bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of CT-based foundational artificial intelligence and radiomics models for prediction of survival for lung cancer patients treated on the NRG/RTOG 0617 clinical trial
Authors: Upadhaya Taman , Chetty Indrin J , McKenzie Elizabeth M , Bagher-Ebadian Hassan , Atkins Katelyn M 
Published: November 2024

Abstract

Objectives
To apply CT-based foundational artificial intelligence (AI) and radiomics models for predicting overall survival (OS) for patients with locally advanced non-small cell lung cancer (NSCLC).

Methods
Data for 449 patients retrospectively treated on the NRG Oncology/Radiation Therapy Oncology Group (RTOG) 0617 clinical trial were analyzed. Foundational AI, radiomics, and clinical features were evaluated using univariate cox regression and correlational analyses to determine independent predictors of survival. Several models were fit using these predictors and model performance was evaluated using nested cross-validation and unseen independent test datasets via area under receiver-operator-characteristic curves, AUCs.

Results
For all patients, the combined foundational AI and clinical models achieved AUCs of 0.67 for the Random Forest (RF) model. The combined radiomics and clinical models achieved RF AUCs of 0.66. In the low-dose arm, foundational AI alone achieved AUC of 0.67, while AUC for the ensemble radiomics and clinical models was 0.65 for the support vector machine (SVM). In the high-dose arm, AUC values were 0.67 for combined radiomics and clinical models and 0.66 for the foundational AI model.

Conclusions
This study demonstrated encouraging results for application of foundational AI and radiomics models for prediction of outcomes. More research is warranted to understand the value of ensemble models toward improving performance via complementary information.

Advances in knowledge
Using foundational AI and radiomics-based models we were able to identify significant signatures of outcomes for NSCLC patients retrospectively treated on a national cooperative group clinical trial. Associated models will be important for application toward prospective patients.
Mental health disorders before, during and after the COVID-19 pandemic: a nationwide study
Authors: Grønkjær Clara S , Christensen Rune H B , Kondziella Daniel , Benros Michael E 
Published: November 2024

Abstract
The COVID-19 pandemic and lockdowns prompted a major concern for mental health effects. Comprehensive nationwide studies are lacking on the indirect effect of the COVID-19 pandemic on the population’s mental health. We aimed to determine whether the COVID-19 pandemic and lockdowns affected mental health service usage, suicide attempts, and suicides.
This comprehensive nationwide register-linked study followed all individuals in Denmark from 1990. The main outcomes were rates of psychiatric admissions, use of psychotropic medication, suicide attempts, suicides, patients in community-based private psychiatry or psychology practices, and referrals to psychiatric hospitals. The impact of the pandemic (March 11, 2020–June 30, 2023) and lockdowns was assessed with log-normal models adjusted for pre-pandemic trends (January 1, 2017–March 10, 2020). We reported Rate Ratios (RR) of the observed and counterfactual rates.
We identified the 5 807 714 (50.3% females) individuals living in Denmark on March 1, 2020. The rates of psychiatric admissions (RR: 0.95, 95% Confidence Interval (CI): 0.91 to 0.99, p-value: 0.017) and suicide attempts (RR: 0.85, 95% CI: 0.76 to 0.95, p-value: 0.007) were lower during the pandemic compared to the pre-pandemic trend. The rates of suicides (RR: 0.89, 95% CI: 0.75-1.05, p-value: 0.173), patients in private practices (RR: 1.00, 95% CI: 0.96-1.04, p-value: 0.986), and referrals (RR: 1.06, 95% CI: 0.95-1.18, p-value: 0.307) were not significantly different during the pandemic compared to the pre-pandemic trend. During the first lockdown, rates were lower for psychiatric admissions (RR: 0.85, 95% CI: 0.80 to 0.90, p-value &lt;0.001), suicide attempts (RR: 0.80, 95% CI: 0.69 to 0.94, p-value: 0.007), suicides (RR: 0.67, 95% CI: 0.52 to 0.86, p-value: 0.002), patients in private practices (RR: 0.88, 95% CI: 0.82 to 0.93, p-value &lt;0.001), and referrals (RR: 0.69, 95% CI: 0.60 to 0.81, p-value &lt; 0.001) compared to the pre-pandemic trend. However, during the pandemic, the rate of psychotropic medication users increased by 6% compared to the pre-pandemic trend (RR: 1.06, 95% CI: 1.05 to 1.06, p-value &lt; 0.001).
The COVID-19 pandemic and lockdowns did not severely influence pre-pandemic trends of the mental health burden in Denmark’s population on a nationwide level.
Functional and connectivity correlates associated with Parkinson’s disease psychosis: a systematic review
Authors: Pisani Sara , Gunasekera Brandon , Lu Yining , Vignando Miriam , Ffytche Dominic , Aarsland Dag , Chaudhuri K R , Ballard Clive , Lee Jee-Young , Kim Yu Kyeong , Velayudhan Latha , Bhattacharyya Sagnik 
Published: November 2024

