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Early stages of Alzheimer's disease (AD) are associated with volume reductions in specific subregions of the medial temporal lobe (MTL). Using a manual segmentation method-the Olsen-Amaral-Palombo (OAP) protocol-previous work in healthy older adults showed that reductions in grey matter volumes in MTL subregions were associated with lower scores on the Montreal Cognitive Assessment (MoCA), suggesting atrophy may occur prior to diagnosis of mild cognitive impairment, a condition that often progresses to AD. However, current "gold standard" manual segmentation methods are labour intensive and time consuming. Here, we examined the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) to detect volumetric differences in MTL subregions of healthy older adults who varied in cognitive status as determined by the MoCA. We trained ASHS on the OAP protocol to create the ASHS-OAP atlas and then examined how well automated segmentation replicated manual segmentation. Volumetric measures obtained from the ASHS-OAP atlas were also contrasted against those from the ASHS-PMC atlas, a widely used atlas provided by the ASHS team. The pattern of volumetric results was similar between the ASHS-OAP atlas and manual segmentation for anterolateral entorhinal cortex and perirhinal cortex, suggesting that ASHS-OAP is a viable alternative to current manual segmentation methods for detecting group differences based on cognitive status. Although ASHS-OAP and ASHS-PMC produced varying volumes for most regions of interest, they both identified early signs of neurodegeneration in CA2/CA3/DG and identified marginal differences in entorhinal cortex. Our findings highlight the utility of automated segmentation methods but still underscore the need for a unified and harmonized MTL segmentation atlas.

We aimed to compare the associations of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) with coronary artery calcification (CAC). Patients who simultaneously underwent ultrasonography to diagnose hepatic steatosis and cardiac computed tomography to detect CAC were included. The presence and severity of CAC were defined with CAC-score thresholds of > 0 and > 300, respectively, and patients were divided into the following groups: no MASLD or MAFLD (reference), MASLD-only, MAFLD-only, and overlapping groups. Overall, 1,060/2,773 (38.2%) patients had CAC, of which 196 (18.5%) had severe CAC. The MASLD and MAFLD prevalence rates were 32.6% and 45.2%, respectively, with an overlap of 30.7%. In an ASCVD risk score-adjusted model, both MASLD (adjusted odd ratios [aOR], 1.21; 95% confidence interval [CI], 1.02-1.44; p = 0.033) and MAFLD (aOR 1.20; 95% CI 1.01-1.42, p = 0.034) were associated with CAC, whereas only MASLD (aOR 1.38; 95% CI 1.01-1.89, p = 0.041) was associated with severe CAC. Compared to the reference group, the overlapping group showed an association with CAC (aOR 1.22; 95% CI 1.01-1.47; p = 0.038); however, the MASLD and MAFLD subgroups did not differ in their association with CAC. MASLD may predict a higher risk of ASCVD more effectively than MAFLD.

Clinical endpoints, such as overall survival, directly measure relevant outcomes. Surrogate endpoints, in contrast, are intermediate, stand-in measures of various tumour-related metrics and include tumour growth, tumour shrinkage, blood results, etc. Surrogates may be a time point measurement, that is, tumour shrinkage at some point (eg, response rate) or biomarker-assessed disease status, measured at given time points (eg, circulating tumour DNA, ctDNA). They can also be measured over time, as with progression-free survival, which is the time until a patient presents with either disease progression or death. Surrogates are increasingly used in trials supporting the marketing authorisation of novel oncology drugs. Yet, the trial-level correlation between surrogates and clinical endpoints—meaning to which extent an improvement in the surrogate predicts an improvement in the direct endpoint—is often moderate to low. Here, we provide a comprehensive classification of surrogate endpoints: time point measurements and time-to-event endpoints in solid and haematological malignancies. Also, we discuss an overlooked aspect of the use of surrogates: the limitations of surrogates outside trial settings, at the bedside. Surrogates can result in the inappropriate stopping or switching of therapy. Surrogates can be used to usher in new strategies (eg, ctDNA in adjuvant treatment of colon cancer), which may erode patient outcomes. In liquid malignancies, surrogates can mislead us to use novel drugs and replace proven standards of care with costly medications. Surrogates can lead one to intensify treatment without clear improvement and possibly worsening quality of life. Clinicians should be aware of the role of surrogates in the development and regulation of drugs and how their use can carry real-world, bedside implications.

BackgroundDigital cognitive assessments, particularly those that can be done at home, present as low-burden biomarkers for participants and patients alike, but their effectiveness in the diagnosis of Alzheimer's disease (AD) or predicting its trajectory is still unclear. Here, we assessed what utility or added value these digital cognitive assessments provide for identifying those at high risk of cognitive decline.MethodsWe analyzed >500 Alzheimer's Disease Neuroimaging Initiative participants who underwent a brief digital cognitive assessment and amyloid beta (Aβ)/tau positron emission tomography scans, examining their ability to distinguish cognitive status and predict cognitive decline.ResultsPerformance on the digital cognitive assessment was superior to both cortical Aβ and entorhinal tau in detecting mild cognitive impairment and future cognitive decline, with mnemonic discrimination deficits emerging as the most critical measure for predicting decline and future tau accumulation.DiscussionDigital assessments are effective at identifying at-risk individuals, supporting their utility as low-burden tools for early AD detection and monitoring.HighlightsPerformance on digital cognitive assessments predicts progression to mild cognitive impairment at a higher proficiency compared to amyloid beta and tau. Deficits in mnemonic discrimination are indicative of future cognitive decline. Impaired mnemonic discrimination predicts future entorhinal and inferior temporal tau.

There is a clinical need for a simple test implementable at the primary point of care to identify individuals with metabolic dysfunction-associated steatotic liver disease (MASLD) in the population. Blood plasma samples from adult patients with varying phenotypes of MASLD were used to identify a minimal set of lipid analytes reflective of underlying histologically confirmed MASLD. Samples were obtained from the NIDDK Nonalcoholic Steatohepatitis Clinical Research Network (NASH CRN) NAFLD Database prospective cohort study (MASLD group; N = 301). Samples of control subjects were obtained from cohort studies at the University of California San Diego (control group; N = 48). Plasma samples were utilized for targeted quantitation of circulating eicosanoids, related bioactive metabolites, and polyunsaturated fatty acids by ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) lipidomics analysis. Bioinformatic approaches were used to discover a panel of bioactive lipids that can be used as a diagnostic tool to identify MASLD. The final panel of fifteen lipid metabolites consists of 12 eicosanoid metabolites and 3 free fatty acids that were identified to be predictive for MASLD by multivariate area under the receiver operating characteristics curve (AUROC) analysis. The panel was highly predictive for MASLD with an AUROC of 0.999 (95% CI = 0.986-1.0) with only one control misclassified. A validation study confirmed the resulting MASLD LIPIDOMICS SCORE, which may require a larger-scale prospective study to optimize. This predictive model should guide the development of a non-invasive "point-of-care" test to identify MASLD patients requiring further evaluation for the presence of metabolic dysfunction-associated steatohepatitis.

