bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk Factors Associated with Readmission and Mortality Among Children Requiring Long-term Mechanical Ventilation: A Systematic Review Protocol
Authors: Scheller Lindsey , Staveski Sandra , Mariano Karley , Weiss Sandra , Alkon Abbey , Casey Leia , Fukuoka Yoshimi 
Published: January 2024

Abstract
Background: With advancements in technology and clinical care, the number of children receiving long-term mechanical ventilation (LTMV) in their homes is rapidly growing worldwide. Home environments provide children on LTMV with a better quality of life, psychosocial development, autonomy, and fewer infections. However, unexpected hospital readmission and death are significant concerns despite home care benefits. Risk factors associated with readmission and mortality have not been fully examined in existing systematic reviews. This systematic review aims to examine modifiable and non-modifiable risk factors associated with readmission and mortality in infants, children, and adolescents on LTMV.
Methods: This systematic review will use the PRISMA P 2015 guidelines.The literature search will include five electronic databases (PubMed, CINAHL, Web of Science, Embase, and Epistemonikos). All quantitative study designs examining risk factors associated with readmission and/or mortality in pediatric patients less than 21 years of age on LTMV will be included. Articles will be limited to peer-reviewed journals and the English language. Covidence software will be used for data management, study screening, and data extraction. The Joanna Briggs Institute critical appraisal tools will be used to assess risk bias in individual studies. The results of a narrative synthesis will be presented in tables and text descriptions.
Discussion: This systematic review, to our knowledge, is the first synthesis of risk factors associated with readmission and mortality among children on LTMV. We use systematic review methodology to decrease risk of bias and increase reproducibility. Findings from this review will provide insight into health outcomes after discharge and identify knowledge gaps in current research. Examining risk factors can shape clinical and policy work to identify and support patients and their families with unique and complex clinical, social, and healthcare needs. Establishing such support can reduce hospitalizations and helps ensure children on LTMV can continue to grow healthy in the home environment with families.
Systematic review registration: International Prospective Register of Systematic Reviews (PROSPERO): CRD42024492773.
A case of diffuse colorectal cancer
Authors: Wang Jing , Chen Pingbo , He Chiyi , Niu Xiaoping , Li Lin 
Published: January 2024

Abstract

Colorectal cancer is a common tumor of digestive system. Most of the lesions are single, but two or more lesions are rare. However, the diffuse canceration of large intestine is rare, and it has hardly been reported at home and abroad at present.
Socioeconomic Determinants of Permanent Contraceptive Use among Multiparous Women in Urban Indonesia: A nationwide cross-sectional survey
Authors: Putri Nuzulul , Laksono Agung Dwi , Astuti Yuly , Matahari Ratu , Ernawaty Ernawaty 
Published: January 2024

Abstract
Background:
Among the various strategies within family planning, permanent contraception is recommended for multiparous mothers. In Indonesia, the prevalence of permanent contraception is high; however, a significant imbalance exists among socioeconomic groups regarding access and utilization. Focusing on multiparous women in urban areas, the family planning target population living in areas with socioeconomic dynamics, the study analyzed how socioeconomic factors influence the utilization of permanent contraceptives.
Method:
The 2019 Government Performance and Accountability Survey (GPAS) was the subject of this cross-sectional investigation. We examined 13,780 multiparous women. We used socioeconomic status as an exposure variable and the usage of permanent contraception as an outcome variable. Age, education, partner, occupation, exposure to family planning information from radio, television, and the internet, as well as the number of living children, constitute the study's eight control variables. We employed binary logistic regression in the final stage.
Results:
The study revealed that wealthier multiparous women in urban areas of Indonesia are more likely to use permanent contraceptives due to better access and financial resources. Additionally, women with higher education levels are more informed about these methods and inclined to use them. Mass media is vital in disseminating information and dispelling myths about family planning.
Conclusions:
These findings suggest the importance of empowering women through education, employment opportunities, and media campaigns to promote equitable access to permanent contraception.
Systematic Literature Review: The Influence and Effectiveness of Deep Learning in Image Processing for Emotion Recognition
Authors: Wicaksana I Putu Ronny Eka , Davinsi Gabriel Rolly , Afriyanto Muhammad Aris , Wibowo Antoni , Suri Puti Andam 
Published: January 2024

