bluuebunny/crossref_metadata_2025_split huggingface dataset:
Handheld ultrasound device in the assessment of the uterus and adnexa
Authors: Araujo Karla Galvão , Adriana Yoshida , Machado Helymar Costa , Sarian Luis Otávio , Derchain Sophie 
Published: April 2024

Abstract
Purpose
To assess the performance of the handheld ultrasound device (HUD) Butterfly-iQ compared to conventional transvaginal ultrasonography (US) in characterizing measurement and morphological aspects of the normal and abnormal uterus and adnexa.
Methods
This prospective accuracy study included 162 patients evaluated with transabdominal HUD, followed by conventional transvaginal US, between May 2021 and September 2022. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated to evaluate gynecological pelvic findings, with conventional US as the reference standard. The intraclass coefficient measured the reliability of pelvic findings measurements and the Kappa coefficient assessed the agreement of categorical variables between the two ultrasound modalities.
Results
For numerical variables, there was good to excellent agreement for uterine longitudinal diameter, uterine volume, endometrial thickness, fibroid larger diameter, crown–rump length, ovarian volume, and adnexal alteration maximum diameter, with intraclass coefficients ranging between 0.76 and 0.95. The sensitivity and specificity of HUD were 88.1% and 97.6%, respectively, for detecting uterine volume larger than 160 cm³, 84.4% and 99.7% for fibroids larger than 20 mm, and 68.7% and 95.9% for adnexal masses larger than 30 mm. Regarding the evaluation of small structures, HUD showed sensitivity and specificity of 12.5% and 99.3% for identifying intracavitary contents, 22.9% and 99.7% for fibroids smaller than 20 mm, and 33.3% and 98.5% for adnexal alterations smaller than 30 mm. Kappa coefficients for differentiating the position of the uterus, the location of the fibroids, and the type of adnexal mass were 0.68, 0.78, and 0.84, respectively. The data included ten cases of early pregnancy. The sensitivity and specificity were 100% for identifying intrauterine and adnexal pregnancies, and 66.7 and 100%, respectively, for characterizing images compatible with ovular remains.
Conclusion
Transabdominal HUD Butterfly-iQ and transvaginal conventional US demonstrated good to excellent agreement in measuring pelvic findings. HUD performed well in identifying early pregnancy, and gynecological pelvic conditions such as fibroids larger than 20 mm but exhibited poor performance in identifying small alterations of the uterus and adnexa.
Research on methods of ice sample preparation and mechanical properties testing for the polar study
Authors: Li Jingbin , Yang Dong , Zhong Hou , Wang Haizhu , Wang Hao , Huang Zhongwei 
Published: April 2024

Abstract

The exploration of the polar region plays an important role in promoting our understanding of the origin and evolution of life, changes in the ecological environment, and resource acquisition. The exploration of the mechanical properties of ice cores is very important for polar exploration operations, and artificial ice samples are an important means to study the mechanical properties of polar ice. In this paper, an efficient ice particle preparation method is proposed to improve the preparation efficiency of artificial ice samples, that is, ice particles with a diameter of 100 ~ 250 µm are generated by using the principle of droplet atomization phase transition, and an ice sample with an average density of 0.901 kg / m3 is further obtained. Through the unique design of heat insulation device and mica gasket method, the mechanical properties of ice samples can be effectively developed in the conventional mechanical laboratory at room temperature. In the temperature range of -5 ~ -45°C, with the decrease of temperature, the compressive strength gradually increased from 2.18 to 6.49 MPa, while the average flexural strength increases slightly from 0.963 MPa to 1.898 MPa. Loading rate has little effect on uniaxial compressive strength and flexural strength of ice samples. The validity of the ice sample preparation and test method proposed here was verified by comparing with the results of previous studies, which laid a solid foundation for further exploration of the mechanical properties of ice.
Ensemble Learning Approach for Prediction of Early Complications after Radiotherapy for Head and Neck Cancer using CT and MRI Radiomic Features
Authors: Khajetash Benyamin , Mahdavi Seied Rabi , Nikoofar Alireza , Johnson Lee , Tavakoli Meysam 
Published: April 2024