By age 40 years, over 90% of adults with Down syndrome have Alzheimer's disease pathology and most progress to dementia. Despite having few systemic vascular risk factors, individuals with Down syndrome have elevated cerebrovascular disease markers that track with the clinical progression of Alzheimer's disease, suggesting a role of cerebrovascular disease that is hypothesized to be mediated by inflammatory factors. This study examined the pathways through which small vessel cerebrovascular disease contributes to Alzheimer's disease-related pathophysiology and neurodegeneration in adults with Down syndrome. One hundred eighty-five participants from the Alzheimer's Biomarkers Consortium-Down Syndrome [mean (SD) age = 45.2 (9.3) years] with available MRI and plasma biomarker data were included in this study. White matter hyperintensity (WMH) volumes were derived from T2-weighted fluid-attenuated inversion recovery MRI scans, and plasma biomarker concentrations of amyloid beta 42/40, phosphorylated tau 217, astrocytosis (glial fibrillary acidic protein) and neurodegeneration (neurofilament light chain) were measured with ultrasensitive immunoassays. We examined the bivariate relationships of WMH, amyloid beta 42/40, phosphorylated tau 217 and glial fibrillary acidic protein with age-residualized neurofilament light chain across Alzheimer's disease diagnostic groups. A series of mediation and path analyses examined statistical pathways linking WMH and Alzheimer's disease pathophysiology to promote neurodegeneration in the total sample and groups stratified by clinical diagnosis. There was a direct and indirect bidirectional effect through the glial fibrillary acidic protein of WMH on phosphorylated tau 217 concentration, which was associated with neurofilament light chain concentration in the entire sample. Amongst cognitively stable participants, WMH was directly and indirectly, through glial fibrillary acidic protein, associated with phosphorylated tau 217 concentration, and in those with mild cognitive impairment, there was a direct effect of WMH on phosphorylated tau 217 and neurofilament light chain concentrations. There were no associations of WMH with biomarker concentrations among those diagnosed with dementia. The findings from this cross-sectional study suggest that among individuals with Down syndrome, cerebrovascular disease promotes neurodegeneration by increasing astrocytosis and tau pathophysiology in the presymptomatic phases of Alzheimer's disease, but future studies will need to confirm these associations with longitudinal data. This work joins an emerging literature that implicates cerebrovascular disease and its interface with neuroinflammation as a core pathological feature of Alzheimer's disease in adults with Down syndrome.

Pancreas transplantation improves glycemic control and mortality in patients with diabetes but requires aggressive immunosuppression to control the alloimmune and autoimmune response. Recent developments in "omics' methods have provided gene transcript-based biomarkers for organ transplant rejection. The tissue Common Response Module (tCRM) score is developed to identify the severity of rejection in kidney, heart, liver, and lung transplants. Still, it has not yet been validated in pancreas transplants (PT). We evaluated the tCRM score's relevance in PT and additional markers of acute cellular rejection (ACR) for PT. An analysis on 51 pancreas biopsies with ACR identified 37 genes and 56 genes significantly upregulated in the case of grade 3 and grade 2 ACR respectively (P

IntroductionModic changes (MC) are bone marrow lesions of vertebral bones, which can be detected with magnetic resonance imaging (MRI) adjacent to degenerated intervertebral discs. Defined by their appearance on T1 and T2 weighted images, there are three interconvertible types: MC1, MC2, and MC3. The inter-observer variability of the MRI diagnosis is high, therefore a diagnostic serum biomarker complementing the MRI to facilitate diagnosis and follow-up would be of great value.MethodsWe used a highly sensitive and reproducible proteomics approach: DIA/SWATH-MS to find serum biomarkers in a subset of the Northern Finland Birth Cohort 1966. Separately, we measured a panel of factors involved in inflammation and angiogenesis to confirm some potential biomarkers published before with an ELISA-based method called V-Plex.ResultsWe found neither an association between the serum concentrations of the proteins detected with DIA/SWATH-MS with the presence of MC, nor a correlation with the size of the MC lesions. We did not find any association between the factors measured with the V-Plex and the presence of MC or their size.ConclusionAltogether, our study suggests that a robust and generally usable biomarker to facilitate the diagnosis of MC cannot readily be found in serum.

The pursuit of translational biomarkers is complex due to the heterogeneous human pathophysiology, but critical for disease diagnosis, prognosis, monitoring therapeutic efficacy, and for patient stratification. In HIV-associated neurocognitive impairment (NCI), biomarkers that delineate the trajectory of neuropathogenesis and neurocognitive sequelae are critical, particularly considering confounders such as substance use, including Methamphetamine (METH). METH use is a significant health concern among persons living with HIV (PWH), aggravating cognitive deficits and neuroinflammation despite of antiretrovirals, introducing elements in the microenvironment that are fundamentally differerent in relation to non-METH users, such as high levels of dopamine (DA) affecting HIV-innate immune targets. Yet, current biomarkers do not detect these differences. We hypothesized that predefined DA-induced signatures detectable in peripheral blood leukocytes, can distinguish HIV+ METH users compared to HIV-negative or PWH that are non METH users. The elevated expression of CD8A, CREBBP, CCL5, and combinations of dopaminergic pathway transcripts clustered METH users with detectable CSF viral load and major depressive disorder (MDD), indicating neuroimmune-mechanistic links. Cathecol-o-methyltransferase (COMT) gene polymorphisms affecting DA metabolism improved the identification of PWH using METH with biomarkers. The results indicate that underlying immunedopaminergic mechanisms provide signatures and genotypes that can identify PWH that are METH users and their attributes.

Structured representations of clinical data can support computational analysis of individuals and cohorts, and ontologies representing disease entities and phenotypic abnormalities are now commonly used for translational research. The Medical Action Ontology (MAxO) provides a computational representation of treatments and other actions taken for the clinical management of patients. Currently, manual biocuration is used to assign MAxO terms to rare diseases, enabling clinical management of rare diseases to be described computationally for use in clinical decision support and mechanism discovery. However, it is challenging to scale manual curation to comprehensively capture information about medical actions for the more than 10,000 rare diseases. We present AutoMAxO, a semi-automated workflow that leverages Large Language Models (LLMs) to streamline MAxO biocuration for rare diseases. AutoMAxO first uses LLMs to retrieve candidate curations from abstracts of relevant publications. Next, the candidate curations are matched to ontology terms from MAxO, Human Phenotype Ontology (HPO), and MONDO disease ontology via a combination of LLMs and post-processing techniques. Finally, the matched terms are presented in a structured form to a human curator for approval. We used this approach to process 4,918 unique medical abstracts and identified annotations for 21 rare genetic diseases, we extracted 18,631 candidate disease-treatment curations, 538 of which were confirmed and transferred to the MAxO annotation dataset. The results of this project underscore the potential of generative AI to accelerate precision medicine by enabling a robust and comprehensive curation of the primary literature to represent information about diseases and procedures in a structured fashion. Although we focused on MAxO in this project, similar approaches could be taken for other biomedical curation tasks.

