bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Antipsychotic Drug Doses for BPSD: A Transfer Learning Approach Using Neuroimaging Data
Authors: Yue Ling , Hong Bo , Tao Tianli , Li Xia , Xiao Shifu , Zhang Han 
Published: January 2025

AbstractBackgroundAbout 50‐90% people with dementia would develop behavioral disturbances, namely, behavioral and psychological symptoms of dementia (BPSD). Antipsychotic medications are widely used to control severe BPSD symptoms which suffers serious safety risks. It is challenge for individualized precise prediction of antipsychotic drug doses. Neuroimaging, particularly MRI, reveals brain structure associated with aging, cognitive decline, and psychiatric symptoms, making it a potential tool for predicting the drug doses. This study employs transfer learning to predict drug dose and offer neuroanatomical interpretation of BPSD from the perspective of deep learning.MethodWe employed a two‐step process to train our model (Figure 1). Initially, a large dataset from the Chinese Brain Molecular and Functional Mapping (CBMFM) project (n=646, 334 females and 312males, age 18‐82) was used to pretrain the model with a brain age prediction task. Subsequently, the pretrained model was fine‐tuned for drug dose prediction from the Alzheimer's Disease and Related Disorders Center in Shanghai Jiao Tong University (ADRDC) dataset (83 BPSD patients, 27 males and 56 females, age 55‐80). Finally, we utilized gradient‐weighted class activation mapping to generate attention maps and conducted statistical analyses on the attention maps to identify critical brain regions for drug dose prediction. To determine the individual usage of different antipsychotic drugs, the concept of defined daily dose (DDD) was used. The DDD, which individualized control the BPSD, was calculated, ranging from 0 to 1.5 mg/day, serving as the label for fine‐tuning.ResultOur pretrained Cas‐ResNet exhibited enhanced performance with fewer training epochs, achieving a competitive Pearson correlation of 0.59 between estimated and real DDD (Figure 2). Through feature interpretability analysis, we identified five significant brain regions crucial for BPSD drug dose prediction, mainly located in the temporal lobe, including the parahippocampal area and the striatum (putamen and caudate)(Figure 3). These findings indicate that the antipsychotic dosage to control the BPSD is linked to brain structural alterations, involving both dementia‐related and emotion‐regulating areas.ConclusionFor the first time, we showed a promising result of using a lightweight deep learning model to predict drug dose prescribed for controlling BPSD. The work promotes the discussion toward appropriate use of antipsychotics in patients with dementia.
YOLOv5‐based Detection and Classification of Early and Late Mild Cognitive Impairment through Corpus Callosum Analysis
Authors: Kancharla Vamshi Krishna , Sinha Neelam 
Published: January 2025

AbstractBackgroundAlzheimer’s disease is a progressive neurodegenerative disorder that mainly affects the brain resulting gradual decline in a cognitive function, memory impairment, alterations in behavior, potentially resulting in the inability to engage in a conversation and react to the surroundings. Corpus callosum (CC) is the principal white fabric matter present in the center of the brain that connects the left and right cerebral hemispheres. Neurodegenerative diseases can impact the size and structure of the CC, leading to its atrophy and dysfunction. This study aims to detect the CC in a given Structural MRI and classify Early Mild Cognitive Impairment (EMCI) vs. Late Mild Cognitive Impairment (LMCI). This study introduces the prospect of utilizing a YOLOv5‐based framework for CC detection, aiming to distinguish between individuals with EMCI and LMCI. In addition, we have also interpreted our results using Eigen CAM.MethodIn this study, we proposed a Fine‐tuned Yolov5 based object detection model for detecting CC and classifying EMCI vs LMCI. Unlike previous studies that focused solely on CC (texture analysis) for detecting MCI, our method considers both CC and the surrounding context for better EMCI vs LMCI classification. In our approach, we used MRI slices along with the corpus callosum area, enclosed in a bounding box tightly fitted to the CC coordinates. The YOLOv5 model consists of three parts: the backbone extracts features, the neck combines features at different scales, and the head makes final predictions. In this case, the object of interest for the model is the CC to classify EMCI vs LMCI.ResultThe dataset used in this study was obtained from ADNI and consists of total 100 subjects, evenly distributed between EMCI vs LCMI. The dataset was partitioned into 80% for training and 20% for testing. We achieved 97% accuracy on test dataset.ConclusionThis study demonstrates YOLOv5’s efficiency in CC detection for EMCI and LMCI classification. The classification results are further interpreted using Eigen CAM. In future Fine‐tunning the model parameters and exploring other CAM varients can improve the results.
Possibilities of Transcatheter Intracerebral Laser Photobiomodulation Therapy in Patients with Dementia in the Treatment of Various Microcirculatory Cerebral Lesions
Authors: Maksimovich Ivan V 
Published: January 2025

