bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variants in NR6A1 cause a novel oculo-vertebral-renal (OVR) syndrome
Authors: Brooks Brian , NEELATHI Uma , Ullah Ehsan , George Aman George , Maftei Mara , Boobalan Elangovan , Sanchez-Mendoza Daniel , Adams Chloe , McGaughey David , Sergeev Yuri , Rawi Ranya AI , Naik Amelia , Bender Chelsea , Maumenee Irene , Michaelides Michel , Tan Tun , Lin Siying , Villasmil Rafael , Blain Delphine , Hufnagel Robert , Arno Gavin , Young Rodrigo , Guan Bin 
Published: November 2024

Abstract

Colobomatous microphthalmia is a potentially blinding congenital ocular malformation that can present either in isolation or together with other syndromic features. Despite a strong genetic component to disease, many cases lack a molecular diagnosis. We describe a novel autosomal dominant oculo-vertebral-renal (OVR) syndrome in six independent families characterized by colobomatous microphthalmia, missing vertebrae and congenital kidney abnormalities. Genome sequencing identified six rare variants in the orphan nuclear receptor gene NR6A1 in these families. We performed in silico, cellular and zebrafish experiments to demonstrate the NR6A1 variants were pathogenic or likely pathogenic for OVR syndrome. Knockdown of either or both zebrafish paralogs of NR6A1 results in abnormal eye and somite development, which was rescued by wild-type but not variant NR6A1 mRNA. Illustrating the power of genomic ascertainment in medicine, our study establishes NR6A1 as a critical factor in eye and vertebral development and a pleiotropic gene responsible for OVR syndrome.
Disagreements in Medical Ethics Question Answering Between Large Language Models and Physicians
Authors: Soffer Shelly , Nesselroth Dafna , Pragier Keren , Anteby Roi , Apakama Donald , Holmes Emma , Sawant Ashwin Shreekant , Abbott Ethan , Lepow Lauren Alyse , Vasudev Ishita , Lampert Joshua , Gendler Moran , Horesh Nir , Efros Orly , Glicksberg Benjamin S , Freeman Robert , Reich David L , Charney Alexander W , Nadkarni Girish N , Klang Eyal 
Published: November 2024

Abstract

Importance.
Medical ethics is inherently complex, shaped by a broad spectrum of opinions, experiences, and cultural perspectives. The integration of large language models (LLMs) in healthcare is new and requires an understanding of their consistent adherence to ethical standards.
Objective.
To compare the agreement rates in answering questions based on ethically ambiguous situations between three frontier LLMs (GPT-4, Gemini-pro-1.5, and Llama-3-70b) and a multi-disciplinary physician group.
Methods.
In this cross-sectional study, three LLMs generated 1,248 medical ethics questions. These questions were derived based on the principles outlined in the American College of Physicians Ethics Manual. The topics spanned traditional, inclusive, interdisciplinary, and contemporary themes. Each model was then tasked in answering all generated questions. Twelve practicing physicians evaluated and responded to a randomly selected 10% subset of these questions. We compared agreement rates in question answering among the physicians, between the physicians and LLMs, and among LLMs.
Results.
The models generated a total of 3,744 answers. Despite physicians perceiving the questions' complexity as moderate, with scores between 2 and 3 on a 5-point scale, their agreement rate was only 55.9%. The agreement between physicians and LLMs was also low at 57.9%. In contrast, the agreement rate among LLMs was notably higher at 76.8% (p < 0.001), emphasizing the consistency in LLM responses compared to both physician-physician and physician-LLM agreement.
Conclusions.
LLMs demonstrate higher agreement rates in ethically complex scenarios compared to physicians, suggesting their potential utility as consultants in ambiguous ethical situations. Future research should explore how LLMs can enhance consistency while adapting to the complexities of real-world ethical dilemmas.
Patient’s knowledge and perception of anesthesia and the anesthesiologist at a tertiary hospital in Mogadishu, Somalia
Authors: Hussein Abdalla Mohamed Hussein , Bacak Mine Bacak , Eraslan Aşır Eraslan , Cimen Sertac Cimen , Ali Irshad Ibrahim Ali , Mohamud Rahma Yusuf Haji Mohamud Haji 
Published: November 2024

