bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of localization and registration accuracy on estimates of deep brain stimulation electrode position in stereotactic space
Authors: Abbass Mohamad , Gilmore Greydon , Santyr Brendan , Chalil Alan , Taha Alaa , Jog Mandar , MacDougall Keith , Parrent Andrew G. , Peters Terry M. , Lau Jonathan C. 
Published: March 2024

AbstractEffects of deep brain stimulation (DBS) depend on millimetric accuracy and are commonly studied across populations by registering patient scans to a stereotactic space. Multiple factors contribute to estimates of electrode position, but the millimetric contributions of these factors remains poorly quantified. We previously validated 32 anatomical fiducials (AFIDs) to measure AFID registration error (AFRE), which can capture focal misregistration not observed using volume-based methods. To this end, we used the AFIDs framework to examine the effects of misregistration on electrode position in stereotactic space, leveraging a retrospective series of patients who underwent subthalamic nucleus DBS. Raters independently localized DBS electrodes and AFIDs on patient scans, which were non-linearly registered to a common stereotactic (MNI) space. AFIDs provided intuitive measures of registration accuracy, with AFREs ranging from 1.49 mm to 6.85 mm across brain regions. Subcortical AFIDs in proximity to the DBS target had AFREs that spatially covaried, suggesting consistent spatial patterns of misregistration to stereotactic space. These identified spatial patterns explained 28% of the variance in electrode position along the axis of maximum variance, corresponding to a median of 0.64 mm (range of 0.05 to 2.05 mm). To our knowledge, these represent the first millimetric estimates of registration accuracy in DBS, allowing uncoupling of registration-related factors from other sources of variance in electrode position. Furthermore, they can be employed for estimating registration-related variance in population studies, for quality control, and to provide a basis for comparison as well as optimization of registration parameters and software.
Conformal prediction enables disease course prediction and allows individualized diagnostic uncertainty in multiple sclerosis
Authors: Sreenivasan Akshai Parakkal , Vaivade Aina , Noui Yassine , Khoonsari Payam Emami , Burman Joachim , Spjuth Ola , Kultima Kim 
Published: March 2024

AbstractAccurate assessment of progression and disease course in multiple sclerosis (MS) is vital for timely and appropriate clinical intervention. The transition from relapsing-remitting MS (RRMS) to secondary progressive MS (SPMS) is gradual and diagnosed retrospectively with a typical delay of three years. To address this diagnostic delay, we developed a predictive model that is able to distinguish between RRMS and SPMS with high accuracy, trained on data from electronic health records collected at routine hospital visits obtained from the Swedish MS Registry containing 22,748 patients with 197,227 hospital visits. To be useful within a clinical setting, we applied conformal prediction to deliver valid measures of uncertainty in predictions at the level of the individual patient. We showed that the model was theoretically and empirically valid, having the highest efficiency at a 92% confidence level, and demonstrated on an external test set that it enables effective prediction of the clinical course of a patient with individual confidence measures. We applied the model to a set of patients who transitioned from RRMS to SPMS during the cohort timeframe and showed that we can accurately predict when patients transition from RRMS to SPMS. We also identified new patients who, with high probability, are in the transition phase from RRMS to SPMS but have not yet received a clinical diagnosis. We conclude that our methodology can assist in monitoring MS disease progression and proactively identify patients undergoing transition to SPMS. An anonymized, publically accessible version of the model is available athttps://msp-tracker.serve.scilifelab.se/.
Protocol For Human Evaluation of Artificial Intelligence Chatbots in Clinical Consultations
Authors: Chiu Edwin Kwan-Yeung , Chung Tom Wai-Hin 
Published: March 2024