AbstractBackgroundMost cerebrovascular lesions are aggravated by dementia. This study examines the possibility of reducing dementia by stimulating cerebral angiogenesis and neurogenesis using Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) in patients with Alzheimer’s disease (AD), distal cerebral atherosclerosis, Binswanger’s disease (BD), and vascular parkinsonism (VP).MethodsThe study included 404 patients with dementia, aged 29‐81 (mean age 78).Examination: assessment of CDR, TDR, MMSE, cerebral MRI, MRA, CT, MSCTA, scintigraphy (SG), rheoencephalography (REG), cerebral multi‐gated angiography (MUGA).48 (11.88%) patients suffered from AD. According to dementia severity, patients were divided into: preclinical stage (TDR‐0) ‐ 4, mild stage (TDR‐1) ‐ 16, moderately severe stage (TDR‐2) ‐ 21, severe stage (TDR‐3) ‐ 7 patients.356 (88.12%) patients suffered from diseases such as distal cerebral atherosclerosis ‐ 302 (84.83%), BD ‐ 17 (4.78%), VP ‐ 37 (10.39%) people. According to dementia severity, patients were divided into: unnoticed dementia ‐ 21, dementia at level (CDR‐1) ‐ 312, (CDR‐2) ‐ 23 people.All patients underwent Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT).ResultsAll 48 (100%) AD patients showed improvement in cerebral microcirculation and 10‐20% increase in cerebral temporal lobes volume, which indicates the development of cerebral angiogenesis and neurogenesis as well as tissue regeneration. The process was accompanied by dementia level decrease and cognitive functions restoration. Consequently, patients were transferred to a milder TDR group. Depending on the initial dementia severity, the resulting positive effect is observed for 2‐12 years.All patients with distal cerebral atherosclerosis 302 (100%), BD 17 (100%) and VP 27 (100%) after Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) showed improved cerebral microcirculation, decreased cerebral involutional changes, which indicates the development of angiogenesis, neurogenesis, and tissue regeneration. This led to a long‐term (over 10 years) decrease in dementia level and cognitive functions restoration.ConclusionsDespite the differences in AD etiology, distal cerebral atherosclerosis, BD and VP, Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) is an effective method for stimulating angiogenesis and neurogenesis. It leads to improved cerebral blood supply and restoration of tissue structures, dementia decrease, and mental and cognitive functions improvement. The resulting effect lasts for a long time.
Bidirectional association between gait speed and cognition in community‐dwelling non‐demented older adults: A eight‐year longitudinal study
Authors: Su Ying‐Hao , Chen Jen‐Hau , Chen Yen‐Ching , Chiou Jeng‐Min , Shiu Chenghsi 
Published: January 2025

