bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diagnosis of Neurological Disorders Rehabilitation Using Effective Feature Elimination and LSTM-RNN Classifier
Authors: Batool Mouazma , Jalal Ahmad , Alazeb Abdulwahab , Mudawi Naif Al , Alshehri Mohammed , Almakdi Sultan , Almujally Nouf Abdullah , Alotaibi Saud S. , Algarni Asaad 
Published: September 2023

Abstract
Neurological disorders affect bodily functions and there is a growing need for advanced solutions to offer therapeutic advice to patients. A framework using artificial intelligence and machine learning techniques has been proposed to address this. The proposed system employs a combination of RGB, inertial, and depth sensors data. The inertial signals have been filtered using a notch filter to obtain the optimal wearable sensor data by examining the upper and lower cutoff frequencies. Multiple features have been calculated, including mel frequency cepstral coefficients (MFCC), statistical features and Gaussian mixture model (GMM) features. On the other hand, silhouettes have been extracted from RGB and depth images, and four crucial parameters have been employed to gauge the level of accuracy with which patients with neurological disorders performed their activities, including the angle formation between the hands and lower/upper half of the body and center of the body, and the angle between the hands of the silhouette. The resulting features have been fused and classified using principle component analysis and a reweighted genetic algorithm. Evaluation using cross-validation on mRI (multi-modal 3d human pose estimation dataset using mmwave, RGB-D, and inertial sensors) and MHEALTH (mobile health) datasets showed a recognition accuracy rate of 97.29\% and a 97.94\%. The study highlights the need for more datasets to address challenges in rehabilitation using human activity recognition with multi-modal sensors.
Bilateral papillary thyroid cancer: Pitfalls of ACR TI-RADS and evaluation of modified parameters
Authors: Li Tingting , Zhang Yongyue , Li Zhiqiang , Mei Fang , Zhai Junsha , Zhang Min , Wang Shumin 
Published: September 2023

Abstract

Purpose To explore modified parameters for The ACR Thyroid Imaging Reporting and Data System (TI-RADS) of contralateral nodules based on preoperative ultrasound features of suspected-lobe papillary thyroid carcinoma (PTC), to assist managing bilateral PTC. Methods 389 consecutive PTC patients (272 in training set and 117 in validation set) who underwent total thyroidectomy in our center were retrospectively analyzed from March 2020 to March 2022. According to postoperative pathological data, the patients were divided into unilateral and bilateral PTC group. The clinicopathological features and sonographic characteristics of suspected nodules were compared between the two groups and further ultrasonic characteristics of underestimated nodules were analyzed. Results Patients with BMI ≥ 25 kg/m2, multifocality in suspected-lobe, isthmus nodule with TI-RADS classification > 3 tended to have bilateral PTC (P < 0.001, P < 0.001, and P = 0.03, respectively). After modifying ACR TI-RADS classification of contralateral nodules using the above three parameters, AUC for diagnosing contralateral lesions increased from 0.79 (95%CI: 0.74–0.84) to 0.83 (0.78–0.87) in training set. Missed-diagnosis rate of contralateral PTCs were both decreased in training set [21.1% (28/133) to 4.5% (6/133)] and validation set [11.4% (8/70) to 2.9% (2/70)]. In addition, the presence of cystic components and halo sign in contralateral nodules tend to be underestimated by ultrasound preoperatively, with underestimation rates of 100% (6/6) and 73.3% (11/15), respectively. Conclusion The modified ACR TI-RADS classification based on suspected-lobe may be an effective method for preoperative malignant risk stratification of contralateral nodules in patients with bilateral PTCs, which can avoid inadequate surgical extent.
Pharmaceutical care for visually impaired patients: A qualitative study of community pharmacists' needs and professional experience
Authors: Merenda Théodora , Denis Jennifer , Patris Stéphanie 
Published: September 2023