Abstract
There are different side effects in radiotherapy of head and neck cancer (HNC) including xerostomia. The present study utilizes the addition of Magnetic Resonance (MR) radiomic image features to typical Computed Tomography (CT)-based features and radiation dose-based characteristics and incorporates the evaluation and validation of individual and ensemble classifiers for prediction of early-onset xerostomia in radiotherapy of HNC. A total of 80 patients diagnosed with HNC were evaluated prospectively. MR and CT imaging, dosimetric, and demographic features of patients were used as model input data. Bilateral parotid radiomic features were extracted from CT, T 1 weighted, and T 2 weighted MR images. Pearson statistical tests were used for selection of features and Random Tree (RT), Neural Network (NN), Linear Support Vector Machine (LSVM) and Bayesian Network (BN) classifiers were evaluated. The results suggest the extracted features from T 1 weighted images have superior prediction ability compared to T 2 weighted acquisitions. The RT and BN models based on T 1 weighted images show better performance than those obtained with T 2 weighted images. T 1 weighted image-based analysis shows area under the curve (AUC) values for The RT and BN models of 0.90 and 0.84, respectively, while corresponding values obtained from T 2 weighted images are 0.79 and 0.78 for RT and BN models respectively. Combined T 1 weighted image-based models RT-BN, RT-LSVM-BN and RT-NN-LSVM-BN also show good performance having AUC values 0.97, 0.92, and 0.90, respectively. These results show that radiomic features from MR images obtained before radiotherapy can be used in addition to other metrics as personalized and unique biomarkers for prediction of early-onset xerostomia. Ensemble classifiers are more efficient than individual classifiers in prediction of early xerostomia.
Clinical profile and outcome of patients intubated in view of altered sensorium- a prospective observational study from North India
Authors: Sengupta Abhinav , Rajan Archana , Didwania Akansha , Ray Animesh , Soneja Manish , Sarda Radhika , Tirlangi Praveen Kumar , Kumar Arvind , Wig Naveet 
Published: April 2024

Abstract

Background
Patients intubated due to AMS in resource-limited settings experience alarmingly high mortality rates. This unique under-researched cohort requires further study for tailored care and resource allocation. This study aimed to investigate the outcomes and predictors of mortality among intubated patients with altered mental status.
Methods
This prospective observational cohort enrolled patients intubated due to a GCS score of less than 8. The patients were followed till the mortality or discharge, and various demographic and clinic-biochemical parameters were recorded. The primary outcome was mortality, and its predictors were studied.
Results
The mean (SD) age was 43 (17) years, 55% being females. The median (IQR) CCI score was 1 (0,1), with diabetes mellitus being the most common (31.8%). The most common cause of AMS was meningoencephalitis (34%), followed by septic encephalopathy (17%). Median GCS at intubation was 6 (4, 8). The median duration of mechanical ventilation was longer in non-survivors (7, 3–15 days). The median length of hospital stay was 11(5,21.5) days, longer in survivors. The overall mortality was 65%. CRP, LDH, and place of intubation were independent predictors of mortality. Both SOFA and APACHE on the day of intubation underpredicted mortality. The hospital-acquired infection rate was high (47%). The median mRS at discharge was 4 (2, 5).
Conclusion
Patients intubated for altered mental status represent a distinct group, facing prolonged ventilation, heightened infection risk, and substantial mortality, challenging conventional prognostic models; post-discharge, they exhibit compromised function, necessitating intensive home care and stringent infection control measures.
Moving trend analysis methodology for hydro-meteorology time series dynamic assessment
Authors: Şen Zekâi 
Published: April 2024