AbstractBackgroundGenerative artificial intelligence (AI) technology has the revolutionary potentials to augment clinical practice and telemedicine. The nuances of real-life patient scenarios and complex clinical environments demand a rigorous, evidence-based approach to ensure safe and effective application.MethodsWe present a protocol for the systematic evaluation of generative AI large language models (LLMs) as chatbots within the context of clinical microbiology and infectious disease consultations. We aim to critically assess the clinical accuracy, comprehensiveness, coherence, and safety of recommendations produced by leading generative AI models, including Claude 2, Gemini Pro, GPT-4.0, and a GPT-4.0-based custom AI chatbot.DiscussionA standardised healthcare-specific prompt template is employed to elicit clinically impactful AI responses. Generated responses will be graded by a panel of human evaluators, encompassing a wide spectrum of domain expertise in clinical microbiology and virology and clinical infectious diseases. Evaluations are performed using a 5-point Likert scale across four clinical domains: factual consistency, comprehensiveness, coherence, and medical harmfulness. Our study will offer insights into the feasibility, limitations, and boundaries of generative AI in healthcare, providing guidance for future research and clinical implementation. Ethical guidelines and safety guardrails should be developed to uphold patient safety and clinical standards.
Pattern and mechanisms of atrophy progression in individuals with a family history of Alzheimer’s disease: a comparative study
Authors: Tremblay Christina , Rahayel Shady , Pastor-Bernier Alexandre , St-Onge Frédéric , Vo Andrew , Rheault François , Daneault Véronique , Morys Filip , Rajah Natasha , Villeneuve Sylvia , Dagher Alain ,   the PREVENT-AD Research Group,   Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Published: March 2024

AbstractAlzheimer’s disease (AD) includes a long period of presymptomatic brain changes. Different risk factors are associated with AD development, including having a family history of AD (FHAD). The Braak scheme suggests that tau pathology, in synergy with amyloid-beta (Aβ), spreads along structural connections in AD, eventually leading to atrophy. Studying the pathways in which atrophy spreads early on, as well as the factors underpinning this pathway, is crucial for improving diagnostic accuracy and early interventions. However, the pattern of atrophy progression in people with a FHAD and the biological factors associated with this progression remain unclear. Here we used structural MRI from three databases (ADNI, PREVENT-AD and Montreal Adult Lifespan Study) to map the atrophy progression in FHAD and AD and assess the constraining effects of structural connectivity on atrophy progression. Cross-sectional and longitudinal data up to 4 years were used to perform atrophy progression analysis in FHAD and AD compared to controls. Positron emission tomography (PET) radiotracers were also used to quantify the distribution of tau and Aβ proteins at baseline. We first derived cortical atrophy progression maps using deformation-based morphometry from 153 FHAD, 156 AD, and 116 controls with similar age, education, and sex at baseline. We next examined the spatial relationship between atrophy progression and spatial patterns of tau and Aβ deposition, structural connectivity, and neurotransmitter receptor and transporter distributions. Our results show that there were similar patterns of atrophy progression in FHAD and AD, notably in the cingulate, temporal and parietal cortices, with more widespread and severe atrophy in AD. Both tau and Aβ pathology tended to accumulate in regions that were structurally connected in FHAD and AD. The pattern of atrophy and its progression also aligned with existing structural connectivity in FHAD. In AD, our findings suggest that atrophy progression results from propagating pathology that occurred much earlier, on an intact connectome. Moreover, a relationship was found between the serotonin 5-HT6 receptors spatial distribution and atrophy progression in AD, supporting an important role of these receptors in neurodegeneration. The current study demonstrates that regions showing atrophy progression in FHAD and AD present with specific connectivity and cellular characteristics, uncovering certain of the mechanisms involved in preclinical and clinical neurodegeneration.
Body composition and checkpoint inhibitor treatment outcomes in advanced melanoma: a multicenter cohort study
Authors: Maat L.S. Ter , Van Duin I.A.J. , Verheijden R.J. , Moeskops P. , Verhoeff J.J.C. , Elias S.G. , van Amsterdam W.A.C. , Burgers F.H. , Van den Berkmortel F.W.P.J. , Boers-Sonderen M.J. , Boomsma M.F. , De Groot J.W. , Haanen J.B.A.G. , Hospers G.A.P. , Piersma D. , Vreugdenhil G. , Westgeest H.M. , Kapiteijn E. , Labots M. , Veldhuis W.B. , Van Diest P.J. , De Jong P.A. , Pluim J.P.W. , Leiner T. , Veta M. , Suijkerbuijk K.P.M. 
Published: March 2024

