bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of COVID-19 Therapy Based on Disease Severity at Siloam Kebon Jeruk Hospital
Authors: Tjahyanto Teddy , Herwanto Velma 
Published: January 2025

Introduction : COVID-19 is an infectious disease that can cause acute respiratory syndrome by droplet transmission. Along with the very fast spread of the virus which occurs in almost all countries, it is necessary to have therapies that can reduce the morbidity and mortality of patients infected with COVID-19. Various factors affect the administration of therapy so a management guideline is needed for medical personnel so that the administration of therapy can be consistent and efficient in accordance with scientific evidence. This study aims to determine the characteristics and therapeutic options of COVID-19 patients based on the severity of the disease so it can be an evaluation for policymakers and health workers in providing COVID-19 therapy.
Methods : This type of research is descriptive, and the research design is cross-sectional with a total population sampling. The study was conducted at Siloam Kebon Jeruk Hospital with a total of 135 respondents from secondary medical record data.

Results : The observed data include the characteristics of the respondents and the therapies for COVID-19 patients, which consist of antiviral, anti-inflammatory, and anticoagulant treatments. Based on the collected data, COVID-19 patients were predominantly male (55.6%) with an average age of 55 years. Many patients presented with moderate severity without requiring oxygen (34.1%) and were classified as having referred outcomes (47.4%). Antiviral therapy using favipiravir was predominantly administered to patients with mild to moderate severity, while remdesivir was mostly given to those with moderate to severe severity. Corticosteroids, such as dexamethasone and methylprednisolone, were the preferred choice for anti-inflammatory therapy (72.2%). Heparin was the most commonly used anticoagulant therapy across all severity levels, and antibiotics were administered to the majority of patients infected with COVID-19 (73.3%).
Conclusions : Evaluation of the low rate of use of corticosteroids and anticoagulants in COVID-19 patients is needed.
Difusi Inovasi Red Hat Academy untuk Mata Pelajaran “Administrasi Sistem Jaringan” Pada Siswa Jurusan TJKT
Authors: Nur Zahro Alviani Okta , Wargahadibrata R.A. Hirmana , Ariani Diana 
Published: January 2025

Penelitian ini menggambarkan proses difusi inovasi Red Hat Academy dalam mata pelajaran “Administrasi Sistem Jaringan” di SMK Letris 1 Indonesia, khususnya untuk siswa Teknik Komputer Jaringan dan Telekomunikasi (TKJT). Menggunakan metode kualitatif dengan pengumpulan data dari 1 guru dan 36 siswa melalui kuesioner, wawancara, observasi, dan catatan lapangan, penelitian ini menggunakan Teknik analisis statistik deskriptif dan model Miles dan Huberman. Hasilnya menunjukkan tahapan difusi inovasi sebagai berikut: pada tahap pengetahuan, penyebaran informasi baik tetapi tidak sepenuhnya sesuai dengan karakter siswa; pada tahap persuasi, penjelasan karakteristik inovasi membantu siswa memahami manfaatnya; pada tahap keputusan, adopsi dilakukan melalui uji coba; pada tahap penerapan, inovasi diterapkan dalam pembelajaran meski ada hambatan yang berhasil diatasi; dan pada tahap konfirmasi, inovasi diputuskan untuk terus digunakan. Temuan ini menegaskan kegunaan Red Hat Academy dalam meningkatkan keterampilan teknis siswa dan perlunya penyesuaian kurikulum dengan kebutuhan industri.

This study describes the diffusion process of Red Hat Academy innovation in the subject “Network System Administration” at SMK Letris 1 Indonesia, especially for Computer Network and Telecommunication Engineering (TKJT) students. Using a qualitative method with data collection from 1 teacher and 36 students through questionnaires, interviews, observations, and field notes, this study used descriptive statistical analysis techniques and the Miles and Huberman model. The results show the stages of innovation diffusion as follows: at the knowledge stage, information dissemination is good but not fully in line with students' characters; at the persuasion stage, explanation of the innovation's characteristics helps students understand its benefits; at the decision stage, adoption is done through trials; at the application stage, the innovation is applied in learning although there are obstacles that are successfully overcome; and at the confirmation stage, the innovation is decided to continue to be used. These findings confirm the usefulness of Red Hat Academy in improving students' technical skills and the need for curriculum customization with industry needs.
Evaluation of New Zwitterionic Viscoelastic Surfactant in Carbonate Acidizing by Novel Injection Sequence: An Experimental Study
Authors: Naderi Salem Hamed , Kandowjani Alireza Ebrahimi , Sedaee Behnam , Mansouri Mehrshad , Shariati Mohsen 
Published: January 2025