Abstract
Temporal hydro-meteorological time series have different components, such as the deterministic (periodicity, trend, jump) and stochastic (uncertainty, statistical, probabilistic) parts that are important for practical applications and prediction in water resources management studies. For many years, stochastic components were assumed to be stationary in order to reliably implement stochastic modelling procedures. In the last 30 years, there are many publications in the literature due to global warming and accordingly, climate change, which exhibits non-stationary behaviors in hydro-meteorology time series records. Oftentimes, classical trend analyzes cover the entire recording time with a single holistic straight-line trend and slope. Such an approach does not provide information on trend evolutionary development at shorter times over the entire record length. This paper proposes a methodology for identifying local finite length trends in a systematic way that moves dynamically over a series of short time frames for internal trend evolution developments and interpretations. In general, partial moving trends of 10-year, 20-year, 30-year and 40-year occur above or below the overall trend and thus provide practical insight into the dynamic trend pattern with important computational results and time series internal structural development with key comments. The moving trend method is similar to the classical moving average methodology with one important difference that instead of arithmetic averages and their horizontal lines, a series of local trend are given over the recording period with increasing or decreasing partial trends. The moving trend methodology is applied to annual records of Danube River discharges, New Jersey state wise temperatures and precipitation time series from the City of Istanbul.
The effect of METTL3 on MDM2 impairs cell cycle homeostasis in podocytes during diabetic kidney disease
Authors: Wu Han , Yu Ziyang , Yang Yitian , Han Zhuoting , Pan Qingjun , Yu Hongyuan , Chen Ying , Xu Li 
Published: April 2024

Abstract
N6-Methyladenosine (m6A) methylation is involved in various pathological processes. Our previous study found abnormal expression of the methyltransferases enzyme METTL3 in aging kidney tissues, resulting in renal fibrosis and aging. In this study, we aim to elucidate its regulatory mechanisms in diabetic kidney disease (DKD) by establishing a conditional METTL3 knockout model. We observed elevated m6A levels in the kidney of mice with type I diabetes and in cultured mouse podocytes exposed to advanced glycation end-products (AGEs), which could be attributed to increased METTL3 expression. Podocyte-specific METTL3 knockdown significantly mitigated podocyte injury in streptozotocin (STZ)-induced diabetic mice, leading to reduced urine albuminuria and renal pathology. Mechanistically, METTL3 induced abnormal m6A modification of MDM2, triggering subsequent degradation in an IGF2BP2 dependent manner. Consequently, this abnormal m6A regulation induces increased MDM2 expression, activates the Notch signaling pathway, induced podocyte cell cycle re-entry under diabetic conditions, releases inflammatory factors, and induces dedifferentiation of podocytes. Thus, METTL3-mediated aberrant m6A modification plays a pivotal role in podocytes under diabetic conditions. Targeting m6A via METTL3 is a potentially effective strategy for DKD treatment.
Effect of chlorhexidine mouthwashes on the microbiota associated with peri- implantitis lesions
Authors: Pose-Otero Félix , Arredondo Alexandre , Parga Ana , Muras Andrea , Gallas Mercedes , Otero-Casal Paz , Pose-Rodríguez José Manuel , Otero Ana 
Published: April 2024

Abstract

Objective
This study aimed to evaluate the impact of 0.05% and 0.12% chlorhexidine (CHX) mouthwashes on the peri-implant pocket microbiota of patients with peri-implantitis.
Materials and methods
We analyzed the microbial composition of peri-implant lesions in 22 patients before and after a 15-day regimen of thrice-daily use of two commercial CHX mouthwashes containing 0.05% (n = 11) and 0.12% CHX (n = 11). Microbial samples were collected using paper points and the taxonomic composition was determined through sequencing of 16S rRNA gene amplicons using Illumina MiSeq.
Results
Although individual responses to CHX mouthwash treatment varied significantly, neither concentration produced a statistically significant change in the microbial diversity associated with peri-implantitis, suggesting limited treatment penetration into peri-implant lesions. Similarly, changes in the abundance of specific odontopathogens were not statistically significant.
Conclusions
We found no significant differences in the effect of mouthwashes with different CHX concentrations on the peri-implant microbiota.
Effects of Freeze-thaw and Dry-wet Cycles on the Collapsibility of the Ili Loess With Variable Initial Moisture Contents
Authors: Cheng Lilong , Zhang Zizhao , Liu Chenxin , Zhang Yongliang , Lv Qianli , Zhang Yanang , Chen Kai , Shi Guangming , Huang Junpeng 
Published: April 2024

