils via right retrograde common femoral artery–celiac access. The patient was discharged with a plan for capsule endoscopy in outpatient setting.

Conclusion
Splenic artery pseudoaneurysm is a life-threatening complication and carries a high mortality rate if left untreated. Prompt identification through various imaging modalities, followed by urgent intervention, is crucial to avoid adverse outcomes.
Cigarette smoke impairs the hematopoietic supportive property of mesenchymal stem cells via the production of reactive oxygen species and NLRP3 activation
Authors: Park Hyun Sung , Lee Byung-Chul , Chae Dong-Hoon , Yu Aaron , Park Jae Han , Heo Jiyoung , Han Myoung Hee , Cho Keonwoo , Lee Joong Won , Jung Ji-Won , Dunbar Cynthia E. , Oh Mi-Kyung , Yu Kyung-Rok 
Published: May 2024

Abstract
Background
Mesenchymal stem cells (MSCs) play important roles in tissue homeostasis by providing a supportive microenvironmental niche for the hematopoietic system. Cigarette smoking induces systemic abnormalities, including an impeded recovery process after hematopoietic stem cell transplantation. However, the role of cigarette smoking-mediated alterations in MSC niche function have not been investigated.

Methods
In the present study, we investigated whether exposure to cigarette smoking extract (CSE) disrupts the hematopoietic niche function of MSCs, and pathways impacted. To investigate the effects on bone marrow (BM)-derived MSCs and support of hematopoietic stem and progenitor cells (HSPCs), mice were repeatedly infused with the CSE named 3R4F, and hematopoietic stem and progenitor cells (HSPCs) supporting function was determined. The impact of 3R4F on MSCs at cellular level were screened by bulk-RNA sequencing and subsequently validated through qRT-PCR. Specific inhibitors were treated to verify the ROS or NLRP3-specific effects, and the cells were then transplanted into the animal model or subjected to coculture with HSPCs.

Results
Both direct ex vivo and systemic in vivo MSC exposure to 3R4F resulted in impaired engraftment in a humanized mouse model. Furthermore, transcriptomic profile analysis showed significantly upregulated signaling pathways related to reactive oxygen species (ROS), inflammation, and aging in 3R4F-treated MSCs. Notably, ingenuity pathway analysis revealed the activation of NLRP3 inflammasome signaling pathway in 3R4F-treated MSCs, and pretreatment with the NLRP3 inhibitor MCC950 rescued the HSPC-supporting ability of 3R4F-treated MSCs.

Conclusion
In conclusion, these findings indicate that exposure to CSE reduces HSPCs supportive function of MSCs by inducing robust ROS production and subsequent NLRP3 activation.
The safety profile of mesenchymal stem cell therapy administered through intrathecal injections for treating neurological disorders: a systematic review and meta-analysis of randomised controlled trials
Authors: Mesa Bedoya Luz Estella , Camacho Barbosa Jhyld Carolaind , López Quiceno Lucas , Barrios Arroyave Freddy , Halpert Karolynn , España Peña Julián Andrés , Salazar Uribe Juan Carlos 
Published: May 2024

Abstract
Background
Based on previous in vivo studies and human trials, intrathecal cell delivery is a safe and relevant therapeutic tool for improving patient's quality of life with neurological conditions. We aimed to characterise the safety profile of intrathecally delivered Mesenchymal stem cells (MSCs).

Methods
Ovid MEDLINE, Embase, Scopus, Cochrane Library, KCI-Korean Journal Database, and Web of Science. Databases were searched from their inception until April 13, 2023. Randomised Controlled Trials (RCTs) that compared intrathecal delivery of MSCs to controls in adult populations were included. Adverse events (AEs) were pooled and meta-analysed using DerSimonian-Laird random effects models with a correction factor 0.5 added to studies with zero count cells. Pooled AEs were described using Risk ratio (RR) and 95% confidence intervals (95% CI). Then, a random-effects meta-regress model on study-level summary data was performed to explore the relationship between the occurrence of AEs and covariates thought to modify the overall effect estimate. Finally, publication bias was assessed.

Results
303 records were reviewed, and nine RCTs met the inclusion criteria and were included in the quantitative synthesis (n = 540 patients). MSCs delivered intrathecally, as compared to controls, were associated with an increased probability of AEs of musculoskeletal and connective tissue disorders (categorised by Common Terminology Criteria for Adverse Events—CTCAE version 5.0) (RR: 1.61, 95% CI 1.19–2.19, I2 = 0%). The random-effects meta-regress model suggested that fresh MSCs increased the probability of occurrence of AEs compared to cryopreserved MSCs (RR: 1.554; p-value = 0.048; 95% CI 1.004–2.404), and the multiple-dose, decreased the probability of AEs by 36% compared to single doses (RR: 0.644; p-value = 0.048; 95% CI 0.416–0.996); however, univariate random effects meta-regression models revealed a not significant association between the occurrence of AEs from MSCs intrathecal delivery and each covariate.