Abstract
Background
Visual impairment is a disability that can have a significant impact on the ability to take medication safely. As a result, pharmacists must adjust their support towards targeted and adapted support for this type of patient. There is little scientific literature about awareness and support for visually impaired people regarding the safe use of medications. Furthermore, this aspect is poorly considered in the basic and continuous training of community pharmacists.
Aim
he aims of the present study were (1) to illustrate the usual clinical practice of community pharmacists to support the optimisation of medication use in visually impaired patients, and (2) to identify their needs and expectations to improve pharmaceutical care for visually impaired patients.
Method
Semi-structured interviews with 18 community pharmacists were conducted. Participants were recruited on a voluntary basis and through a snowball method. Data processing was based on the thematic analysis method of Braun & Clarke (2006). The NVivo software allowed us to organise data to the point of theoretical saturation.
Results
The data processing allowed us to highlight a lack of knowledge and skills of pharmacists in dealing with visually impaired patients. This review proposes a theorisation with a model including four themes to promote the dispensing of adapted pharmaceutical care to patients with visual impairment.
Conclusion
The qualitative data collected in this study provide interesting leads for the development of recommendations and training for pharmacists.
Utilizing chest CT to assess the impact of omalizumab treatment on airway remodeling in refractory asthma
Authors: Shi Honglei , Chen Zehu , Lei Qianqian , Sun Fengfei , Ma Donghai , Niu Tianbai , Huang Yiying , Wu Jian , Wang Zhenguo , Wang Kongqiu , Chen Meizhu , Liu Jing 
Published: September 2023

Abstract
Background
To evaluate the benefits of omalizumab treatment in patients through real-world clinical follow-up data and assess the impact of omalizumab treatment on airway remodeling using chest CT.
Methods
This is a single-center prospective cohort study conducted in the Department of Respiratory and Critical Care Medicine of our hospital from May 2021 to December 2022, focusing on refractory asthma patients who received omalizumab treatment during this period. A comparison was made between the pre-treatment and post-treatment laboratory indicators, pulmonary function parameters, airway parameters, and mucous plug scores obtained from chest CT.
Results
This study included a total of 61 patients with refractory asthma treated with omalizumab. The study found that: ①regardless of whether the treatment lasted for a full four months or not, it significantly improved patient asthma control scores and reduced hospitalization costs and length of stay (p < 0.05). ②After four months of treatment, patients showed a decrease in FENO levels and central airway resistance (Rc) (p < 0.05) as measured by airway resistance examination. Pulmonary ventilation function examination revealed significant improvements (p < 0.05) in MEF75, MEF50, MEF75/25, PEF, and FEV1/FVC. ③After four months of omalizumab treatment, the ratio of wall thickness and outer radius (T/D) and wall area percentage (WA%) of the bronchial wall decreased significantly (p < 0.05). ④After medication, the expression of airway mucous plugs decreased. The mucous plug score was negatively correlated with several indicators of large and small airway function.
Conclusions
Omalizumab treatment can remodel the airways in refractory asthma patients, reducing airway wall thickness, decreasing the percentage of airway wall area, and reducing the expression of airway mucous plugs, thereby improving airflow limitation. Utilizing chest CT provides a novel and intuitive assessment of the efficacy of omalizumab treatment, offering a new perspective for the analysis of omalizumab treatment efficacy.
Trial registration:
This study was registered in Chinese Clinical Trial Registry, the number is ChiCTR2100046343.
An effective model for ontology relations on stock prices: Case of Persian stock market
Authors: Samani Mohammad Hossein , Albadvi Amir 
Published: September 2023

Abstract
The unpredictability of the stock market makes it a serious area of study and analysis. With the help of the accumulated information available in the current digital age and the power of high-performance computing machines, there is a great focus on using these capabilities to design algorithms that can learn stock market trends and successfully predict stock prices. The main goal is to create an intelligent system that provides these features for predicting short-term stock price trends to facilitate the investment decision process. In order to increase the accuracy and productivity of these systems and facilitate the routine of using common-sense knowledge in machine learning systems, developing or enriching knowledge bases and ontology for market modeling will be one of the effective measures in this field. In this research, an attempt has been made to strengthen and enrich the basic ontology created by the authors by using other global ontologies related to the subject of the stock market, and parts of the target space that were not addressed have been added to the ontology. By combining reference ontologies, a level of standardization is also created for the ontology and stability in the representation of concepts and relationships is ensured. In the next step, it has been tried to test the impact of the concepts and relations of the ontology in predicting stock price movements. For this purpose, news in the field of economy is considered as input and a model is created that first filters the textual inputs related to the desired stock symbol and then observes their effect on the price changes of the related stock. The study conducted in this report, after improving the performance and comprehensiveness of the ontology, a model was presented to measure and prove the effect of the relationships in this ontology on price changes. And in practice, according to human limitations and the tools used, this effect was observed and confirmed with the proper certainty by checking the economic news.
Aggressive Primary Pericardial Mesothelioma: A Case Report and Review of the Literature
Authors: Yan Yibo , Li Xiangguang , Hu Lizhi , Zhang Fengxiao , Ye Yinsong 
Published: September 2023