Abstract
In the current digital era, image processing and Emotion Recognition are important topics in the field of artificial intelligence. Deep learning, as one of the most widely used AI techniques in pattern recognition, has shown great potential in addressing these challenges. This research employs a Systematic Literature Review method to collect and analyze previous studies related to deep learning algorithms, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), allowing the researchers to conclude efficient deep learning methods for emotion recognition through image processing. This paper has the result that most studies used CNN to identify emotion from facial expressions, while some studies used RNN. Furthermore, some researchers used combined CNN and RNN to identify emotion from images. Based on the analysis of this research, it is recommended that further studies to take a more holistic approach by considering a wider range of indicators that can be used as signs or signals to analyze a person's emotions. This approach allows for a comprehensive understanding of emotions from multiple perspectives.
STING agonist, SMA-2, inhibits clear cell renal cell carcinoma through improving tumor microenvironment
Authors: Wang Wei , Zhang Fengqing , Hu Yan , Liu Guangming 
Published: January 2024

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most prevalent and lethal subtype of kidney cancer, patients with ccRCC usually have very poor prognosis and short survival. Therefore, it is urgent to develop more effective therapeutics or medications to suppress ccRCC progression. Here, we demonstrated that STING agonist, MSA-2 significantly inhibits tumor progress and prolongs the survival of ccRCC mice by promoting cytokines secretion. Moreover, MSA-2 triggered the trafficking and infiltration of CD8+ T cells, supported by the generation of a chemokine milieu that promoted recruitment and modulation of the immunosuppressive TME in ccRCC. These findings suggest that MSA-2 potentially serves an effective and preferable adjuvant immunotherapy of ccRCC.
The efficacy of modified Ziehl-Neelsen (MZN) and antigen detection enzyme linked immunosorbent assay (ELISA) for detection of cryptosporidia in the stool of gastrointestinal cancer Sudanese patients.
Authors: Abdullah Dafalla Sidig Mohamed Ali , Taha Qutoof Hashim , Taher Tayebalasma Mohamed Ahmed , Omer Esra Rodwan , Alrasheed Tagwa Hafiz Abdelkabeer , Abdalla Sababil Salih , Marjan Salah , Idris Alkhair Abd Almahmoud 
Published: January 2024

Abstract
Background:
Cryptosporidiosis diagnosis based on demonstration of the parasite microscopically in the stool through modified Ziehl-Neelsen (MZN) or auramine phenol staining techniques. The primary goal of this study was to compare between the efficacy of cryptospridia antigen detection potential in the fecal specimens using ELISA and Oocyst detection by MZN staining methods for the diagnosis of human cryptosporidiosis among some Sudanese patients with gastrointestinal cancer. One hundred and eighty-one patients suspected of having gasterointestinal cancer based on their clinical presentation were enrolled in this study. Cryptosporidiosis was diagnosed using polymerase chain reaction (PCR). MZN staining was conducted for fresh stool samples to detect Cryptosporidium Oocyst.
Results:
Of 181 cancer suspected patients, 55 (30.5%) were confirmed as having gastrointestinal cancer. Of the 55 cancer patients 41(74.5%) were confirmed as having colorectal cancer, 7 (12.7%) small intestine cancer, 4(7.3%) liver cancer, 3(5.5%) esophageal cancer. Of the confirmed cancer patients MZN identified 24 (43.6%) and ELISA identified 31(56.4%) as having cryptospridia Oocyst and antigens in their fecal samples, respectively. Based on PCR outcome, the infection rates was significantly higher in colorectal cancer patients than in other cancer patients (P = 0.02). Depending on the criteria of ‘true positive’ samples, sensitivity of MZN and ELISA was 81.06% and 94.25% respectively.
Conclusions:
Fecal antigen ELISA detection test has the advantage of accurate diagnosis of Cryptosporidiosis over MZN staining technique especially in immunocompromised patients.
Investigation on the micro-structure and mesoscale transport behavior in the steel cord-rubber composites with lattice Boltzmann methodology
Authors: Li Yong , Miao Yanan , Zhang Tengwen , Guo Fangkai 
Published: January 2024