Summary
In matrix acidizing, chemical divertants increase the chances of proper acid distribution in the production zones. Viscoelastic surfactants (VESs) are common diverting agents due to easy removal. VES-based acid effectiveness is influenced by pH, shear rate, concentration, and type of VES. Additives such as corrosion inhibitors (CIs) and iron control agents (ICAs) affect VES-based acid performance. This study analyzes a new viscoelastic zwitterionic surfactant’s diversion efficiency via rheology measurements and coreflooding experiments.
The study aimed to optimize a diverting fluid by examining its rheological behavior at pH 4 with surfactant concentrations of 4, 6, and 8 vol% while considering the presence of additives and also explored the effects of CIs and ICAs. Single coreflooding tests determined the injection rate with the lowest PVbt (IRLPVbt) for the diverting fluid and regular acid. By parallel coreflooding tests, utilizing periodic injection method and shut-in time assessed diversion efficiency on carbonate cores with permeability contrasts ranging from 3 to 27. Post-injection computed tomography (CT)-scan images were used to monitor the development of wormholes in the cores.
The rheology analysis showed that the desired VES displayed dominant elastic properties, resembling an elastic solid. The 6 vol% VES exhibited the most favorable rheological behavior, making it the optimal choice for effective diversion. The presence of CI and ICA additives together at concentrations of 1 and 0.5 vol%, respectively, not only had no negative effects but also enhanced the rheological behavior. Through the periodic injection method, injecting the VES-based diverting fluid equivalent to 0.5 pore volume (PV) of the high-permeability core (PVHP), followed by a shut-in time, and subsequent regular acid injection in parallel cores, showed the highest diversion efficiency. The study found that within a permeability contrast range of 3–5, the diversion efficiency was infinite, indicating highly effective diversion, while it measured at 95.9% for a permeability contrast of 32. Increasing the injection volume of the VES-based diverting fluid above 0.5 PVHP decreased the diversion efficiency. This study suggests a new carbonate rock acidizing procedure that could enhance well stimulation efficiency.
Careful design of Large Language Model pipelines enables expert-level retrieval of evidence-based information from conservation syntheses
Authors: Iyer Radhika , Christie Alec , Madhavapeddy Anil , Reynolds Sam , Sutherland William , Jaffer Sadiq 
Published: January 2025

Abstract

Wise use of evidence to support efficient conservation action is key to tackling biodiversity loss with limited time and resources. Evidence syntheses provide key recommendations for conservation decision-makers by assessing and summarising evidence, but are not always easy to access, digest, and use. Recent advances in Large Language Models (LLMs) present both opportunities and risks in enabling faster and more intuitive systems to access evidence syntheses and databases. Such systems for natural language search and open-ended evidence-based responses are pipelines comprising many components. Most critical of these components are the LLM used and how evidence is retrieved from the database. We evaluate the performance of ten LLMs across six different database retrieval strategies against human experts in answering synthetic multiple-choice question exams on the effects of conservation interventions using the Conservation Evidence database. We found that LLM performance was comparable with human experts over 45 filtered questions, both in correctly answering them and retrieving the document used to generate them. Across 1867 unfiltered questions, LLM performance demonstrated a level of conservation-specific knowledge, but this varied across topic areas. A hybrid retrieval strategy that combines keywords and vector embeddings performed best by a substantial margin. We also tested against a state-of-the-art previous generation LLM which was outperformed by all ten current models - including smaller, cheaper models. Our findings suggest that, with careful domain-specific design, LLMs could potentially be powerful tools for enabling expert-level use of evidence syntheses and databases. However, general LLMs used ‘out-of-the-box’ are likely to perform poorly and misinform decision-makers. By establishing that LLMs exhibit comparable performance with human synthesis experts on providing restricted responses to queries of evidence syntheses and databases, future work can build on our approach to quantify LLM performance in providing open-ended responses.
Volume buffering in multi-component phase separation
Authors: Michaels Thomas , de Monchaux-Irons Logan , Han Nina , Frühbauer Benjamin , Jiang Jianning , Allain Frédéric , Jagannathan Madhav , Emmanouilidis Leonidas 
Published: January 2025

