bluuebunny/crossref_metadata_2025_split huggingface dataset:
Value of using artificial intelligence derived clusters by health and social care need in Primary Care: A qualitative interview study
Authors: Holt Sian , Simpson Glenn , Santer Miriam , Everitt Hazel , Farmer Andrew , Zhou Kuangji , Qian Zhiling , Davies Firoza , Dambha-Miller Hajira , Morrison Leanne 
Published: October 2024

AbstractPurposePeople living with MLTCs attending consultations in primary care frequently have unmet social care needs (SCNs), which can be challenging to identify and address. Artificial intelligence (AI) derived clusters could help to identify patients at risk of SCNs. Understanding the views of people living with MLTCs and those involved in their care can help inform the design of effective interventions informed by AI-derived clusters to address SCNs.MethodsQualitative study using semi-structured online and telephone interviews with 24 people living with MLTCs and 20 people involved in the care of MLTCs. Interviews were analysed using Reflexive Thematic Analysis.ResultsPrimary care was viewed as an appropriate place to have conversations about SCNs. However, participants felt health care professionals lack capacity to have these conversations and to identify sources of support. AI was perceived as a tool that could potentially increase capacity for this but only when supplemented with effective, clinical conversations. Interventions harnessing AI should be brief, be easy to use and remain relevant over time, to ensure no additional burden on clinical capacity. Interventions must allow flexibility to be used by multidisciplinary teams within primary care, frame messages positively and facilitate conversations that remain patient centered.ConclusionOur findings suggest that AI-derived clusters to identify and support SCNs in primary care have perceived value, but there were some concerns including the need to consider personal context. AI derived clusters can be used as a tool to inform and prioritise effective clinical conversations.Conference names, dates and locations for any prior presentationsBritish Journal of General Practice Research Conference, March 2024, London.School of Academic Primary Care Southwest Conference, March 2024. Cardiff.Faculty of Medicine Research Conference, June 2024. Southampton.
End-of-life care in hematological malignancies – a nationwide comparative study on the Swedish Register of Palliative Care
Authors: Skåreby Ellen , Fürst Per , von Bahr Lena 
Published: October 2024

ABSTRACTBackgroundPatients with hematological malignancies are less likely to be referred to specialized palliative care, and more likely to receive aggressive end-of-life care than patient with solid tumors. The Swedish Register of Palliative Care (SRPC) collects end-of-life care quality data from a majority of health facilities in Sweden. We here use the national data from the SRPC to evaluate the quality of end-of-life care in patients with hematological malignancies in Sweden.MethodsIn a retrospective, observational registry study all adult registered cancer deaths in the years 2011 to 2019 were included. For the main analysis, patients with unexpected deaths or co-morbidities were excluded. Descriptive statistics and multivariate logistic regression, adjusting for age and sex, were used.ResultsA total of 119 927 patients were included, 8 550 with hematological malignancy (HM) and 111 377 with solid tumor (ST), corresponding to 43% of all deaths due to HM and 61% of ST deaths during the observed period.Significantly more ST patients than HM received end-of-life care in a specialized palliative unit (hospice, palliative ward or specialized home care), 54% vs 42% (p<0.001), and this difference could be seen also in the very old (80+). End-of-life care quality measures were significantly worse for HM patients than ST patients, which could partly be explained by the lower receipt of specialized palliative care. The most common symptom in both groups were pain, followed by anxiety. HM patients were less likely to achieve complete symptom relief (p<0.001) which appears to be related to the receipt of specialized palliative care.ConclusionPatients with hematological malignancies are more likely to die in emergency hospital and less likely to receive specialized palliative competence in end-of-life. This also translates into less qualitative end-of-life care and less efficient symptom relief.
Detecting Glaucoma Worsening Using Optical Coherence Tomography Derived Visual Field Estimates
Authors: Pham Alex T. , Bradley Chris , Hou Kaihua , Herbert Patrick , Unberath Mathias , Ramulu Pradeep Y. , Yohannan Jithin 
Published: October 2024