Abstract
Annular blowout preventer (BOP) is the vital equipment for sate well control. The internal porous microstructures and multiscale flow properties in the steel cord-rubber composites (SRCs) of annular BOP are directly related to the erosion area of drilling mud and rubber environment. However, current studies have rarely reported the fluid transport behavior in SRCs from a mesoscale viewpoint. The computed tomography (CT) scanning technology and lattice Boltzmann method (LBM) were innovatively introduced in this study to reconstruct and compare the real three-dimensional (3D) pore structures and fluid flow in the original and tensile SRCs. The results demonstrated that before and after the stretching, fluid velocities increased as displacement differential pressures increased in the SRCs, but with two different critical values of 3.6131 Pa and 3.1437 Pa, respectively; three transport channels can be observed, where the average and maximal velocities of primary flow channel were both greater than those of secondary flow channels; the average and maximal velocities in the primary flow channel of tensile sample increased by 222.8% and 241.03% than those of original sample. These phenomena should be attributed that when the original sample was stretching, its porosity increased, its micro-pore radius increased, and then its mesoscopic flow channel became wider, resulting in a lower critical value of displacement differential pressure, higher average and maximal velocities. However, the average seepage velocity at the 1/2 section in the original sample was greater than that in the tensile sample owing to the deteriorated connectivity of flow channel. Depending on the Zou-He Boundary and Regularized Boundary, the relative error of simulated average velocities was only 1.389%. The Xu-Yu fractal model always overestimated the permeability values, however, K-C equation underestimated the results.
Association between previous SARs-CoV-2 infection and new prescription of antidepressant drugs: a case-control study in Friuli Venezia Giulia Region, Italy
Authors: Valentina Rosolen , Luigi Castriotta , Marco Driutti , Umberto Albert , Fabio Barbone , Giulio Castelpietra 
Published: January 2024

Abstract
Purpose: A rise in affective and anxiety disorders and in antidepressant (AD) treatment during the COVID-19 pandemic has been extensively described, but few studies were provided at the individual level, further considering COVID-19 severity and vaccination status.
Methods: Case-control study evaluating the association between the new use of ADs and a previous COVID-19 infection, in Friuli Venezia Giulia Region, Italy, from March 1, 2020, to July 19, 2022. Multiple conditional logistic regressions assess the association between a new AD use and a COVID-19 infection previous to the index date, stratified by gender, age and anti-COVID-19 vaccination status. Odds Ratios (OR) and 95% confidence intervals were reported.
Results: COVID-19 was associated with AD treatment after the infection. The disease severity was positively associated with a growing risk of being dispensed an AD, with the highest risk in unvaccinated subjects previously hospitalised in ICU (OR=28.77). The risk of using ADs after COVID-19 infection was higher in unvaccinated subjects aged 65 years and older, both females and males. The association between COVID-19 infection and AD dispensation in vaccinated subjects was not significant, with the exception of females aged 65 years and over.
Conclusions: Anti-COVID-19 vaccination, especially among the elderly, might prevent post-COVID depressive and anxiety symptoms. Clinicians should be aware that COVID-19 patients requiring hospitalisation are more likely to experience these symptoms, given their higher risk of being dispensed ADs. Future studies may benefit by analysing the incidence of both mental disorders and psychotropic treatment in post-COVID patients, considering socioeconomic factors and vaccination status.
Comparing Restoration and Open Space Stakeholder Perspectives in Novel Ecosystems
Authors: Cutts Bethany , Dinan Maude , Randall Joshua , Seekamp Erin , Martin Katherine , Supak Stacy 
Published: January 2024