Abstract
Neural underpinnings of Parkinson’s disease psychosis remain unclear to this day with relatively few studies and reviews available. Using a systematic review approach, here, we aimed to qualitatively synthesize evidence from studies investigating Parkinson’s psychosis-specific alterations in brain structure, function or chemistry using different neuroimaging modalities. PubMed, Web of Science and Embase databases were searched for functional MRI (task-based and resting state), diffusion tensor imaging, PET and single-photon emission computed tomography studies comparing Parkinson’s disease psychosis patients with Parkinson’s patients without psychosis. We report findings from 29 studies (514 Parkinson’s psychosis patients, mean age ± SD = 67.92 ± 4.37 years; 51.36% males; 853 Parkinson’s patients, mean age ± SD = 66.75 ± 4.19 years; 55.81% males). Qualitative synthesis revealed widespread patterns of altered brain function across task-based and resting-state functional MRI studies in Parkinson’s psychosis patients compared with Parkinson’s patients without psychosis. Similarly, white matter abnormalities were reported in parietal, temporal and occipital regions. Hypo-metabolism and reduced dopamine transporter binding were also reported whole brain and in sub-cortical areas. This suggests extensive alterations affecting regions involved in high-order visual processing and attentional networks.
Spinal cord evaluation in multiple sclerosis: clinical and radiological associations, present and future
Authors: Keegan B Mark , Absinta Martina , Cohen-Adad Julien , Flanagan Eoin P , Henry Roland G , Klawiter Eric C , Kolind Shannon , Krieger Stephen , Laule Cornelia , Lincoln John A , Messina Steven , Oh Jiwon , Papinutto Nico , Smith Seth Aaron , Traboulsee Anthony 
Published: November 2024

Abstract
Spinal cord disease is important in most people with multiple sclerosis, but assessment remains less emphasized in patient care, basic and clinical research and therapeutic trials. The North American Imaging in Multiple Sclerosis Spinal Cord Interest Group was formed to determine and present the contemporary landscape of multiple sclerosis spinal cord evaluation, further existing and advanced spinal cord imaging techniques, and foster collaborative work. Important themes arose: (i) multiple sclerosis spinal cord lesions (differential diagnosis, association with clinical course); (ii) spinal cord radiological–pathological associations; (iii) ‘critical’ spinal cord lesions; (iv) multiple sclerosis topographical model; (v) spinal cord atrophy; and (vi) automated and special imaging techniques. Distinguishing multiple sclerosis from other myelopathic aetiology is increasingly refined by imaging and serological studies. Post-mortem spinal cord findings and MRI pathological correlative studies demonstrate MRI’s high sensitivity in detecting microstructural demyelination and axonal loss. Spinal leptomeninges include immune inflammatory infiltrates, some in B-cell lymphoid-like structures. ‘Critical’ demyelinating lesions along spinal cord corticospinal tracts are anatomically consistent with and may be disproportionately associated with motor progression. Multiple sclerosis topographical model implicates the spinal cord as an area where threshold impairment associates with multiple sclerosis disability. Progressive spinal cord atrophy and ‘silent’ multiple sclerosis progression may be emerging as an important multiple sclerosis prognostic biomarker. Manual atrophy assessment is complicated by rater bias, while automation (e.g. Spinal Cord Toolbox), and artificial intelligence may reduce this. Collaborative research by the North American Imaging in Multiple Sclerosis and similar groups with experts combining distinct strengths is key to advancing assessment and treatment of people with multiple sclerosis spinal cord disease.
Glial fibrillary acidic protein in Alzheimer’s disease: a narrative review
Authors: Leipp Florine , Vialaret Jérôme , Mohaupt Pablo , Coppens Salomé , Jaffuel Aurore , Niehoff Ann-Christin , Lehmann Sylvain , Hirtz Christophe 
Published: November 2024