AbstractIntroductionThe association of body composition with checkpoint inhibitor outcomes in melanoma is a matter of ongoing debate. In this study, we aim to add to previous evidence by investigating body mass index (BMI) alongside CT derived body composition metrics in the largest cohort to date.MethodPatients treated with first-line anti-PD1 ± anti-CTLA4 for advanced melanoma were retrospectively identified from 11 melanoma reference centers in The Netherlands. Age, sex, Eastern Cooperative Oncology Group performance status, serum lactate dehydrogenase, presence of brain and liver metastases, number of affected organs and BMI at baseline were extracted from electronic patient files. From baseline CT scans, five body composition metrics were automatically extracted: skeletal muscle index, skeletal muscle density, skeletal muscle gauge, subcutaneous adipose tissue index and visceral adipose tissue index. All predictors were correlated in uni- and multivariable analysis to progression-free, overall and melanoma-specific survival (PFS, OS and MSS) using Cox proportional hazards models.ResultsA total of 1471 eligible patients were included. Median PFS and OS were 8.8 and 34.8 months, respectively. A significantly worse PFS was observed in underweight patients (multivariable HR=1.87, 95% CI 1.14–3.07). Furthermore, better OS was observed in patients with higher skeletal muscle density (multivariable HR=0.91, 95% CI 0.83-0.99) and gauge (multivariable HR=0.88, 95% CI 0.84-0.996), and a worse OS with higher visceral adipose tissue index (multivariable HR=1.13, 95% CI 1.04-1.22). No association with survival outcomes was found for overweightness or obesity and survival outcomes, or for subcutaneous adipose tissue.DiscussionOur findings suggest that underweight BMI is associated with worse PFS, whereas higher skeletal muscle density and lower visceral adipose tissue index were associated with better OS. These associations were independent of previously identified predictors, including sex, age, performance status and extent of disease. No significant association between higher BMI and survival outcomes was observed.
Lifestyle interventions for dementia prevention in Low- and Middle-Income Countries: A systematic review
Authors: Espinoza Jeraldo Rosario Isabel , Zabihi Sedigheh , Miranda-Castillo Claudia , Marshall Charles R , Cooper Claudia 
Published: March 2024

AbstractBy 2050, two-thirds of people with dementia will live in Low- and Middle-Income Countries (LMICs). Efforts to adapt and test multi-modal prevention interventions focusing on lifestyle changes for people at risk of dementia are being developed predominantly in higher income countries, for people with and without cognitive symptoms. However, there is evidence that needs may differ between these groups. We systematically reviewed Randomized Controlled Trials (RCTs) evaluating non-pharmacological interventions in individuals with Mild Cognitive Impairment (MCI) and Subjective Cognitive Decline (SCC) in LMICs. We analysed study quality using the Mixed Methods Assessment Tool (MMAT), meta-analysed and synthesized evidence. We included 25 RCTs, from six countries (most in China, n=17), involving 1304 participants. Across the 15 studies for which there was sufficient data to meta-analyse, we found significant positive effects on cognitive outcomes favouring interventions [1.49 (standardised mean difference, 95% Confidence Interval= 1.06-1.93)]. There was significant publication bias. Using an a priori standard framework, we classified interventions into exercise, multidomain, and arts/creative expression. Group exercise [1.67, 1.24-2.11, n=8]. and multidomain [1.22, 0.22-2.21, n=5] had replicated evidence of effectiveness. There was insufficient data to meta-analyse the creative arts category. We identified one high quality, multi-modal intervention, which combined Chinese mind-body exercises and health education, reporting a positive outcome. The first robust dementia prevention trials are underway in LMICs, evaluating effectiveness of models developed in higher income countries. We propose greater consideration and investment in development of interventions that account for specific LMIC contexts from the outset, so they are acceptable and used by local services.HighlightsThere was evidence that group exercise and multimodal interventions were effective for people with memory concerns in LMICs.We identified publication bias in meta-analyses; the open science agenda is critical to improving care in LMICs and reducing global inequalities.Most included studies were conducted in China, reflecting a need for high-quality evidence from underrepresented regions, including Africa and Latin America.We propose greater investment in developing interventions that account for specific LMIC contexts from the outset, so they are acceptable and used by local services.
The role of dopaminergic medication, lipid, and endocannabinoid pathway alterations in idiopathic andPRKN/PINK1-mediated Parkinson’s disease – a large-scale targeted metabolomics study
Authors: Balck Alexander , Borsche Max , Campbell Philip , Luo Xi , Harvey John , Brückmann Theresa , Ludwig Charlotte , Harms Amy , Lohmann Katja , Morris Huw R , Schapira Anthony H , Hankemeier Thomas , Fleming Ronan , Szymczak Silke , Klein Christine 
Published: March 2024