As demonstrated by the SARS-CoV-2 pandemic, the emergence of novel viral strains with increased transmission rates poses a serious threat to global health. Statistical models of genome sequence evolution may provide a critical tool for early detection of these strains. Using a novel stochastic model that links transmission rates to the entire viral genome sequence, we study the utility of phylogenetic methods that use a phylogenetic tree relating viral samples versus count-based methods that use case counts of variants over time exclusively to detect increased transmission rates and identify candidate causative mutations. We find that phylogenies in particular can detect novel transmission-enhancing variants very soon after their origin and may facilitate the development of early detection systems for outbreak surveillance.

BackgroundEndocrine disrupting chemicals (EDCs) are widely used compounds with the potential to affect child neurodevelopmental outcomes including autism spectrum disorders (ASD). We aimed to examine the urinary concentrations of biomarkers of EDCs, including phthalates, phenols, and parabens, and investigate whether exposure during early infancy was associated with increased risk of later ASD or other non-typical development (Non-TD) or adverse cognitive development.MethodsThis analysis included infants from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) study, a high-risk ASD cohort (n = 148; corresponding to 188 urine samples). Thirty-two EDC biomarkers were quantified in urine among infants 3 and/or 6 months of age. Trends in EDC biomarker concentrations were calculated using least square geometric means. At 36 months of age, children were clinically classified as having ASD (n = 36), nontypical development (Non-TD; n = 18), or typical development (TD; n = 81) through a clinical evaluation. Trinomial logistic regression analysis was used to test the associations between biomarkers with ASD, or Non-TD, as compared to children with TD. In single analyte analysis, generalized estimating equations were used to investigate the association between each EDC biomarkers and longitudinal changes in cognitive development using the Mullen Scales of Early Learning (MSEL) over the four assessment time points (6, 12, 24, and 36 months of age). Additionally, quantile g-computation was used to test for a mixture effect.ResultsEDC biomarker concentrations generally decreased over the study period, except for mono-2-ethyl-5-carboxypentyl terephthalate. Overall, EDC biomarkers at 3 and/or 6 months of age were not associated with an increased risk of ASD or Non-TD, and a few showed significant inverse associations. However, when assessing longitudinal changes in MSEL scores over the four assessment time points, elevated monoethyl phthalate (MEP) was significantly associated with reduced scores in the composite score (β = -0.16, 95% CI: 0.31, -0.02) and subscales of fine motor skills (β = -0.09, 95%CI: 0.17, 0.00), and visual reception (β = -0.11, 95% CI: 0.23, 0.01). Additionally, the sum of metabolites of di (2-ethylhexyl) terephthalate (ƩDEHTP) was associated with poorer visual reception (β = -0.09, 95% CI: 0.16, -0.02), and decreased composite scores (β = -0.11, 95% CI: 0.21, -0.01). Mixtures analyses using quantile g-computation analysis did not show a significant association between mixtures of EDC biomarkers and MSEL subscales or composite scores.ConclusionThese findings highlight the potential importance of infant exposures on cognitive development. Future research can help further investigate whether early infant exposures are associated with longer-term deficits and place special attention on EDCs with increasing temporal trends and whether they may adversely affect neurodevelopment.

IntroductionAlzheimer's disease (AD) pathology is defined by β-amyloid (Aβ) plaques and neurofibrillary tau, but Lewy bodies (LBs; ?-synuclein aggregates) are a common co-pathology for which effective biomarkers are needed.MethodsA validated α-synuclein Seed Amplification Assay (SAA) was used on recent cerebrospinal fluid (CSF) samples from 1638 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 78 with LB-pathology confirmation at autopsy. We compared SAA outcomes with neuropathology, Aβ and tau biomarkers, risk-factors, genetics, and cognitive trajectories.ResultsSAA showed 79% sensitivity and 97% specificity for LB pathology, with superior performance in identifying neocortical (100%) compared to limbic (57%) and amygdala-predominant (60%) LB-pathology. SAA+ rate was 22%, increasing with disease stage and age. Higher Aβ burden but lower CSF p-tau181 associated with higher SAA+ rates, especially in dementia. SAA+ affected cognitive impairment in MCI and Early-AD who were already AD biomarker positive.DiscussionSAA is a sensitive, specific marker for LB-pathology. Its increase in prevalence with age and AD stages, and its association with AD biomarkers, highlights the clinical importance of α-synuclein co-pathology in understanding AD's nature and progression.HighlightsSAA shows 79% sensitivity, 97% specificity for LB-pathology detection in AD. SAA positivity prevalence increases with disease stage and age. Higher Aβ burden, lower CSF p-tau181 linked with higher SAA+ rates in dementia. SAA+ impacts cognitive impairment in early disease stages. Study underpins need for wider LB-pathology screening in AD treatment.

BACKGROUND: Exposure to antiretrovirals at or early after HIV acquisition can suppress viral replication and blunt antibody (Ab) responses; a reduced HIV detectability could impact diagnosis and blood donation screening. METHODS: We used three antigen (Ag)/Ab assays and one nucleic acid test (NAT) to analyze samples collected in pre-exposure prophylaxis (PrEP) trials (iPrEx; Partners PrEP) before infection detection by Ab-only rapid diagnostic tests (RDTs), and in early antiretroviral treatment (ART) initiation studies (RV254; SIPP). RESULTS: Reactivity using NAT and Ag/Ab assays in samples collected up to 8 weeks prior to the first reactive RDT from 251 PrEP trials participants varied between 49-61% for active PrEP users and between 27-37% for placebo users. Among RV254 participants, reactivity in Ag/Ab assays was

Central nervous system (CNS) infections carry a substantial burden of morbidity and mortality worldwide, and accurate and timely diagnosis is required to optimize management. Metagenomic next-generation sequencing (mNGS) has proven to be a valuable tool in detecting pathogens in patients with suspected CNS infection. By sequencing microbial nucleic acids present in a patient's cerebrospinal fluid, brain tissue, or samples collected outside of the CNS, such as plasma, mNGS can detect a wide range of pathogens, including rare, unexpected, and/or fastidious organisms. Furthermore, its target-agnostic approach allows for the identification of both known and novel pathogens. This is particularly useful in cases where conventional diagnostic methods fail to provide an answer. In addition, mNGS can detect multiple microorganisms simultaneously, which is crucial in cases of mixed infections without a clear predominant pathogen. Overall, clinical mNGS testing can help expedite the diagnostic process for CNS infections, guide appropriate management decisions, and ultimately improve clinical outcomes. However, there are key challenges surrounding its use that need to be considered to fully leverage its clinical impact. For example, only a few specialized laboratories offer clinical mNGS due to the complexity of both the laboratory methods and analysis pipelines. Clinicians interpreting mNGS results must be aware of both false negatives-as mNGS is a direct detection modality and requires a sufficient amount of microbial nucleic acid to be present in the sample tested-and false positives-as mNGS detects environmental microbes and their nucleic acids, despite best practices to minimize contamination. Additionally, current costs and turnaround times limit broader implementation of clinical mNGS. Finally, there is uncertainty regarding the best practices for clinical utilization of mNGS, and further work is needed to define the optimal patient population(s), syndrome(s), and time of testing to implement clinical mNGS.

