bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between longitudinal changes in left ventricular structure and function and 24-hour urinary free cortisol in essential hypertension
Authors: Cao Gao-Zhen , Huang Jia-Yi , Lin Qing-Shan , Wang Run , Wu Min , Chen Cong , Xiu Jian-Cheng , Yiu Kai-Hang 
Published: October 2024

AbstractObjective:This study aimed to examine the relationships between 24-hour urinary cortisol levels (24h-UFC) and alterations in left ventricular (LV) structure and function in patients with essential hypertension.Methods:A prospective cohort study was conducted at the Hypertension Center of the University of Hong Kong-Shenzhen Hospital, including 315 patients with essential hypertension. Baseline 24h-UFC levels were measured, and echocardiographic assessments were performed to evaluate left ventricular mass (LVM), left ventricular ejection fraction (LVEF), and the E/e’ ratio (early diastolic trans-mitral flow velocity to early diastolic mitral annular velocity). Patients were divided into tertiles based on their 24h-UFC levels for comparative analysis. Statistical analyses were employed to examine the relationships between UFC levels and changes in cardiac parameters over the follow-up period.Results:Higher baseline 24h-UFC levels were significantly associated with greater increases in LVM and E/e’ during follow-up, indicating adverse LV remodeling and diastolic dysfunction. This correlation remained significant after adjusting for confounding factors such as age, gender, baseline systolic and diastolic blood pressure, heart rate, and their changes. Patients in the highest 24h-UFC tertile exhibited an increase in left ventricular hypertrophy (LVH) prevalence, whereas those in the lower tertiles showed a reduction.Conclusion:Elevated 24h-UFC levels are independently associated with adverse changes in LV structure and diastolic function in patients with essential hypertension.Novelty and RelevanceWhat Is New?This is the first study to elucidate the association between longitudinal changes in left ventricular structure and function and 24-hour urinary free cortisol (24h-UFC) in essential hypertension.What Is Relevant?This cohort study indicates that higher baseline 24h-UFC levels are significantly associated with greater increases in left ventricular mass (LVM) and the E/e’ ratio during the follow-up period, suggesting adverse left ventricular (LV) remodeling and diastolic dysfunction.Clinical/Pathophysiological Implications?This study provides novel insights into the role of cortisol in cardiovascular remodeling in hypertensive patients and may have significant implications for understanding the mechanisms underlying hypertensive heart disease.
Mid-life association between cardiovascular risk factors and cerebral blood flow in a multi-ethnic population
Authors: Vriend Esther M.C. , Dijsselhof Mathijs B.J. , Bouwmeester Thomas A. , Franco Oscar H. , Galenkamp Henrike , Collard Didier , Nederveen Aart J. , van den Born Bert-Jan H. , Mutsaerts Henk J.M.M. 
Published: October 2024

AbstractBackgroundCardiovascular (CV) risk factors are associated with cerebrovascular damage and cognitive decline in late life. However, it is unknown how different ethnic CV risk profiles are related to cerebral haemodynamics in mid-life. We aimed to investigate associations of CV risk factors with cerebral haemodynamics at two timepoints and examine the impact of ethnicity on these measures.MethodsFrom the HELIUS study (53.0 years, 44.8% female), participants of Dutch (n=236), Moroccan (n=122), or South-Asian Surinamese (n=173) descent were included. Cerebral blood flow (CBF) and its spatial coefficient of variation (sCoV, marker of macrovascular efficiency) were obtained in both grey (GM) and white matter (WM). Associations of CV risk factors, WM hyperintensities (WMH), and carotid plaques with cerebral haemodynamics were investigated using linear regressions.ResultsCBF and sCoV differed per ethnicity. Only at the second visit associations were found, without an interaction with ethnicity; history of CV disease with lower GM CBF and higher WM sCoV, higher total cholesterol and lower WMH volume with lower WM CBF, smoking with higher WM sCoV, and higher SBP with lower GM sCoV.ConclusionsThese findings emphasise the need to further explore the longitudinal effects of midlife risk factors and cerebrovascular health, and its interaction with ethnicity.
Machine Learning Algorithms for Neurosurgical Preoperative Planning: A Comprehensive Scoping Review of the Literature
Authors: Bocanegra-Becerra Jhon E. , Sader Neves Ferreira Julia , Simoni Gabriel , Hong Anthony , Rios-Garcia Wagner , Mirahmadi Eraghi Mohammad , Castilla-Encinas Adriam M. , Colan Jhair Alejandro , Rojas-Apaza Rolando , Pariasca Trevejo Emanuel Eduardo Franco , Bertani Raphael , Lopez-Gonzalez Miguel Angel 
Published: October 2024