AbstractAlterations in many metabolites and biochemical pathways have been described in Parkinson’s Disease (PD). However, only a small fraction of these have been replicated in independent studies. As almost every PD patient is treated with dopaminergic medication, it is challenging to discriminate between disease- and drug-related effects, especially in relation to dopamine metabolism. We conducted a large-scale metabolomic study in plasma from 140 idiopathic (IPD), 19PRKN/PINK1-linked PD patients, and 64 healthy controls to disentangle disease-related metabolite alterations from drug-related effects. We distinguished between L-Dopa and non-L-Dopa treated PD patients to uncover nuanced metabolic changes associated with different therapies. We demonstrate that L-Dopa treatment uniquely influences the metabolome, with methyldopa and methoxytyramine, both L-Dopa breakdown products, elevated in L-Dopa-treated IPD andPRKN/PINK-linked PD patients. These alterations were not seen in untreated IPD patients and those on agonist treatment only. Polyamine metabolism alterations, notably elevation of putrescine and ornithine, were partly caused by L-Dopa treatment but also found in non-L-Dopa treated PD patients. In non-L-Dopa-treated patients, endocannabinoid metabolites were lowered and associated with disease duration. We observed lipid metabolism alterations, highlighting potential crosslinks with alpha-synuclein and providing insights into pathophysiological mechanisms. AllPRKN/PINK1-linked PD patients received L-Dopa treatment. However, our data potentially support the well-established role of oxidative damage in these subtypes of PD. In conclusion, our study emphasizes the significant impact of L-Dopa treatment on the metabolome, which might be of relevance not only for metabolomics studies but also for PD biomarker research in general. Finally, our study highlights potential biomarkers and pathways crucial for the understanding disease mechanisms of PD.
Continuous Associations Between Remote Self-Administered Cognitive Measures and Imaging Biomarkers of Alzheimer’s Disease
Authors: Boots Elizabeth A. , Frank Ryan D. , Fan Winnie Z. , Christianson Teresa J. , Kremers Walter K. , Stricker John L. , Machulda Mary M. , Fields Julie A. , Hassenstab Jason , Graff-Radford Jonathan , Vemuri Prashanthi , Jack Clifford R. , Knopman David S. , Petersen Ronald C. , Stricker Nikki H. 
Published: March 2024