AbstractObjectiveMultiple studies have attempted to generate visual field (VF) mean deviation (MD) estimates using cross-sectional optical coherence tomography (OCT) data. However, whether such models offer any value in detecting longitudinal VF progression is unclear. We address this by developing a machine learning (ML) model to convert OCT data to MD and assessing its ability to detect longitudinal worsening.DesignRetrospective, longitudinal studyParticipantsA model dataset of 70,575 paired OCT/VFs to train an ML model converting OCT to VF-MD. A separate progression dataset of 4,044 eyes with ≥ 5 paired OCT/VFs to assess the ability of OCT-derived MD to detect worsening. Progression dataset eyes had two additional unpaired VFs (≥ 7 total) to establish a “ground truth” rate of progression defined by MD slope.MethodsWe trained an ML model using paired VF/OCT data to estimate MD measurements for each OCT scan (OCT-MD). We used this ML model to generate longitudinal OCT-MD estimates for progression dataset eyes. We calculated MD slopes after substituting/supplementing VF-MD with OCT-MD and measured the ability to detect progression. We labeled true progressors using a ground truth MD slope <0.5 dB/year calculated from ≥ 7 VF-MD measurements. We compared the area under the curve (AUC) of MD slopes calculated using both VF-MD (with <7 measurements) and OCT-MD. Because we found OCT-MD substitution had a statistically inferior AUC to VF-MD, we simulated the effect of reducing OCT-MD mean absolute error (MAE) on the ability to detect worsening.Main Outcome MeasuresAUCResultsOCT-MD estimates had an MAE of 1.62 dB. AUC of MD slopes with partial OCT-MD substitution was significantly worse than the VF-MD slope. Supplementing VF-MD with OCT-MD also did not improve AUC, regardless of MAE. OCT-MD estimates needed an MAE ≤ 1.00 dB before AUC was statistically similar to VF-MD alone.ConclusionML models converting OCT data to VF-MD with error levels lower than published in prior work (MAE: 1.62 dB) were inferior to VF-MD data for detecting trend-based VF progression. Models converting OCT data to VF-MD must achieve better prediction errors (MAE ≤ 1 dB) to be clinically valuable at detecting VF worsening.
A network based study of the dynamics ofAβand τ proteins in Alzheimer’s disease
Authors: Bianchi Stefano , Landi Germana , Marella Camilla , Tesi Maria Carla , Testa Claudia ,   Alzheimers Disease Neuroimaging Initiative
Published: October 2024

AbstractDue to the extreme complexity of Alzheimer’s disease (AD), the aetiology of which is not yet known, nor are there any known effective treatments, mathematical modelling can be very useful. Indeed, mathematical models, if deemed reliable, can be used to test medical hypotheses that could be difficult to verify directly. In this context, it is important to understand howAβandτproteins, which in abnormal aggregate conformations are hallmarks of the disease, interact and spread. We are particularly interested in this paper in studying the spreading of misfoldedτ. To this end, we present four different mathematical models, all on networks on which the protein evolves. The models differ in both the choice of network and diffusion operator. Through comparison with clinical data onτconcentration, that we carefully obtained with multimodal analysis techniques, we show that some models are more adequate than others to simulate the dynamics of the protein. This type of study may suggest that, when it comes to modelling certain pathologies, the choice of the mathematical setting must be made with great care if comparison with clinical data is considered decisive.
Frontoparietal theta synchronization causally links working memory with impulsive decision making
Authors: Kapetaniou Georgia E. , Vural Gizem , Soutschek Alexander 
Published: October 2024

AbstractDelaying gratification in value-based decision making is canonically related to activation in the dorsolateral prefrontal cortex (dlPFC), but past research neglected that the dlPFC is part of a larger frontoparietal network. It is therefore unknown whether the dlPFC causally implements delay of gratification in concert with posterior parts of the frontoparietal network rather than in isolation. Here, we addressed this gap by testing the effects of frontoparietal theta synchronization and desynchronization on impulsive decision making using transcranial alternating current stimulation (tACS). Healthy participants performed an intertemporal choice task and a 3-back working memory task while left frontal and parietal cortices were stimulated with a 5 Hz theta frequency at in-phase (synchronization), anti-phase (desynchronization), or sham tACS. We found frontoparietal theta coupling to improve working memory performance, while in the decision task desynchronization was associated with more impulsive choices and stronger hyperbolic discounting of future rewards. Overall, our findings overcome the past focus of the dlPFC in isolation and show that patient decision making causally relies on synchronous activation in a frontoparietal network related to working memory.
Joint Protein Inference Analysis with PyProteinInference Elucidates Biological Understanding of Tandem Mass Spectrometry Data
Authors: Hinkle Trent B. , Bakalarski Corey E. 
Published: October 2024