Abstract

Background: The field of anesthesia, evolving since the nineteenth century, extends beyond surgery to include critical roles in pain management, critical care, and emergency response, reflecting its importance in diverse healthcare scenarios. It addresses a significant gap in understanding in a region where trained nurses rather than specialist doctors often administer anesthesia. The aim is to investigate patients' knowledge and perception of anesthesia and the anesthetist at a tertiary hospital.
Methods: A cross-sectional study was conducted at Erdogan Hospital, Mogadishu, from September to December 2023. Participants were elective patients aged 15 or older, interviewed using pre-tested questionnaires covering demographics, knowledge of anesthesia, and perceptions of anesthesiologists.
Results: Out of 495 participants, 65.5% were aware of anesthesia, predominantly informed by friends and relatives. While most understood the role of anesthesiologists in administering anesthesia during surgery, there was limited awareness of their broader responsibilities. Critical factors associated with more excellent anesthesiology knowledge included educational level, which increased anesthesiology knowledge by a factor of 0.232 units (β=0.232, P-value=0.002). Employed people had 0.369 times more understanding of anesthesiology than unemployed ones (β=0.369, P-value=0.034). Female participants had higher knowledge scores in anesthesiology than male participants (β=0.383, P-value=0.037).
Conclusion: The study highlights a crucial knowledge gap among patients in Somalia regarding anesthesia and the role of anesthesiologists, underscoring the need for enhanced public education and specialized training. The results are, however, limited by the study's singular hospital setting and sample size.
Future Atlantic Meridional Overturning Circulation weakening driven by Labrador Sea warming and salt transport feedback
Authors: Park Hyo-Seok , Lim Won-Il , Stewart Andrew 
Published: November 2024

Abstract

Climate models predict a wide range of AMOC weakening, complicating future projections. Using 30 models from the Climate Model Intercomparison Project Phase 6 (CMIP6), this study finds that AMOC weakening is strongly correlated with increased downward heat flux in the Labrador Sea. A rapid rise in heat uptake and upper-ocean temperatures initiates AMOC weakening, but this is partially offset by reduced ocean heat transport. By the mid-21st century, changes in seawater temperature have a mild effect on density, while the reduced northward salt flux associated with AMOC weakening further decreases Labrador Sea density. Further analysis indicates that the degree of future AMOC weakening aligns with a conceptual model representing AMOC as a thermal wind balance governed by the meridional density gradient. Idealized ocean model simulations confirm that increased downward heat flux in the Labrador Sea can weaken AMOC and trigger a salt transport feedback. These findings suggest that future warming of the Labrador Sea, along with the associated salt transport feedback, will be critical in determining the extent of AMOC weakening.
A Study on the Effect of Snake Plants on Indoor Air Quality and Human Well-being in a Private Hostel in Aizawl, Mizoram
Authors: Mualchin Lalropeki , Lalrinpuii Hilda 
Published: November 2024

Abstract

Snake plants, one of the air purifiers can significantly improve indoor air quality in the kitchen, non-ventilation, and ventilation area and improve indoor air pollutants such as HCHO and TVOC with a consistent temperature, while indoor air pollutants such as PM 2.5 and PM 10 have less effectiveness in reduction by snake plants. Ventilation also contributes to the reduction of indoor air pollutants. From the study, students’ mood and productivity are at a high level, whereas high in stress level during placing snake plants. There is a strong positive relationship between humidity and mold growth, which is one of the major issues in a hostel, and a study found that snake plants may influence in reducing mold growth by regulating humidity levels. This study can play an important role in enhancing indoor air pollutants in the hostel, making it environmentally friendly, cost-effective, and easily accessible for students living in the hostel.
Predicting Patient Survival After Heart Failure Using Ensemble Learning Models
Authors: Santos Dheiver Francisco 
Published: November 2024