AbstractBackgroundSlow gait speed and poor cognitions share numerous risk factors, including age, physical activities, chronic inflammation, education, metabolic abnormality, and the presence of multimorbidity. However, the causal relationship between gait and cognitions remains controversial. This study aimed to explore the reciprocal relationship of gait speed with global and domain‐specific cognition in non‐demented older adults.MethodThis study used data from four waves of Taiwan Initiative for Geriatric Epidemiological Research (TIGER, 2013‐2021) with biennial assessments of casual walking speed and cognitions. Global cognition, memory, executive function, verbal fluency, and attention were assessed using Montreal Cognitive Assessment‐Taiwanese version (MoCA‐T), immediate and delayed recall, trail making test part‐A and part‐B (TMTA and TMTB), categorical naming task, and forward and backward digit span test, respectively. A cross‐lagged panel model (CLPM) and a linear mixed model were both used to investigate the bidirectional association between gait speed and cognitive function. Covariates included baseline age, sex, body mass index physical activities, higher education, physical activities, multimorbidity, smoking, Apolipoprotein E (APOE) ϵ4 status, family income, and marital status.ResultA total of 459 adults with a mean age of 74.5 (standard deviation 5.2) were included, and 239 participants (52%) were female. After adjustments for potential confounders, faster earlier gait speed was associated with better subsequent global cognition (MoCA‐T: β=.28, 95% confidence interval [CI]=.014‐.55), memory performance (immediate and delayed recall: β=.10, 95% CI=.04‐.17; β=.09, 95% CI=.02‐.17), verbal fluency (β=.09, 95% CI=.007‐.18), and executive function (TMTA: β=.15, 95% CI=.047‐.26). Similarly, better earlier cognitions of MoCA‐T (β=.08, 95% CI=.019‐.15), immediate and delayed recall (β=.09, 95% CI=.00‐.17; β=.11, 95% CI=.033‐.19), verbal fluency (β=.08, 95% CI=.003‐.16), and executive function (TMTA: β=.17, 95% CI=.086‐.26) were associated with faster subsequent gait speed. The results of linear mixed models were consistent with findings from CLPM analyses.ConclusionWe found reciprocal associations of gait speed with global cognition, memory, executive function, and verbal fluency. Early screening of gait speed and cognitive function helps identify individuals at risk and supports the maintenance of normal cognition and physical performance.
Neuroimaging Biomarkers in Neuropsychiatric Symptom Clusters
Authors: Kapustin Daniel , Rashidi‐Ranjbar Neda , Wang Wei , Binns Malcolm , McLaughlin Paula M , Abrahao Agessandro , Grimes David A. , Lang Anthony E , Marras Connie , Masellis Mario , Orange Joseph B , Rajji Tarek K. , Roberts Angela C , Saposnik Gustavo , Swartz Richard H , Tang‐Wai David F. , Tartaglia Carmela , Troyer Angela , Zinman Lorne , Fischer Corinne E. , Kumar Sanjeev 
Published: January 2025

AbstractBackgroundNeuropsychiatric symptoms (NPS) constitute a major challenge for patients with Alzheimer’s disease (AD). We have recently demonstrated that in AD, overall NPS burden is significantly associated with patient function. However, few studies have examined the relationship between specific symptom clusters with neurological biomarkers. Therefore, we identified NPS clusters in AD and explored their association with structural neuroimaging markers.MethodParticipants with AD (N = 111) were included from the Ontario Neurodegenerative Disease Research Initiative (ONDRI). NPS were assessed using the neuropsychiatric inventory questionnaire (NPI‐Q), and symptom clusters were identified through exploratory factor analysis. The Semi‐Automatic Brain Region Extraction (SABRE) pipeline was used to compute regional cortical thickness and subcortical volumes using participant MRI data. We then evaluated correlations between symptom clusters with subcortical volumes and regional cortical thickness.ResultFactor analysis identified four symptom clusters explaining 62% of the variance. These were labeled as “behavioral” (disinhibition, irritability, motor disturbance, and agitation), “psychotic” (hallucinations, delusions, and euphoria), “neurovegetative” (apathy and appetite), and “affective” (depression, anxiety, nighttime behavior) clusters.The psychotic cluster was associated with increased cortical thickness in bilateral frontal regions, the left inferior parietal lobe (r=0.23, p=0.02), and with left anterior cingulate volumes (r=0.21, p=0.03). The neurovegetative cluster was associated with reductions in volume among bilateral frontal and right‐sided temporal and parietal regions. The affective cluster was associated with increased left anterior cingulate volume (r=0.21, p=0.03).ConclusionNPS symptom clusters in AD separate into behavioral, psychotic, neurovegetative, and affective dimensions. These symptom groups demonstrate unique associations with neuroimaging markers.
Clinician perspectives on successes and challenges in engaging care partners
Authors: Chertkow Howard 
Published: January 2025