Healthcare facilities produce millions of tons of waste annually, with a significant portion consisting of diagnostic plasticware. Here, we introduce a new detection platform that completely replaces traditional assay plates with a piece of membrane, offering a much greener and more sustainable alternative. The membrane, integrated within the portable vortex fluidic device (P-VFD), enables rapid detection of a clinically relevant protein biomarker, urinary p75ECD. This biomarker is utilized to evaluate the prognosis, disease severity, and progression of amyotrophic lateral sclerosis (ALS). This assay has a limit-of-detection (LOD) of 4.03 pg, which is comparable to the plate-based assay (2.24 pg) and has been optimised through a full factorial design of experiments (DOE) and response surface methodology (RSM). P-VFD has great potential in quantifying p75ECD in human biofluids and can significantly reduce the assay time to 5 min compared to the current plate-based p75ECD ELISA assay (3 days), with at least a 4.4-fold reduction in the usage of the detection antibody.

The kidney is the most common solid organ transplant globally and rates continue to climb, driven by the increasing prevalence of end stage renal disease (ESRD). Compounded by advancements in surgical techniques and immunosuppression leading to longer graft survival, radiologists evermore commonly evaluate kidney transplant patients and candidates, underscoring their role along the transplant process. Multiphase computed tomography (CT) with multiplanar and 3D reformatting is the primary method for evaluating renal donor candidates, detailing renal size, vascular/collecting system anatomy, and identifying significant pathologies such as renal vascular diseases and nephrolithiasis. Ultrasound is the preferred initial postoperative imaging modality for graft evaluation due to its low cost, accessibility, noninvasiveness, and lack of radiation. CT and magnetic resonance imaging (MRI) may be useful adjunctive imaging techniques in diagnosing transplant pathology when ultrasound alone is not diagnostic. Kidney transplant complications are categorized by an approximate timeline framework, aiding in differential diagnosis based on onset, duration, and severity and include perinephric fluid collections, graft compression, iatrogenic injuries, vascular compromise, graft rejection, and neoplastic processes. This review discusses imaging strategies and important findings along the transplant timeline, from donor assessment to long-term recipient complications.

Despite an overall decrease in occurrence, colorectal cancer (CRC) remains the third most common cause of cancer deaths in the USA. Detection of CRC is difficult in high-risk groups, including those with genetic predispositions, with disease traits, or from certain demographics. There is emerging interest in using engineered bacteria to identify early CRC development, monitor changes in the adenoma and CRC microenvironment, and prevent cancer progression. Novel genetic circuits for cancer therapeutics or functions to enhance existing treatment modalities have been tested and verified in vitro and in vivo. Inclusion of biocontainment measures would prepare strains to meet therapeutic standards. Thus, engineered bacteria present an opportunity for detection and treatment of CRC lesions in a highly sensitive and specific manner.

Patients with tuberous sclerosis complex (TSC) develop multi-organ disease manifestations, with kidney angiomyolipomas (AML) and cysts being one of the most common and deadly. Early and regular AML/cyst detection and monitoring are vital to lower TSC patient morbidity and mortality. However, the current standard of care involves imaging-based methods that are not designed for rapid screening, posing challenges for early detection. To identify potential diagnostic screening biomarkers of AML/cysts, we performed global untargeted metabolomics in blood samples from 283 kidney AML/cyst-positive or -negative TSC patients using mass spectrometry. We identified 7 highly sensitive chemical features, including octanoic acid, that predict kidney AML/cysts in TSC patients. Patients with elevated octanoic acid have lower levels of very long-chain fatty acids (VLCFAs), suggesting that dysregulated peroxisome activity leads to overproduction of octanoic acid via VLCFA oxidation. These data highlight AML/cysts blood biomarkers for TSC patients and offers valuable metabolic insights into the disease.

IntroductionAlzheimer's disease (AD) neuropathological changes present with amnestic and nonamnestic (atypical) syndromes. The contribution of comorbid neuropathology as a substratum of atypical expression of AD remains under investigated.MethodsWe examined whether atypical AD exhibited increased comorbid neuropathology compared to typical AD and if such neuropathologies contributed to the accelerated clinical decline in atypical AD.ResultsWe examined 60 atypical and 101 typical AD clinicopathological cases. The number of comorbid pathologies was similar between the groups (p = 0.09). Argyrophilic grain disease was associated with atypical presentation (p = 0.008) after accounting for sex, age of onset, and disease duration. Vascular brain injury was more common in typical AD (p = 0.022). Atypical cases had a steeper Mini-Mental Status Examination (MMSE) decline over time (p = 0.033).DiscussionComorbid neuropathological changes are unlikely to contribute to atypical AD presentation and the steeper cognitive decline seen in this cohort.HighlightsAutopsy cohort of 60 atypical and 101 typical AD; does comorbid pathology explain atypical presentation?Atypical versus Typical AD: No significant differences in comorbid neuropathologies were found (p = 0.09).Argyrophilic Grain Disease Association: significantly correlates with atypical AD presentations, suggesting a unique neuropathological pattern (p = 0.008).Vascular Brain Injury Prevalence: Vascular brain injury is more common in typical AD than in atypical AD (p = 0.022).Cognitive Decline in Atypical AD: Atypical AD patients experience a steeper cognitive decline measured by MMSE than those with typical AD despite lacking more comorbid neuropathology, highlighting the severity of atypical AD pathogenesis (p = 0.033).

The diagnostic value of imaging Aβ plaques in Alzheimer's disease (AD) has accelerated the development of fluorine-18 labeled radiotracers with a longer half-life for easier translation to clinical use. We have developed [18F]flotaza, which shows high binding to Aβ plaques in postmortem human AD brain slices with low white matter binding. We report the binding of [18F]flotaza in postmortem AD hippocampus compared to cognitively normal (CN) brains and the evaluation of [18F]flotaza in transgenic 5xFAD mice expressing Aβ plaques. [18F]Flotaza binding was assessed in well-characterized human postmortem brain tissue sections consisting of HP CA1-subiculum (HP CA1-SUB) regions in AD (n = 28; 13 male and 15 female) and CN subjects (n = 32; 16 male and 16 female). Adjacent slices were immunostained with anti-Aβ and analyzed using QuPath. In vitro and in vivo [18F]flotaza PET/CT studies were carried out in 5xFAD mice. Post-mortem human brain slices from all AD subjects were positively IHC stained with anti-Aβ. High [18F]flotaza binding was measured in the HP CA1-SUB grey matter (GM) regions compared to white matter (WM) of AD subjects with GM/WM > 100 in some subjects. The majority of CN subjects had no decipherable binding. Male AD exhibited greater WM than AD females (AD WM♂/WM♀ > 5; p < 0.001) but no difference amongst CN WM. In vitro studies in 5xFAD mice brain slices exhibited high binding [18F]flotaza ratios (>50 versus cerebellum) in the cortex, HP, and thalamus. In vivo, PET [18F]flotaza exhibited binding to Aβ plaques in 5xFAD mice with SUVR~1.4. [18F]Flotaza is a new Aβ plaque PET imaging agent that exhibited high binding to Aβ plaques in postmortem human AD. Along with the promising results in 5xFAD mice, the translation of [18F]flotaza to human PET studies may be worthwhile.