Abstract

Heart failure (HF) is the leading cause of global death from chronic diseases. Data mining using machine learning (ML) converts massive volumes of raw data created by healthcare institutions into meaningful information that can aid in making
predictions and crucial decisions. After an HF, collecting and analyzing follow-up data from patients is critical to monitor their health recovery. The aim of this study is to use ML and predict the survival possibility of patients after HF based on the follow-up data. Three supervised classifiers i.e., Random Forest (RF), XGBoost (XGB), and Decision Tree (DT) have been used in our study. Moreover, we proposed to design a supervised stacked ensemble learning model that can achieve a prediction accuracy, precision, recall, and F1 score of 99.98
The Relationship Between Hiv Positive Clients’ Satisfaction With Health Services and Their Health Outcomes - A Cross-sectional Survey in the South Eastern Hospitals in Nigeria
Authors: Akunne Maureen Ogochukwu , Ukwe Chinwe Victoria , Isah AbdulMuminu , Ekwunife Obinna Ikechukwu 
Published: November 2024

Abstract

Background: There’s limited information on the interrelationships of HIV-positive individuals’ satisfaction with health services and other health outcomes in the management of HIV infection in the Nigerian literature.
OBJECTIVES: To predict the patients’ adherence to ART, CD4 count, viral load, and quality of life from their satisfaction with health services.
METHODS: A large cross-sectional survey was conducted among the HIV-infected individuals in five tertiary institutions in South Eastern Nigeria using a validated Patient Satisfaction with Health Service Questionnaire (PSHS-Q), a European Quality of Life questionnaire, EQ-5D-5L, and the Center for Adherence Support Evaluation (CASE) Adherence index. Data analysis was done with appropriate descriptive and inferential statistics using IBM SPSS Version 23. P< 0.05 was considered statistically significant.
RESULTS: Levels of general satisfaction with health services were: Not satisfied (385, 24.2%), Slightly satisfied (341, 21.4 %), Satisfied (183, 11.5 %), and Very satisfied (684, 42.9 %). Patient satisfaction with health services is predictive of quality of life (β = 0.013, 95 % CI [0.008 - 0.017], p = 0.0001), but not of adherence to ART (β = 1.308, 95 % CI [0.770 – 2.222], p = 0.321), viral load suppression (β = 0.783, 95 % CI [0.435 – 1.411], p = 0.416) and CD4 Count (β = 0.938, 95% CI [0.568 – 1.551], p = 0.804).
CONCLUSION
The HIV/AIDS patients’ quality of life was positively predicted by their satisfaction with health services. However, their general satisfaction with health services did not affect their adherence to therapy, viral load, and CD4 count.
Improving Explainability in Machine Learning: A Cluster-Driven Approach to Feature Importance
Authors: Parashar Gaurav , Chaudhary Alka , Pandey Dilkeshwar 
Published: November 2024

Abstract

Machine learning (ML) models are increasingly being deployed in critical domains such as healthcare, finance, marketing, autonomous vehicles, and energy. As these models become more accurate and capable, concerns about the trustworthiness of their decisions grow. Trust in ML models is essential, particularly in high-stakes applications, and depends on both the transparency and fairness of the models. Transparency is achieved when an ML model can clearly explain its decision-making process, especially by identifying the key features that influence its predictions. In this paper, we introduce a novel technique, cluster-based feature importance, which identifies feature importance by analyzing localized regions within the dataset. This approach provides deeper insights into the features the model relies on for its predictions. We also compare our method to established explainability techniques, such as LIME and SHAP, to assess its effectiveness.
Performance-Driven Encryption for Cloud Data Transmission and Storage Security
Authors: sagrika  , Kumar Raj , Brar Gursewak Singh 
Published: November 2024