Abstract
Novel ecosystems are places where a return to a previously observed ecosystem state is unlikely. In arid grasslands, such transformations are caused by legacies of land overgrazing or changes in land connectivity. Transformed ecosystems persist due to uncertain climate futures or other anthropogenic effects. Although novel ecosystems often provide valuable services, public land managers have given relatively little attention to the idea that effective stewardship of novel ecosystems may require novel assemblages of people. To address this gap, we examine whether management partnerships that involve agricultural and wildlife interests in restoration are sufficiently attuned to stakeholders invested in retaining unbuilt environment– or open spaces. We use qualitative approaches to analyze perceptions of cultural ecosystem services (CES) in the southern New Mexico landscape. Next, we analyze responses to spatial interviewing exercises focused on relational values to the landscape to examine perceptions related to landscape-level ecosystem patterns. Results offer insight into why thinking about when ecosystem service bundling may lead to creative tension between Restoration Partners and Open Space Stakeholders. Primarily, Restoration Partners comment on the negative impact recreation can have on the land. Yet Open Space Stakeholders envision recreationalists as a key steward of the ecological trajectory of the landscape. Relational value mapping results reveal that the values expressed among Restoration Partners and Open Space Stakeholders are similar when thinking ecologically but hold incommensurate economic and cultural perceptions.
Investigation of proinflammatory genes expression in STZ-induced diabetic rats treated with extract of Hibiscus rosa-sinensis flower
Authors: Oluwamodupe Cecilia , Adeleye Adesola Oluwaseun , Babalola Olorunfemi Oyewole , Ottu Paul Olamide 
Published: January 2024

Abstract
Background
Diabetes mellitus, a metabolic disorder of carbohydrates and fat, which results from the deficiency of insulin secretion or varying degree of insulin resistance, is a major public health problem and has become a global menace.
Aim
This study is aimed to investigate the expression of proinflammatory genes in STZ-induced diabetic rat model, treated with Hibiscus rosa-sinensis flower extract.
Methods
Diabetes was induced by intraperitoneal injection of streptozotocin (65 mg/kg). Thirty-six diabetic rats were divided into 6 groups which includes the diabetic control, another group treated with 100 mg/kg of sildenafil citrate and the 4 other groups treated with varying concentrations of aqueous extract of Hibiscus rosa-sinensis flower (50 mg/kg, 100 mg/kg, 200 mg/kg and 1000 mg/kg). Six animals were given only distilled water throughout the experiment as the normal control. The treatment was administered for 21 days. The mRNA expression of the pro-inflammatory cytokines (IL-6, IL-1β and TNF-α) in the pancreas, kidney, liver and brain of the experimental animals were investigated using reverse-transcriptase polymerase chain reaction (RT-PCR). The fasting blood sugar and body weight of the experimental animals was also monitored throughout the experiment.
Results
Oral administration of Hibiscus rosa-sinensis flower extract (100, 200 and 1000 mg/kg) to STZ-induced diabetic rats significantly (p < 0.05) down-regulated the pancreatic mRNA expression of IL-6, IL-1β and TNF-α when compared with the diabetic control group. 200 and 1000 mg/kg of the extract down-regulated (p < 0.05) the mRNA expression of TNF-α and IL-6 in the kidney when compared with the diabetic and normal control group. 100, 200 and 1000 mg/kg of the extract significantly up-regulated (p < 0.05) the mRNA expression of IL-6 in the liver when compared with the diabetic and normal control group. 200 and 1000 mg/kg of extract significantly down-regulated the mRNA expression of TNF-α in the brain of diabetic rats. In addition, the oral administration of Hibiscus rosa-sinensis flower extract (50, 100, 200 and 1000 mg/kg) significantly (P < 0.05) reduces the fasting blood sugar and increases the body weight of experimental animals.
Conclusion
Observation drawn from this study suggests that Hibiscus rosa-sinensis flower extract possess antidiabetic potential and can suppress the JAK/STAT pathway thereby regulating the mRNA expression of the proinflammatory cytokines.
Fire Danger Forecasting on an Hourly Basis via Weather Station-Based Machine Learning in the Sunshine Coast, Australia
Authors: Ardid Alberto , Valencia Andres , Power Antonhy , Dempsey David 
Published: January 2024