Accurate diagnosis of lung cancer is important for treatment decision-making. Tumor biopsy and histologic examination are the standard for determining histologic lung cancer subtypes. Liquid biopsy, particularly cell-free DNA (cfDNA), has recently shown promising results in cancer detection and classification. In this study, we investigate the potential of cfDNA methylome for the noninvasive classification of lung cancer histologic subtypes. We focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcriptional activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in cross-validation and an AUC of 0.747 in the independent validation. Tumor copy-number alterations inferred from cfDNA methylome analysis revealed potential for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasive lung cancer subtyping, offering insights for cancer monitoring and early detection.SignificanceThis study explores the use of cfDNA methylomes for the classification of lung cancer subtypes, vital for effective treatment. By identifying specific methylation markers in tumor tissues, we developed a robust classification model achieving high accuracy for noninvasive subtype detection. This cfDNA methylome approach offers promising avenues for early detection and monitoring.

IntroductionIdentifying reliable biomarkers that reflect cancer survivorship symptoms remains a challenge for researchers. DNA methylation (DNAm) measurements reflecting epigenetic changes caused by anti-cancer therapy may provide needed insights. Given lack of consensus describing utilization of DNAm data to predict survivorship issues, a review evaluating the current landscape is warranted.ObjectiveProvide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors.MethodsA literature review was conducted including studies if they focused on cohorts of cancer survivors, utilized peripheral blood cell DNAm data, and evaluated the associations of DNAm and survivorship issues.ResultsA total of 22 studies were identified, with majority focused on breast (n = 7) or childhood cancer (n = 9) survivors, and half studies included less than 100 patients (n = 11). Survivorship issues evaluated included those related to neurocognition (n = 5), psychiatric health (n = 3), general wellness (n = 9), chronic conditions (n = 5), and treatment specific toxicities (n = 4). Studies evaluated epigenetic age metrics (n = 10) and DNAm levels at individual CpG sites or regions (n = 12) for their associations with survivorship issues in cancer survivors along with relevant confounding factors. Significant associations of measured DNAm in the peripheral blood samples of cancer survivors and survivorship issues were identified.Discussion/conclusionStudies utilizing epigenetic age metrics and differential methylation analysis demonstrated significant associations of DNAm measurements with survivorship burdens. Associations were observed encompassing diverse survivorship outcomes and timeframes relative to anti-cancer therapy initiation. These findings underscore the potential of these measurements as useful biomarkers in survivorship care and research.

Deflectometric profilometers are used to precisely measure the form of beam shaping optics of synchrotrons and X-ray free-electron lasers. They often utilize autocollimators which measure slope by evaluating the displacement of a reticle image on a detector. Based on our privileged access to the raw image data of an autocollimator, novel strategies to reduce the systematic measurement errors by using a set of overlapping images of the reticle obtained at different positions on the detector are discussed. It is demonstrated that imaging properties such as, for example, geometrical distortions and vignetting, can be extracted from this redundant set of images without recourse to external calibration facilities. This approach is based on the fact that the properties of the reticle itself do not change - all changes in the reticle image are due to the imaging process. Firstly, by combining interpolation and correlation, it is possible to determine the shift of a reticle image relative to a reference image with minimal error propagation. Secondly, the intensity of the reticle image is analysed as a function of its position on the CCD and a vignetting correction is calculated. Thirdly, the size of the reticle image is analysed as a function of its position and an imaging distortion correction is derived. It is demonstrated that, for different measurement ranges and aperture diameters of the autocollimator, reductions in the systematic errors of up to a factor of four to five can be achieved without recourse to external measurements.

Positron emission tomography (PET) is a widely utilized medical imaging modality that uses positron-emitting radiotracers to visualize biochemical processes in a living body. The spatiotemporal distribution of a radiotracer is estimated by detecting the coincidence photon pairs generated through positron annihilations. In human tissue, about 40% of the positrons form positroniums prior to the annihilation. The lifetime of these positroniums is influenced by the microenvironment in the tissue and could provide valuable information for better understanding of disease progression and treatment response. Currently, there are few methods available for reconstructing high-resolution lifetime images in practical applications. This paper presents an efficient statistical image reconstruction method for positronium lifetime imaging (PLI). We also analyze the random triple-coincidence events in PLI and propose a correction method for random events, which is essential for real applications. Both simulation and experimental studies demonstrate that the proposed method can produce lifetime images with high numerical accuracy, low variance, and resolution comparable to that of the activity images generated by a PET scanner with currently available time-of-flight resolution.

Digital PCR (dPCR) holds immense potential for precisely detecting nucleic acid markers essential for personalized medicine. However, its broader application is hindered by high consumable costs, complex procedures, and restricted multiplexing capabilities. To address these challenges, an all-in-one dPCR system is introduced that eliminates the need for microfabricated chips, offering fully automated operations and enhanced multiplexing capabilities. Using this innovative oscillation-induced droplet generation technique, OsciDrop, this system supports a comprehensive dPCR workflow, including precise liquid handling, pipette-based droplet printing, in situ thermocycling, multicolor fluorescence imaging, and machine learning-driven analysis. The system's reliability is demonstrated by quantifying reference materials and evaluating HER2 copy number variation in breast cancer. Its multiplexing capability is showcased with a quadruplex dPCR assay that detects key EGFR mutations, including 19Del, L858R, and T790M in lung cancer. Moreover, the digital stepwise melting analysis (dSMA) technique is introduced, enabling high-multiplex profiling of seven major EGFR variants spanning 35 subtypes. This innovative dPCR system presents a cost-effective and versatile alternative, overcoming existing limitations and paving the way for transformative advances in precision diagnostics.