AbstractSelection and application of protein inference algorithms can have a significant impact on the data output from tandem mass spectrometry (MS/MS) experiments, yet its use is often an afterthought in proteomics research due to the inability to apply different inference algorithms in existing analysis systems today. PyProteinInference provides a comprehensive suite of tools to guide researchers through the application of multiple inference algorithms and computation of protein-level, set-based false discovery rates (FDR) from tandem mass spectrometry (MS/MS) data using a unified interface. Here, we describe the software and its application to a K562 whole-cell lysate as well as in a CRAF affinity-purification mass spectrometry experiment to demonstrate its utility in facilitating conclusions about underlying biological mechanisms in proteomic data.
Altered Proteasome Composition in Aging Brains, Genetic Proteasome Augmentation Mitigates Age-Related Cognitive Declines, and Acute Proteasome Agonist Treatment Rescues Age-Related Cognitive Deficits in Mice
Authors: Pickering Andrew M. 
Published: October 2024

ABSTRACTThe aging brain experiences a significant decline in proteasome function, The proteasome is critical for many key neuronal functions including neuronal plasticity, and memory formation/retention. Treatment with proteasome inhibitors impairs these processes. Our study reveals a marked reduction in 20S and 26S proteasome activities in aged mice brains driven by reduced functionality of aged proteasome. This is matched by a decline in 20S proteasome but an increase in 26S proteasome. Our data suggests this may be a compensatory response to reduced functionality. By overexpressing the proteasome subunit PSMB5 in the neurons of mice, enhancing proteasome function, we slowed age-related declines in spatial learning and memory as well neuromuscular declines. We then showed acute treatment with a proteasome activator to rescue spatial learning and memory deficits in aged mice. These findings highlight the potential of proteasome augmentation as a therapeutic strategy to mitigate age-related cognitive declines.
CelFDrive: Artificial Intelligence assisted microscopy for automated detection of rare events
Authors: Brooks Scott , Toral-Pérez Sara , Corcoran David S. , Kilborn Karl , Bodensteiner Brian , Baumann Hella , Burroughs Nigel J. , McAinsh Andrew D. , Bretschneider Till 
Published: October 2024

1Abstract1.1SummaryCelFDrive automates high-resolution 3D imaging cells of interest across a variety of fluorescence microscopes, integrating deep learning cell classification from auxiliary low resolution widefield images. CelFDrive enables efficient detection of rare events in large cell populations, such as the onset of cell division, and subsequent rapid switching to 3D imaging modes, increasing the speed for finding cells of interest by an order of magnitude.1.2Availability and ImplementationCelFDrive is available freely for academic purposes at the CelFDrive GitHub repository. and can be installed on Windows, macOS or Linux-based machines with relevant conda environments [1]. To interact with microscopy hardware requires additional software; we use SlideBook software from Intelligent Imaging Innovations (3i), but CelFDrive can be deployed with any microscope control software that can interact with a Python environment. Graphical Processing Units (GPUs) are recommended to increase the speed of application but are not required. On 3i systems the software can be deployed with a range of microscopes including their Lattice LightSheet microscope (LLSM) and spinning disk confocal (SDC).1.3Contacts.brooks.2@warwick.ac.uk
Pathogenicity and intestinal barrier disruptive ability ofMalassezia furfurin an alternative model hostCaenorhabditis elegansis partially alleviated byLacticaseibacillus rhamnosus
Authors: Kishida Chiho , Tsuru Ayano , Takabayashi Satoka , Wu Xueyang , Tanimoto Yoshihiko , Kage-Nakadai Eriko 
Published: October 2024