Abstract

Sudden wildfire outbreaks can have devastating consequences, making accurate short-term forecasting crucial for timely evacuations and effective fire management strategies. Current systems, reliant on traditional methods and historical data, may not adequately capture the rapidly changing conditions leading to wildfires. This study introduces a novel machine learning-based approach for forecasting wildfire danger, tested on the Sunshine Coast of Australia. By analyzing real-time data from local weather stations, we aim to identify distinct weather patterns occurring hours to days before potential wildfires at high temporal resolution. Using 20 years of historical data, we trained machine learning models that achieved high accuracy in classifying pre-fire conditions and improve by 47% the overall performance compared to the classical forest fire danger index approach. The research also envisions extending this approach to other regions, overcoming data limitations for more effective global wildfire. This advancement addresses the immediate need for improved forecasting and sets the stage for more adaptable systems in the future.
ODRNN: Optimized Deep Recurrent Neural Networks for Automatic Detection of Leukaemia
Authors: Shree K. Dhana , Logeswari S. 
Published: January 2024

Abstract
Leukaemia, a kind of cancer that may occur in individuals of all ages, including kids and adults, is a significant contributor to worldwide death rates. This illness is currently diagnosed by manual evaluation of blood samples obtained using microscopic imaging, which is frequently slower, lengthy, imprecise. Additionally, inspection under a microscope, leukemic cells look and develop similarly to normal cells, making identification more difficult. Convolutional Neural Networks (CNN) for Deep Learning has provided cutting-edge techniques for picture classification challenges throughout the previous several decades, there is still potential for development with regard to performance, effectiveness, and learning technique. As a consequence, the study provided a unique deep learning approach known as Optimized Deep Recurrent Neural Network (ODRNN) for identifying Leukaemia sickness by analysing microscopic images of blood samples. Deep recurrent neural networks (DRNN) are used in the recommended strategy for diagnosing Leukaemia, then the Red Deer Optimization algorithm (RDOA) applies to optimize the weight gained by DRNN. The mass of DRNN from RDOA will be tuned on the deer roaring rate behavior. The model that has been proposed is evaluated on two openly accessible Leukaemia blood sample datasets, AML, ALL_IDB1 and ALL_IDB2. It is possible to create an accurate computer-aided diagnosis for Leukaemia malignancy by using the proposed deep learning model, which shows encouraging results. The research work uses statistical metrics related to disease including specificity, recall, accuracy, precision and F1 score to assess the effectiveness of the proposed model for identification and classification. The proposed method achieves highly impressive results, with scores of 98.96%, 99.85%, 99.98%, 99.23%, and 99.98%, respectively.
Modification of Cotton2K model for simulating cotton growth and yield under various deficit irrigation strategies
Authors: Gao Jun , Tang Zi-Ya , Wang Yu , Wang Jun , Zhou Bao-Ping 
Published: January 2024

Abstract

Light interception plays an important role in cotton (Gossypium hirsutum L.) production, there are few researches on the cotton’s light interception response on irrigation strategy on semi-arid region. Cotton2K is a simulation model for cotton growth developed by Marani (2004), successor of CALGOS (CALifornia GOSsym) (Marani et al.,1992) which derived from GOSSYM. The modified Cotton2K model reimplemented photosynthesis sub procedures compared with the original one, calibrated using field experiments data during the two cotton growing seasons of 2019 and 2020.The normalized root mean squared error (NRMSE) in above ground biomass over the irrigation treatments was 17.44%, showing high simulation accuracy.