Abstract

As cloud technology continues to grow at a rapid pace, it offers substantial advantages to the IT sector, including scalability, cost savings, and ease of access. However, protecting data stored in the cloud remains a critical challenge, with increasing vulnerabilities to unauthorized access and cyber threats. This paper presents a comprehensive method for enhancing cloud security by integrating encryption and compression techniques. The proposed approach begins by encrypting data through the Diffie-Hellman key exchange, followed by compression and encoding with Huffman coding to reduce data size while strengthening security. A second layer of encryption is then applied using the AES algorithm, resulting in a dual-encryption framework that enhances both protection and storage efficiency. The primary goal of this research is to deliver a secure, efficient solution for safeguarding cloud data in a resource-conscious manner.
Epileptic encephalopathy, autism and cognitive deficit caused by the SYNGAP1 gene mutation
Authors: Gamirova R. G. , Zabirova K. R. , Gorobets E. A. , Safina A. R. , Samoilova L. R. , Volgina S. Ya. 
Published: November 2024

The paper analyzes data from scientific publications and presents a clinical case study of a rare genetic epileptic encephalopathy caused by a mutation in the SYNGAP1 gene. The case study focuses on a 4-year-old girl who has been diagnosed with epileptic encephalopathy due to the mutation. The paper describes the anamnesis of the child’s illness, including family history, neurological, neuropsychological, and speech assessments, as well as the results of genetic testing, electroencephalography, and magnetic resonance imaging (MRI). The findings indicate that the main symptoms of the condition are typically epilepsy, autism spectrum disorder, difficulty with phrasal speech, and mental retardation. Common types of seizures include atypical absence seizures, myoclonic seizures, atonic seizures, and eyelid myoclonia with absences. On the electroencephalogram, there is a slowdown in occipital activity and diffuse, prolonged «peak-polypic-slow-wave» complexes. Pathognomonic neuroimaging changes in the brain are typically absent. Valproic acid, levetiracetam, and ethosuximide have been shown to be the most effective treatments for controlling epileptic seizures. Due to the rarity of this syndrome, the authors have provided a detailed clinical case report from their practice.Conclusion. SYNGAP1-related epileptic encephalopathy has a specific clinical presentation, including characteristic EEG findings and a particular pattern of seizures. The diagnostic approach for children with this condition, autism spectrum disorder, and delayed language development should include video electroencephalography with sleep deprivation, as well as genetic testing if necessary, using next-generation sequencing, to ensure early detection and appropriate treatment planning.
Clinical and etiological characteristics and cytokine profile in school-age children with community-acquired pneumonia
Authors: Mizernitsky Yu. L. , Vakhitov Kh. M. , Sitdikova G. F. , Safiullin T. R. , Nurmieva A. R. , Loskutova E. V. 
Published: November 2024

The urgent task of modern pediatrics is the study of the etiology and pathophysiology of community-acquired pneumonia in school-aged children due to difficulties in diagnosis and treatment, as well as the high risk of life-threatening complications and death.Purpose. To investigate the activity of pro-inflammatory and anti-inflammatory responses as measured by cytokine levels in the peripheral blood of children with community-acquired pneumococcal and non-pneumococcal pneumonia.Material and methods. The etiology of community-acquired pneumonia was confirmed by comparing the results of rapid testing of pneumococcus in urine and data from traditional bacteriological methods. The study included 118 children (57 boys and 61 girls) aged 7 to 16 years with various morphological variants of community-acquired pneumonia, which were divided into 2 groups. The first group included 28 children with pneumococcal etiology of community-acquired pneumonia, and the second group included 90 patients with non-pneumococcal community-acquired pneumonia. Levels of interleukins IL-1, IL-4, IL-8 and TNF-α were determined in all children by enzyme immunoassays.Results. In the etiology of community-acquired pneumonia in school-age children, atypical pathogens are responsible for more than 50% of cases. The clinical effectiveness of rapid testing of pneumococcal antigens in urine has been shown, and their use in routine pediatric practice has made it possible to timely identify a group of severe community-acquired pneumonia and reasonably prescribe antibacterial medications. It has been demonstrated that pneumococcal-induced pneumonia is characterized by higher levels of proinflammatory cytokines. These levels, along with the clinical course of the disease, confirm the high level of systemic inflammation. Relatively lower levels of proinflammatory cytokines corresponded to a more mild clinical picture of community-acquired pneumonia of non-pneumococcal etiology, which on the one hand may reflect a relatively «balanced» inflammatory response, and on the other hand determine the protracted and polyclinic course of the infectious process.Conclusion. The etiology of community-acquired pneumonia in school-age children is dominated by atypical pathogens. Community-acquired pneumonia of pneumococcal etiology has more severe clinical courses, and their early identification will allow for the appropriate prescription of initial antibacterial treatment.
Phenotypic and genotypic features of children with familial hypercholesterolemia
Authors: Sadykova D. I. , Slastnikova E. S. , Galimova L. F. , Shagimardanova E. I. , Nigmatullina R. R. , Salakhova K. R. , Khaliullina Ch. D. 
Published: November 2024