AbstractMalassezia furfuris associated with various diseases; however, the mechanisms underlying its pathogenicity remain largely unknown. In the present study,Caenorhabditis eleganswas used as the model host to evaluateM. furfurpathogenicity. Additionally, effects of lactic acid bacteria againstM. furfurpathogenicity were evaluated. Compared toEscherichia coliOP50 (OP, control), both live and heat-killedM. furfurreduced the lifespan and body size ofC. elegans, although heat-killedM. furfurwas less effective than liveM. furfurin lifespan shortening. Furthermore, unlike heat-killedM. furfur,liveM. furfurdisrupted the nematode intestinal barrier.nsy-1andsek-1loss-of-function mutants were susceptible toM. furfur, suggesting their involvement in the defense againstM. furfurinfection. Expression of genes involved in host defense and of those coding for C-type lectin domain-containing proteins and antimicrobial peptides was upregulated inM. furfur-infectedC. elegans.Lacticaseibacillus rhamnosus(LR) significantly ameliorated lifespan shortening and body size reduction inM. furfur-infectedC. elegansand protected against intestinal barrier disruption, suggesting that LR protects nematodes fromM. furfurvirulence. This study highlightsM. furfurpathogenicity and intestinal barrier disruptive ability inC. elegansand suggests that theM. furfurvirulence is partially attenuated by LR.ImportanceInfection withMalassezia furfurshortens the lifespan and disrupts the intestinal barrier in the model hostC. elegans. The probioticLacticaseibacillus rhamnosus(LR) attenuatesM. furfurvirulence, thus partially protecting the intestinal tract. Signaling of the innate immune response toM. furfurinC. elegansis mediated bynsy-1andsek-1, suggesting that the expression of genes involved in the biological defense response may be regulated downstream ofnsy-1andsek-1. This study enhances our understanding of the diseases associated withM. furfurand offers insights into potential preventive and therapeutic methods using probiotics.
Sugarcane yellow leaf virus impairs the transcriptomic defense responses of sugarcane to its new aphid vectorMelanaphis sorghi
Authors: Pimenta Ricardo José Gonzaga , Aono Alexandre Hild , Sforça Danilo Augusto , Melloni Maria Natália Guindalini , Gonçalves Marcos Cesar , Pinto Luciana Rossini , de Souza Anete Pereira 
Published: October 2024

AbstractSugarcane (Saccharumspp.) is a preeminent sugar and bioenergy crop and has great economic importance in tropical countries. A major disease affecting this crop is yellow leaf disease, which is caused by sugarcane yellow leaf virus (SCYLV,Polerovirus SCYLV,Solemoviridae). The sugarcane aphidMelanaphis sacchariis considered the main vector of SCYLV, and the closely related sorghum aphidMelanaphis sorghi,which has recently emerged as a pest of great relevance in sorghum, has also been suspected as a vector. Genetic resistance is an important resource for preventing yield losses caused by SCYLV and its vectors, but knowledge on the underlying molecular mechanisms is lacking. Therefore, the present work was aimed at investigating the transcriptomic responses of sugarcane to SCYLV andM. sorghi, which was reported to transmit this virus for the first time herein. Two sugarcane cultivars, one susceptible and one tolerant to SCYLV, were fed upon by aviruliferous and viruliferous aphids. The transcriptome of the plants was assessed by RNA-Seq using differential gene expression analyses and a gene coexpression network. The susceptible cultivar showed an incipient reaction to bothM. sorghiand SCYLV, with very few differentially expressed genes (DEGs) identified in comparison with aphid-free plants. The response of the tolerant cultivar to aviruliferousM. sorghiinvolved pathways typically associated with defense against herbivory, which were also enriched in coexpression network modules in which DEGs were overrepresented. Some of these genes were hubs in their respective modules, indicating they are potential key regulators of the defense responses. However, these responses were diminished when viruliferous aphids were used, and other processes linked to infection with SCYLV were altered. These results indicated that SCYLV could affect sugarcane defense responses to its vector, similar to other viruses of the same genus. Some possible implications for the epidemiology and impact of SCYLV andM. sorghiare discussed.
OfWRKY33 binds to the key linalool synthase geneOfTPS7to promote linalool synthesis inOsmanthus fragransflowers
Authors: Xi Wan , Jiang Meng-Yu , Zhu Lin-lin , Zeng Xu-Mei , Ju Huan , Yang Qin-Lian , Zhang Ting-Yu , Wang Cai-Yun , Zheng Ri-Ru 
Published: October 2024