Abstract
Astrocytes are fundamental in neural functioning and homeostasis in the central nervous system. These cells respond to injuries and pathological conditions through astrogliosis, a reactive process associated with neurodegenerative diseases such as Alzheimer’s disease. This process is thought to begin in the early stages of these conditions. Glial fibrillary acidic protein (GFAP), a type III intermediate filament protein predominantly expressed in astrocytes, has emerged as a key biomarker for monitoring this response. During astrogliosis, GFAP is released into biofluids, making it a candidate for non-invasive diagnosis and tracking of neurodegenerative diseases. Growing evidence positions GFAP as a biomarker for Alzheimer’s disease with specificity and disease-correlation characteristics comparable to established clinical markers, such as Aβ peptides and phosphorylated tau protein. To improve diagnostic accuracy, particularly in the presence of confounders and comorbidities, incorporating a panel of biomarkers may be advantageous. This review will explore the potential of GFAP within such a panel, examining its role in early diagnosis, disease progression monitoring and its integration into clinical practice for Alzheimer’s disease management.
Feature attributions for water–solubility predictions obtained via artificial intelligence methods and chemists
Authors: Sadakane Teruhisa , Nakata Koki , Suda Kayo , Yokogawa Daisuke 
Published: November 2024

Abstract
The field of explainable artificial intelligence has garnered significant research interest. In particular, “feature attribution” in the field of chemistry has been focused upon. However, studies on comparisons of the relationship between artificial intelligence–based and human-based feature attributions when predicting the same outcome are scarce. Thus, this study aimed to investigate this relationship by comparing machine learning–based feature attributions (graph neural networks and integrated gradients) with those of chemists (Hansch–Fujita method) considering the case of predicting water–solubility. The artificial intelligence–based attributions were found to be similar to those of chemists despite their distinct origins.
Enhancing perceptual, attentional, and working memory demands through variable practice schedules: insights from high-density EEG multi-scale analyses
Authors: Cretton Alexandre , Schipper Kate , Hassan Mahmoud , Ruggeri Paolo , Barral Jérôme 
Published: November 2024

Abstract
Contextual interference (CI) enhances learning by practicing motor tasks in a random order rather than a blocked order. One hypothesis suggests that the benefits arise from enhanced early perceptual/attentional processes, while another posits that better learning is due to highly activated mnemonic processes. We used high-density electroencephalography in a multi-scale analysis approach, including topographic analyses, source estimations, and functional connectivity, to examine the intertwined dynamics of attentional and mnemonic processes within short time windows. We recorded scalp activity from 35 participants as they performed an aiming task at three different distances, under both random and blocked conditions using a crossover design. Our results showed that topographies associated with processes related to perception/attention (N1, P3a) and working memory (P3b) were more pronounced in the random condition. Source estimation analyses supported these findings, revealing greater involvement of the perceptual ventral pathway, anterior cingulate and parietal cortices, along with increased functional connectivity in ventral alpha and frontoparietal theta band networks during random practice. Our results suggest that CI is driven, in the random compared to the blocked condition, by enhanced specific processes such as perceptual, attentional, and working memory processes, as well as large-scale functional networks sustaining more general attentional and executive processes.
Changes in resting-state functional connectivity of large-scale brain networks in bulimia nervosa: evidence from causal analysis
Authors: Wang Jiani , Wang Xinghao , Wang Yiling , Li Weihua , Li Zhanjiang , Tang Lirong , Huang Xinyu , Grzegorzek Marcin , Chen Qian , Wang Zhenchang , Zhang Peng 
Published: November 2024

Abstract
Bulimia nervosa (BN) has been observationally linked to the functional connectivity (FC) of large-scale brain networks, but the biological mechanisms remain unclear. This study used two-sample Mendelian randomization (MR) with genetic variations as instrumental variables (IVs) to explore potential causal relationships between FC and BN. Summary data from genome-wide association studies (GWAS) involving 2,564 individuals were analyzed to identify genetically predicted BN. Functional magnetic resonance imaging parameters and materials were sourced from the UK Biobank. The variables underwent independent component analysis processing by the database to generate the final GWAS dataset. Various methods, including MR Pleiotropy RESidual Sum and Outlier, MR Egger, and weighted median, were employed to detect heterogeneity and pleiotropy, with inverse variance weighting serving as the principal estimation method (P &lt; 0.05). The FC imaging-derived phenotypes revealed that BN exerted a causal influence on the FC between large-scale networks, including the visual network, default mode network (DMN), frontoparietal network, somatosensory network (SSN), and ventral attention network. Additionally, BN had a causal impact on the within-network FC of both the DMN and SSN. The study provides evidence that BN leads to further changes in FC patterns within and between large-scale brain networks.
Causal relationship between cortical structural changes and onset of anxiety disorder: evidence from Mendelian randomization
Authors: Teng Fei , Wang Mengqi , Lu Zhangyu , Zhang Chunyu , Xiao Linglong , Chen ZhaoMing , Huang Mengshuang , Xie Linglin , Chen Zheyu , Wang Wei 
Published: November 2024