AbstractInvolvement of caregivers in dementia research is an admirable goal. Involvement of caregivers in care planning for patients and people living with dementia, is essential to good medicine. However, it is important to assess and realistically consider areas where researchers and caregivers, and physicians and caregivers, may disagree. Several kinds of such disagreement and formulating an approach to these will be discussed. Three examples: Involvement of patients in Alzheimer Disease clinical trials. The researcher must be realistic but optimistic in the possible benefits of clinical trials. At the same time, expectations must be managed. It would be naive to consider that caregivers and people with lived experience participate for purely altruistic reasons. Therefore, when a clinical trial fails to produce obvious benefits (the patient may be in a placebo group, or the drug may have limited efficacy), the caregiver often considers withdrawing from the study. How should a researcher approach such a situation? Is there a way for caregivers and patients to be given autonomy, and yet carry clinical trials to the necessary completion? A second example involves prognostication. particularly when (as in Canada) medical assistance in death is now available for dementia patients. Who determines the narrative to be presented to the patient? If the caregiver wishes for greater pessimism or optimism on the part of the physician, is it ethical to diverge from the “scientific” information to accomodate prognostication to the preference of the caregiver? A third complex area is communication. Some caregivers are now requesting that the word “dementia” not be used, because it brings with it stigma. Other families maintain that the new terminology (such as “major neurocognitive disorder”) is mere obfuscation a lacks the clarity needed for communication. Should the language and terminology used be determined by caregivers? Should this be an area of discussion at the beginning of any medical interaction?We will discuss these and other scenarios where the complexity of the relationship between caregiver and physician/researcher are notable, and suggest approaches and processes to address these.
Elevated Blood Biomarkers of Neurodegeneration and Blood Brain Barrier Dysfunction Correlate with Lower MRI Regional Brain Volumes Two Years after COVID‐19
Authors: Frontera Jennifer A. , Ge Yulin , Boutajangout Allal , Ahmed Wajiha , Betensky Rebecca A , Debure Ludovic , Jiang Li , Links Jon , Masurkar Arjun V. , Sun Zhe , Thawani Sujata , Vedvyas Alok , Wisniewski Thomas 
Published: January 2025

AbstractBackgroundCognitive impairment is one of the most frequently reported post‐acute sequelae of COVID‐19, yet the pathophysiology underpinning this symptom remains unknown. We aimed to explore the correlation of blood markers of inflammation, BBB disruption and neurodegeneration with MRI volume measurements in COVID‐19 patients with and without cognitive impairment, and among patients with no prior history of COVID‐19.MethodWe conducted a prospective study of COVID‐19 patients (COV+; laboratory verified SARS‐CoV‐2 infection) and non‐COVID‐19 controls (COV‐; no history of SARS‐CoV‐2 infection and negative SARS‐CoV‐2 nucleocapsid antibody). All patients underwent neuropsychological testing using the Uniform Data Set Version 3 Cognitive Battery. Patients were coded as having cognitive impairment (COG+) based on neuropsychological testing (≥1 abnormal test result), and clinician interview with the patient and informant. 3T MRI (3D T1‐MPRAGE) sequences were utilized for regional volume measurements using MRICloud (Johns Hopkins University) segmentation software. The ratios of regional to total intracranial volume (SPM software) were reported to correct for differences in head size. Fasting plasma biomarkers of neurodegeneration, BBB dysfunction, and inflammation were measured concurrent with MRI testing. Bivariate Spearman correlation coefficients were calculated comparing MRI regional volumetric measures with blood biomarkers among COV+ versus COV‐ subjects with and without cognitive impairment (COG+ versus COG‐). Significance was set at P≤0.001 after Bonferroni correction.ResultA total of 90 subjects were included (N=75 COV+ with median 724 days from index SARS‐CoV‐2 infection, N=15 COV‐; N=39 COG+, N=51 COG‐). Among all COV+ subjects (N=75), neurodegenerative biomarkers (NFL, amyloid‐ß‐40, GFAP, ptau‐181), BBB markers (hepatocyte growth factor) and TNF‐a were significantly negatively correlated with regional MRI volumes, most notably in the limbic and hippocampal regions (Figure 1, bold=P≤0.001); whereas this signature of correlations was not observed in COV‐ subjects (N=15). Among COV+ subjects with cognitive impairment (COV+COG+, N=33), significant negative correlations were observed between neurodegenerative biomarkers (NFL, amyloid‐ß‐40, GFAP, ptau‐181) and MRI volumes (particularly frontal, temporal and limbic), whereas COV+COG‐ subjects (N=42) did not demonstrate this pattern (Figure 2).ConclusionTwo‐years post‐COVID‐19, signature correlations between neurodegenerative, BBB and cytokine blood biomarkers and MRI regional volumes differ between COVID‐19 subjects versus controls, particularly among those with cognitive impairment.
LSM14A as a potential CSF biomarker for mild cognitive impairment and Alzheimer’s disease
Authors: Ildız Sümeyra , İlhan Nazlıcan , Samancı Bedia , Sordu Pelin , Alaylıoğlu Merve , Hanagasi Hasmet , Gurvit İbrahim Hakan , Bilgiç Başar , Dursun Erdinc , Gezen‐Ak Duygu 
Published: January 2025