AbstractIntroductionPreoperative neurosurgical planning is a keen step to avoiding surgical complications, reducing morbidity, and improving patient safety. The incursion of machine learning (ML) in this domain has recently gained attention, given the notable advantages in processing large data sets and potentially generating efficient and accurate algorithms in patient care.ObjectiveTo evaluate the evolving applications of ML algorithms in the preoperative planning of brain and spine surgery.MethodsIn accordance with the Arksey and O’Malley framework, a scoping review was conducted using three databases (Pubmed, Embase, and Web of Science). Articles that described the use of ML for preoperative planning in brain and spine surgery were included. Relevant data were collected regarding the neurosurgical field of application, patient baseline features, disease description, type of ML technology, study’s aim, preoperative ML algorithm description, and advantages and limitations of ML algorithms.ResultsOur search strategy yielded 7,407 articles, of which 8 studies (5 retrospective, 2 prospective, and 1 experimental study) satisfied the inclusion criteria. Clinical information from 518 patients (62.7% female; mean age: 44.8 years) was used for generating ML algorithms, including convolutional neural network (14.3%), logistic regression (14.3%), random forest (14.3%), and other algorithms (Table 1). Neurosurgical fields of applications included functional neurosurgery (37.5%), tumor surgery (37.5%), and spine surgery (25%). The main advantages of ML included automated processing of clinical and imaging information, selection of an individualized patient surgical approach and data-driven support for treatment decision-making. All studies reported technical limitations, such as long processing time, algorithmic bias, limited generalizability, and the need for database updating and maintenance.ConclusionML algorithms for preoperative neurosurgical planning are being developed for efficient, automated, and safe treatment decision-making. Enhancing the robustness, transparency, and understanding of ML applications will be crucial for their successful integration into neurosurgical practice.
Developing policy to support sustainable diets in Aotearoa New Zealand with contributors
Authors: Kidd Bruce , Enright Hemi , McKerchar Christina , Cleghorn Christine 
Published: October 2024

AbstractAotearoa New Zealand (Aotearoa NZ) is an example of a high-income country with high environmental impacts and health consequences associated with its food system. These impacts can be partially addressed by enabling dietary transitions to healthy and sustainable diets. The EAT-Lancet Commission proposed an internationally acceptable reference diet to promote planetary health. We aimed to work with contributors to develop policy actions to support New Zealanders to transition to healthy sustainable diets. These policies were further examined according to the World Cancer Research Fund, NOURISHING and High Level Panel of Experts (HLPE) on Food Security and Nutrition Food System frameworks. Semi-structured interviews (13) and focus groups (6) were conducted with contributors from government agencies, industry, academics, community and rural and urban tangata whenua communities. All interviews and focus groups were first transcribed using Otter.aI then reviewed by the research team. Thematic analysis was used to identify and summarise each policy. 111 policies were suggested across the NOURISHING framework policy domains: 11 (10%) in behaviour change communication; 35 (32%) in the food environment; and 65 (59%) addressing the food system. Participants spoke of behaviour change communication policies of education, awareness campaigns, and workshops such as cooking classes. Food environment policies targeted supermarkets and food retail, local food environments, and government standards and regulations including food taxes and subsidies. Policies in the food system area looked at food waste, supporting local food production and government structures and support. Contributors identified policies that advocate and support planetary health.Key policy insights□The majority of policies identified by contributors focused on food systems and specifically food production□Many contributors highlighted existing policies or initiatives already implemented locally and nationally but needed further support□There is limited research demonstrating the effectiveness of policies and initiatives addressing sustainable food systems in Aotearoa New Zealand□Funding, resources and research of existing local initiatives and policies supporting sustainable food systems in Aotearoa New Zealand and globally are urgently required
Outbreak ofLeishmania tropicaamongst militia members in a non-endemic district under conflict in the lowlands of Somali Region in Ethiopia
Authors: Abera Adugna , Tadesse Henok , Beyene Dereje , Geleta Desalegn , Abose Ebise , Kinde Solomon , Abdosh Mussie , Difabachew Hailemariam , Belachew Mahlet , Gire Abdulahi , Bishaw Tesfahun , Habtetsion Medhanye , Olani Zelalem , Eyelachew Endawoke , Birhanu Worku , Choukri Kaoutar , Coppens Jasmine , Tadese Gemechu , Haile Kebron , Bekele Henok , Abte Melkamu , Tollera Getachew , Hailu Mesay , Kebede Zeyede , van der Auwera Gert , Seife Fikre , Dujardin Jean-Claude , van Griensven Johan , Wolday Dawit , Embiale Wendemagegn , Pareyn Myrthe , Tasew Geremew 
Published: October 2024