Abstract
Previous studies have reported a correlation between anxiety disorders and changes in brain structure, yet the specific alterations in brain region volumes remain unclear. This study aimed to infer the causal relationship between anxiety disorders and changes in brain structure volume through Mendelian Randomization analysis. We selected 63 cortical structure volumes from the GWAS database as exposure data and anxiety disorder data from the FinnGen and UK Biobank databases as outcomes. We found a significant correlation between atrophy in the Left precentral volume area (Odds Ratio [OR] = 0.935, 95% Confidence intervals [CI]: 0.891–0.981, P value, P = 0.007) and an increased risk of anxiety disorders. Additionally, changes identified in specific brain regions, such as atrophy in the Right rostral anterior cingulate area (OR = 0.993, 95% CI: 0.987–0.999, P = 0.025) and increased volume in the Left superior parietal area (OR = 1.001, 95% CI: 1.000–1.001, P = 0.028), may correlate with an increased risk of anxiety disorders. Furthermore, both phenotypes demonstrated directional consistency in their respective and overall meta-analyzed OR values pre- and post-merger, enhancing the reliability of the results. This study elucidates the causal relationship between anxiety disorders and specific brain structures, providing new insights for further research into psychiatric disorders.
Highly concentrated solution of lithium chloride in organic solvents with heteroditopic receptors
Authors: Kondo Shin-ichi , Mimuro Tsubasa , Yoshida Akihiro , Sugawara Reo , Hirasawa Manabu 
Published: November 2024

Abstract
The solubilization and selective extraction of lithium salts, in particular lithium chloride, in organic solvents have recently attracted attention due to the application in industry. A heteroditopic receptor 1b, which has ether oxygens and 2 urea moieties as cation and anion recognition sites, respectively, cooperatively associates with LiCl in organic solvents. The selective solid–liquid extraction of LiCl and LiBr was observed by 1H NMR in CDCl3 and MeCN-d3. It is possible to prepare highly concentrated solutions of 1b and LiCl in MeCN up to a concentration of 9.6 M, and these solutions exhibit properties similar to those of ionic liquids.
Global Trends in CD4 Count Measurement and Distribution at First Antiretroviral Treatment Initiation
Authors: de Waal Reneé , Wools-Kaloustian Kara , Brazier Ellen , Althoff Keri N , Jaquet Antoine , Duda Stephany N , Kumarasamy Nagalingeswaran , Savory Theodora , Byakwaga Helen , Murenzi Gad , Justice Amy , Ekouevi Didier K , Cesar Carina , Pasayan Mark K U , Thawani Agness , Kasozi Charles , Babakazo Pelagie , Karris Maile , Messou Eugene , Cortes Claudia P , Kunzekwenyika Cordelia , Choi Jun Yong , Owarwo Noela C , Niyongabo Annabelle , Marconi Vincent C , Ezechi Oliver , Castilho Jessica L , Petoumenos Kathy , Johnson Leigh F , Ford Nathan , Kassanjee Reshma 
Published: November 2024

Abstract

Background
While people with human immunodeficiency virus (PWH) start antiretroviral treatment (ART) regardless of CD4 count, CD4 measurement remains crucial for detecting advanced human immunodeficiency virus (HIV) disease and evaluating ART programs. We explored CD4 measurement (proportion of PWH with a CD4 result available) and prevalence of CD4 &lt;200 cells/µL (hereafter “CD4 &lt;200”) at ART initiation within the International epidemiology Databases to Evaluate AIDS (IeDEA) global collaboration.

Methods
We included PWH at participating ART programs who first initiated ART at age 15–80 years during 2005–2019. We described proportions of PWH with a CD4 result (measured within 6 months before to 2 weeks after ART initiation) and, among those with a CD4 result, with CD4 &lt;200, by year of ART initiation and region.