AbstractBackgroundmRNAs are required to progress cellular processes such as synaptic plasticity and memory formation. Processing bodies (P‐bodies) are storage units for mRNAs located at dendritic translation sites, so these mRNAs can participate in synaptic plasticity immediately when needed. P‐bodies consist of 3 main proteins: DDX6, 4E‐T, and LSM14A. It is thought that LSM14A is the part that binds to the mRNAs within the P‐bodies via its Lsm region, which is the region that recognizes and binds to mRNA. And so, LSM14A plays essential roles in mRNA translation, storage, and degradation. In neurodegenerative disorders, dendritic damage is seen in the early stages. It is unclear how much dendritic substance is released into the extracellular space after cellular damage. Some studies show the presence of exosomes and mRNA in the cerebrospinal fluid (CSF). The finding of mRNAs at dendrites with P‐bodies suggests that mRNAs could pass into the CSF via P‐bodies. In this study, we investigated the presence and the level of LSM14A in the CSF to determine its potential to be an early‐phase biomarker of Alzheimer's disease (AD).MethodIn this study, the level of LSM14A protein was detected by ELISA in CSF of 21 patients with mild cognitive impairment (MCI), 40 patients with AD, and 18 cognitively unimpaired individuals. Raw data was analyzed by GraphPad InStat DTCG 3.06 with a one‐way ANOVA method followed by the Tukey‐Kramer posthoc test.ResultThe level of LSM14A in the MCI group is significantly higher than in the control group, and the level of LSM14A positively correlated with patients' age. In AD patients, LSM14A levels increased in the first two years of the disease. LSM14A was negatively correlated with AD duration.ConclusionAccording to our results, the level of LSM14A in the CSF is high in the MCIs. The disease duration of AD cases that were less than two years also showed elevated levels of LSM14A. Our preliminary results suggest that CSF LSM14A protein might be a CSF biomarker for the early stage of AD.
Rapidly progressive dementia: criteria proposal
Authors: Satyadev Nihal , Tipton Philip W , Dunham S Richard , Brier Matthew R , Morris John C. , Graff‐Radford Neill R , Day Gregory S 
Published: January 2025

AbstractBackgroundRapidly progressive dementia (RPD) is variably defined across published cohorts. A standardized definition is needed to support multicenter studies required to inform the causes of RPD and optimize recognition and management of treatment‐responsive causes. An optimal definition will capture the broad spectrum of causes of RPD, adequately differentiate patients with rapid and typically progressive presentations of neurodegenerative disease, and be reliably implemented across healthcare settings and centers.MethodThe Clinical Dementia Rating® (CDR) is a validated dementia staging tool that is widely used in clinical trials and observational studies. We applied the CDR to diagnose RPD in patients who developed dementia (CDR ≥1) within 1 year or incapacitation (CDR ≥2) within 2 years of symptom onset. This definition was prospectively applied to patients with suspected RPD at Mayo Clinic in Florida (MCF: Jacksonville, FL; Jan 2020 – Oct 2023) and Washington University in St. Louis (WU: Saint Louis, MO; Jun 2016 – Dec 2019), and retrospectively applied to individuals within the National Alzheimer’s Coordinating Center (NACC) dataset. Criteria performance was compared across cohorts.ResultTwo‐hundred twenty‐six patients were referred with suspected RPD at MCF‐WU. Of these, 155/226 (68.6%) met our proposed RPD criteria, including patients with Alzheimer disease and related dementias (ADRD; 34/155, 21.9%), Creutzfeldt Jacob disease (CJD; 25/155, 16.1%), autoimmune encephalitis (52/155, 33.5%), vascular pathologies (14/155, 9.0%), toxic/metabolic disruptions (7/155, 4.5%) and primary psychiatric disorders (4/155, 2.6%). A small subset of NACC participants met our proposed RPD criteria (836/20,418; 0.04%), emphasizing the unique nature of RPD. Causes of RPD in NACC included ADRD (676/836, 80.1%), CJD (72/836, 8.6%), and vascular pathologies (24/836, 2.9%). Rates of progression (∆CDR sum‐of‐boxes/year) clearly distinguished patients with RPD from non‐RPD in both cohorts (MCF‐WU, 13.6±5.8 vs 4.7±5.9, p<0.001; NACC, 6.7±3.1 vs. 1.7±1.4, p<0.001).ConclusionOur CDR‐based definition of RPD distinguished patients with a broad spectrum of causes of RPD from those with typically progressive dementia across multiple cohorts. Broad application of this criteria would standardize diagnosis of RPD and support the design and implementation of multicenter studies RPD.