Abstract

The concentrations of biomolecules in cells are subject to substantial fluctuations, but how cells deal with such variability is still poorly understood. Recently the formation of biomolecular condensates through liquid-liquid phase separation has been proposed as a powerful buffering mechanism to enable local protein concentration to be robust to expression fluctuations. Here, using theory, simulations, in vitro and in vivo experiments we show an orthogonal noise buffering mechanism mediated by phase separation, whereby the total volume of condensates is buffered when the global protein concentration changes. Spatial control mechanisms are needed to robustly localize cellular activities and volume buffering by phase separation offers such a mechanism. Our work thus provides new insights into the potential role of condensates in regulating spatial activities in cells.
Sildenafil Promotes Osteogenic Differentiation of Human Mesenchymal Stem Cells and Inhibits Bone Loss by Affecting the TGF-β Signaling Pathway
Authors: Hu Menglong , Wu Likun , Wei Erfan , Pan Xingtong , Zhu Qiyue , Xiuyun Xv , Lv Letian , Dong Xinyi , Liu Hao , Liu Yunsong 
Published: January 2025

Abstract

Background
Osteoporosis, a common bone disorder, is primarily managed pharmacologically. However, existing medications are associated with non-trivial side-effects. Sildenafil, which already finds many clinical applications, promotes angiogenesis and cellular differentiation. Osteoporotic patients often exhibit a reduced intraosseous vasculature and impaired cellular differentiation; sildenafil may thus usefully treat osteoporosis.
Methods
Here, the effects of sildenafil on the osteogenic differentiation of human mesenchymal stem cells (hMSCs) were explored, as were the molecular mechanisms in play. We treated hMSCs with varying concentrations of sildenafil and measured cell proliferation and osteogenic differentiation in vitro. We used a mouse model of subcutaneous ectopic osteogenesis to assess sildenafil's effect on hMSC osteogenic differentiation in vivo. We also explored the effects of sildenafil on bone loss in tail-suspended (TS) and ovariectomized (OVX) mice. Mechanistically, we employed RNA-sequencing to define potentially relevant molecular pathways.
Results
Low sildenafil concentrations significantly enhanced osteogenic hMSC differentiation; the optimal sildenafil concentration may be 10 mg/L. Sildenafil mitigated osteoporosis in OVX and TS mice. Low sildenafil concentrations probably promoted hMSC osteogenic differentiation by acting on the transforming growth factor-β (TGF-β) signaling pathway.
Conclusions
In conclusion, low sildenafil concentrations enhanced hMSC osteogenic differentiation and inhibited bone loss. Sildenafil may usefully treat osteoporosis. Our findings offer new insights into the physiological effects of the material.
Extracellular Matrix Dysfunction Drives Synaptic Pathology in Schizophrenia
Authors: Unzueta-Larrinaga Paula , Cuesta-Vega Esteban , Barrena-Barbadillo Rocío , Olabarrieta Estibaliz , Recio-Barbero Maria , Horrillo Igor , Mentxaka Oihane , Segarra Rafael , Meana J. Javier , Nacher Juan , Diez-Alarcia Rebeca , Callado Luis F. , Urigüen Leyre 
Published: January 2025