Abstract
Pericardial mesothelioma is a rare malignant tumor with atypical and nonspecific clinical manifestations. Therefore, the diagnosis of pericardial tumors is usually made in advanced stages, and there is currently no satisfactory treatment method, resulting in a low average survival period. In this case analysis, we report a case of a giant primary pericardial mesothelioma, describe its diagnosis and treatment, and discuss treatment methods for pericardial mesothelioma through a literature review.
Factors Affecting Nursing Students Knowledge Regarding Preoperative Nursing Care
Authors: Alnjadat Rafi Mahmoud , Etoom Mohammad Ahmad 
Published: September 2023

Abstract
Background: Preoperative competence is a crucial aspect of nursing student’s education to improve the quality of care and patient safety. It assists nursing students in maintaining and enhancing their practice by determining strength and areas that should be developed.
Purpose: This study aims to assess the level of nursing students’ knowledge regarding preoperative nursing care and determine the most influencing demographic variables.
Methods: A descriptive cross-sectional design using an online self-administered questionnaire was utilised among 202 nursing students selected by simple random sampling. The Perceived Preoperative Nursing Care Competence Scale for Nursing Students (PPreCC-NS) was used to assess the perceived preoperative nursing care competence of nursing students. Descriptive statistics were obtained, and multiple regression was used for data analysis.
Results: The overall level of perceived preoperative nursing care competence was adequate 99.09 (SD = 10.81). The highest mean score was recorded for ability to fulfil legal responsibilities and adherence to ethical principles (M = 23.6, SD = 2.53). The lowest mean score was obtained for research and professional development (M = 17.6, SD = 2.60). The regression analysis showed that place of residency explained significantly about 4.53% of the variance in the nursing students’ knowledge regarding preoperative nursing care, and it was the strongest predictor (B = 0.218, p = 0.002).
Conclusion: The perceived level of preoperative nursing care among nursing students was found to be adequate and associated with place of residence. Future research should be conducted to explore factors affecting nursing students’ preoperative competence in different cultures and contexts.
A Time Series Driven Model for Early Sepsis Prediction Based on Transformer Module
Authors: Tang Yan , Zhang Yu , Li Jiaxi 
Published: September 2023

Abstract

Sepsis remains a critical concern in intensive care units due to its high mortality rate. Early identification and intervention are paramount to improving patient outcomes. In this study, we have proposed predictive models for early sepsis prediction based on time-series data, utilizing both CNN-Transformer and LSTM-Transformer architectures. By collecting time-series data from patients at 4, 8, and 12 hours prior to sepsis diagnosis and subjecting it to various network models for analysis and comparison. In contrast to traditional recurrent neural networks, our model exhibited a substantial improvement of approximately 20%. On average, our model demonstrated an accuracy of 0.964 (± 0.018), a precision of 0.956 (± 0.012), a recall of 0.967 (± 0.012), and an F1 score of 0.959 (± 0.014). Furthermore, by adjusting the time window, it was observed that the Transformer-based model demonstrated exceptional predictive capabilities, particularly within the earlier time window (i.e., 12 hours before onset), thus holding significant promise for early clinical diagnosis and intervention. Besides, we employed the SHAP algorithm to visualize the weight distribution of different features, enhancing the interpretability of our model and facilitating early clinical diagnosis and intervention.
A Bayesian Bernoulli-Exponential Joint Model for Binary Longitudinal Outcomes and Informative Time with Applications to Bladder Cancer Recurrence Data
Authors: Oduro Michael Safo 
Published: September 2023