Chronic conditions associated with aging have proven difficult to prevent or treat. Senescence is a cell fate defined by loss of proliferative capacity and the development of a pro-inflammatory senescence-associated secretory phenotype comprised of cytokines/chemokines, proteases, and other factors that promotes age-related diseases. Specifically, an increase in senescent peripheral blood mononuclear cells (PBMCs), including T cells, is associated with conditions like frailty, rheumatoid arthritis, and bone loss. However, it is unknown if the percentage of senescent PBMCs associated with age-associated orthopedic decline could be used for potential diagnostic or prognostic use in orthopedics. Here, we report senescent cell detection using the fluorescent compound C12FDG to quantify PBMCs senescence across a large cohort of healthy and osteoarthritic patients. There is an increase in the percent of circulating C12FDG+ PBMCs that is commensurate with increases in age and senescence-related serum biomarkers. Interestingly, C12FDG+ PBMCs and T cells also were found to be elevated in patients with mild to moderate osteoarthritis, a progressive joint disease that is strongly associated with inflammation. The percent of C12FDG+ PBMCs and age-related serum biomarkers were decreased in a small subgroup of study participants taking the senolytic drug fisetin. These results demonstrate quantifiable measurements in a large group of participants that could create a composite score of healthy aging sensitive enough to detect changes following senolytic therapy and may predict age-related orthopedic decline. Detection of peripheral senescence in PBMCs and subsets using C12FDG may be clinically useful for quantifying cellular senescence and determining how and if it plays a pathological role in osteoarthritic progression.

The processing and analysis of computed tomography (CT) imaging is important for both basic scientific development and clinical applications. In AutoCT, we provide a comprehensive pipeline that integrates an end-to-end automatic preprocessing, registration, segmentation, and quantitative analysis of 3D CT scans. The engineered pipeline enables atlas-based CT segmentation and quantification leveraging diffeomorphic transformations through efficient forward and inverse mappings. The extracted localized features from the deformation field allow for downstream statistical learning that may facilitate medical diagnostics. On a lightweight and portable software platform, AutoCT provides a new toolkit for the CT imaging community to underpin the deployment of artificial intelligence-driven applications.

Six decades after its conception, proton computed tomography (pCT) and proton radiography have yet to be used in medical clinics. However, good progress has been made on relevant detector technologies in the past two decades, and a few prototype pCT systems now exist that approach the performance needed for a clinical device.The tracking and energy-measurement technologies in common use are described, as are the few pCT scanners that are in routine operation at this time.Most of these devices still look like detector R\&D efforts as opposed to medical devices, are difficult to use, are at least factor of five slower than desired for clinical use, and are too small to image many parts of the human body.Recommendations are made for what to consider when engineering a pre-clinical pCT scanner that is designed to meet clinical needs in terms of performance, cost, and ease of use.

Therapeutic antibodies for reducing Aβ plaque load in Alzheimer’s disease (AD) is currently making rapid progress. The diagnostic imaging of Aβ plaque load in AD has been underway and is now used in clinical studies. Here, we report our preliminary findings on imaging a therapeutic antibody, Lecanemab, in a postmortem AD brain anterior cingulate. [125I]5-iodo-3-pyridinecarboxamido-Lecanemab ([125I]IPC-Lecanemab) was prepared by coupling N-succinimidyl-5-([125I]iodo)-3-pyridinecarboxylate with Lecanemab in modest yields. The distinct binding of [125I]IPC-Lecanemab to Aβ-rich regions in postmortem human AD brains was higher in grey matter (GM) containing Aβ plaques compared to white matter (WM) (GM/WM was 1.6). Anti-Aβ immunostaining was correlated with [125I]IPC-Lecanemab regional binding in the postmortem AD human brains. [125I]IPC-Lecanemab binding was consistent with the binding of Aβ small molecules, [18F]flotaza and [125I]IBETA, in the same subjects. [18F]Flotaza and [125I]IBETA, however, exhibited significantly higher GM/WM ratios (>20) compared to [125I]IPC-Lecanemab. Our results suggest that radiolabeled [125I]IPC-Lecanemab retains the ability to bind to Aβ in human AD and may therefore be useful as a PET imaging radiotracer when labeled as [124I]IPC-Lecanemab. The ability to directly visualize in vivo a promising therapeutic antibody for AD may be useful in treatment planning and dosing and could be complimentary to small-molecule diagnostic imaging to assess outcomes of therapeutic interventions.

IntroductionThe Vietnamese Smell Identification Test (VSIT) has been validated in determining olfactory dysfunction in the Vietnamese population; however, its value in diagnosing Parkinson's disease (PD) has not been established.MethodsThis case-control study was conducted at University Medical Center HCMC, Ho Chi Minh City, Vietnam. The study sample included non-demented PD patients and healthy controls (HC) who were gender- and age-matched. All participants were evaluated for odor identification ability using the VSIT and the Brief Smell Identification Test (BSIT).ResultsA total of 218 HCs and 218 PD patients participated in the study. The median VSIT and BSIT scores were significantly different between PD and HC groups (VSIT, 5 (3) vs. 9 (2), P  0.05).ConclusionThe VSIT can be a valuable ancillary tool for supporting the diagnosis of PD in Vietnam. Olfactory dysfunction in PD was unrelated to the disease duration and severity. The VSIT can be applied to improve the accuracy of clinical PD diagnosis.

IntroductionPeople with Down syndrome (DS) have a 75% to 90% lifetime risk of Alzheimer's disease (AD). AD pathology begins a decade or more prior to onset of clinical AD dementia in people with DS. It is not clear if plasma biomarkers of AD pathology are correlated with early cognitive and functional impairments in DS, and if these biomarkers could be used to track the early stages of AD in DS or to inform inclusion criteria for clinical AD treatment trials.MethodsThis large cross-sectional cohort study investigated the associations between plasma biomarkers of amyloid beta (Aβ)42/40, total tau, and neurofilament light chain (NfL) and cognitive (episodic memory, visual-motor integration, and visuospatial abilities) and functional (adaptive behavior) impairments in 260 adults with DS without dementia (aged 25-81 years).ResultsIn general linear models lower plasma Aβ42/40 was related to lower visuospatial ability, higher total tau was related to lower episodic memory, and higher NfL was related to lower visuospatial ability and lower episodic memory.DiscussionPlasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest.HighlightsPlasma Alzheimer's disease (AD) biomarkers correlate with cognition prior to dementia in Down syndrome.Lower plasma amyloid beta 42/40 was related to lower visuospatial abilities.Higher plasma total tau and neurofilament light chain were associated with lower cognitive performance.Plasma biomarkers show potential for tracking early stages of AD symptomology.

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Hyperpolarization techniques significantly enhance the sensitivity of magnetic resonance (MR) and thus present fascinating new directions for research and applications with in vivo MR imaging and spectroscopy (MRI/S). Hyperpolarized 13C MRI/S, in particular, enables real-time non-invasive assessment of metabolic processes and holds great promise for a diverse range of clinical applications spanning fields like oncology, neurology, and cardiology, with a potential for improving early diagnosis of disease, patient stratification, and therapy response assessment. Despite its potential, technical challenges remain for achieving clinical translation. This paper provides an overview of the discussions that took place at the international workshop "New Horizons in Hyperpolarized 13C MRI," in March 2023 at the Bavarian Academy of Sciences and Humanities, Munich, Germany. The workshop covered new developments, as well as future directions, in topics including polarization techniques (particularly focusing on parahydrogen-based methods), novel probes, considerations related to data acquisition and analysis, and emerging clinical applications in oncology and other fields.

Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape. The potential's stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention, before phenotypic changes become detectable.