Results
We included 1 355 104 PWH from 42 countries in 7 regions; 63% were female. The median (interquartile range) age at ART initiation was 37 (3144) years in males and 32 (26–39) years in females. CD4 measurement initially increased, or remained stable over time until around 2013, but then declined to low levels in some regions (Southern Africa, except South Africa: from 54% to 13%; East Africa: 85% to 31%; Central Africa: 72% to 20%; West Africa: 91% to 53%; and Latin America: 87% to 56%). Prevalence of CD4 &lt;200 declined over time in all regions, but plateaued after 2015 at ≥30%.

Conclusions
CD4 measurement has declined sharply in recent years, especially in sub-Saharan Africa. Among those with a CD4 measurement, the prevalence of CD4 &lt;200 remains concerningly high. Scaling up CD4 testing and securing adequate funding are urgent priorities.
Epigenetic biomarker for preeclampsia-associated preterm birth and potential preventative medicine
Authors: Nilsson Eric E , Winchester Paul , Proctor Cathy , Beck Daniel , Skinner Michael K 
Published: November 2024

Abstract
Preterm birth (PTB) has dramatically increased within the population (i.e. &gt;10%) and preeclampsia is a significant sub-category of PTB. Currently, there are no practical clinical parameters or biomarkers which predict preeclampsia induced PTB. The current study investigates the potential use of epigenetic (DNA methylation) alterations as a maternal preeclampsia biomarker. Non-preeclampsia term births were compared to preeclampsia PTBs to identify DNA methylation differences (i.e. potential epigenetic biomarker). Maternal buccal cell cheek swabs were used as a marker cell for systemic epigenetic alterations in the individuals, which are primarily due to environmentally induced early life or previous generations impacts, and minimally impacted or associated with the disease etiology or gestation variables. A total of 389 differential DNA methylation regions (DMRs) were identified and associated with the presence of preeclampsia. The DMRs were genome-wide and were predominantly low CpG density (&lt;2 CpG/100 bp). In comparison with a previous PTB buccal cell epigenetic biomarker there was a 15% (60 DMR) overlap, indicating that the majority of the DMRs are unique for preeclampsia. Few previously identified preeclampsia genes have been identified, however, the DMRs had gene associations in the P13 K-Akt signaling pathway and metabolic gene family, such as phospholipid signaling pathway. Preliminary validation of the DMR use as a potential maternal biomarker used a cross-validation analysis on the samples and provided 78% accuracy. Although prospective expanded clinical trials in first trimester pregnancies and clinical comparisons are required, the current study provides the potential proof of concept a preeclampsia epigenetic biomarker may exist. The availability of a preeclampsia PTB maternal susceptibility biomarker may facilitate clinical management and allow preventative medicine approaches to identify and treat the preeclampsia condition prior to its occurrence.
Short-term Frailty Index Fluctuations in Older Adults: Noise or Signal?
Authors: Stolz Erwin , Schultz Anna , Hoogendijk Emiel O , Theou Olga , Rockwood Kenneth 
Published: November 2024

Abstract

Background
Reversible short-term fluctuations in the frailty index (FI) are often thought of as representing only noise or error. Here, we assess (i) the size and source of short-term FI fluctuations, (ii) variation across sociodemographic characteristics, (iii) association with chronic diseases, (iv) correlation with age, frailty level, frailty change, and mortality, and (v) whether fluctuations reflect discrete health transitions.

Methods
Nationwide, biweekly longitudinal data from 426 community-dwelling older adults (70+) were collected in the FRequent health Assessment In Later life (FRAIL70+) study using a measurement burst design (5 122 repeated observations, median of 13 repeated observations per person). We calculated the intraindividual standard deviation of the FI and used location-scale mixed regression models.

Results
Mean intraindividual standard deviation was 0.04 (standard deviation = .03). Fluctuations were driven foremost by cognitive problems, somatic symptoms, and limitations in instrumental and mobility-related activities of daily living. Short-term fluctuations correlated with higher FI levels (r = 0.62), 1-year FI change (r = 0.26), and older age (+3% per year). Older adults who took to bed due to a health problem (+50%), those who had an overnight hospital stay (+50%), and those who died during follow-up (+44%) exhibited more FI fluctuations.

Conclusions
Short-term FI fluctuations were neither small nor random. Instead, as older adults become frailer, their measured health also becomes more unstable; hence, short-term fluctuations in overall health status can be seen as a concomitant phenomenon of the aging process. Researchers and clinicians should be aware of the existence of reversible fluctuations in the FI over weeks and months and its consequences for frailty monitoring.