AbstractFollowing the emergence of a conflict, an outbreak of cutaneous leishmaniasis (CL) occurred in a non- endemic lowland area in the Somali Region in Ethiopia, raising public health concerns. All 1050 patients were militia members, immunologically naïve and displaced into a conflict area with a likely sylvatic transmission cycle. We identifiedLeishmania tropicaas the causative species, challenging the previous assumption thatL. aethiopicawas Ethiopia’s primary agent of CL. Notably, over 77% of patients had more than 10 lesions, a presentation atypical forL. tropicaelsewhere.Phlebotomus orientalisandP. sergenti, vectors for visceral leishmaniasis (VL) and CL in North Africa respectively, were captured. Further research is needed to explore the eco-epidemiology of the outbreak and the patient’s treatment responses. Insights will help develop management strategies to control this newly emerging form of CL, prevent its spread to other regions, and hybridize with Leishmania strains causing VL endemic.
Land-use changes impact root-fungal network connectivity in a global biodiversity hotspot
Authors: Carneiro de Melo Moura Carina , Guerrero-Ramirez Nathaly R. , Krashevska Valentyna , Polle Andrea , Siregar Iskandar Z. , Ballauff Johannes , Siregar Ulfah J. , Encinas-Viso Francisco , Bell Karen , Nevill Paul , Gailing Oliver 
Published: October 2024

AbstractCross-kingdom associations play a fundamental role in ecological processes. Yet our understanding of plant-fungal co-occurrences in tropical rainforests and the potential impacts of land-use change shaping species connections remains limited.By using amplicon sequencing on DNA from roots and their associated fungal communities, we aim to understand the impact of rainforest transformation on the composition and structure of root-fungal ecological networks in human-modified landscapes in Sumatra, Indonesia.Each land-use type supports a distinctive set of indicator species, which are organisms that reflect specific environmental conditions and can signal changes in ecosystem health. We observed a decline in the richness of plant species indicators and plant-fungal associations with increasing land-use intensification. Additionally, there is a turnover in root communities, shifting from native and endemic species in rainforests to non-native, generalist herbaceous species in rubber and oil palm plantations.Plant-fungal connectivity significantly declined with increasing land-use intensification, suggesting that managed ecosystems may have weakened root-fungal interactions. Network analysis highlights the distinct responses of various fungal groups. For instance, arbuscular mycorrhizal fungi (AMF) showed fewer connections with modules linked to oil palm and rubber roots, indicating weakened root-fungal associations in monocultures. This aligns with the observed reduction in AMF diversity in converted land-use areas compared to forests, further reinforcing the negative impact of land-use practices in oil palm and rubber monocultures on AMF diversity.Synthesis. Dimensioning the impacts of rainforest transformations belowground is constrained by our understanding of fungal functional guilds. Highly modified systems exhibited fewer connections, suggesting a dynamic restructuring of root-fungal relationships in response to land-use changes. Understanding the intricate interplay between plants and fungi in the face of land-use change can provide valuable information for conservation efforts, agricultural practices, and ecosystem management strategies aimed at promoting biodiversity, soil health, and ecosystem resilience in the context of changing environmental conditions. Moreover, it underscores the importance of communities’ networks in land-use planning and management decisions to support plant and fungal diversity in terrestrial ecosystems.
Prediction and discovery of protein-protein direct interactions and stable complexes based on gene co-expression and co-evolution
Authors: Miglionico P. , Nemati Fard Lorenzo Amir , Gloeckner C.J. , Raimondi F. 
Published: October 2024