AbstractVolatile aroma compounds make significant contributions to human perception of flowers.Osmanthus fragransis a famous aroma plant and linalool along with its oxides are proved to be the dominant aroma active compounds. Although some terpene synthases (TPSs) have been characterized, a comprehensive study of the hub metabolic gene and its transcriptional regulation remain to be revealed. Here, we selected a specific cultivar Boyeyingui (BBYG) with the highest content of linalool among 20 wide-cultivated cultivars for genome and transcriptome sequencings. Among the 25 new putativeOfTPSs,onlyOfTPS6,OfTPS7could exclusively produce linaloolin planta. Biochemical analysis demonstrated that OfTPS6, OfTPS7 were able to catalyze geranyl diphosphate (GPP) into linalool and a small proportion of other monoterpenesin vitro. Spatial and temporal correlation analysis further confirmed the transcript level ofOfTPS7was closely associated with linalool content in diverse cultivars and different tissues, suggestingOfTPS7was the essential linalool synthase gene. Combined with yeast one-hybrid screen and weighted correlation network analysis (WGCNA), a nucleus-localized transcriptional factor OfWRKY33 was considered as a potential modulator. Y1H, dual-luciferase assay and electrophoretic mobility shift assay (EMSA) demonstrated that OfWRKY33 directly bound to the W-box ofOfTPS7promoter to stimulate its transcription. OfWRKY33 could coordinately induce the expressions ofOfTPS7,1-deoxy-d-xylulose 1(OfDXS1), thereby promoting the linalool formation. The results first revealed the hub linalool synthase geneOfTPS7and a novel TF participating in the complex transcriptional regulation of linalool biosynthesis inO. fragransflowers.
Glioblastoma Treatment by Systemic Actinium-225 α-particle Dendrimer-radioconjugates is Improved by Chemotherapy
Authors: Nair Rajiv Ranjit , Sarkar Aira , Hariharan Pooja , Gabrielson Kathleen L. , Wu Tony , Liu Chang , Santosh Anjalia , Liyanage Wathsala G.H.M , Bhujwalla Zaver M , Vidaver Marie-France Penet , Kannan Rangaramanujam M , Sofou Stavroula 
Published: October 2024

AbstractRATIONALEThe poor prognosis of glioblastoma is largely due to drug resistance and tumor location that, together, make it difficult to treat aggressively without affecting the rest of the brain.METHODOLOGYHigh-energy, short-range (40-80µm) dendrimer-delivered α-particles could address both challenges, because (1) they cause complex, highly cytotoxic double-strand DNA breaks, and (2) irradiation of the neighboring brain is minimal, since dendrimers selectively delivers them to tumors. Since cancer cells that are not directly hit by α-particles will likely not be killed, the patterns of tumor irradiation affect efficacy. Systemically injected dendrimers extensively accumulate in glioblastomas, where they are taken up by tumor associated macrophages (TAMs), which tend to infiltrate tumors. We hypothesized that dendrimers labeled with α-particle emitters, when being carried by TAMs, could more evenly irradiate glioblastomas, improving survival. In this study, the efficacy of dendrimers radiolabeled with the α-particle emitter actinium-225 (dendrimer-radioconjugates) was evaluated when administered alone and/or after temozolomide, in a syngeneic immune-competent orthotopic GL261-C57BL/6 mouse model.RESULTSSystemically-administered dendrimer-radioconjugates, at activities that did not result in long-term toxicities, prolonged survival of mice with orthotopic GL261 tumors, compared to standard-of-care temozolomide (39 vs 31 days mean survival, p=0.0061) and non-treated animals (30 days, p=0.0009). Importantly, injection of temozolomide 24 hours before administration of dendrimer-radioconjugatesfurther improved survival remarkably(44 days). This improvement in efficacy was attributed to: (1) the significant increase (by 33%) in tumor absorbed doses delivered by dendrimer-radioconjugates when injected after chemotherapy, without altering normal organ dosimetry, while sparing the tumor-surrounding healthy brain; (2) the potentially deeper tumor penetration of dendrimer-radioconjugates, suggested by the enhancement of dendrimer penetration within GL261-spheroids, employed as model tumor-avascular regions and/or TAM-free regions; and/or (3) the formation of a more lethal cocktail when both modalities acted on same cancer cells, that was correlated with increased levels of dendrimer-radioconjugates associating with GL261 cellsin vitroand with greater incidences of karyomegalyin vivo.CONCLUSIONSThis study demonstrates the potential of a ‘brain tumor targeted’ systemic actinium-225 radiopharmaceutical therapy that inhibits growth of glioblastoma cells and prolongs survival of mice with orthotopic brain tumors, further improved by standard-of-care temozolomide, without notable toxicities.