Abstract

Schizophrenia is a complex disorder with strong evidence implicating neurodevelopmental abnormalities in its pathophysiology. Olfactory neuroepithelial cells from patients provide a unique platform for studying neurodevelopmental processes. These cells can be cultured into neurospheres and differentiated into neurons, allowing the study of patient-specific alterations related to the disorder. In this study, we utilized olfactory neuroepithelial cells from patients with schizophrenia and controls to explore putative neurodevelopmental dysregulations.
RNA-sequencing of neurospheres transcriptome revealed significant alterations in extracellular matrix-related gene expression, suggesting extracellular matrix dysregulation as an underlying contributor to schizophrenia etiopathogenesis.Upon differentiation of olfactory neuroepithelial cells into neurons, transcriptomic analysis identified a significant downregulation of genes involved in synaptic organization and extracellular matrix interactions. To validate these findings, we quantified the protein levels of these genes in olfactory neuroepithelium-derived neurons and in postmortem dorsolateral prefrontal cortex tissue from schizophrenia patients and matched controls. Consistent with our transcriptomic data, schizophrenia subjects exhibited decreased levels of L1CAM, SCG2, and NPTXR proteins. Furthermore, we identified a correlation between the protein levels of L1CAM and NPTXR in the brains of individuals with schizophrenia, a relationship that was absent in control subjects.
Our findings provide robust evidence for extracellular matrix and synaptic dysregulation in schizophrenia, linking neurodevelopmental disruptions to molecular alterations in both patient-derived cellular models and postmortem brain. These results underscore the utility of olfactory neuroepithelium cells as a model for studying the neurodevelopmental basis of schizophrenia. They also highlight extracellular matrix-related pathways as potential targets for future search of biomarkers and therapeutic development.
Evaluation of chemical elements as potential biomarkers in the treatment of goat mastitis
Authors: Uzoka Ugonna Henry , Fujikura Juliana Miwa , Polveiro Richard Costa , Caldeira Jéssica Lobo Albuquerque , Netto Maria Júlia Fernandes , Menezes Luísa Maria Souza , Cesário Cristiane do Carmo , Valente Fabricio Luciani , Moreira Maria Aparecida Scatamburlo 
Published: January 2025

Abstract

Mastitis represents a significant inflammatory condition in dairy goat herds, causing substantial economic losses through reduced milk production and increased veterinary interventions. The escalating challenge of multidrug-resistant bacteria has prompted research into alternative therapeutic strategies, including milk microbiota transfer (MMT) and phytochemical treatments. This study evaluated milk chemical elements as biomarkers during two alternative treatments for Staphylococcus warneri-induced mastitis: milk microbiota transplantation and intra-mammary infusion of 7-epiclusianone, a phytochemical derived from Garcinia brasiliensis fruit. The experimental design involved seven female Parda Alpina goats, with six goats infected with S. warneri treated using milk from a healthy donor. Intra-mammary 7-epiclusianone was administered two days post-MMT. The right udder received the treatments, with the left udder serving as a control. Elemental analysis of 120 milk samples was performed using scanning electron microscopy coupled with X-ray dispersive spectroscopy, monitoring trace and macro elements. Significant elemental composition variations were observed, with iron, copper, and zinc showing immediate responsiveness from the first day of MMT. Most elements exhibited minor fluctuations, returning to control levels by the treatment's conclusion. The 7-epiclusianone treatment maintained stable elemental concentrations when compared to the control and a reduction in sodium levels was observed. The study identifies zinc, copper, iron, and sodium as promising biomarkers during goat mastitis treatment. The combined MMT and 7-epiclusianone approach aligned milk elemental level with the control levels post treatment, offering a non-invasive method for monitoring mastitis treatment efficacy. Future research should validate these elemental biomarkers across larger and more diverse goat populations.
Glucose monitoring, support systems and motivating factors among newly diagnosed type2 diabetic clients: an explorative study in the Upper East Region, Ghana
Authors: Asebiga Clement Asoya , Bam Victoria , Lomotey Alberta Yemotsoo 
Published: January 2025