Abstract

Suffering from seasonal climate changes, the loess in the Ili region of Xinjiang is frequently subject to cycles of freezing-thawing(F-T) and wetting-drying(W-D), and the engineering properties of the loess are highly variable. In the present research, the collapsibility characteristics of the loess slope located in Xinyuan country is investigated, for which the uni-axial compression tests were carried out with the consideration of various F-T and W-D cycles. In parallel, both the SEM and NMR tests were carried out. Test results obtained from the research indicated that both F-T cycles and W-D cycles exacerbate the deterioration of the loess and the most serious situation will be reached after after 6–10 cycles. Under these two physical cycles, the micro-structure of the loess generally develops from relatively aggregated state to the dispersed one. Correspondingly, the porosity of the loess increases initially, followed by an obvious descending with wet-dry cycles. Whereas, the characteristics of the loess subjected to the F-T cycles is opposite.The in-behind reason is that the irreversible alteration of the loess micro-structure attributed to the frost heave force generated by F-T cycles and the water absorption-swelling effect are accounted for. The main contribution of this study is to give more explanations for the causes and action mechanisms of loess wet subsidence in seasonal permafrost zones, and provide a scientific basis for loess wet subsidence disaster prevention and control.
Arc bubble edge detection method based on deep transfer learning in underwater wet welding
Authors: Guo Bo , Li Xu 
Published: April 2024

Abstract

Arc bubble in underwater wet welding reflects the stability of the welding process. An arc bubble edge detection method based on deep transfer learning is proposed to overcome the shortcomings of conventional algorithms in processing underwater wet welding images. The method consists of two training stages: pre-training and fine-tuning. In the pre-training stage, a large source domain dataset is used to train VGG16 as a feature extractor. In the fine-tuning stage, we proposed the Attention-Scale-Semantics (ASS) model, which consists of a Convolutional Block Attention Module (CBAM), a Scale Fusion Module (SCM) and a Semantic Fusion Module (SEM). The ASS model is retrained with the small underwater wet welding target domain dataset to fine-tune the model parameters. The CBAM can adaptively weight the feature maps, focusing on more important feature to better capture edge information. The SCM training method makes extensive use of feature information to simplify the training steps. Additionally, the skip structure of SEM effectively resolves the problem of semantic loss in the high-level network during the training process and improves the accuracy of edge detection. We compare the ASS model to the conventional edge detection model on the BSDS500 dataset and underwater wet welding images, demonstrating that the ASS model is superior to the conventional edge detection model. By comparing with Richer Convolutional Features (RCF), Fully Convolution Network (FCN) and UNet, the excellent performance of the ASS model in arc bubble edge detection method is verified.
Investigation of the therapeutic role of Lichong Shengsui Drink for the treatment of ovarian cancer in sight of network pharmacology integrated molecular dynamics
Authors: DI Yu , CHEN Chunfa , WU Jufang , HUANG Ping , RAO Lijuan , LIU Ruizhi , WU Minna , Di LiSong , XIAO Jing 
Published: April 2024