Abstract
Background: A variety of methods exist for the analysis of longitudinal data, many of which are characterized with the assumption of fixed visit time points for study individuals. This, however is not always a tenable assumption. Phenomenon that alter subject visit patterns such as adverse events due to investigative treatment administered, travel or any other emergencies may result in unbalanced data and varying individual visit time points. Visit times can be considered informative, because subsequent or current subject outcomes can change or be adapted due to previous subject outcomes.
Methods: In this paper, a Bayesian Bernoulli-Exponential model for analyzing joint binary outcomes and exponentially distributed informative visit times is developed. Via statistical simulations, the influence of controlled variations in visit patterns, prior and sample size schemes on model performance is assessed. As an application example, the proposed model is applied to a Bladder Cancer Recurrence data.
Results and Conclusions: Results from the simulation analysis indicated that the Bayesian Bernoulli-Exponential joint model converged in stationarity, and performed relatively better for small to medium sample size scenarios with less varying time sequences regardless of the choice of prior. In larger samples, the model performed better for less varying time sequences. This model's application to the bladder cancer data showed a statistically significant effect of prior tumor recurrence on the probability of subsequent recurrences.
Pseudomonas aquigelida sp. nov., an Antarctic bacterium isolated from seawater of Fildes Bay, King George Island
Authors: Higuera-Llantén Sebastián , Pavlov María S. , Sousa Leandro P. , Vásquez-Ponce Felipe , Parás-Silva Juan , Martínez José R.W. , Munita José M. , Wozniak Aniela , García Patricia C. , Ugalde Juan A. , Lira Felipe , Alcalde-Rico Manuel , Olivares-Pacheco Jorge , Martínez José Luis 
Published: September 2023

Abstract
The isolate Pseudomonas sp. IB20T was obtained from Fildes Bay seawater, King George Island, Antarctica. To characterize this novel species, a polyphasic approach was addressed, and phenotypic, phylogenetic, phylogenomic, and chemotaxonomic analyses were performed. IB20T is a rod-shaped and motile bacterium because of multiple polar flagella and shows an optimal growth temperature of 25°C. Phylogenetic analyses based on 16S rRNA gene sequence and multilocus sequence analysis (MLSA) demonstrated that this strain belongs to the Pseudomonas fluorescens group presenting the highest similarity of multilocus sequence with Pseudomonas antarctica LMG22709T. To further characterize this strain, genomic analyses were made. The average nucleotide identity (ANIb) and average amino acid identity (AAI) scores of all species phylogenetically closest to IB20T were less than 95–96%, values currently accepted to describe a novel species. P. antarctica CMS 35T shows the highest ANIb and AAI scores (92,67%, and 95,98%, respectively). A remarkable feature in the IB20T genome is the presence of the type III secretion system (T3SS), one of the most important virulence elements in pathogenic members of the Pseudomonas genus. This T3SS was not found in any of the genomes of the strains phylogenetically closest to IB20T. Finally, chemotaxonomic analyses demonstrated that the primary fatty acids making up their cells include summed feature 3 (C16:1ω7c/C15:0iso 2−OH), C16:0, and C18:1ω7c. After conducting comprehensive phenotypic and genotypic analyses, we can propose the IB20T strain as a novel species within the Pseudomonas genus. Consequently, we designate it as Pseudomonas aquigelida, with the type strain being IB20.
Evaluation of binding affinities of anacardic acid and D-12 molecules in the active site of p300 HAT enzyme from Molecular docking and Molecular dynamics simulation analysis
Authors: Magudeeswaran Sivanandam , Poomani Kumaradhas 
Published: September 2023

Abstract
The p300 is a HAT family enzyme it regulates the transcription process in the eukaryotic cell nucleus. The irregular function of this enzyme is leads to cancer, cardiovascular and neurological disorders; needs a potential drug molecule for inhibition. The anacardic acid and D-12 molecules are potential inhibitor of p300 HAT enzyme with long tail in the structure. Even though, the detailed intermolecular interactions and stability of the molecules with p300 HAT enzyme are not explained in detail. The molecular docking analysis confirms D-12 [-14.1 kcal/mol] molecule gives the high docking score compared than the anacardic acid [-12.5 kcal/mol]. Both the molecules form an intermolecular interaction with catalytic site amino acid residues (Trp1436 and Tyr1467) of p300 HAT enzyme; in which, D-12 forms strong intermolecular interactions and it is stable during the MD simulation. During the MD simulation, the interaction between anacardic acid and catalytic site residues (Trp1436 and Tyr1467) are becoming weak; indicates that the molecule slightly moved away from the active site compared with the D-12 molecule. The intermolecular interaction between D-12 and Cys1438 is maintained during the entire simulation and the distances are 3.2 and 3.5 Å. This confirms that D-12 molecule is more stable than the anacardic acid in the active site of p300 HAT enzyme.
SGLT2 inhibitors decrease overhydration and proteasuria in patients with chronic kidney disease: a longitudinal observational study
Authors: Schork Anja , Eberbach Marie-Luise , Bohnert Bernhard N. , Wörn Matthias , Heister David J. , Eisinger Felix , Vogel Elisabeth , Heyne Nils , Birkenfeld Andreas L. , Artunc Ferruh 
Published: September 2023