In pancreatic ductal adenocarcinoma (PDAC), no recurrent metastasis-specific mutation has been found, suggesting that epigenetic mechanisms, such as DNA methylation, are the major contributors of late-stage disease progression. Here, we performed the first whole-genome bisulfite sequencing (WGBS) on mouse and human PDAC organoid models to identify stage-specific and molecular subtype-specific DNA methylation signatures. With this approach, we identified thousands of differentially methylated regions (DMRs) that can distinguish between the stages and molecular subtypes of PDAC. Stage-specific DMRs are associated with genes related to nervous system development and cell-cell adhesions, and are enriched in promoters and bivalent enhancers. Subtype-specific DMRs showed hypermethylation of GATA6 foregut endoderm transcriptional networks in the squamous subtype and hypermethylation of EMT transcriptional networks in the progenitor subtype. These results indicate that aberrant DNA methylation contributes to both PDAC progression and subtype differentiation, resulting in significant and reoccurring DNA methylation patterns with diagnostic and prognostic potential.

Imaging is increasingly used to detect and monitor bacterial infection. Both anatomic (X-rays, computed tomography, ultrasound, and MRI) and nuclear medicine ([111In]-WBC SPECT, [18F]FDG PET) techniques are used in clinical practice but lack specificity for the causative microorganisms themselves. To meet this challenge, many groups have developed imaging methods that target pathogen-specific metabolism, including PET tracers integrated into the bacterial cell wall. We have previously reported the d-amino acid derived PET radiotracers d-methyl-[11C]-methionine, d-[3-11C]-alanine, and d-[3-11C]-alanine-d-alanine, which showed robust bacterial accumulation in vitro and in vivo. Given the clinical importance of radionuclide half-life, in the current study, we developed [18F]3,3,3-trifluoro-d-alanine (d-[18F]-CF3-ala), a fluorine-18 labeled tracer. We tested the hypothesis that d-[18F]-CF3-ala would be incorporated into bacterial peptidoglycan given its structural similarity to d-alanine itself. NMR analysis showed that the fluorine-19 parent amino acid d-[19F]-CF3-ala was stable in human and mouse serum. d-[19F]-CF3-ala was also a poor substrate for d-amino acid oxidase, the enzyme largely responsible for mammalian d-amino acid metabolism and a likely contributor to background signals using d-amino acid derived PET tracers. In addition, d-[19F]-CF3-ala showed robust incorporation into Escherichia coli peptidoglycan, as detected by HPLC/mass spectrometry. Based on these promising results, we developed a radiosynthesis of d-[18F]-CF3-ala via displacement of a bromo-precursor with [18F]fluoride followed by chiral stationary phase HPLC. Unexpectedly, the accumulation of d-[18F]-CF3-ala by bacteria in vitro was highest for Gram-negative pathogens in particular E. coli. In a murine model of acute bacterial infection, d-[18F]-CF3-ala could distinguish live from heat-killed E. coli, with low background signals. These results indicate the viability of [18F]-modified d-amino acids for infection imaging and indicate that improved specificity for bacterial metabolism can improve tracer performance.

Proton resonance frequency shift (PRFS) MR thermometry is the most common method used in clinical thermal treatments because of its fast acquisition and high sensitivity to temperature. However, motion is the biggest obstacle in PRFS MR thermometry for monitoring thermal treatment in moving organs. This challenge arises because of the introduction of phase errors into the PRFS calculation through multiple methods, such as image misregistration, susceptibility changes in the magnetic field, and intraframe motion during MRI acquisition. Various approaches for motion correction have been developed for real-time, motion-robust, and volumetric MR thermometry. However, current technologies have inherent trade-offs among volume coverage, processing time, and temperature accuracy. These tradeoffs should be considered and chosen according to the thermal treatment application. In hyperthermia treatment, precise temperature measurements are of increased importance rather than the requirement for exceedingly high temporal resolution. In contrast, ablation procedures require robust temporal resolution to accurately capture a rapid temperature rise. This paper presents a comprehensive review of current cutting-edge MRI techniques for motion-robust MR thermometry, and recommends which techniques are better suited for each thermal treatment. We expect that this study will help discern the selection of motion-robust MR thermometry strategies and inspire the development of motion-robust volumetric MR thermometry for practical use in clinics.

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

IntroductionWith emergence of disease-modifying therapies, efficient diagnostic pathways are critically needed to identify treatment candidates, evaluate disease severity, and support prognosis. A combination of plasma biomarkers and brief digital cognitive assessments could provide a scalable alternative to current diagnostic work-up.MethodsWe examined the accuracy of plasma biomarkers and a 10-minute supervised tablet-based cognitive assessment (Tablet-based Cognitive Assessment Tool Brain Health Assessment [TabCAT-BHA]) in predicting amyloid β positive (Aβ+) status on positron emission tomography (PET), concurrent disease severity, and functional decline in 309 older adults with subjective cognitive impairment (n = 49), mild cognitive impairment (n = 159), and dementia (n = 101).ResultsCombination of plasma pTau181, Aβ42/40, neurofilament light (NfL), and TabCAT-BHA was optimal for predicting Aβ-PET positivity (AUC = 0.962). Whereas NfL and TabCAT-BHA optimally predicted concurrent disease severity, combining these with pTau181 and glial fibrillary acidic protein was most accurate in predicting functional decline.DiscussionCombinations of plasma and digital cognitive markers show promise for scalable diagnosis and prognosis of ADRD.HighlightsThe need for cost-efficient diagnostic and prognostic markers of AD is urgent. Plasma and digital cognitive markers provide complementary diagnostic contributions. Combination of these markers holds promise for scalable diagnosis and prognosis. Future validation in community cohorts is needed to inform clinical implementation.

IntroductionEarly risk stratification for clinical dementia could lead to preventive therapies. We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer's disease (AD) and related dementias (ARDR).MethodsAn MRI ADRD signature was derived from cortical thickness maps in Framingham Heart Study (FHS) participants with AD dementia and matched controls. The signature was related to the risk of ADRD and cognitive function in FHS. Results were replicated in the University of California Davis Alzheimer's Disease Research Center (UCD-ADRC) cohort.ResultsParticipants in the bottom quartile of the signature had more than three times increased risk for ADRD compared to those in the upper three quartiles (P

Feline chronic gingivostomatitis (FCGS) is a debilitating inflammatory oral mucosal disease with a multifactorial etiology. The clinical diagnosis of FCGS is made based on inspection of severe inflammatory lesions and histological confirmation rather than a molecular diagnostic outcome. This gap limits the ability to provide an early diagnosis. In this report, we seek to provide additional diagnostic tools using genomics to aid in providing clinically relevant information. The use of in-depth diagnostic tools, like transcriptomics of diseased tissues, to diagnose FCGS and stratify patients into predictive treatment response groups would dramatically improve both clinical decisions and patient outcomes. In this study, we addressed the gap in diagnostic options using transcriptomic analysis of caudal oral mucosal swab specimens coupled to detailed medical record linkage of FCGS-affected cats undergoing tooth extractions and in some cases administration of mesenchymal stromal cells (MSCs). To better identify markers of disease and potential response to treatment, the transcriptomes of FCGS-afflicted cats were compared to those of healthy cats and those with chronic periodontitis to clearly establish diagnostic biomarker signal transduction connections. Phosphatidylinositol 3-kinase/Ak strain transforming (PI3K/AKT) and stress-activated protein kinases/Jun N-terminal kinase (SAP/JNK) signaling pathways were significantly differentially regulated in FCGS-afflicted cats. Activation of these pathways also differed in the treatment response groups. In conjunction, the enzymes Caspase 4 (CASP4), matrix metalloproteinase-8 (MMP8), and prostaglandin-endoperoxide synthase 2 (PTGS2) were identified as potential biomarkers for the prediction of treatment response outcomes. The observations in the case study support the use of transcriptomics of FCGS patients to contribute to improved molecular diagnostics for the diagnosis and treatment of FCGS.