Conclusions
Intrathecal delivery of MSCs was associated with a slight increase in AEs associated with musculoskeletal and connective tissue disorders, albeit without serious AEs. We conclude that intrathecal MSCs delivery is safe for patients with neurological conditions. However, further high-quality, large-scale RCTs are needed to confirm these findings.
Quantum support vector machine for forecasting house energy consumption: a comparative study with deep learning models
Authors: K Karan Kumar , Nutakki Mounica , Koduru Suprabhath , Mandava Srihari 
Published: May 2024

AbstractThe Smart Grid operates autonomously, facilitating the smooth integration of diverse power generation sources into the grid, thereby ensuring a continuous, reliable, and high-quality supply of electricity to end users. One key focus within the realm of smart grid applications is the Home Energy Management System (HEMS), which holds significant importance given the fluctuating availability of generation and the dynamic nature of loading conditions. This paper presents an overview of HEMS and the methodologies utilized for load forecasting. It introduces a novel approach employing Quantum Support Vector Machine (QSVM) for predicting periodic power consumption, leveraging the AMPD2 dataset. In the establishment of a microgrid, various factors such as energy consumption patterns of household appliances, solar irradiance, and overall load are taken into account in dataset creation. In the realm of load forecasting in Home Energy Management Systems (HEMS), the Quantum Support Vector Machine (QSVM) stands out from other methods due to its unique approach and capabilities. Unlike traditional forecasting methods, QSVM leverages quantum computing principles to handle complex and nonlinear electricity consumption patterns. QSVM demonstrates superior accuracy by effectively capturing intricate relationships within the data, leading to more precise predictions. Its ability to adapt to diverse datasets and produce significantly low error values, such as RMSE and MAE, showcases its efficiency in forecasting electricity load consumption in smart grids. Moreover, the QSVM model’s exceptional flexibility and performance, as evidenced by achieving an accuracy of 97.3% on challenging datasets like AMpds2, highlight its distinctive edge over conventional forecasting techniques, making it a promising solution for enhancing forecasting accuracy in HEMS.The article provides a brief summary of HEMS and load forecasting techniques, demonstrating and comparing them with deep learning models to showcase the efficacy of the proposed algorithms.
Simultaneous detection of influenza A, B and respiratory syncytial virus in wastewater samples by one-step multiplex RT-ddPCR assay
Authors: Zafeiriadou Anastasia , Kaltsis Lazaros , Thomaidis Nikolaos S. , Markou Athina 
Published: May 2024

Abstract
Background
After the occurrence of the COVID-19 pandemic, detection of other disseminated respiratory viruses using highly sensitive molecular methods was declared essential for monitoring the spread of health-threatening viruses in communities. The development of multiplex molecular assays are essential for the simultaneous detection of such viruses even at low concentrations. In the present study, a highly sensitive and specific multiplex one-step droplet digital PCR (RT-ddPCR) assay was developed for the simultaneous detection and absolute quantification of influenza A (IAV), influenza B (IBV), respiratory syncytial virus (RSV), and beta-2-microglobulin transcript as an endogenous internal control (IC B2M).

Results
The assay was first evaluated for analytical sensitivity and specificity, linearity, reproducibility, and recovery rates with excellent performance characteristics and then applied to 37 wastewater samples previously evaluated with commercially available and in-house quantitative real-time reverse transcription PCR (RT-qPCR) assays. IAV was detected in 16/37 (43%), IBV in 19/37 (51%), and RSV in 10/37 (27%) of the wastewater samples. Direct comparison of the developed assay with real-time RT-qPCR assays showed statistically significant high agreement in the detection of IAV (kappa Cohen’s correlation coefficient: 0.834, p = 0.001) and RSV (kappa: 0.773, p = 0.001) viruses between the two assays, while the results for the detection of IBV (kappa: 0.355, p = 0.27) showed good agreement without statistical significance.

Conclusions
Overall, the developed one-step multiplex ddPCR assay is cost-effective, highly sensitive and specific, and can simultaneously detect three common respiratory viruses in the complex matrix of wastewater samples even at low concentrations. Due to its high sensitivity and resistance to PCR inhibitors, the developed assay could be further used as an early warning system for wastewater monitoring.