Abstract
Background
SGLT2 inhibitors are used to reduce the risk of progression of chronic kidney disease (CKD). In patients with type 2 diabetes, they have been found to reduce extracellular volume. Given the high prevalence of extracellular volume expansion and overhydration in CKD, we investigated whether SGLT2 inhibitors might correct these disturbances in CKD patients.
Methods
CKD patients who started treatment with an SGLT2 inhibitor were investigated in this prospective observational study for 6 months. Body composition and fluid status were measured by bioimpedance spectroscopy. In addition, spot urine samples were analyzed for albuminuria, glucosuria and urinary aprotinin-sensitive serine protease activity.
Results
42 patients (29% with diabetic/hypertensive CKD, 31% with IgA nephropathy; 88% dapagliflozin 10 mg, 10% dapagliflozin 5 mg, 2% empagliflozin 20 mg; median eGFR 46 mL/min/1.73m² and albuminuria 1911 mg/g creatinine) participated in the study. Median glucosuria increased to 14 (10–19) g/g creatinine. At baseline, patients displayed overhydration (OH) with + 0.4 (-0.2–2.2) L/1.73m² which decreased by 0.5 (0.1–1.2) L/1.73m² after 6 months. Decrease of OH correlated with higher OH at BL, decrease of albuminuria, glucosuria and urinary aprotinin-sensitive protease activity. Adipose tissue mass was not significantly reduced after 6 months.
Conclusions
SGLT2 inhibitors reduce overhydration in patients with CKD, which is pronounced in the presence of high albuminuria, glucosuria and urinary aprotinin-sensitive protease activity.
Trial Registration
The study was registered at the German Clinical Trials Register (DRKS00028560).
The Role of Mass Media on Malaria Care-Seeking Behavior: Insights from the Nigeria Malaria Indicator Survey 2021
Authors: Atwijukiire Humphrey , Ikwara Asher Emmanuel , Angut Mary Madalen 
Published: September 2023

Abstract

Background
Malaria remains a global health crisis, and ending this crisis demands support and action of all people around the world. Sub-Saharan Africa bears the heaviest brunt, with children under five being the most affected. Mass media campaigns play a pivotal role in increasing awareness, promoting malaria care-seeking behavior, and advancing prevention efforts.
Methods
Secondary data analysis of the 2021 Nigeria Malaria Indicator Survey (NMIS) scrutinized malaria care-seeking behavior among women aged 15–49 who had children with a fever in the previous two weeks. Employing a two-stage sampling strategy, data were collected from 568 clusters spanning both urban and rural areas. Descriptive statistics, bivariate, and logistic regression tests were utilized to assess the role of mass media on malaria care-seeking behavior.
Results
The majority of participants resided in rural areas (74.5%), were aged 25–29 (29.2%), lacked formal education (47.5%), and adhered to the Islamic faith (63.9%). Many households lacked basic media tools, with 62% lacking radios, 66.7% lacking TVs, and 86.4% not having access to newspapers or magazines. Only 57.9% of participants reported not having seen or heard any malaria-related messages. 38.5% did not seek malaria treatment when their children had a fever, and 68.1% delayed seeking care for two or more days. Respondents who used the internet before the last 12 months were 1.7 times more likely to seek malaria care (AOR = 1.717, 95%CI:1.020–2.889).
Conclusion
This study delves into the intricate interplay between mass media exposure, and malaria care-seeking behaviors in Nigeria. The stark limitations in access to mass media hinder access to malaria information and malaria care-seeking behaviors. These findings indicate a gap in the roles of mass media on malaria care seeking. To better understand the factors limiting the availability of information on malaria through the media, more research is required.