Adverse pregnancy outcomes are common among pregnant individuals and are associated with long-term risk of cardiovascular disease. Individuals with adverse pregnancy outcomes also have an increased incidence of cardiovascular disease risk factors after delivery. Despite this, evidence-based approaches to managing these patients after pregnancy to reduce cardiovascular disease risk are lacking. In this scientific statement, we review the current evidence on interpregnancy and postpartum preventive strategies, blood pressure management, and lifestyle interventions for optimizing cardiovascular disease using the American Heart Association Life's Essential 8 framework. Clinical, health system, and community-level interventions can be used to engage postpartum individuals and to reach populations who experience the highest burden of adverse pregnancy outcomes and cardiovascular disease. Future trials are needed to improve screening of subclinical cardiovascular disease in individuals with a history of adverse pregnancy outcomes, before the onset of symptomatic disease. Interventions in the fourth trimester, defined as the 12 weeks after delivery, have great potential to improve cardiovascular health across the life course.

Approaches to quantify stress responses typically rely on subjective surveys and questionnaires. Wearable sensors can potentially be used to continuously monitor stress-relevant biomarkers. However, the biological stress response is spread across the nervous, endocrine, and immune systems, and the capabilities of current sensors are not sufficient for condition-specific stress response evaluation. Here we report an electronic skin for stress response assessment that non-invasively monitors three vital signs (pulse waveform, galvanic skin response and skin temperature) and six molecular biomarkers in human sweat (glucose, lactate, uric acid, sodium ions, potassium ions and ammonium). We develop a general approach to prepare electrochemical sensors that relies on analogous composite materials for stabilizing and conserving sensor interfaces. The resulting sensors offer long-term sweat biomarker analysis of over 100 hours with high stability. We show that the electronic skin can provide continuous multimodal physicochemical monitoring over a 24-hour period and during different daily activities. With the help of a machine learning pipeline, we also show that the platform can differentiate three stressors with an accuracy of 98.0%, and quantify psychological stress responses with a confidence level of 98.7%.

ObjectiveTo investigate whether functional upper eyelid malposition is associated with unrecognized deficits in automated perimetry among glaucoma patients by examining patients undergoing eyelid surgery who had not been identified as requiring eyelid taping during glaucoma field testing.MethodsIn this retrospective pre-post study, an automated database search followed by manual chart review was used to identify eligible patients from January 2012 to March 2020. Included patients had reliable visual field testing within two years before and after functional upper blepharoplasty or ptosis repair and no comorbid ocular diagnoses. As part of routine practice, glaucoma visual field technicians taped patients with pupil-obstructing eyelid malposition; taped examinations were excluded from analysis. Clinical and demographic characteristics, mean deviation, and pattern standard deviation were evaluated within a two year period before and after eyelid surgery.ResultsThe final analysis included 60 eyes of 38 patients. Change in visual field parameters after eyelid surgery did not reach statistical significance in crude or adjusted analyses. Among patients with ptosis, the margin reflex distance-1 was not associated with change in mean deviation after surgery (Pearson R2 ​= ​0.0061; P ​= ​0.700). Five of 17 eyes excluded from analysis due to unreliable pre-operative visual fields demonstrated substantial improvement after surgery.ConclusionsFunctional upper eyelid malposition does not appear to cause spurious visual field abnormalities among glaucoma patients with reliable visual fields who were determined not to require eyelid taping at the time of their visual fields. Unreliable visual fields could be a sign of eyelid interference in this population.

PurposeTimely diagnosis of diabetic retinopathy is important in preventing vision loss. This study aims to determine if remote retinal imaging enables earlier eye care access among newly-diagnosed diabetic patients.DesignRetrospective cohort study.MethodsUsing the OptumLabs® Data Warehouse - a longitudinal, real-world dataset containing deidentified administrative claims and electronic health record (EHR) data, we included 968 846 adults with newly diagnosed type 2 diabetes and at least 1 year of continuous enrollment. We compared time from initial diabetes diagnosis to first eye exam by remote screening or in-person eye exam.ResultsWe found that at year 1 after diagnosis, 5459 (0.56%) patients underwent remote imaging and 208 023 (21.5%) underwent in-person exam. The mean (95% CI) time to eye exam was 3.48 (3.38-3.58) months for remote imaging and 4.22 (4.20-4.23) months for in-person visits (p

BackgroundSeizure detection is challenging outside the clinical environment due to the lack of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We developed a novel, discreet, unobstructive in-ear sensing system that enables long-term electroencephalography (EEG) recording. This is the first study we are aware of that systematically compares the seizure detection utility of in-ear EEG with that of simultaneously recorded intracranial EEG. In addition, we present a similar comparison between simultaneously recorded in-ear EEG and scalp EEG.MethodsIn this foundational research, we conducted a clinical feasibility study and validated the ability of the ear-EEG system to capture focal-onset seizures against 1255 hrs of simultaneous ear-EEG data along with scalp or intracranial EEG in 20 patients with refractory focal epilepsy (11 with scalp EEG, 8 with intracranial EEG, and 1 with both).ResultsIn a blinded, independent review of the ear-EEG signals, two epileptologists were able to detect 86.4% of the seizures that were subsequently identified using the clinical gold standard EEG modalities, with a false detection rate of 0.1 per day, well below what has been reported for ambulatory monitoring. The few seizures not detected on the ear-EEG signals emanated from deep within the mesial temporal lobe or extra-temporally and remained very focal, without significant propagation. Following multiple sessions of recording for a median continuous wear time of 13 hrs, patients reported a high degree of tolerance for the device, with only minor adverse events reported by the scalp EEG cohort.ConclusionsThese preliminary results demonstrate the potential of using ear-EEG to enable routine collection of complementary, prolonged, and remote neurophysiological evidence, which may permit real-time detection of paroxysmal events such as seizures and epileptiform discharges. This study suggests that the ear-EEG device may assist clinicians in making an epilepsy diagnosis, assessing treatment efficacy, and optimizing medication titration.