AbstractBackgroundEasily accessible and self-administered cognitive assessments that can aid early detection for Alzheimer’s disease (AD) dementia risk are critical for timely intervention.Objectives/DesignThis cross-sectional study investigated continuous associations between Mayo Test Drive (MTD) – a remote, self-administered, multi-device compatible, web-based cognitive assessment – and AD-related imaging biomarkers.Participants/Setting684 adults from the Mayo Clinic Study of Aging and Mayo Clinic Alzheimer’s Disease Research Center participated (age=70.4±11.2, 49.7% female). Participants were predominantly cognitively unimpaired (CU; 94.0%).MeasurementsParticipants completed (1) brain amyloid and tau PET scans and MRI scans for hippocampal volume (HV) and white matter hyperintensities (WMH); (2) MTD remotely, consisting of the Stricker Learning Span and Symbols Test which combine into an MTD composite; and (3) in-person neuropsychological assessment including measures to obtain Mayo Preclinical Alzheimer’s disease Cognitive Composite (Mayo-PACC) and Global-z. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers and scores from remote and in-person cognitive measures.ResultsLower performances on MTD were associated with greater amyloid, entorhinal tau, and global tau PET burden, lower HV, and higher WMH. Mayo-PACC and Global-z were associated with all imaging biomarkers except global tau PET burden. MCI/Dementia participants showed lower performance on all MTD measures compared to CU with large effect sizes (Hedge’s g’s=1.65-2.02), with similar findings for CU versus MCI only (Hedge’s g’s=1.46-1.83).ConclusionsMTD is associated with continuous measures of AD-related imaging biomarkers, demonstrating ability to detect subtle cognitive change using a brief, remote assessment in predominantly CU individuals and criterion validity for MTD.
Osteoarthritis across Joint Sites in the Million Veteran Program: Insights from Electronic Health Records and Military Service History
Authors: Lavin Kaleen M , Richman Joshua S , McDonald Merry-Lynn N , Singh Jasvinder A. 
Published: March 2024

ABSTRACTObjectiveTo characterize the relationship between OA frequency and a host of demographic characteristics, comorbidities, military service history, and physical health variables in a veteran population.MethodsWe investigated the Million Veteran Program (MVP) cohort to outline frequency of OA across six joint sites (knee, spine, hip, hand, finger, thumb) in veterans with respect to demographics (age, sex, race/ethnicity, etc.), military service data, and detailed electronic health records profiling OA and other comorbidities. The large veteran contingent provided the unique opportunity to investigate the association of OA with prior service across military branches and war eras.ResultsWe validated previous reports of sex- and age-dependent differences in OA frequency, and we identified that generalized OA was associated with a higher frequency of sixteen Deyo-Charlson comorbidities. These associations generally persisted within each isolated joint site-specific OA. Depending on military branch, prior military engagement was differentially associated with frequency of OA. Prior Army and Navy service were associated with higher and lower risk, respectively of OA across all joint sites. However, multivariable-adjusted models adjusting for a range of covariates (including age, sex, and ancestry) reversed the apparent protective effect of prior Navy serviceConclusionThese findings highlight the breadth of factors associated with OA in the MVP veteran population and suggest that physical status may be a modifiable risk factor for OA. This work may contribute to designing strategies to optimize appropriate detection, intervention, treatment, and even rehabilitation strategies for OA in veterans and the general population.
Digital Nanofluidic Chip for Simple and Highly Quantitative Detection of HPV Target
Authors: Liu Li , Dollery Stephen J. , Tobin Gregory J. , Lu Guoyu , Du Ke 
Published: March 2024

AbstractQuantitative analysis of human papillomavirus (HPV)-infected cervical cancer is essential for early diagnosis and timely treatment of cervical cancer. Here, we introduce a novel energy transfer-labeled oligonucleotide probe to enhance the loop-mediated isothermal amplification (LAMP) assay for highly sensitive and specific detection of HPV 16. Conducted as a single-step assay within a digital nanofluidic chip featuring numerous reaction reservoirs, our method facilitates target amplification under isothermal conditions. Targeting an HPV 16 gene, our chip demonstrates the capability to detect HPV DNA at concentrations as low as 1 fM, spanning a dynamic range of five orders of magnitude. Importantly, our digital chip allows for highly quantitative detection of target genes at low concentrations, with the correlation between target concentration and the number of microwells exhibiting fluorescence signals. Furthermore, we have developed a computer vision method for automated and 100% accurate quantification of target concentrations. This research holds promising applications in clinical diagnosis and is poised for seamless integration into both hospital and point-of-care settings.