AbstractIn this study we employed a data-driven approach to explore the evolutionary and genetic determinants of protein direct interactions and stable complex formation in the human proteome. We found that simple co-evolutionary and co-expression metrics are highly informative of direct interactions and stable complexes. We used this information to train supervised binary classifiers to predict interactions either directly involved in the formation of a complex (as annotated in IntAct) or forming stable complexes (from Complex Portal). In the former task, our model was able to discriminate direct interactions with an AUROC=0.813, while in the latter it discriminated interaction forming stable complexes with an AUROC=0.964. In both cases, our approach outperformed String, that we employed as a baseline. Feature importance analysis revealed different contributions to the prediction of these distinct interaction types. Co-evolutionary features, in particular those referred to protein domains involved in interaction interfaces, are more important to discriminate direct interactions. On the other hand, co-expression features contributed more to the prediction of stable complexes. From these pairwise predictions we generated a proteome-wide network that we clustered to assess the recovery of known complexes from Complex Portal within network communities. We were able to recover known complexes at a higher accuracy compared to other approaches.In conclusion, we propose a new method able to discriminate direct interactions as well as forming stable complexes. This method can be used to stratify molecular interaction networks, as well as to perform discovery of new functional complexes at a proteome-wide scale.
Conservation of mRNA operon formation in the control of the heat shock response in mammalian cells
Authors: Pataki Emese , Gerst Jeffrey E. 
Published: October 2024

AbstractProkaryotic organisms rely on polycistronic transcription (i.e.operons) to express multiple mRNAs from a single promoter, enabling rapid and robust responses to stimuli. In yeast, a similar mechanism exists whereby monocistronic mRNAs are selectively assembled into ribonucleoprotein particles, termed RNA operons or transperons, to regulate the expression of genes involved in the same biological process. One example is the heat shock protein (HSP) transperon that confers the eukaryotic heat shock response (HSR), a conserved cellular mechanism that enables organisms to cope with proteotoxic stress. As it was unknown whether transperons exist in higher eukaryotes, we examined whether a similar mechanism operates in mammalian cells. Using both single-molecule fluorescentin situhybridization and RNA pulldown techniques, we show that mammalian HSP mRNAs colocalize and multiplex to form mRNA assemblages during heat stress. These RNP assemblies are dependent on heat shock factor 1 transcriptional regulator and involve both inter- and intrachromosomal interactions among the HSP genes. Bioinformatic analysis identifies a conserved sequence motif within the coding regions of HSP mRNAs and mutational studies in yeast suggest that it is critical for mRNA multiplexing and the HSR. These findings emphasize the evolutionarily conserved nature of heat shock gene regulation across species and suggest that mammalian cells employ RNA operons/transperons in organizing their heat shock response.
White Tea Mitigates Obesity-Related Metabolic Disorders Through Apelin and Insulin Modulation in Rats
Authors: Sümer Ayşegül , Demirtaş Öznur , Pınarbaş Esra , Kutlu Eda Yılmaz , Kılıç Hülya 
Published: October 2024

AbstractObesity, a prevalent global health issue, is influenced by genetic, metabolic, environmental, and behavioral factors, often leading to serious complications like type 2 diabetes, cardiovascular diseases, and reduced life expectancy. Recent studies have highlighted apelin, a bioactive peptide, for its significant role in obesity and related metabolic disorders. Apelin, primarily found in adipose tissue, regulates appetite, energy expenditure, and insulin sensitivity, making it a promising target for antiobesity treatments. Concurrently, tea, especially white tea, rich in bioactive compounds, has shown potential health benefits, including antiobesity effects. This study investigates the impact of white tea on weight gain, glucose metabolism, and lipid metabolism by analyzing its effects on apelin-13, apelin-36, and insulin levels in a high-fat diet (HFD)-induced obesity model in rats. Thirty-two male Sprague Dawley rats were divided into four groups: control, HFD, HFD+orlistat, and HFD+white tea. Over 13 weeks, the HFD groups received their respective treatments while being monitored for weight gain and metabolic changes. Results indicated that the HFD group exhibited significant weight gain and elevated cholesterol levels compared to the control. White tea-treated rats showed reduced weight gain and lower cholesterol levels, suggesting its antiobesity properties. Apelin-13 levels were significantly lower in the HFD group, while white tea mitigated this effect, highlighting its potential role in modulating apelin levels and improving insulin sensitivity. The findings support the hypothesis that white tea can be an effective antiobesity agent, offering a safer, natural alternative to conventional treatments. Further research is warranted to elucidate the precise mechanisms underlying these beneficial effects.
Transparent and robust Artificial intelligence-driven Electrocardiogram model for Left Ventricular Systolic Dysfunction
Authors: Lee Min Sung , Jang Jong-Hwan , Kang Sora , Han Ga In , Yoo Ah-Hyun , Jo Yong-Yeon , Son Jeong Min , Kwon Joon-myoung , Lee Sooyeon , Lee Ji Sung , Lee Hak Seung , Kim Kyung-Hee 
Published: October 2024