Dyslipidemia is a metabolic disorder in which the ratio of lipid particles in the blood changes. It is often associated with other conditions and diseases during childhood. Lipid metabolism disorders in children can be divided into two categories: primary, which are inherited from parents or occur de novo, and secondary, which occur during life. Familial hypercholesterolemia is the most common type of primary disorder, characterized by an increase in blood lipoprotein levels. However, the lipid composition in children with established familial hypercholesterolemia can vary. One factor that may contribute to higher lipid levels in these children is the presence of mutations in the apolipoprotein E gene.Purpose of the study was to investigate the phenotypic and genotypic features of children with familial hypercholesterolemia in order to better understand this condition.Materials and methods. Children with a clinical diagnosis of familial hypercholesterolemia underwent DNA sequencing to identify mutations in genes related to LDLR, APOB, LDLRAP1, and APOE genes.Results. Children with familial hypercholesterolemia most often carry the polymorphism c.388T>C in the ApoE gene (g.45411941T>C, p.Cys130Arg, rs429358). Also, 24.1% of children were found to be isolated carriers of various ApoE haplotypes, which are risk factors for dyslipidemia. In children with a pathogenic mutation characteristic of familial hypercholesterolemia and carriage of polymorphisms in the ApoE gene, the LDL level was statistically higher compared to non-carriers.Conclusion. Carriage of various polymorphisms in the ApoE gene in children with familial hypercholesterolemia may lead to an increase in the already elevated levels of LDL and total cholesterol.
Digital Health Innovations to Catalyze the Transition to Value-Based Health Care
Authors: Zhang Lan , Bullen Christopher , Chen Jinsong 
Published: November 2024

Abstract
The health care industry is currently going through a transformation due to the integration of technologies and the shift toward value-based health care (VBHC). This article explores how digital health solutions play a role in advancing VBHC, highlighting both the challenges and opportunities associated with adopting these technologies. Digital health, which includes mobile health, wearable devices, telehealth, and personalized medicine, shows promise in improving diagnostic accuracy, treatment options, and overall health outcomes. The article delves into the concept of transformation in health care by emphasizing its potential to reform care delivery through data communication, patient engagement, and operational efficiency. Moreover, it examines the principles of VBHC, with a focus on patient outcomes, and emphasizes how digital platforms play a role in treatment among tertiary hospitals by using patient-reported outcome measures. The article discusses challenges that come with implementing VBHC, such as stakeholder engagement and standardization of patient-reported outcome measures. It also highlights the role played by health innovators in facilitating the transition toward VBHC models. Through real-life case examples, this article illustrates how digital platforms have had an impact on efficiencies, patient outcomes, and empowerment. In conclusion, it envisions directions for solutions in VBHC by emphasizing the need for interoperability, standardization, and collaborative efforts among stakeholders to fully realize the potential of digital transformation in health care. This research highlights the impact of digital health in creating a health care system that focuses on providing high-quality, efficient, and patient-centered care.