Abstract
Objective
To explore the mechanism of the Lichong Shengsui Drink (including Panax Ginseng, Epimrdii Herba, Sparganii Rhizoma, Curcumae Rhizoma, Hedysarum Multijugum Maxim, Fritillariae Thunbrgii Bulbus, Cervus nippon and Bigflower Cape Jasmine) in the treatment of ovarian cancer by network pharmacology and molecular docking technology.
Methods
TCMSP, HERB(http://herb.ac.cn/), SwissTargetPrediction, and TCM-Batman were used to retrieve the chemical components and action targets of drugs; the DEGs of ovarian cancer gene chip: GSE105437, GSE66957, GSE146533 were obtained by GEO2R. The common genes of DEGs and active ingredient targets were obtained by the Venn method. The PPI network of the common genes obtained by STRING, and the network of active ingredients and its target were visualized by Cytoscape 3.10.2. The hub genes of the PPI network and hub ingredient of the active ingredient targets network were obtained by Cytohubba. GO and KEGG enrichment analyses were completed for the ingredient targets, shared genes, and hub proteins. Finally, The structures of common targets and core components were downloaded from PubChem and PDB and were then molecular docked by CB-dock2.
Results
A total of 90 effective components of this compound were screened out which have 3514 target genes, 2534 DEGs of the ovarian cancer gene chip of GSE105437, GSE66957, and GSE146533 were picked out: they have 185 common genes in total by Venn. The PPI network of the 185 common genes and the ingredient-targets network were then constructed, as well, and hub genes and hub ingredients were identified by Cytohubba. Top 10 genes of ESR1, EGFR, CXCR4, KIT, AKT1, PGR, CD24, SRC, SNAI2, STAT3 and top 10 ingredients of Adenosine triphosphate, 17-beta-estradiol, 17alpha-estradiol, estrone, 11-eicosenoicacid, arachidonate, crocetin, cholesterol, galactosamine, beta-sitosterol were obtained. The first four ingredients were widely perceived as connected to the hub genes. However, 11-eicosenoicacid, arachidonate, and crocetin were still yet not known. With the help of molecular docking technology; the three compounds had excellent binding properties with the hub genes.KEGG pathways of the hub genes were associated with PIP3 activates AKT signaling, intracellular signaling by second messengers, diseases of signal transduction, and so on; and the GO process was associated with cell differentiation, cellular developmental process, cellular response to chemical stimulus, and so on.
Conclusion
Our study provided valuable information that Lichong Shengsui Drink might regulate the expression of ESR1, EGFR, CXCR4, and so on for the therapy of ovarian cancer in the form of multi-biological process, multi-factors, multi-pathways, and multi-targets.
Talking cancer - cancer talking: a linguistic and thematic analysis of patient narratives
Authors: Kaptein Ad A. , Meer Pim B. van der , Fisher Fleur L. , Laarhoven Hanneke W.M. van , Pennebaker James W. , Vingerhoets Ad J.J.M. 
Published: April 2024

Abstract

Purpose The narratives of patients with cancer in various diagnostic categories and clinical stages are explored, using thematic analysis and LIWC-methodology. Exploring the psychological response - “the lived experience” - to cancer has humanistic, scientific, and clinical importance, informing researchers, clinicians, and patients about focus and methods of improving quality of life and quality of care.
Methods Narratives of 20 patients were listened to in the patients’ homes - “at the kitchen table” - in order to optimally capture the lived experience of cancer. Audiotaped narratives were transcribed and analyzed with the Linguistic Inquiry and Word Count (LIWC) methodology. Thematic Analysis was used to explore themes in the narratives.
Results Scores on relevant LIWC-dimensions of the 20 patients were compared with norm data for respondents without cancer. Compared to LIWC-scores of healthy respondents, the patients with cancer scored higher on ‘anger’ and ‘sadness’ (psychologic processes dimension), lower on ‘insight’, ‘causes’ and ‘tentatives’ (cognitive processes dimension), and lower on ‘religion’. The Thematic Analysis data of the narratives disclosed as major themes resilience, fatigue, social relationships, turning inward psychologically, preferences for shared-decision making, and psychological support. LIWC-scores and Thematic Analysis scores paint a picture of patients doing their utmost to make sense of their illness experience, potentially informing psychological support for people with cancer.
Conclusion LIWC analysis and Thematic Analysis of the patients’ illness narratives demonstrate the clinical relevance of studying the lived experience of cancer. Narratives of patients with cancer are detectable with LIWC-methodology and Thematic Analysis; they offer pathways to clinical interventions. Incorporating illness narratives into clinical cancer care contributes to care that focuses on “outcomes that matter”.