AbstractHeart failure (HF) is an escalating global health concern, worsened by an aging population and limitations in traditional diagnostic methods like electrocardiograms (ECG). The advent of deep learning has shown promise for utilizing 12-lead ECG models for the early detection of left ventricular systolic dysfunction (LVSD), a crucial HF indicator. This study validates the AiTiALVSD, an AI/machine learning-enabled Software as a Medical Device, for its effectiveness, transparency, and robustness in detecting LVSD. Conducted at Mediplex Sejong Hospital in the Republic of Korea, this retrospective single-center cohort study involved patients suspected of LVSD. The AiTiALVSD model, which is based on a deep learning algorithm, was assessed against echocardiography findings. To improve model transparency, the study utilized Testing with Concept Activation Vectors (TCAV) and included clustering analysis and robustness tests against ECG noise and lead reversals. The study involved 688 participants and found AiTiALVSD to have a high diagnostic performance, with an AUROC of 0.919. There was a significant correlation between AiTiALVSD scores and left ventricular ejection fraction values, confirming the model’s predictive accuracy. TCAV analysis showed the model’s alignment with medical knowledge, establishing its clinical plausibility. Despite its robustness to ECG artifacts, there was a noted decrease in specificity in the presence of ECG noise. AiTiALVSD’s high diagnostic accuracy, transparency, and resilience to common ECG discrepancies underscore its potential for early LVSD detection in clinical settings. This study highlights the importance of transparency and robustness in AI/ML-based diagnostics, setting a new benchmark in cardiac care.
P450-Catalyzed Biaryl Macrocyclization of Leaderless Ribosomal Peptides
Authors: Liu Runze , Ren Hongyu , Wu Gengfan , He Bei-Bei , Pang Cuiping , Shen Zhuanglin , Liu Jing , Song Zhi-Man , Zhou Jiahai , Li Yong-Xin 
Published: October 2024

AbstractMacrocyclic peptides, an intriguing class of molecules, embody promising frameworks for the development of chemical probes and prospective therapeutic agents. However, the lack of an established wide-substrate scope synthesis methodology has made it challenging to achieve both efficiency and selectivity simultaneously. P450-catalyzed ribosomal synthesized and post-translational modification peptides (RiPPs) are a new family of macrocyclic peptides with typical biaryl crosslinks. In this study, we report the discovery of a RiPP-modified P450 macrocyclase, GpeC, which natively catalyzes the biaryl C(sp2)-C(sp2) crosslink of tryptophan-tyrosine in a tetrapeptide module. Unlike most previously documented P450-RiPPs that possess a substantial leader peptide region, hindering biocatalytic applications, our P450 GpeC exhibits catalytic potential with leaderless precursor peptides and a wide substrate tolerance, highlighting its adaptability and potential for creating diverse macrocyclic structures. The crystal structure of GpeC, combined with in silico calculations and site-directed mutagenesis, provides strong evidence for the extreme flexibility of intra-cyclic amino acids within the biaryl-cyclized tetrapeptide. This flexibility enables the substitution of any of the other 19 amino acids, indicating that GpeC is a robust and adaptable catalyst for biaryl cyclization, providing a valuable resource for the biocatalytic synthesis of complex macrocyclic compounds.