Abstract

Background: The World Health Organization (WHO) estimated that over 463 million people are living with Diabetes mellitus which is likely to be doubled by the year 2045 meaning 55000 new cases daily. Type 2 Diabetes (T2D) accounts for over 90% of these cases. The situation is worse in Africa due to the poor diagnostic systems. In Ghana, the condition affects over 2.4 million people. The need for the current study is underscored by the emerging importance of data on patient’s experiences coupled with the gap in knowledge on the experiences of newly diagnosed T2D clients. The objective of this study is therefore to explore the experiences of newly diagnosed T2D clients on glucose monitoring, support system availability and motivating factors for them to continue to adhere to their glucose monitoring as a life style modification measure.
Methods: A Qualitative explorative design was used targeting clients diagnosed with T2D within the last 6 months before data collection. A purposive sampling technique was used to recruit 15 participants. In-depth face to face interview was conducted individually using a semi structured questionnaire. Data was transcribed and analyzed using thematic approach.
Results: The findings of the study indicates that T2D clients are faced with unique challenges in glucose monitoring as a lifestyle modification and as a result commit avoidable errors due to lack of knowledge such as; waiting to feel unwell before going for reviews and not disclosing their condition and its management including glucose monitoring to others. Cost was their number one challenge when it comes to glucose monitoring. Their main source of support was found to be from close relatives. Checking and getting improved results was motivating to them
Recommendation and Conclusion: Challenges faced by T2D clients’ results in them committing errors that could have been avoided as new clients which points to lack of knowledge. An intensification of public education on the condition and the need for regular glucose monitoring and further studies on how these experiences of cost, access to care and lack of support affects clients are recommended.
Evaluation of efficacy of sexual novelty as a novel therapeutic strategy to treat Hypoactive Sexual Desire Disorder in women in monogamous heterosexual relationships attributing reduced sexual desire to sexual boredom: A prospective randomized study
Authors: Bhat Gajanan , Shastry Anuradha 
Published: January 2025

Abstract

Hypoactive Sexual Desire Dysfunction (HSDD) in women has a complex origin, and addressing modifiable factors can lead to the best outcomes. One contributing factor is sexual boredom, particularly in women in monogamous relationships and we decided to evaluate sexual novelty as a therapeutic strategy in such women using prospective randomized study design These women were recruited following screening using a Decreased Sexual Desire Screener (DSDS). Participants’ baseline sexual boredom was assessed using the Sexual Boredom Scale (SBS). Reasons for sexual boredom were identified, and customized novelty packages were developed accordingly. The participants were divided into two groups: Group A received psychotherapy alone (n = 196), while Group B (n = 202) received psychotherapy along with a customized sexual novelty package. Sexual desire levels were measured and compared at baseline and after a six-month intervention using the Elements of Desire Questionnaire (EDQ). The groups were similar in age, duration of monogamy, SBS scores, and baseline EDQ scores. Post-intervention results indicated that the sexual novelty group experienced a statistically significant improvement in EDQ scores. Moreover, multiple regression models showed that lower age of the participant and a longer period of monogamy adversely affected sexual desire.
Personalized Prediction Model Generated with Machine Learning for Kidney Function One Year After Living Kidney Donation
Authors: Oki Rikako , Hirai Toshihio , Iwadoh Kazuhiro , Kijima Yu , Hashimoto Hiroyuki , Nishimura Yasunori , Banno Taro , Unagami Kohei , Omoto Kazuya , Shimizu Tomokazu , Hoshino Junichi , Takagi Toshio , Ishida Hideki 
Published: January 2025

Abstract

Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. This study aimed to develop a machine learning (ML) model to predict serum creatinine (Cre) levels at one year post-donation using preoperative clinical data, including kidney-, fat-, and muscle-volumetry values from computed tomography. A total of 204 living kidney donors were included. Symbolic regression via genetic programming was employed to create an ML-based Cre prediction model using preoperative clinical variables. Validation was conducted using a 7:3 training-to-test data split. The ML model demonstrated a median absolute error of 0.079 mg/dL for predicting Cre. In the validation cohort, it outperformed conventional methods (which assume post-donation eGFR to be 70% of the preoperative value) with higher R² (0.58 vs. 0.27), lower root mean squared error (5.27 vs. 6.89), and lower mean absolute error (3.92 vs. 5.8). Key predictive variables included preoperative Cre and remnant kidney volume. The model was deployed as a web application for clinical use. The ML model offers accurate predictions of post-donation kidney function and may assist in monitoring donor outcomes, enhancing personalized care after kidney donation.